Characterizing mammographic images by using generic texture features

PubMed Central

2012-01-01

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

Effect of Proximity of Features on the Damage Threshold During Submicron Additive Manufacturing Via Two-Photon Polymerization

DOE PAGES

Saha, Sourabh K.; Divin, Chuck; Cuadra, Jefferson A.; ...

2017-05-12

Two-photon polymerization (TPP) is a laser writing process that enables fabrication of millimeter scale three-dimensional (3D) structures with submicron features. In TPP, writing is achieved via nonlinear two-photon absorption that occurs at high laser intensities. Thus, it is essential to carefully select the incident power to prevent laser damage during polymerization. Currently, the feasible range of laser power is identified by writing small test patterns at varying power levels. Here in this paper, we demonstrate that the results of these tests cannot be generalized, because the damage threshold power depends on the proximity of features and reduces by as muchmore » as 47% for overlapping features. We have identified that this reduction occurs primarily due to an increase in the single-photon absorptivity of the resin after curing. We have captured the damage from proximity effects via X-ray 3D computed tomography (CT) images of a non-homogenous part that has varying feature density. Part damage manifests as internal spherical voids that arise due to boiling of the resist. We have empirically quantified this proximity effect by identifying the damage threshold power at different writing speeds and feature overlap spacings. In addition, we present a first-order analytical model that captures the scaling of this proximity effect. Based on this model and the experiments, we have identified that the proximity effect is more significant at high writing speeds; therefore, it adversely affects the scalability of manufacturing. The scaling laws and the empirical data generated here can be used to select the appropriate TPP writing parameters.« less

Effect of Proximity of Features on the Damage Threshold During Submicron Additive Manufacturing Via Two-Photon Polymerization

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

Saha, Sourabh K.; Divin, Chuck; Cuadra, Jefferson A.

Two-photon polymerization (TPP) is a laser writing process that enables fabrication of millimeter scale three-dimensional (3D) structures with submicron features. In TPP, writing is achieved via nonlinear two-photon absorption that occurs at high laser intensities. Thus, it is essential to carefully select the incident power to prevent laser damage during polymerization. Currently, the feasible range of laser power is identified by writing small test patterns at varying power levels. Here in this paper, we demonstrate that the results of these tests cannot be generalized, because the damage threshold power depends on the proximity of features and reduces by as muchmore » as 47% for overlapping features. We have identified that this reduction occurs primarily due to an increase in the single-photon absorptivity of the resin after curing. We have captured the damage from proximity effects via X-ray 3D computed tomography (CT) images of a non-homogenous part that has varying feature density. Part damage manifests as internal spherical voids that arise due to boiling of the resist. We have empirically quantified this proximity effect by identifying the damage threshold power at different writing speeds and feature overlap spacings. In addition, we present a first-order analytical model that captures the scaling of this proximity effect. Based on this model and the experiments, we have identified that the proximity effect is more significant at high writing speeds; therefore, it adversely affects the scalability of manufacturing. The scaling laws and the empirical data generated here can be used to select the appropriate TPP writing parameters.« less

Systems and Methods for Fabricating Objects Including Amorphous Metal Using Techniques Akin to Additive Manufacturing

NASA Technical Reports Server (NTRS)

Hofmann, Douglas (Inventor)

2017-01-01

Systems and methods in accordance with embodiments of the invention fabricate objects including amorphous metals using techniques akin to additive manufacturing. In one embodiment, a method of fabricating an object that includes an amorphous metal includes: applying a first layer of molten metallic alloy to a surface; cooling the first layer of molten metallic alloy such that it solidifies and thereby forms a first layer including amorphous metal; subsequently applying at least one layer of molten metallic alloy onto a layer including amorphous metal; cooling each subsequently applied layer of molten metallic alloy such that it solidifies and thereby forms a layer including amorphous metal prior to the application of any adjacent layer of molten metallic alloy; where the aggregate of the solidified layers including amorphous metal forms a desired shape in the object to be fabricated; and removing at least the first layer including amorphous metal from the surface.

Occupational methaemoglobinaemia. Mechanisms of production, features, diagnosis and management including the use of methylene blue.

PubMed

Bradberry, Sally M

2003-01-01

Methaemoglobin is formed by oxidation of ferrous (FeII) haem to the ferric (FeIII) state and the mechanisms by which this occurs are complex. Most cases are due to one of three processes. Firstly, direct oxidation of ferrohaemoglobin, which involves the transfer of electrons from ferrous haem to the oxidising compound. This mechanism proceeds most readily in the absence of oxygen. Secondly, indirect oxidation, a process of co-oxidation which requires haemoglobin-bound oxygen and is involved, for example, in nitrite-induced methaemoglobinaemia. Thirdly, biotransformation of a chemical to an active intermediate that initiates methaemoglobin formation by a variety of mechanisms. This is the means by which most aromatic compounds, such as amino- and nitro-derivatives of benzene, produce methaemoglobin. Methaemoglobinaemia is an uncommon occupational occurrence. Aromatic compounds are responsible for most cases, their lipophilic nature and volatility facilitating absorption during dermal and inhalational exposure, the principal routes implicated in the workplace. Methaemoglobinaemia presents clinically with symptoms and signs of tissue hypoxia. Concentrations around 80% are life-threatening. Features of toxicity may develop over hours or even days when exposure, whether by inhalation or repeated skin contact, is to relatively low concentrations of inducing chemical(s). Not all features observed in patients with methaemoglobinaemia are due to methaemoglobin formation. For example, the intravascular haemolysis caused by oxidising chemicals such as chlorates poses more risk to life than the methaemoglobinaemia that such chemicals induce. If an occupational history is taken, the diagnosis of methaemoglobinaemia should be relatively straightforward. In addition, two clinical observations may help: firstly, the victim is often less unwell than one would expect from the severity of 'cyanosis' and, secondly, the 'cyanosis' is unresponsive to oxygen therapy. Pulse oximetry is

Build platform that provides mechanical engagement with additive manufacturing prints

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

Elliott, Amelia M.

A build platform and methods of fabricating an article with such a platform in an extrusion-type additive manufacturing machine are provided. A platform body 202 includes features 204 that extend outward from the body 202. The features 204 define protrusive areas 206 and recessive areas 208 that cooperate to mechanically engage the extruded material that forms the initial layers 220 of an article when the article is being fabricated by a nozzle 12 of the additive manufacturing machine 10.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers

PubMed Central

2011-01-01

Background Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the genetic architecture of complex traits is to include intra-locus (dominance) and inter-locus (epistasis) interaction of alleles as well as the additive genetic effects when fitting a model to a trait. Several Bayesian MCMC approaches exist for the genome-wide estimation of genetic effects with high accuracy of genetic value prediction. Including pairwise interaction for thousands of loci would probably go beyond the scope of such a sampling algorithm because then millions of effects are to be estimated simultaneously leading to months of computation time. Alternative solving strategies are required when epistasis is studied. Methods We extended a fast Bayesian method (fBayesB), which was previously proposed for a purely additive model, to include non-additive effects. The fBayesB approach was used to estimate genetic effects on the basis of simulated datasets. Different scenarios were simulated to study the loss of accuracy of prediction, if epistatic effects were not simulated but modelled and vice versa. Results If 23 QTL were simulated to cause additive and dominance effects, both fBayesB and a conventional MCMC sampler BayesB yielded similar results in terms of accuracy of genetic value prediction and bias of variance component estimation based on a model including additive and dominance effects. Applying fBayesB to data with epistasis, accuracy could be improved by 5% when all pairwise interactions were modelled as well. The accuracy decreased more than 20% if genetic variation was spread over 230 QTL. In this scenario, accuracy based on modelling only additive and dominance effects was generally superior to

Major features of immunesenescence, including reduced thymic output, are ameliorated by high levels of physical activity in adulthood.

PubMed

Duggal, Niharika Arora; Pollock, Ross D; Lazarus, Norman R; Harridge, Stephen; Lord, Janet M

2018-04-01

It is widely accepted that aging is accompanied by remodelling of the immune system including thymic atrophy and increased frequency of senescent T cells, leading to immune compromise. However, physical activity, which influences immunity but declines dramatically with age, is not considered in this literature. We assessed immune profiles in 125 adults (55-79 years) who had maintained a high level of physical activity (cycling) for much of their adult lives, 75 age-matched older adults and 55 young adults not involved in regular exercise. The frequency of naïve T cells and recent thymic emigrants (RTE) were both higher in cyclists compared with inactive elders, and RTE frequency in cyclists was no different to young adults. Compared with their less active counterparts, the cyclists had significantly higher serum levels of the thymoprotective cytokine IL-7 and lower IL-6, which promotes thymic atrophy. Cyclists also showed additional evidence of reduced immunesenescence, namely lower Th17 polarization and higher B regulatory cell frequency than inactive elders. Physical activity did not protect against all aspects of immunesenescence: CD28 -ve CD57 +ve senescent CD8 T-cell frequency did not differ between cyclists and inactive elders. We conclude that many features of immunesenescence may be driven by reduced physical activity with age. © 2018 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Online feature selection with streaming features.

PubMed

Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

2013-05-01

We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

Deterministic object tracking using Gaussian ringlet and directional edge features

NASA Astrophysics Data System (ADS)

Krieger, Evan W.; Sidike, Paheding; Aspiras, Theus; Asari, Vijayan K.

2017-10-01

Challenges currently existing for intensity-based histogram feature tracking methods in wide area motion imagery (WAMI) data include object structural information distortions, background variations, and object scale change. These issues are caused by different pavement or ground types and from changing the sensor or altitude. All of these challenges need to be overcome in order to have a robust object tracker, while attaining a computation time appropriate for real-time processing. To achieve this, we present a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), which employs Kirsch kernel filtering for edge features and a ringlet feature mapping for rotational invariance. The method also includes an automatic scale change component to obtain accurate object boundaries and improvements for lowering computation times. We evaluated the DRIFT algorithm on two challenging WAMI datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Additional evaluations on general tracking video sequences are performed using the Visual Tracker Benchmark and Visual Object Tracking 2014 databases to demonstrate the algorithms ability with additional challenges in long complex sequences including scale change. Experimental results show that the proposed approach yields competitive results compared to state-of-the-art object tracking methods on the testing datasets.

LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasets.

PubMed

Crowell, Kevin L; Slysz, Gordon W; Baker, Erin S; LaMarche, Brian L; Monroe, Matthew E; Ibrahim, Yehia M; Payne, Samuel H; Anderson, Gordon A; Smith, Richard D

2013-11-01

The addition of ion mobility spectrometry to liquid chromatography-mass spectrometry experiments requires new, or updated, software tools to facilitate data processing. We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension. LC-IMS-MS Feature Finder is available as a command-line tool for download at http://omics.pnl.gov/software/LC-IMS-MS_Feature_Finder.php. The Microsoft.NET Framework 4.0 is required to run the software. All other dependencies are included with the software package. Usage of this software is limited to non-profit research to use (see README). rds@pnnl.gov. Supplementary data are available at Bioinformatics online.

Identifying significant environmental features using feature recognition.

DOT National Transportation Integrated Search

2015-10-01

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

Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs.

PubMed

Vitezica, Zulma G; Varona, Luis; Elsen, Jean-Michel; Misztal, Ignacy; Herring, William; Legarra, Andrès

2016-01-29

Most developments in quantitative genetics theory focus on the study of intra-breed/line concepts. With the availability of massive genomic information, it becomes necessary to revisit the theory for crossbred populations. We propose methods to construct genomic covariances with additive and non-additive (dominance) inheritance in the case of pure lines and crossbred populations. We describe substitution effects and dominant deviations across two pure parental populations and the crossbred population. Gene effects are assumed to be independent of the origin of alleles and allelic frequencies can differ between parental populations. Based on these assumptions, the theoretical variance components (additive and dominant) are obtained as a function of marker effects and allelic frequencies. The additive genetic variance in the crossbred population includes the biological additive and dominant effects of a gene and a covariance term. Dominance variance in the crossbred population is proportional to the product of the heterozygosity coefficients of both parental populations. A genomic BLUP (best linear unbiased prediction) equivalent model is presented. We illustrate this approach by using pig data (two pure lines and their cross, including 8265 phenotyped and genotyped sows). For the total number of piglets born, the dominance variance in the crossbred population represented about 13 % of the total genetic variance. Dominance variation is only marginally important for litter size in the crossbred population. We present a coherent marker-based model that includes purebred and crossbred data and additive and dominant actions. Using this model, it is possible to estimate breeding values, dominant deviations and variance components in a dataset that comprises data on purebred and crossbred individuals. These methods can be exploited to plan assortative mating in pig, maize or other species, in order to generate superior crossbred individuals in terms of performance.

3D additive manufactured 316L components microstructural features and changes induced by working life cycles

NASA Astrophysics Data System (ADS)

Pace, M. L.; Guarnaccio, A.; Dolce, P.; Mollica, D.; Parisi, G. P.; Lettino, A.; Medici, L.; Summa, V.; Ciancio, R.; Santagata, A.

2017-10-01

The ability of processing through laser beams different kinds of metallic powders for direct production of 3D components with complex geometries has been gaining an impressive and growing attention for specific industrial applications. The process which can be distinguished as Selective Laser Sintering or Selective Laser Melting is even considered, more generally, as Additive Manufacturing where layer by layer material is built by the interaction between a laser beam and a powder bed. The rapid heating of the powder due to the laser beam energy transfer process followed by a rapid cooling rate induces within the manufactured material a cellular structure with fine sub-grains, which are in the range of few hundreds of micrometers. These metastable structures, which are smaller than the grain size in conventionally manufactured 316L stainless steel components, can undertake towards a recrystallization process due to either heat or mechanical treatments. For instance, when sub-grain boundaries of the cells are enriched with Mo and higher concentration of dislocation, dynamical processes occur generating local residual stresses. In these circumstances the segregation of Mo in cell boundaries is out of thermodynamic equilibrium conditions so that microstructures and phases are metastable. In the range of 1100-1400 °C heat treatments a complete dissolution of Mo in the Fe matrix with a gradual disappearance of sub-microns cell is observed feeding the growth of larger austenitic sub-grains formation. It follows a higher degree of Mo dissolution in the material matrix and a decrease of dislocation's concentration (Saeidi et al., 2015) [1]. In the work here presented we point out which are the microstructural features of stainless steel 316L components realized by Additive Manufacturing. Furthermore, the occurrence of a microstructural evolution is presented after experiencing to fatigue of 80000 cycles some door joints obtained by this technique. A decrease of dislocation

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.

78 FR 67369 - National Vaccine Injury Compensation Program: Addition to the Vaccine Injury Table to Include All...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-12

... Vaccine Injury Compensation Program: Addition to the Vaccine Injury Table to Include All Vaccines Against...) announces that all FDA- approved vaccines against seasonal influenza are covered under the National Vaccine... individuals who have been injured by covered childhood vaccines. Prior to this publication, trivalent...

Clinical features of children and adults with a muscular dystrophy using powered indoor/outdoor wheelchairs: disease features, comorbidities and complications of disability.

PubMed

Frank, Andrew Oliver; De Souza, Lorraine H

2018-05-01

To describe the clinical features of electric powered indoor/outdoor wheelchair users with a muscular dystrophy, likely to influence optimal prescription; reflecting features of muscular dystrophies, conditions secondary to disability, and comorbidities impacting on equipment provision. Cross-sectional retrospective case note review of recipients of electric powered indoor/outdoor wheelchairs provided by a specialist regional wheelchair service. Data on demography, diagnostic/clinical, and wheelchair prescription were systematically extracted. Fifty-one men and 14 women, mean age 23.7 (range 10-67, s.d. 12.95) years, were studied. Forty had Duchenne muscular dystrophy, 22 had other forms of muscular dystrophy, and three were unclassified. Twenty-seven were aged under 19. Notable clinical features included problematic pain (10), cardiomyopathy (5), and ventilatory failure (4). Features related to disability were (kypho)scoliosis (20) and edema/cellulitis (3) whilst comorbidities included back pain (5). Comparison of younger with older users revealed younger users had more features of muscular dystrophy affecting electric powered chair provision (56%) whilst older users had more comorbidity (37%). Tilt-in-space was prescribed for 81% of users, specialized seating for 55% and complex controls for 16%. Muscular dystrophy users were prescribed electric powered indoor/outdoor chairs with many additional features reflecting the consequences of profound muscle weakness. In addition to facilitating independence and participation, electric powered indoor/outdoor chairs have major therapeutic benefits. Implications for rehabilitation Powered wheelchairs have therapeutic benefits in managing muscular dystrophy pain and weakness. The use of specialized seating needs careful consideration in supporting progressive muscle weakness and the management of scoliosis. Pain, discomfort, pressure risk, and muscle fatigue may be reduced by use of tilt-in-space.

Additional Improvements to the NASA Lewis Ice Accretion Code LEWICE

NASA Technical Reports Server (NTRS)

Wright, William B.; Bidwell, Colin S.

1995-01-01

Due to the feedback of the user community, three major features have been added to the NASA Lewis ice accretion code LEWICE. These features include: first, further improvements to the numerics of the code so that more time steps can be run and so that the code is more stable; second, inclusion and refinement of the roughness prediction model described in an earlier paper; third, inclusion of multi-element trajectory and ice accretion capabilities to LEWICE. This paper will describe each of these advancements in full and make comparisons with the experimental data available. Further refinement of these features and inclusion of additional features will be performed as more feedback is received.

Features in visual search combine linearly

PubMed Central

Pramod, R. T.; Arun, S. P.

2014-01-01

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328

Toxicological features of maleilated polyflavonoids from Pinus radiata (D. Don.) as potential functional additives for biomaterials design.

PubMed

García, Danny E; Medina, Paulina A; Zúñiga, Valentina I

2017-11-01

Polyflavonoids from Pinus radiata (D. Don.) are an abundant natural oligomers highly desirable as renewable chemicals. However, structural modification of polyflavonoids is a viable strategy in order to use such polyphenols as macrobuilding-blocks for biomaterial design. Polyflavonoids were esterified with three five-member cyclic anhydrides (maleic, itaconic, and citraconic) at 20 °C during 24 h in order to diversify physicochemical-, and biological-properties for agricultural, and food-packaging applications. In addition, the influence of the chemical modification, as well as the chemical structure of the grafting on toxicological features was evaluated. Structural features of derivatives were analyzed by spectroscopy (FT-IR and 1 H-NMR), and the degree of substitution was calculated. Toxicological profile was assessed by using three target species in a wide range of concentration (0.01-100 mgL - 1 ). Effect of polyflavonoids on the growth rate (Selenastrum capricornutum), mortality (Daphnia magna), and germination and radicle length (Lactuca sativa) was determined. Chemical modification affects the toxicological profile on the derivatives in a high extent. Results described remarkable differences in function of the target specie. The bioassays indicate differences of the polyflavonoids toxicological profile associated to the chemical structure of the grafting. Results allowed conclude that polyflavonoids from pine bark show slight toxic properties. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tumors of the Testis: Morphologic Features and Molecular Alterations.

PubMed

Howitt, Brooke E; Berney, Daniel M

2015-12-01

This article reviews the most frequently encountered tumor of the testis; pure and mixed malignant testicular germ cell tumors (TGCT), with emphasis on adult (postpubertal) TGCTs and their differential diagnoses. We additionally review TGCT in the postchemotherapy setting, and findings to be integrated into the surgical pathology report, including staging of testicular tumors and other problematic issues. The clinical features, gross pathologic findings, key histologic features, common differential diagnoses, the use of immunohistochemistry, and molecular alterations in TGCTs are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Arthrogryposis-renal dysfunction-cholestasis (ARC) syndrome: from molecular genetics to clinical features.

PubMed

Zhou, Yaoyao; Zhang, Junfeng

2014-09-20

Arthrogryposis-renal dysfunction-cholestasis (ARC) syndrome is a rare but fatal autosomal recessive multisystem disorder caused by mutations in the VPS33B or VIPAR gene. The classical presentation of ARC includes congenital joint contractures, renal tubular dysfunction, and cholestasis. Additional features include ichthyosis, central nervous system malformation, platelet anomalies, and severe failure to thrive. Diagnosis of ARC syndrome relies on clinical features, organ biopsy, and mutational analysis. However, no specific treatment currently exists for this syndrome. This is an overview of the latest knowledge regarding the genetic features and clinical manifestations of ARC syndrome. Greater awareness and understanding of this syndrome should allow more timely intervention with potential for improving long-term outcome.

Automated solar collector installation design including ability to define heterogeneous design preferences

DOEpatents

Wayne, Gary; Frumkin, Alexander; Zaydman, Michael; Lehman, Scott; Brenner, Jules

2014-04-29

Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of pre -defined "features" with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Embodiments may also include definition of one or more design apertures, each of which may correspond to boundaries in which solar collector layouts should comply with distinct sets of user-defined design preferences. Distinct apertures may provide heterogeneous regions of collector layout according to the user-defined design preferences.

Automated solar collector installation design including ability to define heterogeneous design preferences

DOEpatents

Wayne, Gary; Frumkin, Alexander; Zaydman, Michael; Lehman, Scott; Brenner, Jules

2013-01-08

Embodiments may include systems and methods to create and edit a representation of a worksite, to create various data objects, to classify such objects as various types of pre-defined "features" with attendant properties and layout constraints. As part of or in addition to classification, an embodiment may include systems and methods to create, associate, and edit intrinsic and extrinsic properties to these objects. A design engine may apply of design rules to the features described above to generate one or more solar collectors installation design alternatives, including generation of on-screen and/or paper representations of the physical layout or arrangement of the one or more design alternatives. Embodiments may also include definition of one or more design apertures, each of which may correspond to boundaries in which solar collector layouts should comply with distinct sets of user-defined design preferences. Distinct apertures may provide heterogeneous regions of collector layout according to the user-defined design preferences.

Monitoring Geothermal Features in Yellowstone National Park with ATLAS Multispectral Imagery

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Berglund, Judith

2000-01-01

The National Park Service (NPS) must produce an Environmental Impact Statement for each proposed development in the vicinity of known geothermal resource areas (KGRAs) in Yellowstone National Park. In addition, the NPS monitors indicator KGRAs for environmental quality and is still in the process of mapping many geothermal areas. The NPS currently maps geothermal features with field survey techniques. High resolution aerial multispectral remote sensing in the visible, NIR, SWIR, and thermal spectral regions could enable YNP geothermal features to be mapped more quickly and in greater detail In response, Yellowstone Ecosystems Studies, in partnership with NASA's Commercial Remote Sensing Program, is conducting a study on the use of Airborne Terrestrial Applications Sensor (ATLAS) multispectral data for monitoring geothermal features in the Upper Geyser Basin. ATLAS data were acquired at 2.5 meter resolution on August 17, 2000. These data were processed into land cover classifications and relative temperature maps. For sufficiently large features, the ATLAS data can map geothermal areas in terms of geyser pools and hot springs, plus multiple categories of geothermal runoff that are apparently indicative of temperature gradients and microbial matting communities. In addition, the ATLAS maps clearly identify geyserite areas. The thermal bands contributed to classification success and to the computation of relative temperature. With masking techniques, one can assess the influence of geothermal features on the Firehole River. Preliminary results appear to confirm ATLAS data utility for mapping and monitoring geothermal features. Future work will include classification refinement and additional validation.

Discriminative analysis of lip motion features for speaker identification and speech-reading.

PubMed

Cetingül, H Ertan; Yemez, Yücel; Erzin, Engin; Tekalp, A Murat

2006-10-01

There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application.

Features and machine learning classification of connected speech samples from patients with autopsy proven Alzheimer's disease with and without additional vascular pathology.

PubMed

Rentoumi, Vassiliki; Raoufian, Ladan; Ahmed, Samrah; de Jager, Celeste A; Garrard, Peter

2014-01-01

Mixed vascular and Alzheimer-type dementia and pure Alzheimer's disease are both associated with changes in spoken language. These changes have, however, seldom been subjected to systematic comparison. In the present study, we analyzed language samples obtained during the course of a longitudinal clinical study from patients in whom one or other pathology was verified at post mortem. The aims of the study were twofold: first, to confirm the presence of differences in language produced by members of the two groups using quantitative methods of evaluation; and secondly to ascertain the most informative sources of variation between the groups. We adopted a computational approach to evaluate digitized transcripts of connected speech along a range of language-related dimensions. We then used machine learning text classification to assign the samples to one of the two pathological groups on the basis of these features. The classifiers' accuracies were tested using simple lexical features, syntactic features, and more complex statistical and information theory characteristics. Maximum accuracy was achieved when word occurrences and frequencies alone were used. Features based on syntactic and lexical complexity yielded lower discrimination scores, but all combinations of features showed significantly better performance than a baseline condition in which every transcript was assigned randomly to one of the two classes. The classification results illustrate the word content specific differences in the spoken language of the two groups. In addition, those with mixed pathology were found to exhibit a marked reduction in lexical variation and complexity compared to their pure AD counterparts.

Additive manufacturing method for SRF components of various geometries

DOEpatents

Rimmer, Robert; Frigola, Pedro E; Murokh, Alex Y

2015-05-05

An additive manufacturing method for forming nearly monolithic SRF niobium cavities and end group components of arbitrary shape with features such as optimized wall thickness and integral stiffeners, greatly reducing the cost and technical variability of conventional cavity construction. The additive manufacturing method for forming an SRF cavity, includes atomizing niobium to form a niobium powder, feeding the niobium powder into an electron beam melter under a vacuum, melting the niobium powder under a vacuum in the electron beam melter to form an SRF cavity; and polishing the inside surface of the SRF cavity.

41 CFR 302-7.21 - If my HHG shipment includes an item for which a weight additive is assessed by the HHG carrier (e...

Code of Federal Regulations, 2014 CFR

2014-07-01

... includes an item for which a weight additive is assessed by the HHG carrier (e.g., boat, trailer... BAGGAGE ALLOWANCE General Rules § 302-7.21 If my HHG shipment includes an item for which a weight additive... payment? (a) No, you will not be responsible for the shipping charges that result from a weight additive...

41 CFR 302-7.21 - If my HHG shipment includes an item for which a weight additive is assessed by the HHG carrier (e...

Code of Federal Regulations, 2012 CFR

2012-07-01

... includes an item for which a weight additive is assessed by the HHG carrier (e.g., boat, trailer...) General Rules § 302-7.21 If my HHG shipment includes an item for which a weight additive is assessed by... will not be responsible for the shipping charges that result from a weight additive so long as the...

41 CFR 302-7.21 - If my HHG shipment includes an item for which a weight additive is assessed by the HHG carrier (e...

Code of Federal Regulations, 2013 CFR

2013-07-01

... includes an item for which a weight additive is assessed by the HHG carrier (e.g., boat, trailer...) General Rules § 302-7.21 If my HHG shipment includes an item for which a weight additive is assessed by... will not be responsible for the shipping charges that result from a weight additive so long as the...

Stimulus information contaminates summation tests of independent neural representations of features

NASA Technical Reports Server (NTRS)

Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

2002-01-01

Many models of visual processing assume that visual information is analyzed into separable and independent neural codes, or features. A common psychophysical test of independent features is known as a summation study, which measures performance in a detection, discrimination, or visual search task as the number of proposed features increases. Improvement in human performance with increasing number of available features is typically attributed to the summation, or combination, of information across independent neural coding of the features. In many instances, however, increasing the number of available features also increases the stimulus information in the task, as assessed by an optimal observer that does not include the independent neural codes. In a visual search task with spatial frequency and orientation as the component features, a particular set of stimuli were chosen so that all searches had equivalent stimulus information, regardless of the number of features. In this case, human performance did not improve with increasing number of features, implying that the improvement observed with additional features may be due to stimulus information and not the combination across independent features.

Spatial features register: toward standardization of spatial features

USGS Publications Warehouse

Cascio, Janette

1994-01-01

As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 2.

KENNEDY SPACE CENTER, FLA. - The Rocket Garden at the KSC Visitor Complex features eight authentic rockets from the past, including a Mercury-Atlas rocket. The garden also features a climb-in Mercury, Gemino and Apollo capsule replicas, seating pods and informative graphic elements.

NASA Image and Video Library

2003-07-22

KENNEDY SPACE CENTER, FLA. - The Rocket Garden at the KSC Visitor Complex features eight authentic rockets from the past, including a Mercury-Atlas rocket. The garden also features a climb-in Mercury, Gemino and Apollo capsule replicas, seating pods and informative graphic elements.

Identifying Medication Management Smartphone App Features Suitable for Young Adults With Developmental Disabilities: Delphi Consensus Study

PubMed Central

Salgado, Teresa M; Fedrigon, Alexa; Riccio Omichinski, Donna; Meade, Michelle A

2018-01-01

Background Smartphone apps can be a tool to facilitate independent medication management among persons with developmental disabilities. At present, multiple medication management apps exist in the market, but only 1 has been specifically designed for persons with developmental disabilities. Before initiating further app development targeting this population, input from stakeholders including persons with developmental disabilities, caregivers, and professionals regarding the most preferred features should be obtained. Objective The aim of this study was to identify medication management app features that are suitable to promote independence in the medication management process by young adults with developmental disabilities using a Delphi consensus method. Methods A compilation of medication management app features was performed by searching the iTunes App Store, United States, in February 2016, using the following terms: adherence, medication, medication management, medication list, and medication reminder. After identifying features within the retrieved apps, a final list of 42 features grouped into 4 modules (medication list, medication reminder, medication administration record, and additional features) was included in a questionnaire for expert consensus rating. A total of 52 experts in developmental disabilities, including persons with developmental disabilities, caregivers, and professionals, were invited to participate in a 3-round Delphi technique. The purpose was to obtain consensus on features that are preferred and suitable to promote independence in the medication management process among persons with developmental disabilities. Consensus for the first, second, and third rounds was defined as ≥90%, ≥80%, and ≥75% agreement, respectively. Results A total of 75 responses were received over the 3 Delphi rounds—30 in the first round, 24 in the second round, and 21 in the third round. At the end of the third round, cumulative consensus was achieved

Feature engineering for MEDLINE citation categorization with MeSH.

PubMed

Jimeno Yepes, Antonio Jose; Plaza, Laura; Carrillo-de-Albornoz, Jorge; Mork, James G; Aronson, Alan R

2015-04-08

Research in biomedical text categorization has mostly used the bag-of-words representation. Other more sophisticated representations of text based on syntactic, semantic and argumentative properties have been less studied. In this paper, we evaluate the impact of different text representations of biomedical texts as features for reproducing the MeSH annotations of some of the most frequent MeSH headings. In addition to unigrams and bigrams, these features include noun phrases, citation meta-data, citation structure, and semantic annotation of the citations. Traditional features like unigrams and bigrams exhibit strong performance compared to other feature sets. Little or no improvement is obtained when using meta-data or citation structure. Noun phrases are too sparse and thus have lower performance compared to more traditional features. Conceptual annotation of the texts by MetaMap shows similar performance compared to unigrams, but adding concepts from the UMLS taxonomy does not improve the performance of using only mapped concepts. The combination of all the features performs largely better than any individual feature set considered. In addition, this combination improves the performance of a state-of-the-art MeSH indexer. Concerning the machine learning algorithms, we find that those that are more resilient to class imbalance largely obtain better performance. We conclude that even though traditional features such as unigrams and bigrams have strong performance compared to other features, it is possible to combine them to effectively improve the performance of the bag-of-words representation. We have also found that the combination of the learning algorithm and feature sets has an influence in the overall performance of the system. Moreover, using learning algorithms resilient to class imbalance largely improves performance. However, when using a large set of features, consideration needs to be taken with algorithms due to the risk of over-fitting. Specific

The performance improvement of automatic classification among obstructive lung diseases on the basis of the features of shape analysis, in addition to texture analysis at HRCT

NASA Astrophysics Data System (ADS)

Lee, Youngjoo; Kim, Namkug; Seo, Joon Beom; Lee, JuneGoo; Kang, Suk Ho

2007-03-01

In this paper, we proposed novel shape features to improve classification performance of differentiating obstructive lung diseases, based on HRCT (High Resolution Computerized Tomography) images. The images were selected from HRCT images, obtained from 82 subjects. For each image, two experienced radiologists selected rectangular ROIs with various sizes (16x16, 32x32, and 64x64 pixels), representing each disease or normal lung parenchyma. Besides thirteen textural features, we employed additional seven shape features; cluster shape features, and Top-hat transform features. To evaluate the contribution of shape features for differentiation of obstructive lung diseases, several experiments were conducted with two different types of classifiers and various ROI sizes. For automated classification, the Bayesian classifier and support vector machine (SVM) were implemented. To assess the performance and cross-validation of the system, 5-folding method was used. In comparison to employing only textural features, adding shape features yields significant enhancement of overall sensitivity(5.9, 5.4, 4.4% in the Bayesian and 9.0, 7.3, 5.3% in the SVM), in the order of ROI size 16x16, 32x32, 64x64 pixels, respectively (t-test, p<0.01). Moreover, this enhancement was largely due to the improvement on class-specific sensitivity of mild centrilobular emphysema and bronchiolitis obliterans which are most hard to differentiate for radiologists. According to these experimental results, adding shape features to conventional texture features is much useful to improve classification performance of obstructive lung diseases in both Bayesian and SVM classifiers.

Novel Features for Brain-Computer Interfaces

PubMed Central

Woon, W. L.; Cichocki, A.

2007-01-01

While conventional approaches of BCI feature extraction are based on the power spectrum, we have tried using nonlinear features for classifying BCI data. In this paper, we report our test results and findings, which indicate that the proposed method is a potentially useful addition to current feature extraction techniques. PMID:18364991

The Purification of the Chlamydomonas reinhardtii chloroplast ClpP complex: additional subunits and structural features

PubMed Central

Derrien, Benoît; Majeran, Wojciech; Effantin, Grégory; Ebenezer, Joseph; Friso, Giulia; van Wijk, Klaas J.; Steven, Alasdair C.; Maurizi, Michael R.; Vallon, Olivier

2012-01-01

The ClpP peptidase is a major constituent of the proteolytic machinery of bacteria and organelles. The chloroplast ClpP complex is unusual, in that it associates a large number of subunits, one of which (ClpP1) is encoded in the chloroplast, the others in the nucleus. The complexity of these large hetero-oligomeric complexes has been a major difficulty in their overproduction and biochemical characterization. In this paper, we describe the purification of native chloroplast ClpP complex from the green alga Chlamydomonas reinhardtii, using a strain that carries the Strep-tag II at the C-terminus of the ClpP1 subunit. Similar to land plants, the algal complex comprises active and inactive subunits (3 ClpP and 5 ClpR, respectively). Evidence is presented that a sub-complex can be produced by dissociation, comprising ClpP1 and ClpR1, 2, 3 and 4, similar to the ClpR-ring described in land plants. Our Chlamydomonas ClpP preparation also contains two ClpT subunits, ClpT3 and ClpT4, which like the land plant ClpT1 and ClpT2 show 2 Clp-N domains. ClpTs are believed to function in substrate binding and/or assembly of the two heptameric rings. Phylogenetic analysis indicates that ClpT subunits have appeared independently in Chlorophycean algae, in land plants and in dispersed cyanobacterial genomes. Negative staining electron microscopy shows that the Chlamydomonas complex retains the barrel-like shape of homo-oligomeric ClpPs, with 4 additional peripheral masses that we speculate represent either the additional IS1 domain of ClpP1 (a feature unique to algae) or ClpTs or extensions of ClpR subunits PMID:22772861

Breast masses in mammography classification with local contour features.

PubMed

Li, Haixia; Meng, Xianjing; Wang, Tingwen; Tang, Yuchun; Yin, Yilong

2017-04-14

Mammography is one of the most popular tools for early detection of breast cancer. Contour of breast mass in mammography is very important information to distinguish benign and malignant mass. Contour of benign mass is smooth and round or oval, while malignant mass has irregular shape and spiculated contour. Several studies have shown that 1D signature translated from 2D contour can describe the contour features well. In this paper, we propose a new method to translate 2D contour of breast mass in mammography into 1D signature. The method can describe not only the contour features but also the regularity of breast mass. Then we segment the whole 1D signature into different subsections. We extract four local features including a new contour descriptor from the subsections. The new contour descriptor is root mean square (RMS) slope. It can describe the roughness of the contour. KNN, SVM and ANN classifier are used to classify benign breast mass and malignant mass. The proposed method is tested on a set with 323 contours including 143 benign masses and 180 malignant ones from digital database of screening mammography (DDSM). The best accuracy of classification is 99.66% using the feature of root mean square slope with SVM classifier. The performance of the proposed method is better than traditional method. In addition, RMS slope is an effective feature comparable to most of the existing features.

Expanding the North American Breeding Bird Survey analysis to include additional species and regions

USGS Publications Warehouse

Sauer, John; Niven, Daniel; Pardieck, Keith L.; Ziolkowski, David; Link, William

2017-01-01

The North American Breeding Bird Survey (BBS) contains data for >700 bird species, but analyses often focus on a core group of ∼420 species. We analyzed data for 122 species of North American birds for which data exist in the North American Breeding Bird Survey (BBS) database but are not routinely analyzed on the BBS Summary and Analysis Website. Many of these species occur in the northern part of the continent, on routes that fall outside the core survey area presently analyzed in the United States and southern Canada. Other species not historically analyzed occur in the core survey area with very limited data but have large portions of their ranges in Mexico and south. A third group of species not historically analyzed included species thought to be poorly surveyed by the BBS, such as rare, coastal, or nocturnal species. For 56 species found primarily in regions north of the core survey area, we expanded the scope of the analysis, using data from 1993 to 2014 during which ≥3 survey routes had been sampled in 6 northern strata (Bird Conservation regions in Alaska, Yukon, and Newfoundland and Labrador) and fitting log-linear hierarchical models for an augmented BBS survey area that included both the new northern strata and the core survey area. We also applied this model to 168 species historically analyzed in the BBS that had data from these additional northern strata. For both groups of species we calculated survey-wide trends for the both core and augmented survey areas from 1993 to 2014; for species that did not occur in the newly defined strata, we computed trends from 1966 to 2014. We evaluated trend estimates in terms of established credibility criteria for BBS results, screening for imprecise trends, small samples, and low relative abundance. Inclusion of data from the northern strata permitted estimation of trend for 56 species not historically analyzed, but only 4 of these were reasonably monitored and an additional 13 were questionably monitored; 39

Clinical report of a 17q12 microdeletion with additionally unreported clinical features.

PubMed

Roberts, Jennifer L; Gandomi, Stephanie K; Parra, Melissa; Lu, Ira; Gau, Chia-Ling; Dasouki, Majed; Butler, Merlin G

2014-01-01

Copy number variations involving the 17q12 region have been associated with developmental and speech delay, autism, aggression, self-injury, biting and hitting, oppositional defiance, inappropriate language, and auditory hallucinations. We present a tall-appearing 17-year-old boy with marfanoid habitus, hypermobile joints, mild scoliosis, pectus deformity, widely spaced nipples, pes cavus, autism spectrum disorder, intellectual disability, and psychiatric manifestations including physical and verbal aggression, obsessive-compulsive behaviors, and oppositional defiance. An echocardiogram showed borderline increased aortic root size. An abdominal ultrasound revealed a small pancreas, mild splenomegaly with a 1.3 cm accessory splenule, and normal kidneys and liver. A testing panel for Marfan, aneurysm, and related disorders was negative. Subsequently, a 400 K array-based comparative genomic hybridization (aCGH) + SNP analysis was performed which identified a de novo suspected pathogenic deletion on chromosome 17q12 encompassing 28 genes. Despite the limited number of cases described in the literature with 17q12 rearrangements, our proband's phenotypic features both overlap and expand on previously reported cases. Since syndrome-specific DNA sequencing studies failed to provide an explanation for this patient's unusual habitus, we postulate that this case represents an expansion of the 17q12 microdeletion phenotype. Further analysis of the deleted interval is recommended for new genotype-phenotype correlations.

Extending Primitive Spatial Data Models to Include Semantics

NASA Astrophysics Data System (ADS)

Reitsma, F.; Batcheller, J.

2009-04-01

Our traditional geospatial data model involves associating some measurable quality, such as temperature, or observable feature, such as a tree, with a point or region in space and time. When capturing data we implicitly subscribe to some kind of conceptualisation. If we can make this explicit in an ontology and associate it with the captured data, we can leverage formal semantics to reason with the concepts represented in our spatial data sets. To do so, we extend our fundamental representation of geospatial data in a data model by including a URI in our basic data model that links it to our ontology defining our conceptualisation, We thus extend Goodchild et al's geo-atom [1] with the addition of a URI: (x, Z, z(x), URI) . This provides us with pixel or feature level knowledge and the ability to create layers of data from a set of pixels or features that might be drawn from a database based on their semantics. Using open source tools, we present a prototype that involves simple reasoning as a proof of concept. References [1] M.F. Goodchild, M. Yuan, and T.J. Cova. Towards a general theory of geographic representation in gis. International Journal of Geographical Information Science, 21(3):239-260, 2007.

Method for assessment of stormwater treatment facilities - Synthetic road runoff addition including micro-pollutants and tracer.

PubMed

Cederkvist, Karin; Jensen, Marina B; Holm, Peter E

2017-08-01

Stormwater treatment facilities (STFs) are becoming increasingly widespread but knowledge on their performance is limited. This is due to difficulties in obtaining representative samples during storm events and documenting removal of the broad range of contaminants found in stormwater runoff. This paper presents a method to evaluate STFs by addition of synthetic runoff with representative concentrations of contaminant species, including the use of tracer for correction of removal rates for losses not caused by the STF. A list of organic and inorganic contaminant species, including trace elements representative of runoff from roads is suggested, as well as relevant concentration ranges. The method was used for adding contaminants to three different STFs including a curbstone extension with filter soil, a dual porosity filter, and six different permeable pavements. Evaluation of the method showed that it is possible to add a well-defined mixture of contaminants despite different field conditions by having a flexibly system, mixing different stock-solutions on site, and use bromide tracer for correction of outlet concentrations. Bromide recovery ranged from only 12% in one of the permeable pavements to 97% in the dual porosity filter, stressing the importance of including a conservative tracer for correction of contaminant retention values. The method is considered useful in future treatment performance testing of STFs. The observed performance of the STFs is presented in coming papers. Copyright © 2017 Elsevier Ltd. All rights reserved.

LC-IMS-MS Feature Finder

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

2013-03-07

LC-IMS-MS Feature Finder is a command line software application which searches for possible molecular ion signatures in multidimensional liquid chromatography, ion mobility spectrometry, and mass spectrometry data by clustering deisotoped peaks with similar monoisotopic mass values, charge states, elution times, and drift times. The software application includes an algorithm for detecting multiple conformations and co-eluting species in the ion mobility dimension. LC-IMS-MS Feature Finder is designed to create an output file with detected features that includes associated information about the detected features.

Forensic detection of noise addition in digital images

NASA Astrophysics Data System (ADS)

Cao, Gang; Zhao, Yao; Ni, Rongrong; Ou, Bo; Wang, Yongbin

2014-03-01

We proposed a technique to detect the global addition of noise to a digital image. As an anti-forensics tool, noise addition is typically used to disguise the visual traces of image tampering or to remove the statistical artifacts left behind by other operations. As such, the blind detection of noise addition has become imperative as well as beneficial to authenticate the image content and recover the image processing history, which is the goal of general forensics techniques. Specifically, the special image blocks, including constant and strip ones, are used to construct the features for identifying noise addition manipulation. The influence of noising on blockwise pixel value distribution is formulated and analyzed formally. The methodology of detectability recognition followed by binary decision is proposed to ensure the applicability and reliability of noising detection. Extensive experimental results demonstrate the efficacy of our proposed noising detector.

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Field-enhanced electrodes for additive-injection non-thermal plasma (NTP) processor

DOEpatents

Rosocha, Louis A [Los Alamos, NM; Ferreri, Vincent [Westminster, CO; Kim, Yongho [Los Alamos, NM

2009-04-21

The present invention comprises a field enhanced electrode package for use in a non-thermal plasma processor. The field enhanced electrode package includes a high voltage electrode and a field-enhancing electrode with a dielectric material layer disposed in-between the high voltage electrode and the field-enhancing electrode. The field-enhancing electrode features at least one raised section that includes at least one injection hole that allows plasma discharge streamers to occur primarily within an injected additive gas.

Coding of visual object features and feature conjunctions in the human brain.

PubMed

Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

2008-01-01

Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

Feature selection from a facial image for distinction of sasang constitution.

PubMed

Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun; Kim, Keun Ho

2009-09-01

Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here.

Topographic Feature Names on Venus: Progress in 2000, Review of 1997-2000 Development, Current State, and Prospective

NASA Technical Reports Server (NTRS)

Burba, G. A.; Blue, J.; Campbell, D. B.; Dollfus, A.; Gaddis, L.; Jurgens, R. F.; Marov, M. Ya.; Pettengill, G. H.; Stofan, E. R.

2001-01-01

12 names assigned on Venus in 2000. The current list includes 1821 names of 21 feature types. 95% of names present 11 types of features. The main named types are craters - 872, and coronae - 267. These two types possess 62% of the names. Additional information is contained in the original extended abstract.

Endomyocardial fibrosis in Sudan: clinical and echocardiographic features

PubMed Central

Khalil, Siddiq Ibrahim; Khalil, Suha; El Tigani, Salma; Saad, Hanan A

2017-01-01

Summary Objective: Endomyocardial fibrosis (EMF) is a rare disease and is often an underdiagnosed and forgotten cardiomyopathy. The objective of this study was to document the current frequency of EMF in Sudan by defining and selecting cases from patients attending the echocardiography laboratory. Additionally we aimed to create an EMF registry for Sudan. Methods: The study started in January 2007 and is on-going. All the patients attending our echocardiography clinics in four different hospitals in Khartoum, Sudan, were included. Transthoracic echocardiography was used as the main diagnostic and selection tool. The diagnosis of EMF was based on predefined criteria and definitions, and was further supported by additional clinical, ECG, laboratory and chest X-ray findings. Results: Out of 4 332 cases studied, 23 (0.5%) were found to have features of EMF. Females constituted 52% and the age range was 24 to 67 years. All patients presented with dyspnoea grades III–IV. Advanced heart failure with gross fluid overload was seen in 54% of cases and ascites was seen in 30%. EMF was biventricular in 53%, left ventricular in 29% and right ventricular in 18% of cases. Apical and ventricular wall fibrosis was found in all cases, followed by atrial enlargement, atrioventricular valve incompetence, ventricular cavity obliteration, restrictive flow pattern and pericardial effusion. Additional echocardiographic features are defined and discussed. Conclusion: Although a rare disease, cases of EMF can be identified in Sudan if a high index of suspicion is observed. New echocardiographic features of ventricular wall layering, endocardial fibrous shelf and endomyocardiopericarial fibrosis were identified and are discussed. PMID:28906536

Automatic extraction of planetary image features

NASA Technical Reports Server (NTRS)

LeMoigne-Stewart, Jacqueline J. (Inventor); Troglio, Giulia (Inventor); Benediktsson, Jon A. (Inventor); Serpico, Sebastiano B. (Inventor); Moser, Gabriele (Inventor)

2013-01-01

A method for the extraction of Lunar data and/or planetary features is provided. The feature extraction method can include one or more image processing techniques, including, but not limited to, a watershed segmentation and/or the generalized Hough Transform. According to some embodiments, the feature extraction method can include extracting features, such as, small rocks. According to some embodiments, small rocks can be extracted by applying a watershed segmentation algorithm to the Canny gradient. According to some embodiments, applying a watershed segmentation algorithm to the Canny gradient can allow regions that appear as close contours in the gradient to be segmented.

Complex Topographic Feature Ontology Patterns

USGS Publications Warehouse

Varanka, Dalia E.; Jerris, Thomas J.

2015-01-01

Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

Prostate cancer detection: Fusion of cytological and textural features.

PubMed

Nguyen, Kien; Jain, Anil K; Sabata, Bikash

2011-01-01

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification.

Additional Security Considerations for Grid Management

NASA Technical Reports Server (NTRS)

Eidson, Thomas M.

2003-01-01

The use of Grid computing environments is growing in popularity. A Grid computing environment is primarily a wide area network that encompasses multiple local area networks, where some of the local area networks are managed by different organizations. A Grid computing environment also includes common interfaces for distributed computing software so that the heterogeneous set of machines that make up the Grid can be used more easily. The other key feature of a Grid is that the distributed computing software includes appropriate security technology. The focus of most Grid software is on the security involved with application execution, file transfers, and other remote computing procedures. However, there are other important security issues related to the management of a Grid and the users who use that Grid. This note discusses these additional security issues and makes several suggestions as how they can be managed.

Clinical features of the myasthenic syndrome arising from mutations in GMPPB.

PubMed

Rodríguez Cruz, Pedro M; Belaya, Katsiaryna; Basiri, Keivan; Sedghi, Maryam; Farrugia, Maria Elena; Holton, Janice L; Liu, Wei Wei; Maxwell, Susan; Petty, Richard; Walls, Timothy J; Kennett, Robin; Pitt, Matthew; Sarkozy, Anna; Parton, Matt; Lochmüller, Hanns; Muntoni, Francesco; Palace, Jacqueline; Beeson, David

2016-08-01

Congenital myasthenic syndrome (CMS) due to mutations in GMPPB has recently been reported confirming the importance of glycosylation for the integrity of neuromuscular transmission. Review of case notes of patients with mutations in GMPPB to identify the associated clinical, neurophysiological, pathological and laboratory features. In addition, serum creatine kinase (CK) levels within the Oxford CMS cohort were retrospectively analysed to assess its usefulness in the differential diagnosis of this new entity. All patients had prominent limb-girdle weakness with minimal or absent craniobulbar manifestations. Presentation was delayed beyond infancy with proximal muscle weakness and most patients recall poor performance in sports during childhood. Neurophysiology showed abnormal neuromuscular transmission only in the affected muscles and myopathic changes. Muscle biopsy showed dystrophic features and reduced α-dystroglycan glycosylation. In addition, myopathic changes were present on muscle MRI. CK was significantly increased in serum compared to other CMS subtypes. Patients were responsive to pyridostigimine alone or combined with 3,4-diaminopyridine and/or salbutamol. Patients with GMPPB-CMS have phenotypic features aligned with CMS subtypes harbouring mutations within the early stages of the glycosylation pathway. Additional features shared with the dystroglycanopathies include myopathic features, raised CK levels and variable mild cognitive delay. This syndrome underlines that CMS can occur in the absence of classic myasthenic manifestations such as ptosis and ophthalmoplegia or facial weakness, and links myasthenic disorders with dystroglycanopathies. This report should facilitate the recognition of this disorder, which is likely to be underdiagnosed and can benefit from symptomatic treatment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A combined experimental and in silico characterization to highlight additional structural features and properties of a potentially new drug

NASA Astrophysics Data System (ADS)

Bastos, Isadora T. S.; Costa, Fanny N.; Silva, Tiago F.; Barreiro, Eliezer J.; Lima, Lídia M.; Braz, Delson; Lombardo, Giuseppe M.; Punzo, Francesco; Ferreira, Fabio F.; Barroso, Regina C.

2017-10-01

LASSBio-1755 is a new cycloalkyl-N-acylhydrazone parent compound designed for the development of derivatives with antinociceptive and anti-inflammatory activities. Although single crystal X-ray diffraction has been considered as the golden standard in structure determination, we successfully used X-ray powder diffraction data in the structural determination of new synthesized compounds, in order to overcome the bottle-neck due to the difficulties experienced in harvesting good quality single crystals of the compounds. We therefore unequivocally assigned the relative configuration (E) to the imine double bond and a s-cis conformation of the amide function of the N-acylhydrazone compound. These features are confirmed by a computational analysis performed on the basis of molecular dynamics calculations, which are extended not only to the structural characteristics but also to the analysis of the anisotropic atomic displacement parameters, a further information - missed in a typical powder diffraction analysis. The so inferred data were used to perform additional cycles of refinement and eventually generate a new cif file with additional physical information. Furthermore, crystal morphology prediction was performed, which is in agreement with the experimental images acquired by scanning electron microscopy, thus providing useful information on possible alternative paths for better crystallization strategies.

Feature Selection from a Facial Image for Distinction of Sasang Constitution

PubMed Central

Koo, Imhoi; Kim, Jong Yeol; Kim, Myoung Geun

2009-01-01

Recently, oriental medicine has received attention for providing personalized medicine through consideration of the unique nature and constitution of individual patients. With the eventual goal of globalization, the current trend in oriental medicine research is the standardization by adopting western scientific methods, which could represent a scientific revolution. The purpose of this study is to establish methods for finding statistically significant features in a facial image with respect to distinguishing constitution and to show the meaning of those features. From facial photo images, facial elements are analyzed in terms of the distance, angle and the distance ratios, for which there are 1225, 61 250 and 749 700 features, respectively. Due to the very large number of facial features, it is quite difficult to determine truly meaningful features. We suggest a process for the efficient analysis of facial features including the removal of outliers, control for missing data to guarantee data confidence and calculation of statistical significance by applying ANOVA. We show the statistical properties of selected features according to different constitutions using the nine distances, 10 angles and 10 rates of distance features that are finally established. Additionally, the Sasang constitutional meaning of the selected features is shown here. PMID:19745013

Effects of anodizing parameters and heat treatment on nanotopographical features, bioactivity, and cell culture response of additively manufactured porous titanium.

PubMed

Amin Yavari, S; Chai, Y C; Böttger, A J; Wauthle, R; Schrooten, J; Weinans, H; Zadpoor, A A

2015-06-01

Anodizing could be used for bio-functionalization of the surfaces of titanium alloys. In this study, we use anodizing for creating nanotubes on the surface of porous titanium alloy bone substitutes manufactured using selective laser melting. Different sets of anodizing parameters (voltage: 10 or 20V anodizing time: 30min to 3h) are used for anodizing porous titanium structures that were later heat treated at 500°C. The nanotopographical features are examined using electron microscopy while the bioactivity of anodized surfaces is measured using immersion tests in the simulated body fluid (SBF). Moreover, the effects of anodizing and heat treatment on the performance of one representative anodized porous titanium structures are evaluated using in vitro cell culture assays using human periosteum-derived cells (hPDCs). It has been shown that while anodizing with different anodizing parameters results in very different nanotopographical features, i.e. nanotubes in the range of 20 to 55nm, anodized surfaces have limited apatite-forming ability regardless of the applied anodizing parameters. The results of in vitro cell culture show that both anodizing, and thus generation of regular nanotopographical feature, and heat treatment improve the cell culture response of porous titanium. In particular, cell proliferation measured using metabolic activity and DNA content was improved for anodized and heat treated as well as for anodized but not heat-treated specimens. Heat treatment additionally improved the cell attachment of porous titanium surfaces and upregulated expression of osteogenic markers. Anodized but not heat-treated specimens showed some limited signs of upregulated expression of osteogenic markers. In conclusion, while varying the anodizing parameters creates different nanotube structure, it does not improve apatite-forming ability of porous titanium. However, both anodizing and heat treatment at 500°C improve the cell culture response of porous titanium

Features of resilience

DOE PAGES

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; ...

2017-02-20

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. As a result, the proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Features of resilience

USGS Publications Warehouse

Connelly, Elizabeth B.; Allen, Craig R.; Hatfield, Kirk; Palma-Oliveira, José M.; Woods, David D.; Linkov, Igor

2017-01-01

The National Academy of Sciences (NAS) definition of resilience is used here to organize common concepts and synthesize a set of key features of resilience that can be used across diverse application domains. The features in common include critical functions (services), thresholds, cross-scale (both space and time) interactions, and memory and adaptive management. We propose a framework for linking these features to the planning, absorbing, recovering, and adapting phases identified in the NAS definition. The proposed delineation of resilience can be important in understanding and communicating resilience concepts.

Clinical and cytogenetic features of a Potocki-Lupski syndrome with the shortest 0.25Mb microduplication in 17p11.2 including RAI1.

PubMed

Lee, Cha Gon; Park, Sang-Jin; Yim, Shin-Young; Sohn, Young Bae

2013-08-01

Potocki-Lupski syndrome (PTLS [MIM 610883]) is a recently recognized microduplication syndrome associated with 17p11.2. It is characterized by mild facial dysmorphic features, hypermetropia, infantile hypotonia, failure to thrive, mental retardation, autistic spectrum disorders, behavioral abnormalities, sleep apnea, and cardiovascular anomalies. In several studies, the critical PTLS region was deduced to be 1.3Mb in length, and included RAI1 and 17 other genes. We report a 3-year-old Korean boy with the smallest duplication in 17p11.2 and a milder phenotype. He had no family history of neurologic disease or developmental delay and no history of seizure, autistic features, or behavior problems. He showed subtle facial dysmorphic features (dolichocephaly and a mildly asymmetric smile) and flat feet. All laboratory tests were normal and he had no evidence of internal organ anomalies. He was found to have mild intellectual disabilities (full scale IQ 65 on K-WPPSI) and language developmental delay (age of 2.2year-old on PRESS). Array comparative genomic hybridization (CGH) showed about a 0.25Mb microduplication on chromosome 17p11.2 containing four Refseq (NCBI reference sequence) genes, including RAI1 [arr 17p11.2(17,575,978-17,824,623)×3]. When compared with previously reported cases, the milder phenotype of our patient may be associated with the smallest duplication in 17p11.2, 0.25Mb in length. Copyright © 2012 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Tablet and Smartphone Accessibility Features in the Low Vision Rehabilitation

PubMed Central

Irvine, Danielle; Zemke, Alex; Pusateri, Gregg; Gerlach, Leah; Chun, Rob; Jay, Walter M.

2014-01-01

Abstract Tablet and smartphone use is rapidly increasing in developed countries. With this upsurge in popularity, the devices themselves are becoming more user-friendly for all consumers, including the visually impaired. Traditionally, visually impaired patients have received optical rehabilitation in the forms of microscopes, stand magnifiers, handheld magnifiers, telemicroscopes, and electronic magnification such as closed circuit televisions (CCTVs). In addition to the optical and financial limitations of traditional devices, patients do not always view them as being socially acceptable. For this reason, devices are often underutilised by patients due to lack of use in public forums or when among peers. By incorporating smartphones and tablets into a patient’s low vision rehabilitation, in addition to traditional devices, one provides versatile and mainstream options, which may also be less expensive. This article explains exactly what the accessibility features of tablets and smartphones are for the blind and visually impaired, how to access them, and provides an introduction on usage of the features. PMID:27928274

Feature Grouping and Selection Over an Undirected Graph.

PubMed

Yang, Sen; Yuan, Lei; Lai, Ying-Cheng; Shen, Xiaotong; Wonka, Peter; Ye, Jieping

2012-01-01

High-dimensional regression/classification continues to be an important and challenging problem, especially when features are highly correlated. Feature selection, combined with additional structure information on the features has been considered to be promising in promoting regression/classification performance. Graph-guided fused lasso (GFlasso) has recently been proposed to facilitate feature selection and graph structure exploitation, when features exhibit certain graph structures. However, the formulation in GFlasso relies on pairwise sample correlations to perform feature grouping, which could introduce additional estimation bias. In this paper, we propose three new feature grouping and selection methods to resolve this issue. The first method employs a convex function to penalize the pairwise l ∞ norm of connected regression/classification coefficients, achieving simultaneous feature grouping and selection. The second method improves the first one by utilizing a non-convex function to reduce the estimation bias. The third one is the extension of the second method using a truncated l 1 regularization to further reduce the estimation bias. The proposed methods combine feature grouping and feature selection to enhance estimation accuracy. We employ the alternating direction method of multipliers (ADMM) and difference of convex functions (DC) programming to solve the proposed formulations. Our experimental results on synthetic data and two real datasets demonstrate the effectiveness of the proposed methods.

Additives

NASA Technical Reports Server (NTRS)

Smalheer, C. V.

1973-01-01

The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.

Terrain-driven unstructured mesh development through semi-automatic vertical feature extraction

NASA Astrophysics Data System (ADS)

Bilskie, Matthew V.; Coggin, David; Hagen, Scott C.; Medeiros, Stephen C.

2015-12-01

A semi-automated vertical feature terrain extraction algorithm is described and applied to a two-dimensional, depth-integrated, shallow water equation inundation model. The extracted features describe what are commonly sub-mesh scale elevation details (ridge and valleys), which may be ignored in standard practice because adequate mesh resolution cannot be afforded. The extraction algorithm is semi-automated, requires minimal human intervention, and is reproducible. A lidar-derived digital elevation model (DEM) of coastal Mississippi and Alabama serves as the source data for the vertical feature extraction. Unstructured mesh nodes and element edges are aligned to the vertical features and an interpolation algorithm aimed at minimizing topographic elevation error assigns elevations to mesh nodes via the DEM. The end result is a mesh that accurately represents the bare earth surface as derived from lidar with element resolution in the floodplain ranging from 15 m to 200 m. To examine the influence of the inclusion of vertical features on overland flooding, two additional meshes were developed, one without crest elevations of the features and another with vertical features withheld. All three meshes were incorporated into a SWAN+ADCIRC model simulation of Hurricane Katrina. Each of the three models resulted in similar validation statistics when compared to observed time-series water levels at gages and post-storm collected high water marks. Simulated water level peaks yielded an R2 of 0.97 and upper and lower 95% confidence interval of ∼ ± 0.60 m. From the validation at the gages and HWM locations, it was not clear which of the three model experiments performed best in terms of accuracy. Examination of inundation extent among the three model results were compared to debris lines derived from NOAA post-event aerial imagery, and the mesh including vertical features showed higher accuracy. The comparison of model results to debris lines demonstrates that additional

Feature-to-Feature Inference Under Conditions of Cue Restriction and Dimensional Correlation.

PubMed

Lancaster, Matthew E; Homa, Donald

2017-01-01

The present study explored feature-to-feature and label-to-feature inference in a category task for different category structures. In the correlated condition, each of the 4 dimensions comprising the category was positively correlated to each other and to the category label. In the uncorrelated condition, no correlation existed between the 4 dimensions comprising the category, although the dimension to category label correlation matched that of the correlated condition. After learning, participants made inference judgments of a missing feature, given 1, 2, or 3 feature cues; on half the trials, the category label was also included as a cue. The results showed superior inference of features following training on the correlated structure, with accurate inference when only a single feature was presented. In contrast, a single-feature cue resulted in chance levels of inference for the uncorrelated structure. Feature inference systematically improved with number of cues after training on the correlated structure. Surprisingly, a similar outcome was obtained for the uncorrelated structure, an outcome that must have reflected mediation via the category label. A descriptive model is briefly introduced to explain the results, with a suggestion that this paradigm might be profitably extended to hierarchical structures where the levels of feature-to-feature inference might vary with the depth of the hierarchy.

Prostate cancer detection: Fusion of cytological and textural features

PubMed Central

Nguyen, Kien; Jain, Anil K.; Sabata, Bikash

2011-01-01

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification. PMID:22811959

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.

Metacatalog of Planetary Surface Features for Multicriteria Evaluation of Surface Evolution: the Integrated Planetary Feature Database

NASA Astrophysics Data System (ADS)

Hargitai, Henrik

2016-10-01

We have created a metacatalog, or catalog or catalogs, of surface features of Mars that also includes the actual data in the catalogs listed. The goal is to make mesoscale surface feature databases available in one place, in a GIS-ready format. The databases can be directly imported to ArcGIS or other GIS platforms, like Google Mars. Some of the catalogs in our database are also ingested into the JMARS platform.All catalogs have been previously published in a peer-reviewed journal, but they may contain updates of the published catalogs. Many of the catalogs are "integrated", i.e. they merge databases or information from various papers on the same topic, including references to each individual features listed.Where available, we have included shapefiles with polygon or linear features, however, most of the catalogs only contain point data of their center points and morphological data.One of the unexpected results of the planetary feature metacatalog is that some features have been described by several papers, using different, i.e., conflicting designations. This shows the need for the development of an identification system suitable for mesoscale (100s m to km sized) features that tracks papers and thus prevents multiple naming of the same feature.The feature database can be used for multicriteria analysis of a terrain, thus enables easy distribution pattern analysis and the correlation of the distribution of different landforms and features on Mars. Such catalog makes a scientific evaluation of potential landing sites easier and more effective during the selection process and also supports automated landing site selections.The catalog is accessible at https://planetarydatabase.wordpress.com/.

The additional lateralizing and localizing value of the postictal EEG in frontal lobe epilepsy.

PubMed

Whitehead, Kimberley; Gollwitzer, Stephanie; Millward, Helen; Wehner, Tim; Scott, Catherine; Diehl, Beate

2016-03-01

The aim of this study was to describe the additional lateralizing and localizing value of the postictal EEG in frontal lobe epilepsy (FLE). The ictal EEG in FLE is frequently challenging to localize. We identified patients investigated for epilepsy surgery with unilateral FLE based on consistent semiology, a clear lesion and/or with frontal onset on intracranial EEG. A one hour section of postictal EEG was analyzed by two raters for new or activated EEG features and it was assessed whether these features offered additional information when compared to the ictal EEG. Postictal features assessed included asymmetrical return of the posterior dominant rhythm and potentiated lateralized or regional frontal slowing, spikes or sharp waves. Thirty-eight patients were included who had a combined total of ninety-six seizures. 47/96 (49%) postictal periods contained correctly lateralizing or localizing information. The sensitivity for asymmetrical return of the posterior dominant rhythm was 24%. The sensitivity for regional frontal slow and frontal spikes was 23% and 20% respectively. Further analysis showed that in 14/38 (39%) patients, at least one seizure with an unhelpful ictal EEG was followed by postictal EEG features that added new localizing or lateralizing information. A subgroup of 11 patients who were ⩾1 year seizure-free (ILAE class 1) and thus classified as having a 'gold-standard' FLE diagnosis were analyzed separately and it was found that 14/30 of their seizures (47%) had extra postictal information. The new postictal information was always concordant with the ultimate diagnosis, except for asymmetric postictal return of background activity ipsilateral to the epileptogenic zone in three patients. This study shows that a close examination of the postictal EEG can offer additional information which can contribute to the identification of a potentially resectable epileptogenic zone. Copyright © 2015 International Federation of Clinical Neurophysiology

Semantic Features for Classifying Referring Search Terms

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

May, Chandler J.; Henry, Michael J.; McGrath, Liam R.

2012-05-11

When an internet user clicks on a result in a search engine, a request is submitted to the destination web server that includes a referrer field containing the search terms given by the user. Using this information, website owners can analyze the search terms leading to their websites to better understand their visitors needs. This work explores some of the features that can be used for classification-based analysis of such referring search terms. We present initial results for the example task of classifying HTTP requests countries of origin. A system that can accurately predict the country of origin from querymore » text may be a valuable complement to IP lookup methods which are susceptible to the obfuscation of dereferrers or proxies. We suggest that the addition of semantic features improves classifier performance in this example application. We begin by looking at related work and presenting our approach. After describing initial experiments and results, we discuss paths forward for this work.« less

[Mutation analysis of FGFR3 gene in a family featuring hereditary dwarfism].

PubMed

Zhang, Qiong; Jiang, Hai-ou; Quan, Qing-li; Li, Jun; He, Ting; Huang, Xue-shuang

2011-12-01

To investigate the clinical symptoms and potential mutation in FGFR3 gene for a family featuring hereditary dwarfism in order to attain diagnosis and provide prenatal diagnosis. Five patients and two unaffected relatives from the family, in addition with 100 healthy controls, were recruited. Genome DNA was extracted. Exons 10 and 13 of the FGFR3 gene were amplified using polymerase chain reaction (PCR). PCR products were sequenced in both directions. All patients had similar features including short stature, short limbs, lumbar hyperlordosis but normal craniofacial features. A heterozygous mutation G1620T (N540K) was identified in the cDNA from all patients but not in the unaffected relatives and 100 control subjects. A heterozygous G380R mutation was excluded. The hereditary dwarfism featured by this family has been caused by hypochondroplasia (HCH) due to a N540K mutation in the FGFR3 gene.

Real-Time Detection and Measurement of Eye Features from Color Images

PubMed Central

Borza, Diana; Darabant, Adrian Sergiu; Danescu, Radu

2016-01-01

The accurate extraction and measurement of eye features is crucial to a variety of domains, including human-computer interaction, biometry, and medical research. This paper presents a fast and accurate method for extracting multiple features around the eyes: the center of the pupil, the iris radius, and the external shape of the eye. These features are extracted using a multistage algorithm. On the first stage the pupil center is localized using a fast circular symmetry detector and the iris radius is computed using radial gradient projections, and on the second stage the external shape of the eye (of the eyelids) is determined through a Monte Carlo sampling framework based on both color and shape information. Extensive experiments performed on a different dataset demonstrate the effectiveness of our approach. In addition, this work provides eye annotation data for a publicly-available database. PMID:27438838

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor

PubMed Central

Hast, Anders; Wählby, Carolina; Sintorn, Ida-Maria

2017-01-01

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images. PMID:29190737

Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)

NASA Astrophysics Data System (ADS)

Starkey, Andrew; Usman Ahmad, Aliyu; Hamdoun, Hassan

2017-10-01

This paper investigates the application of a novel method for classification called Feature Weighted Self Organizing Map (FWSOM) that analyses the topology information of a converged standard Self Organizing Map (SOM) to automatically guide the selection of important inputs during training for improved classification of data with redundant inputs, examined against two traditional approaches namely neural networks and Support Vector Machines (SVM) for the classification of EEG data as presented in previous work. In particular, the novel method looks to identify the features that are important for classification automatically, and in this way the important features can be used to improve the diagnostic ability of any of the above methods. The paper presents the results and shows how the automated identification of the important features successfully identified the important features in the dataset and how this results in an improvement of the classification results for all methods apart from linear discriminatory methods which cannot separate the underlying nonlinear relationship in the data. The FWSOM in addition to achieving higher classification accuracy has given insights into what features are important in the classification of each class (left and right-hand movements), and these are corroborated by already published work in this area.

Internal versus external features in triggering the brain waveforms for conjunction and feature faces in recognition.

PubMed

Nie, Aiqing; Jiang, Jingguo; Fu, Qiao

2014-08-20

Previous research has found that conjunction faces (whose internal features, e.g. eyes, nose, and mouth, and external features, e.g. hairstyle and ears, are from separate studied faces) and feature faces (partial features of these are studied) can produce higher false alarms than both old and new faces (i.e. those that are exactly the same as the studied faces and those that have not been previously presented) in recognition. The event-related potentials (ERPs) that relate to conjunction and feature faces at recognition, however, have not been described as yet; in addition, the contributions of different facial features toward ERPs have not been differentiated. To address these issues, the present study compared the ERPs elicited by old faces, conjunction faces (the internal and the external features were from two studied faces), old internal feature faces (whose internal features were studied), and old external feature faces (whose external features were studied) with those of new faces separately. The results showed that old faces not only elicited an early familiarity-related FN400, but a more anterior distributed late old/new effect that reflected recollection. Conjunction faces evoked similar late brain waveforms as old internal feature faces, but not to old external feature faces. These results suggest that, at recognition, old faces hold higher familiarity than compound faces in the profiles of ERPs and internal facial features are more crucial than external ones in triggering the brain waveforms that are characterized as reflecting the result of familiarity.

Tardigrada of Ireland: a review of records and an updated checklist of species including a new addition to the Irish fauna.

PubMed

DeMilio, Erica; Lawton, Colin; Marley, Nigel J

2016-01-01

The phylum Tardigrada was not recorded in Ireland until the Clare Island Survey of 1909-1911, with only rare subsequent reports on Irish tardigrade species. In recent decades, significant taxonomic revision has occurred within Tardigrada. This has resulted in the need for a review of all known historical records from Ireland and Northern Ireland in order to produce an updated checklist of valid taxa. The new checklist includes fifty-one tardigrade species and subspecies including a new addition to the Irish fauna reported herein, Echiniscus quadrispinosus quadrispinosus Richters, 1902 from Newtown, Ballyvaughan, Co. Clare.

Noble reaction features of bromoborane in oxidative addition of B-Br σ-bond to [M(PMe3)2] (M=Pt or Pd): theoretical study.

PubMed

Zeng, Guixiang; Sakaki, Shigeyoshi

2011-06-06

Through detailed calculations by density functional theory and second-order Møller-Plesset perturbation theory (MP2) to fourth-order Møller-Plesset perturbation theory including single, double, and quadruple excitations [MP4(SDQ)] methods, we investigated the oxidative addition of the B-Br bond of dibromo(trimethylsiloxy)borane [Br(2)B(OSiMe(3))] to Pt(0) and Pd(0) complexes [M(PMe(3))(2)] (M = Pt or Pd) directly yielding a trans bromoboryl complex trans-[MBr{BBr(OSiMe(3))}(PMe(3))(2)]. Two reaction pathways are found for this reaction: One is a nucleophilic attack pathway which directly leads to the trans product, and the other is a stepwise reaction pathway which occurs through successive cis oxidative addition of the B-Br bond to [M(PMe(3))(2)] and thermal cis-trans isomerization. In the Pt system, the former course occurs with a much smaller energy barrier (E(a) = 5.8 kcal/mol) than the latter one (E(a) = 20.7 kcal/mol), where the DFT-calculated E(a) value is presented hereafter. In the Pd system, only the latter course is found in which the rate-determining steps is the cis-trans isomerization with the E(a) of 15.1 kcal/mol. Interestingly, the thermal cis-trans isomerization occurs on the singlet potential energy surface against our expectation. This unexpected result is understood in terms of the strong donation ability of the boryl group. Detailed analyses of electronic processes in all these reaction steps as well as remarkable characteristic features of [Br(2)B(OSiMe(3))] are also provided. © 2011 American Chemical Society

Retinal vasculature classification using novel multifractal features

NASA Astrophysics Data System (ADS)

Ding, Y.; Ward, W. O. C.; Duan, Jinming; Auer, D. P.; Gowland, Penny; Bai, L.

2015-11-01

Retinal blood vessels have been implicated in a large number of diseases including diabetic retinopathy and cardiovascular diseases, which cause damages to retinal blood vessels. The availability of retinal vessel imaging provides an excellent opportunity for monitoring and diagnosis of retinal diseases, and automatic analysis of retinal vessels will help with the processes. However, state of the art vascular analysis methods such as counting the number of branches or measuring the curvature and diameter of individual vessels are unsuitable for the microvasculature. There has been published research using fractal analysis to calculate fractal dimensions of retinal blood vessels, but so far there has been no systematic research extracting discriminant features from retinal vessels for classifications. This paper introduces new methods for feature extraction from multifractal spectra of retinal vessels for classification. Two publicly available retinal vascular image databases are used for the experiments, and the proposed methods have produced accuracies of 85.5% and 77% for classification of healthy and diabetic retinal vasculatures. Experiments show that classification with multiple fractal features produces better rates compared with methods using a single fractal dimension value. In addition to this, experiments also show that classification accuracy can be affected by the accuracy of vessel segmentation algorithms.

Detection of Coronal Mass Ejections Using Multiple Features and Space-Time Continuity

NASA Astrophysics Data System (ADS)

Zhang, Ling; Yin, Jian-qin; Lin, Jia-ben; Feng, Zhi-quan; Zhou, Jin

2017-07-01

Coronal Mass Ejections (CMEs) release tremendous amounts of energy in the solar system, which has an impact on satellites, power facilities and wireless transmission. To effectively detect a CME in Large Angle Spectrometric Coronagraph (LASCO) C2 images, we propose a novel algorithm to locate the suspected CME regions, using the Extreme Learning Machine (ELM) method and taking into account the features of the grayscale and the texture. Furthermore, space-time continuity is used in the detection algorithm to exclude the false CME regions. The algorithm includes three steps: i) define the feature vector which contains textural and grayscale features of a running difference image; ii) design the detection algorithm based on the ELM method according to the feature vector; iii) improve the detection accuracy rate by using the decision rule of the space-time continuum. Experimental results show the efficiency and the superiority of the proposed algorithm in the detection of CMEs compared with other traditional methods. In addition, our algorithm is insensitive to most noise.

External facial features modify the representation of internal facial features in the fusiform face area.

PubMed

Axelrod, Vadim; Yovel, Galit

2010-08-15

Most studies of face identity have excluded external facial features by either removing them or covering them with a hat. However, external facial features may modify the representation of internal facial features. Here we assessed whether the representation of face identity in the fusiform face area (FFA), which has been primarily studied for internal facial features, is modified by differences in external facial features. We presented faces in which external and internal facial features were manipulated independently. Our findings show that the FFA was sensitive to differences in external facial features, but this effect was significantly larger when the external and internal features were aligned than misaligned. We conclude that the FFA generates a holistic representation in which the internal and the external facial features are integrated. These results indicate that to better understand real-life face recognition both external and internal features should be included. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Using different classification models in wheat grading utilizing visual features

NASA Astrophysics Data System (ADS)

Basati, Zahra; Rasekh, Mansour; Abbaspour-Gilandeh, Yousef

2018-04-01

Wheat is one of the most important strategic crops in Iran and in the world. The major component that distinguishes wheat from other grains is the gluten section. In Iran, sunn pest is one of the most important factors influencing the characteristics of wheat gluten and in removing it from a balanced state. The existence of bug-damaged grains in wheat will reduce the quality and price of the product. In addition, damaged grains reduce the enrichment of wheat and the quality of bread products. In this study, after preprocessing and segmentation of images, 25 features including 9 colour features, 10 morphological features, and 6 textual statistical features were extracted so as to classify healthy and bug-damaged wheat grains of Azar cultivar of four levels of moisture content (9, 11.5, 14 and 16.5% w.b.) and two lighting colours (yellow light, the composition of yellow and white lights). Using feature selection methods in the WEKA software and the CfsSubsetEval evaluator, 11 features were chosen as inputs of artificial neural network, decision tree and discriment analysis classifiers. The results showed that the decision tree with the J.48 algorithm had the highest classification accuracy of 90.20%. This was followed by artificial neural network classifier with the topology of 11-19-2 and discrimient analysis classifier at 87.46 and 81.81%, respectively

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 4 2011-10-01 2011-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 4 2013-10-01 2013-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 4 2012-10-01 2012-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

48 CFR 452.236-70 - Additive or Deductive Items.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 48 Federal Acquisition Regulations System 4 2014-10-01 2014-10-01 false Additive or Deductive... Additive or Deductive Items. As prescribed in 436.205, insert the following provision: Additive or... listed in the schedule) those additive or deductive bid items providing the most features of the work...

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Tardigrada of Ireland: a review of records and an updated checklist of species including a new addition to the Irish fauna

PubMed Central

DeMilio, Erica; Lawton, Colin; Marley, Nigel J.

2016-01-01

Abstract The phylum Tardigrada was not recorded in Ireland until the Clare Island Survey of 1909–1911, with only rare subsequent reports on Irish tardigrade species. In recent decades, significant taxonomic revision has occurred within Tardigrada. This has resulted in the need for a review of all known historical records from Ireland and Northern Ireland in order to produce an updated checklist of valid taxa. The new checklist includes fifty-one tardigrade species and subspecies including a new addition to the Irish fauna reported herein, Echiniscus quadrispinosus quadrispinosus Richters, 1902 from Newtown, Ballyvaughan, Co. Clare. PMID:27667947

Nematode.net update 2011: addition of data sets and tools featuring next-generation sequencing data

PubMed Central

Martin, John; Abubucker, Sahar; Heizer, Esley; Taylor, Christina M.; Mitreva, Makedonka

2012-01-01

Nematode.net (http://nematode.net) has been a publicly available resource for studying nematodes for over a decade. In the past 3 years, we reorganized Nematode.net to provide more user-friendly navigation through the site, a necessity due to the explosion of data from next-generation sequencing platforms. Organism-centric portals containing dynamically generated data are available for over 56 different nematode species. Next-generation data has been added to the various data-mining portals hosted, including NemaBLAST and NemaBrowse. The NemaPath metabolic pathway viewer builds associations using KOs, rather than ECs to provide more accurate and fine-grained descriptions of proteins. Two new features for data analysis and comparative genomics have been added to the site. NemaSNP enables the user to perform population genetics studies in various nematode populations using next-generation sequencing data. HelmCoP (Helminth Control and Prevention) as an independent component of Nematode.net provides an integrated resource for storage, annotation and comparative genomics of helminth genomes to aid in learning more about nematode genomes, as well as drug, pesticide, vaccine and drug target discovery. With this update, Nematode.net will continue to realize its original goal to disseminate diverse bioinformatic data sets and provide analysis tools to the broad scientific community in a useful and user-friendly manner. PMID:22139919

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

PubMed Central

Liu, Aiming; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-01-01

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain–computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain–computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain–computer interface systems. PMID:29117100

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata.

PubMed

Liu, Aiming; Chen, Kun; Liu, Quan; Ai, Qingsong; Xie, Yi; Chen, Anqi

2017-11-08

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features, which not only create an additional overhead of managing the space complexity, but also might include outliers, thereby reducing classification accuracy. The firefly algorithm (FA) can adaptively select the best subset of features, and improve classification accuracy. However, the FA is easily entrapped in a local optimum. To solve this problem, this paper proposes a method of combining the firefly algorithm and learning automata (LA) to optimize feature selection for motor imagery EEG. We employed a method of combining common spatial pattern (CSP) and local characteristic-scale decomposition (LCD) algorithms to obtain a high dimensional feature set, and classified it by using the spectral regression discriminant analysis (SRDA) classifier. Both the fourth brain-computer interface competition data and real-time data acquired in our designed experiments were used to verify the validation of the proposed method. Compared with genetic and adaptive weight particle swarm optimization algorithms, the experimental results show that our proposed method effectively eliminates redundant features, and improves the classification accuracy of MI EEG signals. In addition, a real-time brain-computer interface system was implemented to verify the feasibility of our proposed methods being applied in practical brain-computer interface systems.

Multi-tube fuel nozzle with mixing features

DOEpatents

Hughes, Michael John

2014-04-22

A system includes a multi-tube fuel nozzle having an inlet plate and a plurality of tubes adjacent the inlet plate. The inlet plate includes a plurality of apertures, and each aperture includes an inlet feature. Each tube of the plurality of tubes is coupled to an aperture of the plurality of apertures. The multi-tube fuel nozzle includes a differential configuration of inlet features among the plurality of tubes.

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features

PubMed Central

Liu, Zhiya; Song, Xiaohong; Seger, Carol A.

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting. PMID:26274332

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features.

PubMed

Liu, Zhiya; Song, Xiaohong; Seger, Carol A

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting.

New Nomenclatures for Heat Treatments of Additively Manufactured Titanium Alloys

NASA Astrophysics Data System (ADS)

Baker, Andrew H.; Collins, Peter C.; Williams, James C.

2017-07-01

The heat-treatment designations and microstructure nomenclatures for many structural metallic alloys were established for traditional metals processing, such as casting, hot rolling or forging. These terms do not necessarily apply for additively manufactured (i.e., three-dimensionally printed or "3D printed") metallic structures. The heat-treatment terminology for titanium alloys generally implies the heat-treatment temperatures and their sequence relative to a thermomechanical processing step (e.g., forging, rolling). These designations include: β-processing, α + β-processing, β-annealing, duplex annealing and mill annealing. Owing to the absence of a thermomechanical processing step, these traditional designations can pose a problem when titanium alloys are first produced via additive manufacturing, and then heat-treated. This communication proposes new nomenclatures for heat treatments of additively manufactured titanium alloys, and uses the distinct microstructural features to provide a correlation between traditional nomenclature and the proposed nomenclature.

Cytomorphological features of ALK-positive lung adenocarcinomas: psammoma bodies and signet ring cells.

PubMed

Pareja, Fresia; Crapanzano, John P; Mansukhani, Mahesh M; Bulman, William A; Saqi, Anjali

2015-03-01

Correlation between histology and genotype has been described in lung adenocarcinomas. For example, studies have demonstrated that adenocarcinomas with an anaplastic lymphoma kinase (ALK) gene rearrangement may have mucinous features. The objective of the current study was to determine whether a similar association can be identified in cytological specimens. A retrospective search for ALK-rearranged cytopathology (CP) and surgical pathology (SP) lung carcinomas was conducted. Additional ALK-negative (-) lung adenocarcinomas served as controls. For CP and SP cases, the clinical data (i.e., age, sex, and smoking history), architecture, nuclear features, presence of mucin-containing cells (including signet ring cells), and any additional salient characteristics were evaluated. The search yielded 20 ALK-positive (+) adenocarcinomas. Compared with patients with ALK(-) lung adenocarcinomas (33 patients; 12 with epidermal growth factor receptor [EGFR]-mutation, 11 with Kristen rat sarcoma [KRAS]-mutation, and 10 wild-type adenocarcinomas), patients with ALK(+) adenocarcinoma presented at a younger age; and there was no correlation noted with sex or smoking status. The most common histological pattern in SP was papillary/micropapillary. Mucinous features were associated with ALK rearrangement in SP specimens. Signet ring cells and psammoma bodies were evident in and significantly associated with ALK(+) SP and CP specimens. However, psammoma bodies were observed in rare adenocarcinomas with an EGFR mutation. Both the ALK(+) and ALK(-) groups had mostly high nuclear grade. Salient features, including signet ring cells and psammoma bodies, were found to be significantly associated with ALK(+) lung adenocarcinomas and are identifiable on CP specimens. Recognizing these may be especially helpful in the molecular triage of scant CP samples. © 2014 American Cancer Society.

Predicting couple therapy outcomes based on speech acoustic features

PubMed Central

Nasir, Md; Baucom, Brian Robert; Narayanan, Shrikanth

2017-01-01

Automated assessment and prediction of marital outcome in couples therapy is a challenging task but promises to be a potentially useful tool for clinical psychologists. Computational approaches for inferring therapy outcomes using observable behavioral information obtained from conversations between spouses offer objective means for understanding relationship dynamics. In this work, we explore whether the acoustics of the spoken interactions of clinically distressed spouses provide information towards assessment of therapy outcomes. The therapy outcome prediction task in this work includes detecting whether there was a relationship improvement or not (posed as a binary classification) as well as discerning varying levels of improvement or decline in the relationship status (posed as a multiclass recognition task). We use each interlocutor’s acoustic speech signal characteristics such as vocal intonation and intensity, both independently and in relation to one another, as cues for predicting the therapy outcome. We also compare prediction performance with one obtained via standardized behavioral codes characterizing the relationship dynamics provided by human experts as features for automated classification. Our experiments, using data from a longitudinal clinical study of couples in distressed relations, showed that predictions of relationship outcomes obtained directly from vocal acoustics are comparable or superior to those obtained using human-rated behavioral codes as prediction features. In addition, combining direct signal-derived features with manually coded behavioral features improved the prediction performance in most cases, indicating the complementarity of relevant information captured by humans and machine algorithms. Additionally, considering the vocal properties of the interlocutors in relation to one another, rather than in isolation, showed to be important for improving the automatic prediction. This finding supports the notion that behavioral

Major histocompatibility complex harbors widespread genotypic variability of non-additive risk of rheumatoid arthritis including epistasis.

PubMed

Wei, Wen-Hua; Bowes, John; Plant, Darren; Viatte, Sebastien; Yarwood, Annie; Massey, Jonathan; Worthington, Jane; Eyre, Stephen

2016-04-25

Genotypic variability based genome-wide association studies (vGWASs) can identify potentially interacting loci without prior knowledge of the interacting factors. We report a two-stage approach to make vGWAS applicable to diseases: firstly using a mixed model approach to partition dichotomous phenotypes into additive risk and non-additive environmental residuals on the liability scale and secondly using the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups per marker. We found widespread significant (P < 2.5e-05) vGWAS signals within the major histocompatibility complex (MHC) across all three study cohorts of rheumatoid arthritis. We further identified 10 epistatic interactions between the vGWAS signals independent of the MHC additive effects, each with a weak effect but jointly explained 1.9% of phenotypic variance. PTPN22 was also identified in the discovery cohort but replicated in only one independent cohort. Combining the three cohorts boosted power of vGWAS and additionally identified TYK2 and ANKRD55. Both PTPN22 and TYK2 had evidence of interactions reported elsewhere. We conclude that vGWAS can help discover interacting loci for complex diseases but require large samples to find additional signals.

Features of Wisdom: Prototypical Attributes of Wise People.

ERIC Educational Resources Information Center

Maciel, Anna G.; And Others

Features of everyday conceptions of a "wise person" were examined, based on a model of wisdom-related knowledge (Baltes & Smith, 1990). The goal was to examine whether the psychological theory underlying this model is consistent with lay conceptions of wisdom, and whether everyday conceptions contain additional features not contained…

Poliosis overlying a nevus with blue nevus features.

PubMed

Young, Lorraine C; Van Dyke, Gregory S; Lipton, Shira; Binder, Scott W

2008-02-28

Poliosis is a localized patch of gray or white hair. Because it can be seen with a variety of disorders and drugs, a full history and exam is indicated. Additionally, it can be associated with underlying benign and malignant tumors, necessitating histological identification. We review the lesions that are reported with poliosis. In addition, we will report a case of poliosis overlying an intradermal nevus with congenital as well as blue nevus features. To the best of our knowledge, blue nevus features associated with poliosis have not been previously described.

Confidence-Based Feature Acquisition

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; desJardins, Marie; MacGlashan, James

2010-01-01

Confidence-based Feature Acquisition (CFA) is a novel, supervised learning method for acquiring missing feature values when there is missing data at both training (learning) and test (deployment) time. To train a machine learning classifier, data is encoded with a series of input features describing each item. In some applications, the training data may have missing values for some of the features, which can be acquired at a given cost. A relevant JPL example is that of the Mars rover exploration in which the features are obtained from a variety of different instruments, with different power consumption and integration time costs. The challenge is to decide which features will lead to increased classification performance and are therefore worth acquiring (paying the cost). To solve this problem, CFA, which is made up of two algorithms (CFA-train and CFA-predict), has been designed to greedily minimize total acquisition cost (during training and testing) while aiming for a specific accuracy level (specified as a confidence threshold). With this method, it is assumed that there is a nonempty subset of features that are free; that is, every instance in the data set includes these features initially for zero cost. It is also assumed that the feature acquisition (FA) cost associated with each feature is known in advance, and that the FA cost for a given feature is the same for all instances. Finally, CFA requires that the base-level classifiers produce not only a classification, but also a confidence (or posterior probability).

FEX: A Knowledge-Based System For Planimetric Feature Extraction

NASA Astrophysics Data System (ADS)

Zelek, John S.

1988-10-01

Topographical planimetric features include natural surfaces (rivers, lakes) and man-made surfaces (roads, railways, bridges). In conventional planimetric feature extraction, a photointerpreter manually interprets and extracts features from imagery on a stereoplotter. Visual planimetric feature extraction is a very labour intensive operation. The advantages of automating feature extraction include: time and labour savings; accuracy improvements; and planimetric data consistency. FEX (Feature EXtraction) combines techniques from image processing, remote sensing and artificial intelligence for automatic feature extraction. The feature extraction process co-ordinates the information and knowledge in a hierarchical data structure. The system simulates the reasoning of a photointerpreter in determining the planimetric features. Present efforts have concentrated on the extraction of road-like features in SPOT imagery. Keywords: Remote Sensing, Artificial Intelligence (AI), SPOT, image understanding, knowledge base, apars.

Local Feature Selection for Data Classification.

PubMed

Armanfard, Narges; Reilly, James P; Komeili, Majid

2016-06-01

Typical feature selection methods choose an optimal global feature subset that is applied over all regions of the sample space. In contrast, in this paper we propose a novel localized feature selection (LFS) approach whereby each region of the sample space is associated with its own distinct optimized feature set, which may vary both in membership and size across the sample space. This allows the feature set to optimally adapt to local variations in the sample space. An associated method for measuring the similarities of a query datum to each of the respective classes is also proposed. The proposed method makes no assumptions about the underlying structure of the samples; hence the method is insensitive to the distribution of the data over the sample space. The method is efficiently formulated as a linear programming optimization problem. Furthermore, we demonstrate the method is robust against the over-fitting problem. Experimental results on eleven synthetic and real-world data sets demonstrate the viability of the formulation and the effectiveness of the proposed algorithm. In addition we show several examples where localized feature selection produces better results than a global feature selection method.

On the influence of additive and multiplicative noise on holes in dissipative systems.

PubMed

Descalzi, Orazio; Cartes, Carlos; Brand, Helmut R

2017-05-01

We investigate the influence of noise on deterministically stable holes in the cubic-quintic complex Ginzburg-Landau equation. Inspired by experimental possibilities, we specifically study two types of noise: additive noise delta-correlated in space and spatially homogeneous multiplicative noise on the formation of π-holes and 2π-holes. Our results include the following main features. For large enough additive noise, we always find a transition to the noisy version of the spatially homogeneous finite amplitude solution, while for sufficiently large multiplicative noise, a collapse occurs to the zero amplitude solution. The latter type of behavior, while unexpected deterministically, can be traced back to a characteristic feature of multiplicative noise; the zero solution acts as the analogue of an absorbing boundary: once trapped at zero, the system cannot escape. For 2π-holes, which exist deterministically over a fairly small range of values of subcriticality, one can induce a transition to a π-hole (for additive noise) or to a noise-sustained pulse (for multiplicative noise). This observation opens the possibility of noise-induced switching back and forth from and to 2π-holes.

A Search Engine Features Comparison.

ERIC Educational Resources Information Center

Vorndran, Gerald

Until recently, the World Wide Web (WWW) public access search engines have not included many of the advanced commands, options, and features commonly available with the for-profit online database user interfaces, such as DIALOG. This study evaluates the features and characteristics common to both types of search interfaces, examines the Web search…

Gas and isotope chemistry of thermal features in Yellowstone National Park, Wyoming

USGS Publications Warehouse

Bergfeld, D.; Lowenstern, Jacob B.; Hunt, Andrew G.; Shanks, W.C. Pat; Evans, William

2011-01-01

This report presents 130 gas analyses and 31 related water analyses on samples collected from thermal features at Yellowstone between 2003 and 2009. An overview of previous studies of gas emissions at Yellowstone is also given. The analytical results from the present study include bulk chemistry of gases and waters and isotope values for water and steam (delta18O, dealtaD), carbon dioxide (delta13C only), methane (delta13C only), helium, neon, and argon. We include appendixes containing photos of sample sites, geographic information system (GIS) files including shape and kml formats, and analytical results in spreadsheets. In addition, we provide a lengthy discussion of previous work on gas chemistry at Yellowstone and a general discussion of the implications of our results. We demonstrate that gases collected from different thermal areas often have distinct chemical signatures, and that differences across the thermal areas are not a simple function of surface temperatures or the type of feature. Instead, gas chemistry and isotopic composition are linked to subsurface lithologies and varying contributions from magmatic, crustal, and meteoric sources.

MCNP4A: Features and philosophy

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

Hendricks, J.S.

This paper describes MCNP, states its philosophy, introduces a number of new features becoming available with version MCNP4A, and answers a number of questions asked by participants in the workshop. MCNP is a general-purpose three-dimensional neutron, photon and electron transport code. Its philosophy is ``Quality, Value and New Features.`` Quality is exemplified by new software quality assurance practices and a program of benchmarking against experiments. Value includes a strong emphasis on documentation and code portability. New features are the third priority. MCNP4A is now available at Los Alamos. New features in MCNP4A include enhanced statistical analysis, distributed processor multitasking, newmore » photon libraries, ENDF/B-VI capabilities, X-Windows graphics, dynamic memory allocation, expanded criticality output, periodic boundaries, plotting of particle tracks via SABRINA, and many other improvements. 23 refs.« less

Mobile personal health records: an evaluation of features and functionality.

PubMed

Kharrazi, Hadi; Chisholm, Robin; VanNasdale, Dean; Thompson, Benjamin

2012-09-01

To evaluate stand-alone mobile personal health record (mPHR) applications for the three leading cellular phone platforms (iOS, BlackBerry, and Android), assessing each for content, function, security, and marketing characteristics. Nineteen stand-alone mPHR applications (8 for iOS, 5 for BlackBerry, and 6 for Android) were identified and evaluated. Main criteria used to include mPHRs were: operating standalone on a mobile platform; not requiring external connectivity; and covering a wide range of health topics. Selected mPHRs were analyzed considering product characteristics, data elements, and application features. We also reviewed additional features such as marketing tactics. Within and between the different mobile platforms attributes for the mPHR were highly variable. None of the mPHRs contained all attributes included in our evaluation. The top four mPHRs contained 13 of the 14 features omitting only the in-case-of emergency feature. Surprisingly, seven mPHRs lacked basic security measures as important as password protection. The mPHRs were relatively inexpensive: ranging from no cost to $9.99. The mPHR application cost varied in some instances based on whether it supported single or multiple users. Ten mPHRs supported multiple user profiles. Notably, eight mPHRs used scare tactics as marketing strategy. mPHR is an emerging health care technology. The majority of existing mPHR apps is limited by at least one of the attributes considered for this study; however, as the mobile market continues to expand it is likely that more comprehensive mPHRs will be developed in the near future. New advancements in mobile technology can be utilized to enhance mPHRs by long-term patient empowerment features. Marketing strategies for mPHRs should target specific subpopulations and avoid scare tactics. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Supplementary Microstructural Features Induced During Laser Surface Melting of Thermally Sprayed Inconel 625 Coatings

NASA Astrophysics Data System (ADS)

Ahmed, Nauman; Voisey, K. T.; McCartney, D. G.

2014-02-01

Laser surface melting of thermally sprayed coatings has the potential to enhance their corrosion properties by incorporating favorable microstructural changes. Besides homogenizing the as-sprayed structure, laser melting may induce certain microstructural modifications (i.e., supplementary features) in addition to those that directly improve the corrosion performance. Such features, being a direct result of the laser treatment process, are described in this paper which is part of a broader study in which high velocity oxy-fuel sprayed Inconel 625 coatings on mild-steel substrates were treated with a diode laser and the modified microstructure characterized using optical and scanning electron microscopy and x-ray diffraction. The laser treated coating features several different zones, including a region with a microstructure in which there is a continuous columnar dendritic structure through a network of retained oxide stringers.

Premotor and non-motor features of Parkinson’s disease

PubMed Central

Goldman, Jennifer G.; Postuma, Ron

2014-01-01

Purpose of review This review highlights recent advances in premotor and non-motor features in Parkinson’s disease, focusing on these issues in the context of prodromal and early stage Parkinson’s disease. Recent findings While Parkinson’s disease patients experience a wide range of non-motor symptoms throughout the disease course, studies demonstrate that non-motor features are not solely a late manifestation. Indeed, disturbances of smell, sleep, mood, and gastrointestinal function may herald Parkinson’s disease or related synucleinopathies and precede these neurodegenerative conditions by 5 or more years. In addition, other non-motor symptoms such as cognitive impairment are now recognized in incident or de novo Parkinson’s disease cohorts. Many of these non-motor features reflect disturbances in non-dopaminergic systems and early involvement of peripheral and central nervous systems including olfactory, enteric, and brainstem neurons as in Braak’s proposed pathological staging of Parkinson’s disease. Current research focuses on identifying potential biomarkers that may detect persons at risk for Parkinson’s disease and permit early intervention with neuroprotective or disease-modifying therapeutics. Summary Recent studies provide new insights on the frequency, pathophysiology, and importance of non-motor features in Parkinson’s disease as well as the recognition that these non-motor symptoms occur in premotor, early, and later phases of Parkinson’s disease. PMID:24978368

Sensor feature fusion for detecting buried objects

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

Clark, G.A.; Sengupta, S.K.; Sherwood, R.J.

1993-04-01

Given multiple registered images of the earth`s surface from dual-band sensors, our system fuses information from the sensors to reduce the effects of clutter and improve the ability to detect buried or surface target sites. The sensor suite currently includes two sensors (5 micron and 10 micron wavelengths) and one ground penetrating radar (GPR) of the wide-band pulsed synthetic aperture type. We use a supervised teaming pattern recognition approach to detect metal and plastic land mines buried in soil. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in amore » two step process to classify a subimage. Thee first step, referred to as feature selection, determines the features of sub-images which result in the greatest separability among the classes. The second step, image labeling, uses the selected features and the decisions from a pattern classifier to label the regions in the image which are likely to correspond to buried mines. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the sensors add value to the detection system. The most important features from the various sensors are fused using supervised teaming pattern classifiers (including neural networks). We present results of experiments to detect buried land mines from real data, and evaluate the usefulness of fusing feature information from multiple sensor types, including dual-band infrared and ground penetrating radar. The novelty of the work lies mostly in the combination of the algorithms and their application to the very important and currently unsolved operational problem of detecting buried land mines from an airborne standoff platform.« less

A DFT-Based Method of Feature Extraction for Palmprint Recognition

NASA Astrophysics Data System (ADS)

Choge, H. Kipsang; Karungaru, Stephen G.; Tsuge, Satoru; Fukumi, Minoru

Over the last quarter century, research in biometric systems has developed at a breathtaking pace and what started with the focus on the fingerprint has now expanded to include face, voice, iris, and behavioral characteristics such as gait. Palmprint is one of the most recent additions, and is currently the subject of great research interest due to its inherent uniqueness, stability, user-friendliness and ease of acquisition. This paper describes an effective and procedurally simple method of palmprint feature extraction specifically for palmprint recognition, although verification experiments are also conducted. This method takes advantage of the correspondences that exist between prominent palmprint features or objects in the spatial domain with those in the frequency or Fourier domain. Multi-dimensional feature vectors are formed by extracting a GA-optimized set of points from the 2-D Fourier spectrum of the palmprint images. The feature vectors are then used for palmprint recognition, before and after dimensionality reduction via the Karhunen-Loeve Transform (KLT). Experiments performed using palmprint images from the ‘PolyU Palmprint Database’ indicate that using a compact set of DFT coefficients, combined with KLT and data preprocessing, produces a recognition accuracy of more than 98% and can provide a fast and effective technique for personal identification.

47 CFR 68.318 - Additional limitations.

Code of Federal Regulations, 2010 CFR

2010-10-01

... TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Conditions for Terminal Equipment Approval § 68.318 Additional... incorporate the specified features. (b) Registered terminal equipment with automatic dialing capability. (1... proceeding to dial another number. (6) Network addressing signals shall be transmitted no earlier than: (i...

47 CFR 68.318 - Additional limitations.

Code of Federal Regulations, 2012 CFR

2012-10-01

... TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Conditions for Terminal Equipment Approval § 68.318 Additional... incorporate the specified features. (b) Registered terminal equipment with automatic dialing capability. (1... proceeding to dial another number. (6) Network addressing signals shall be transmitted no earlier than: (i...

47 CFR 68.318 - Additional limitations.

Code of Federal Regulations, 2011 CFR

2011-10-01

... TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Conditions for Terminal Equipment Approval § 68.318 Additional... incorporate the specified features. (b) Registered terminal equipment with automatic dialing capability. (1... proceeding to dial another number. (6) Network addressing signals shall be transmitted no earlier than: (i...

47 CFR 68.318 - Additional limitations.

Code of Federal Regulations, 2013 CFR

2013-10-01

... TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Conditions for Terminal Equipment Approval § 68.318 Additional... incorporate the specified features. (b) Registered terminal equipment with automatic dialing capability. (1... proceeding to dial another number. (6) Network addressing signals shall be transmitted no earlier than: (i...

47 CFR 68.318 - Additional limitations.

Code of Federal Regulations, 2014 CFR

2014-10-01

... TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Conditions for Terminal Equipment Approval § 68.318 Additional... incorporate the specified features. (b) Registered terminal equipment with automatic dialing capability. (1... proceeding to dial another number. (6) Network addressing signals shall be transmitted no earlier than: (i...

Identifying predictive features in drug response using machine learning: opportunities and challenges.

PubMed

Vidyasagar, Mathukumalli

2015-01-01

This article reviews several techniques from machine learning that can be used to study the problem of identifying a small number of features, from among tens of thousands of measured features, that can accurately predict a drug response. Prediction problems are divided into two categories: sparse classification and sparse regression. In classification, the clinical parameter to be predicted is binary, whereas in regression, the parameter is a real number. Well-known methods for both classes of problems are briefly discussed. These include the SVM (support vector machine) for classification and various algorithms such as ridge regression, LASSO (least absolute shrinkage and selection operator), and EN (elastic net) for regression. In addition, several well-established methods that do not directly fall into machine learning theory are also reviewed, including neural networks, PAM (pattern analysis for microarrays), SAM (significance analysis for microarrays), GSEA (gene set enrichment analysis), and k-means clustering. Several references indicative of the application of these methods to cancer biology are discussed.

Additional Nodal Disease Prediction in Breast Cancer with Sentinel Lymph Node Metastasis Based on Clinicopathological Features.

PubMed

Orsaria, Paolo; Caredda, Emanuele; Genova, Federica; Materazzo, Marco; Capuano, Ilaria; Vanni, Gianluca; Granai, Alessandra Vittoria; DE Majo, Adriano; Portarena, Ilaria; Sileri, Pierpaolo; Petrella, Giuseppe; Palombi, Leonardo; Buonomo, Oreste Claudio

2018-04-01

The standard-of-care in breast cancer (BC) with positive sentinel lymph node (SLN) metastasis includes complete axillary lymph node dissection (ALND); however, almost half of such cases have no further tumor burden. This study aimed to assess the clinicopathological factors that predict non-SLN metastasis to define subgroups of SLN-positive patients in whom the axilla may be staged by SLN biopsy alone, while avoiding unnecessary overtreatment. The records of 191 patients with histologically-proven primary BC who underwent a positive (SLN) biopsy between 2005 and 2017 were reviewed. Patients with at least one tumor-involved SLN who underwent completion ALND were enrolled. Demographic and clinicopathological characteristics, including age, primary tumor size and histological grade, lymphovascular invasion, ratio of positive SLNs to the harvested SLNs, SLN metastasis size, and molecular subtype classification according to immunohistochemical biomarker status [estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2)], were evaluated. Data were collected retrospectively and analyzed using the Mann-Whitney and Chi-square tests (statistical significance: p<0.05). The incidence of non-SLN metastasis associated with positive SLN was 48.6% (93/191). The risk of additional nodal spread correlated with high sentinel nodal ratio >0.67 [odds ratio (OR)=2.55, p=0.032], luminal BC subtype (OR=2.67, p=0.06), HER2 overexpression (OR=0.4, p=0.016), and ER + PR - HER2 - profile (OR=2.95, p=0.027). There was a tendency (statistically insignificant; p>0.05) toward higher incidence of non SLN metastasis with increasing age and histological grade, which could be attributed to the small sample size. According to this study, sentinel nodal ratio and BC subtypes as per ER, PR, and HER2 status significantly predicted the likelihood of additional lymphatic involvement. Validation of these parameters in prospective studies is indicated, and may

Current use and potential of additive manufacturing for optical applications

NASA Astrophysics Data System (ADS)

Brunelle, Matthew; Ferralli, Ian; Whitsitt, Rebecca; Medicus, Kate

2017-10-01

Additive manufacturing, or 3D printing, has become widely used in recent years for the creation of both prototype and end-use parts. Because the parts are created in a layer-by-layer manner, the flexibility of additive manufacturing is unparalleled and has opened the design space to enable features like undercuts and internal channels which cannot exist on traditional, subtractively manufactured parts. This flexibility can also be leveraged for optical applications. This paper outlines some of the current uses of 3D printing in the optical manufacturing process at Optimax. Several materials and additive technologies are utilized, including polymer printing through fused deposition modeling, which creates parts by depositing a softened thermoplastic filament in a layerwise fashion. Stereolithography, which uses light to cure layers of a photopolymer resin, will also be discussed. These technologies are used to manufacture functional prototypes, fixtures, sealed housings, and other components. Additionally, metal printing through selective laser melting, which uses a laser to melt metal powder layers into a dense solid, will be discussed due to the potential to manufacture thermally stable opticalmechanical assembly frameworks and functional optics. Examples of several additively manufactured optical components will be shown.

Three featured plenary sessions

NASA Astrophysics Data System (ADS)

2012-07-01

The conference included three plenary sessions. The plenary on Governance, Security, Economy, and the Ecosystem of the Changing Arctic featured Vera Alexander, president, Arctic Research Consortium of the U.S.; Alan Thornhill, chief environmental officer, U.S. Department of the Interior's Bureau of Ocean Energy Management; and Fran Ulmer, chair, U.S. Arctic Research Commission. A plenary on the U.N. Convention on the Law of the Sea featured Ambassador David Balton, deputy assistant secretary for oceans and fisheries, U.S. Department of State; and Rear Admiral Frederick Kenney Jr., judge advocate general and chief counsel, U.S. Coast Guard. The plenary on Science and the 21st Century featured Phil Keslin, chief technology officer, small lab within Google.

Augmenting Phase Space Quantization to Introduce Additional Physical Effects

NASA Astrophysics Data System (ADS)

Robbins, Matthew P. G.

Quantum mechanics can be done using classical phase space functions and a star product. The state of the system is described by a quasi-probability distribution. A classical system can be quantized in phase space in different ways with different quasi-probability distributions and star products. A transition differential operator relates different phase space quantizations. The objective of this thesis is to introduce additional physical effects into the process of quantization by using the transition operator. As prototypical examples, we first look at the coarse-graining of the Wigner function and the damped simple harmonic oscillator. By generalizing the transition operator and star product to also be functions of the position and momentum, we show that additional physical features beyond damping and coarse-graining can be introduced into a quantum system, including the generalized uncertainty principle of quantum gravity phenomenology, driving forces, and decoherence.

Design for Additive Bio-Manufacturing: From Patient-Specific Medical Devices to Rationally Designed Meta-Biomaterials.

PubMed

Zadpoor, Amir A

2017-07-25

Recent advances in additive manufacturing (AM) techniques in terms of accuracy, reliability, the range of processable materials, and commercial availability have made them promising candidates for production of functional parts including those used in the biomedical industry. The complexity-for-free feature offered by AM means that very complex designs become feasible to manufacture, while batch-size-indifference enables fabrication of fully patient-specific medical devices. Design for AM (DfAM) approaches aim to fully utilize those features for development of medical devices with substantially enhanced performance and biomaterials with unprecedented combinations of favorable properties that originate from complex geometrical designs at the micro-scale. This paper reviews the most important approaches in DfAM particularly those applicable to additive bio-manufacturing including image-based design pipelines, parametric and non-parametric designs, metamaterials, rational and computationally enabled design, topology optimization, and bio-inspired design. Areas with limited research have been identified and suggestions have been made for future research. The paper concludes with a brief discussion on the practical aspects of DfAM and the potential of combining AM with subtractive and formative manufacturing processes in so-called hybrid manufacturing processes.

Design for Additive Bio-Manufacturing: From Patient-Specific Medical Devices to Rationally Designed Meta-Biomaterials

PubMed Central

Zadpoor, Amir A.

2017-01-01

Recent advances in additive manufacturing (AM) techniques in terms of accuracy, reliability, the range of processable materials, and commercial availability have made them promising candidates for production of functional parts including those used in the biomedical industry. The complexity-for-free feature offered by AM means that very complex designs become feasible to manufacture, while batch-size-indifference enables fabrication of fully patient-specific medical devices. Design for AM (DfAM) approaches aim to fully utilize those features for development of medical devices with substantially enhanced performance and biomaterials with unprecedented combinations of favorable properties that originate from complex geometrical designs at the micro-scale. This paper reviews the most important approaches in DfAM particularly those applicable to additive bio-manufacturing including image-based design pipelines, parametric and non-parametric designs, metamaterials, rational and computationally enabled design, topology optimization, and bio-inspired design. Areas with limited research have been identified and suggestions have been made for future research. The paper concludes with a brief discussion on the practical aspects of DfAM and the potential of combining AM with subtractive and formative manufacturing processes in so-called hybrid manufacturing processes. PMID:28757572

Aging, selective attention, and feature integration.

PubMed

Plude, D J; Doussard-Roosevelt, J A

1989-03-01

This study used feature-integration theory as a means of determining the point in processing at which selective attention deficits originate. The theory posits an initial stage of processing in which features are registered in parallel and then a serial process in which features are conjoined to form complex stimuli. Performance of young and older adults on feature versus conjunction search is compared. Analyses of reaction times and error rates suggest that elderly adults in addition to young adults, can capitalize on the early parallel processing stage of visual information processing, and that age decrements in visual search arise as a result of the later, serial stage of processing. Analyses of a third, unconfounded, conjunction search condition reveal qualitatively similar modes of conjunction search in young and older adults. The contribution of age-related data limitations is found to be secondary to the contribution of age decrements in selective attention.

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.

The emotional regulatory features of bulimic episodes and compulsive exercise in muscle dysmorphia: a case report.

PubMed

Murray, Stuart B; Maguire, Sarah; Russell, Janice; Touyz, Stephen W

2012-01-01

Muscle dysmorphia is a recently identified psychiatric condition, whose relationship to the eating disorders remains unclear. This case describes an adolescent male who met diagnostic criteria for both an eating disorder not otherwise specified and muscle dysmorphia, allowing the first examination of read muscle dysmorphia presentations. This case suggests that muscle dysmorphia may present inclusive of episodes of binge eating and purging in addition to compulsive exercise, which may serve an emotional regulation function. We suggest that the assessment of muscle dysmorphia include a comprehensive assessment of all eating disorder features including bulimic symptoms, and that treatment address these features. Clinical implications for the conceptualization of muscle dysmorphia are discussed. Copyright © 2011 John Wiley & Sons, Ltd and Eating Disorders Association.

Airborne electromagnetic detection of shallow seafloor topographic features, including resolution of multiple sub-parallel seafloor ridges

NASA Astrophysics Data System (ADS)

Vrbancich, Julian; Boyd, Graham

2014-05-01

The HoistEM helicopter time-domain electromagnetic (TEM) system was flown over waters in Backstairs Passage, South Australia, in 2003 to test the bathymetric accuracy and hence the ability to resolve seafloor structure in shallow and deeper waters (extending to ~40 m depth) that contain interesting seafloor topography. The topography that forms a rock peak (South Page) in the form of a mini-seamount that barely rises above the water surface was accurately delineated along its ridge from the start of its base (where the seafloor is relatively flat) in ~30 m water depth to its peak at the water surface, after an empirical correction was applied to the data to account for imperfect system calibration, consistent with earlier studies using the same HoistEM system. A much smaller submerged feature (Threshold Bank) of ~9 m peak height located in waters of 35 to 40 m depth was also accurately delineated. These observations when checked against known water depths in these two regions showed that the airborne TEM system, following empirical data correction, was effectively operating correctly. The third and most important component of the survey was flown over the Yatala Shoals region that includes a series of sub-parallel seafloor ridges (resembling large sandwaves rising up to ~20 m from the seafloor) that branch out and gradually decrease in height as the ridges spread out across the seafloor. These sub-parallel ridges provide an interesting topography because the interpreted water depths obtained from 1D inversion of TEM data highlight the limitations of the EM footprint size in resolving both the separation between the ridges (which vary up to ~300 m) and the height of individual ridges (which vary up to ~20 m), and possibly also the limitations of assuming a 1D model in areas where the topography is quasi-2D/3D.

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

PubMed

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

2014-02-01

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

Additive Manufacturing for Affordable Rocket Engines

NASA Technical Reports Server (NTRS)

West, Brian; Robertson, Elizabeth; Osborne, Robin; Calvert, Marty

2016-01-01

Additive manufacturing (also known as 3D printing) technology has the potential to drastically reduce costs and lead times associated with the development of complex liquid rocket engine systems. NASA is using 3D printing to manufacture rocket engine components including augmented spark igniters, injectors, turbopumps, and valves. NASA is advancing the process to certify these components for flight. Success Story: MSFC has been developing rocket 3D-printing technology using the Selective Laser Melting (SLM) process. Over the last several years, NASA has built and tested several injectors and combustion chambers. Recently, MSFC has 3D printed an augmented spark igniter for potential use the RS-25 engines that will be used on the Space Launch System. The new design is expected to reduce the cost of the igniter by a factor of four. MSFC has also 3D printed and tested a liquid hydrogen turbopump for potential use on an Upper Stage Engine. Additive manufacturing of the turbopump resulted in a 45% part count reduction. To understanding how the 3D printed parts perform and to certify them for flight, MSFC built a breadboard liquid rocket engine using additive manufactured components including injectors, turbomachinery, and valves. The liquid rocket engine was tested seven times in 2016 using liquid oxygen and liquid hydrogen. In addition to exposing the hardware to harsh environments, engineers learned to design for the new manufacturing technique, taking advantage of its capabilities and gaining awareness of its limitations. Benefit: The 3D-printing technology promises reduced cost and schedule for rocket engines. Cost is a function of complexity, and the most complicated features provide the largest opportunities for cost reductions. This is especially true where brazes or welds can be eliminated. The drastic reduction in part count achievable with 3D printing creates a waterfall effect that reduces the number of processes and drawings, decreases the amount of touch

The relationship between 2D static features and 2D dynamic features used in gait recognition

NASA Astrophysics Data System (ADS)

Alawar, Hamad M.; Ugail, Hassan; Kamala, Mumtaz; Connah, David

2013-05-01

In most gait recognition techniques, both static and dynamic features are used to define a subject's gait signature. In this study, the existence of a relationship between static and dynamic features was investigated. The correlation coefficient was used to analyse the relationship between the features extracted from the "University of Bradford Multi-Modal Gait Database". This study includes two dimensional dynamic and static features from 19 subjects. The dynamic features were compromised of Phase-Weighted Magnitudes driven by a Fourier Transform of the temporal rotational data of a subject's joints (knee, thigh, shoulder, and elbow). The results concluded that there are eleven pairs of features that are considered significantly correlated with (p<0.05). This result indicates the existence of a statistical relationship between static and dynamics features, which challenges the results of several similar studies. These results bare great potential for further research into the area, and would potentially contribute to the creation of a gait signature using latent data.

Pathogenic features and characteristics of food borne pathogens biofilm: Biomass, viability and matrix.

PubMed

Lin, Shiqi; Yang, Ling; Chen, Gu; Li, Bing; Chen, Dingqiang; Li, Lin; Xu, Zhenbo

2017-10-01

Biofilm is a ubiquitous growth pattern of bacterial species survival but is notorious for its threat on public health and food contamination. Extensive studies of the biofilm structure, formation, quantification, quorum sensing system and underlying control strategies have been reported during the past decades. Insightful elucidation of the pathogenic features and characteristic of bacterial biofilm can facilitate in devising appropriate control strategies for biofilm eradication. Therefore, this review mainly summarized the pathogenic features of biofilms from food borne microorganisms, including the biomass (which could be quantified using crystal violet and fluorogenic dye Syto9 assays), viability (which could be determined by tetrazolium salts, fluorescein diacetate, resazurin staining and alamar blue assays) and matrix (which are commonly detected by dimethyl methylene blue and wheat germ agglutinin assays). In addition, three features were further compared with its particular benefits in specific application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improved pulmonary nodule classification utilizing quantitative lung parenchyma features.

PubMed

Dilger, Samantha K N; Uthoff, Johanna; Judisch, Alexandra; Hammond, Emily; Mott, Sarah L; Smith, Brian J; Newell, John D; Hoffman, Eric A; Sieren, Jessica C

2015-10-01

Current computer-aided diagnosis (CAD) models for determining pulmonary nodule malignancy characterize nodule shape, density, and border in computed tomography (CT) data. Analyzing the lung parenchyma surrounding the nodule has been minimally explored. We hypothesize that improved nodule classification is achievable by including features quantified from the surrounding lung tissue. To explore this hypothesis, we have developed expanded quantitative CT feature extraction techniques, including volumetric Laws texture energy measures for the parenchyma and nodule, border descriptors using ray-casting and rubber-band straightening, histogram features characterizing densities, and global lung measurements. Using stepwise forward selection and leave-one-case-out cross-validation, a neural network was used for classification. When applied to 50 nodules (22 malignant and 28 benign) from high-resolution CT scans, 52 features (8 nodule, 39 parenchymal, and 5 global) were statistically significant. Nodule-only features yielded an area under the ROC curve of 0.918 (including nodule size) and 0.872 (excluding nodule size). Performance was improved through inclusion of parenchymal (0.938) and global features (0.932). These results show a trend toward increased performance when the parenchyma is included, coupled with the large number of significant parenchymal features that support our hypothesis: the pulmonary parenchyma is influenced differentially by malignant versus benign nodules, assisting CAD-based nodule characterizations.

Military personnel recognition system using texture, colour, and SURF features

NASA Astrophysics Data System (ADS)

Irhebhude, Martins E.; Edirisinghe, Eran A.

2014-06-01

This paper presents an automatic, machine vision based, military personnel identification and classification system. Classification is done using a Support Vector Machine (SVM) on sets of Army, Air Force and Navy camouflage uniform personnel datasets. In the proposed system, the arm of service of personnel is recognised by the camouflage of a persons uniform, type of cap and the type of badge/logo. The detailed analysis done include; camouflage cap and plain cap differentiation using gray level co-occurrence matrix (GLCM) texture feature; classification on Army, Air Force and Navy camouflaged uniforms using GLCM texture and colour histogram bin features; plain cap badge classification into Army, Air Force and Navy using Speed Up Robust Feature (SURF). The proposed method recognised camouflage personnel arm of service on sets of data retrieved from google images and selected military websites. Correlation-based Feature Selection (CFS) was used to improve recognition and reduce dimensionality, thereby speeding the classification process. With this method success rates recorded during the analysis include 93.8% for camouflage appearance category, 100%, 90% and 100% rates of plain cap and camouflage cap categories for Army, Air Force and Navy categories, respectively. Accurate recognition was recorded using SURF for the plain cap badge category. Substantial analysis has been carried out and results prove that the proposed method can correctly classify military personnel into various arms of service. We show that the proposed method can be integrated into a face recognition system, which will recognise personnel in addition to determining the arm of service which the personnel belong. Such a system can be used to enhance the security of a military base or facility.

Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing

PubMed Central

Wen, Tailai; Huang, Daoyu; Lu, Kun; Deng, Changjian; Zeng, Tanyue; Yu, Song; He, Zhiyi

2018-01-01

The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications. During the learning process of the E-nose to predict the types of different odors, the prediction accuracy was not quite satisfying because the raw features extracted from sensors’ responses were regarded as the input of a classifier without any feature extraction processing. Therefore, in order to obtain more useful information and improve the E-nose’s classification accuracy, in this paper, a Weighted Kernels Fisher Discriminant Analysis (WKFDA) combined with Quantum-behaved Particle Swarm Optimization (QPSO), i.e., QWKFDA, was presented to reprocess the original feature matrix. In addition, we have also compared the proposed method with quite a few previously existing ones including Principal Component Analysis (PCA), Locality Preserving Projections (LPP), Fisher Discriminant Analysis (FDA) and Kernels Fisher Discriminant Analysis (KFDA). Experimental results proved that QWKFDA is an effective feature extraction method for E-nose in predicting the types of wound infection and inflammable gases, which shared much higher classification accuracy than those of the contrast methods. PMID:29382146

Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing.

PubMed

Wen, Tailai; Yan, Jia; Huang, Daoyu; Lu, Kun; Deng, Changjian; Zeng, Tanyue; Yu, Song; He, Zhiyi

2018-01-29

The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications. During the learning process of the E-nose to predict the types of different odors, the prediction accuracy was not quite satisfying because the raw features extracted from sensors' responses were regarded as the input of a classifier without any feature extraction processing. Therefore, in order to obtain more useful information and improve the E-nose's classification accuracy, in this paper, a Weighted Kernels Fisher Discriminant Analysis (WKFDA) combined with Quantum-behaved Particle Swarm Optimization (QPSO), i.e., QWKFDA, was presented to reprocess the original feature matrix. In addition, we have also compared the proposed method with quite a few previously existing ones including Principal Component Analysis (PCA), Locality Preserving Projections (LPP), Fisher Discriminant Analysis (FDA) and Kernels Fisher Discriminant Analysis (KFDA). Experimental results proved that QWKFDA is an effective feature extraction method for E-nose in predicting the types of wound infection and inflammable gases, which shared much higher classification accuracy than those of the contrast methods.

Metrology test object for dimensional verification in additive manufacturing of metals for biomedical applications.

PubMed

Teeter, Matthew G; Kopacz, Alexander J; Nikolov, Hristo N; Holdsworth, David W

2015-01-01

Additive manufacturing continues to increase in popularity and is being used in applications such as biomaterial ingrowth that requires sub-millimeter dimensional accuracy. The purpose of this study was to design a metrology test object for determining the capabilities of additive manufacturing systems to produce common objects, with a focus on those relevant to medical applications. The test object was designed with a variety of features of varying dimensions, including holes, cylinders, rectangles, gaps, and lattices. The object was built using selective laser melting, and the produced dimensions were compared to the target dimensions. Location of the test objects on the build plate did not affect dimensions. Features with dimensions less than 0.300 mm did not build or were overbuilt to a minimum of 0.300 mm. The mean difference between target and measured dimensions was less than 0.100 mm in all cases. The test object is applicable to multiple systems and materials, tests the effect of location on the build, uses a minimum of material, and can be measured with a variety of efficient metrology tools (including measuring microscopes and micro-CT). Investigators can use this test object to determine the limits of systems and adjust build parameters to achieve maximum accuracy. © IMechE 2014.

Radar signature generation for feature-aided tracking research

NASA Astrophysics Data System (ADS)

Piatt, Teri L.; Sherwood, John U.; Musick, Stanton H.

2005-05-01

Accurately associating sensor kinematic reports to known tracks, new tracks, or clutter is one of the greatest obstacles to effective track estimation. Feature-aiding is one technology that is emerging to address this problem, and it is expected that adding target features will aid report association by enhancing track accuracy and lengthening track life. The Sensor's Directorate of the Air Force Research Laboratory is sponsoring a challenge problem called Feature-Aided Tracking of Stop-move Objects (FATSO). The long-range goal of this research is to provide a full suite of public data and software to encourage researchers from government, industry, and academia to participate in radar-based feature-aided tracking research. The FATSO program is currently releasing a vehicle database coupled to a radar signature generator. The completed FATSO system will incorporate this database/generator into a Monte Carlo simulation environment for evaluating multiplatform/multitarget tracking scenarios. The currently released data and software contains the following: eight target models, including a tank, ammo hauler, and self-propelled artillery vehicles; and a radar signature generator capable of producing SAR and HRR signatures of all eight modeled targets in almost any configuration or articulation. In addition, the signature generator creates Z-buffer data, label map data, and radar cross-section prediction and allows the user to add noise to an image while varying sensor-target geometry (roll, pitch, yaw, squint). Future capabilities of this signature generator, such as scene models and EO signatures as well as details of the complete FATSO testbed, are outlined.

A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

PubMed

Hsieh, Chi-Hsuan; Chiu, Yu-Fang; Shen, Yi-Hsiang; Chu, Ta-Shun; Huang, Yuan-Hao

2016-02-01

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.

Pitch features of environmental sounds

NASA Astrophysics Data System (ADS)

Yang, Ming; Kang, Jian

2016-07-01

A number of soundscape studies have suggested the need for suitable parameters for soundscape measurement, in addition to the conventional acoustic parameters. This paper explores the applicability of pitch features that are often used in music analysis and their algorithms to environmental sounds. Based on the existing alternative pitch algorithms for simulating the perception of the auditory system and simplified algorithms for practical applications in the areas of music and speech, the applicable algorithms have been determined, considering common types of sound in everyday soundscapes. Considering a number of pitch parameters, including pitch value, pitch strength, and percentage of audible pitches over time, different pitch characteristics of various environmental sounds have been shown. Among the four sound categories, i.e. water, wind, birdsongs, and urban sounds, generally speaking, both water and wind sounds have low pitch values and pitch strengths; birdsongs have high pitch values and pitch strengths; and urban sounds have low pitch values and a relatively wide range of pitch strengths.

Suppression effects in feature-based attention

PubMed Central

Wang, Yixue; Miller, James; Liu, Taosheng

2015-01-01

Attending to a feature enhances visual processing of that feature, but it is less clear what occurs to unattended features. Single-unit recording studies in middle temporal (MT) have shown that neuronal modulation is a monotonic function of the difference between the attended and neuron's preferred direction. Such a relationship should predict a monotonic suppressive effect in psychophysical performance. However, past research on suppressive effects of feature-based attention has remained inconclusive. We investigated the suppressive effect for motion direction, orientation, and color in three experiments. We asked participants to detect a weak signal among noise and provided a partially valid feature cue to manipulate attention. We measured performance as a function of the offset between the cued and signal feature. We also included neutral trials where no feature cues were presented to provide a baseline measure of performance. Across three experiments, we consistently observed enhancement effects when the target feature and cued feature coincided and suppression effects when the target feature deviated from the cued feature. The exact profile of suppression was different across feature dimensions: Whereas the profile for direction exhibited a “rebound” effect, the profiles for orientation and color were monotonic. These results demonstrate that unattended features are suppressed during feature-based attention, but the exact suppression profile depends on the specific feature. Overall, the results are largely consistent with neurophysiological data and support the feature-similarity gain model of attention. PMID:26067533

Hypospadias as a novel feature in spinal bulbar muscle atrophy.

PubMed

Nordenvall, Anna Skarin; Paucar, Martin; Almqvist, Catarina; Nordenström, Anna; Frisén, Louise; Nordenskjöld, Agneta

2016-04-01

Spinal and bulbar muscle atrophy (SBMA) is an X-linked neuromuscular disorder caused by CAG repeat expansions in the androgen receptor (AR) gene. The SBMA phenotype consists of slowly progressive neuromuscular symptoms and undermasculinization features as the result of malfunction of the AR. The latter mainly includes gynecomastia and infertility. Hypospadias is also a feature of undermasculinization with an underdeveloped urethra and penis; it has not been described as part of the SBMA phenotype but has been suggested to be associated with a prolonged CAG repeat in the AR gene. This study includes the first epidemiologic description of the co-occurrence of hypospadias and SBMA in subjects and their male relatives in Swedish population-based health registers, as well as an additional clinical case. One boy with severe hypospadias was screened for mutations in the AR gene and was found to have 42 CAG repeats in it, which is in the full range of mutations causing SBMA later in life. We also detected a maximum of four cases displaying the combination of SBMA and hypospadias in our national register databases. This is the third case report with hypospadias in association with CAG repeat expansions in the AR gene in the full range known to cause SBMA later in life. Our findings suggest that hypospadias may be an under diagnosed feature of the SBMA phenotype and we propose that neurologists working with SBMA further investigate and report the true prevalence of hypospadias among patients with SBMA.

Generating One Biometric Feature from Another: Faces from Fingerprints

PubMed Central

Ozkaya, Necla; Sagiroglu, Seref

2010-01-01

This study presents a new approach based on artificial neural networks for generating one biometric feature (faces) from another (only fingerprints). An automatic and intelligent system was designed and developed to analyze the relationships among fingerprints and faces and also to model and to improve the existence of the relationships. The new proposed system is the first study that generates all parts of the face including eyebrows, eyes, nose, mouth, ears and face border from only fingerprints. It is also unique and different from similar studies recently presented in the literature with some superior features. The parameter settings of the system were achieved with the help of Taguchi experimental design technique. The performance and accuracy of the system have been evaluated with 10-fold cross validation technique using qualitative evaluation metrics in addition to the expanded quantitative evaluation metrics. Consequently, the results were presented on the basis of the combination of these objective and subjective metrics for illustrating the qualitative properties of the proposed methods as well as a quantitative evaluation of their performances. Experimental results have shown that one biometric feature can be determined from another. These results have once more indicated that there is a strong relationship between fingerprints and faces. PMID:22399877

Vertical Feature Mask Feature Classification Flag Extraction

Atmospheric Science Data Center

2013-03-28

  Vertical Feature Mask Feature Classification Flag Extraction This routine demonstrates extraction of the ... in a CALIPSO Lidar Level 2 Vertical Feature Mask feature classification flag value. It is written in Interactive Data Language (IDL) ...

TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

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

Krafft, S; The University of Texas Graduate School of Biomedical Sciences, Houston, TX; Briere, T

2015-06-15

Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. Amore » total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP

Speech recognition features for EEG signal description in detection of neonatal seizures.

PubMed

Temko, A; Boylan, G; Marnane, W; Lightbody, G

2010-01-01

In this work, features which are usually employed in automatic speech recognition (ASR) are used for the detection of neonatal seizures in newborn EEG. Three conventional ASR feature sets are compared to the feature set which has been previously developed for this task. The results indicate that the thoroughly-studied spectral envelope based ASR features perform reasonably well on their own. Additionally, the SVM Recursive Feature Elimination routine is applied to all extracted features pooled together. It is shown that ASR features consistently appear among the top-rank features.

SSVEP recognition using common feature analysis in brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2015-04-15

Canonical correlation analysis (CCA) has been successfully applied to steady-state visual evoked potential (SSVEP) recognition for brain-computer interface (BCI) application. Although the CCA method outperforms the traditional power spectral density analysis through multi-channel detection, it requires additionally pre-constructed reference signals of sine-cosine waves. It is likely to encounter overfitting in using a short time window since the reference signals include no features from training data. We consider that a group of electroencephalogram (EEG) data trials recorded at a certain stimulus frequency on a same subject should share some common features that may bear the real SSVEP characteristics. This study therefore proposes a common feature analysis (CFA)-based method to exploit the latent common features as natural reference signals in using correlation analysis for SSVEP recognition. Good performance of the CFA method for SSVEP recognition is validated with EEG data recorded from ten healthy subjects, in contrast to CCA and a multiway extension of CCA (MCCA). Experimental results indicate that the CFA method significantly outperformed the CCA and the MCCA methods for SSVEP recognition in using a short time window (i.e., less than 1s). The superiority of the proposed CFA method suggests it is promising for the development of a real-time SSVEP-based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

Robust Feature Matching in Terrestrial Image Sequences

NASA Astrophysics Data System (ADS)

Abbas, A.; Ghuffar, S.

2018-04-01

From the last decade, the feature detection, description and matching techniques are most commonly exploited in various photogrammetric and computer vision applications, which includes: 3D reconstruction of scenes, image stitching for panoramic creation, image classification, or object recognition etc. However, in terrestrial imagery of urban scenes contains various issues, which include duplicate and identical structures (i.e. repeated windows and doors) that cause the problem in feature matching phase and ultimately lead to failure of results specially in case of camera pose and scene structure estimation. In this paper, we will address the issue related to ambiguous feature matching in urban environment due to repeating patterns.

Classification of visual and linguistic tasks using eye-movement features.

PubMed

Coco, Moreno I; Keller, Frank

2014-03-07

The role of the task has received special attention in visual-cognition research because it can provide causal explanations of goal-directed eye-movement responses. The dependency between visual attention and task suggests that eye movements can be used to classify the task being performed. A recent study by Greene, Liu, and Wolfe (2012), however, fails to achieve accurate classification of visual tasks based on eye-movement features. In the present study, we hypothesize that tasks can be successfully classified when they differ with respect to the involvement of other cognitive domains, such as language processing. We extract the eye-movement features used by Greene et al. as well as additional features from the data of three different tasks: visual search, object naming, and scene description. First, we demonstrated that eye-movement responses make it possible to characterize the goals of these tasks. Then, we trained three different types of classifiers and predicted the task participants performed with an accuracy well above chance (a maximum of 88% for visual search). An analysis of the relative importance of features for classification accuracy reveals that just one feature, i.e., initiation time, is sufficient for above-chance performance (a maximum of 79% accuracy in object naming). Crucially, this feature is independent of task duration, which differs systematically across the three tasks we investigated. Overall, the best task classification performance was obtained with a set of seven features that included both spatial information (e.g., entropy of attention allocation) and temporal components (e.g., total fixation on objects) of the eye-movement record. This result confirms the task-dependent allocation of visual attention and extends previous work by showing that task classification is possible when tasks differ in the cognitive processes involved (purely visual tasks such as search vs. communicative tasks such as scene description).

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

PubMed

Botía, Juan A; Vandrovcova, Jana; Forabosco, Paola; Guelfi, Sebastian; D'Sa, Karishma; Hardy, John; Lewis, Cathryn M; Ryten, Mina; Weale, Michael E

2017-04-12

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used R software package for the generation of gene co-expression networks (GCN). WGCNA generates both a GCN and a derived partitioning of clusters of genes (modules). We propose k-means clustering as an additional processing step to conventional WGCNA, which we have implemented in the R package km2gcn (k-means to gene co-expression network, https://github.com/juanbot/km2gcn ). We assessed our method on networks created from UKBEC data (10 different human brain tissues), on networks created from GTEx data (42 human tissues, including 13 brain tissues), and on simulated networks derived from GTEx data. We observed substantially improved module properties, including: (1) few or zero misplaced genes; (2) increased counts of replicable clusters in alternate tissues (x3.1 on average); (3) improved enrichment of Gene Ontology terms (seen in 48/52 GCNs) (4) improved cell type enrichment signals (seen in 21/23 brain GCNs); and (5) more accurate partitions in simulated data according to a range of similarity indices. The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.

Precise Modelling of Telluric Features in Astronomical Spectra

NASA Astrophysics Data System (ADS)

Seifahrt, A.; Käufl, H. U.; Zängl, G.; Bean, J.; Richter, M.; Siebenmorgen, R.

2010-12-01

Ground-based astronomical observations suffer from the disturbing effects of the Earth's atmosphere. Oxygen, water vapour and a number of atmospheric trace gases absorb and emit light at discrete frequencies, shaping observing bands in the near- and mid-infrared and leaving their fingerprints - telluric absorption and emission lines - in astronomical spectra. The standard approach of removing the absorption lines is to observe a telluric standard star: a time-consuming and often imperfect solution. Alternatively, the spectral features of the Earth's atmosphere can be modelled using a radiative transfer code, often delivering a satisfying solution that removes these features without additional observations. In addition the model also provides a precise wavelength solution and an instrumental profile.

Composite, ordered material having sharp surface features

DOEpatents

D'Urso, Brian R.; Simpson, John T.

2006-12-19

A composite material having sharp surface features includes a recessive phase and a protrusive phase, the recessive phase having a higher susceptibility to a preselected etchant than the protrusive phase, the composite material having an etched surface wherein the protrusive phase protrudes from the surface to form a sharp surface feature. The sharp surface features can be coated to make the surface super-hydrophobic.

Contourlet Textual Features: Improving the Diagnosis of Solitary Pulmonary Nodules in Two Dimensional CT Images

PubMed Central

Wang, Jingjing; Sun, Tao; Gao, Ni; Menon, Desmond Dev; Luo, Yanxia; Gao, Qi; Li, Xia; Wang, Wei; Zhu, Huiping; Lv, Pingxin; Liang, Zhigang; Tao, Lixin; Liu, Xiangtong; Guo, Xiuhua

2014-01-01

Objective To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer. Materials and Methods A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data. Results Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93. Conclusion Our results indicate that the combined contourlet textural features of solitary

Contourlet textual features: improving the diagnosis of solitary pulmonary nodules in two dimensional CT images.

PubMed

Wang, Jingjing; Sun, Tao; Gao, Ni; Menon, Desmond Dev; Luo, Yanxia; Gao, Qi; Li, Xia; Wang, Wei; Zhu, Huiping; Lv, Pingxin; Liang, Zhigang; Tao, Lixin; Liu, Xiangtong; Guo, Xiuhua

2014-01-01

To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer. A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data. Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93. Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile

Additive Technology: Update on Current Materials and Applications in Dentistry.

PubMed

Barazanchi, Abdullah; Li, Kai Chun; Al-Amleh, Basil; Lyons, Karl; Waddell, J Neil

2017-02-01

Additive manufacturing or 3D printing is becoming an alternative to subtractive manufacturing or milling in the area of computer-aided manufacturing. Research on material for use in additive manufacturing is ongoing, and a wide variety of materials are being used or developed for use in dentistry. Some materials, however, such as cobalt chromium, still lack sufficient research to allow definite conclusions about the suitability of their use in clinical dental practice. Despite this, due to the wide variety of machines that use additive manufacturing, there is much more flexibility in the build material and geometry when building structures compared with subtractive manufacturing. Overall additive manufacturing produces little material waste and is energy efficient when compared to subtractive manufacturing, due to passivity and the additive layering nature of the build process. Such features make the technique suitable to be used with fabricating structures out of hard to handle materials such as cobalt chromium. The main limitations of this technology include the appearance of steps due to layering of material and difficulty in fabricating certain material generally used in dentistry for use in 3D printing such as ceramics. The current pace of technological development, however, promises exciting possibilities. © 2016 by the American College of Prosthodontists.

Follicular morphological characteristics may be associated with invasion in follicular thyroid neoplasms with papillary-like nuclear features.

PubMed

Can, Nuray; Celik, Mehmet; Sezer, Yavuz Atakan; Ozyilmaz, Filiz; Ayturk, Semra; Tastekin, Ebru; Sut, Necdet; Gurkan, Hakan; Ustun, Funda; Bulbul, Buket Yilmaz; Guldiken, Sibel; Puyan, Fulya Oz

2017-08-20

The newly proposed nomenclature and diagnostic criteria for encapsulated follicular variant of papillary thyroid carcinoma (EFVPTC), the noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), could improve the consistency and accuracy of diagnosing this entity. Diagnosis of NIFTP requires evaluation of the complete tumor border or capsule. The presence of tumor invasion in follicular thyroid neoplasms with papillary-like nuclear features has been recently discussed by many authors. In this study, we examined the predictive value and association of follicular morphological characteristics with the tumor invasion. In addition, we analyzed the association between tumor encapsulation and molecular profile in EFVPTC/NIFTP cases. A total of 106 cases of FVPTC were included in the study. The tumors were grouped based on the presence of tumor capsule and characteristics of tumor border, as 1) completely encapsulated tumors without invasion, 2) encapsulated tumors with invasion, 3) infiltrative tumors without a capsule. Clinicopathological features, histomorphological features [nuclear criteria, minor diagnostic features, follicles oriented perpendicular to tumor border/capsule (FOPBC)] and molecular alterations in BRAF, NRAS, and KRAS genes were evaluated. FOPBC were significantly more frequently seen in encapsulated tumors with invasion (p = 0.008). The nuclear features were not associated with the presence of encapsulation and characteristics of tumor border. BRAF mutation was more frequent in infiltrative tumors, while NRAS mutation was more frequent in encapsulated tumors, but the results were not statistically significant (p = 0.917). In conclusion, FOPBC histomorphological feature may be associated with tumor invasion in EFVPTC/NIFTP. Additionally, BRAF/KRAS/NRAS mutation analysis may prevent inadequate treatment in these patients.

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares

PubMed Central

Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Mur, Marieke

2016-01-01

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (>100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as “human”, “mammal”, and “animal”). The feature-based model includes both object parts (such as “eye”, “tail”, and “handle”) and other descriptive features (such as “circular”, “green”, and “stubbly”). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images not used in fitting. Both models explained significant variance in IT and the amounts explained were not significantly different. The combined model did not explain significant additional IT variance, suggesting that it is the shared model variance (features correlated with categories, categories correlated with features) that best explains IT. The similarity judgments were almost fully explained by the categorical model, which explained significantly more variance than the feature-based model. The combined model did not explain significant additional variance in the similarity judgments. Our findings suggest that IT uses features that help to distinguish categories as stepping stones

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares.

PubMed

Jozwik, Kamila M; Kriegeskorte, Nikolaus; Mur, Marieke

2016-03-01

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (>100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as "human", "mammal", and "animal"). The feature-based model includes both object parts (such as "eye", "tail", and "handle") and other descriptive features (such as "circular", "green", and "stubbly"). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images not used in fitting. Both models explained significant variance in IT and the amounts explained were not significantly different. The combined model did not explain significant additional IT variance, suggesting that it is the shared model variance (features correlated with categories, categories correlated with features) that best explains IT. The similarity judgments were almost fully explained by the categorical model, which explained significantly more variance than the feature-based model. The combined model did not explain significant additional variance in the similarity judgments. Our findings suggest that IT uses features that help to distinguish categories as stepping stones toward a semantic representation

Trajectory analysis via a geometric feature space approach

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

Rintoul, Mark D.; Wilson, Andrew T.

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Trajectory analysis via a geometric feature space approach

DOE PAGES

Rintoul, Mark D.; Wilson, Andrew T.

2015-10-05

This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less

Interstitial pneumonia with autoimmune features: an additional risk factor for ARDS?

PubMed

Grasselli, Giacomo; Vergnano, Beatrice; Pozzi, Maria Rosa; Sala, Vittoria; D'Andrea, Gabriele; Scaravilli, Vittorio; Mantero, Marco; Pesci, Alberto; Pesenti, Antonio

2017-09-18

Interstitial pneumonia with autoimmune features (IPAF) identifies a recently recognized autoimmune syndrome characterized by interstitial lung disease and autoantibodies positivity, but absence of a specific connective tissue disease diagnosis or alternative etiology. We retrospectively reviewed the clinical presentation, diagnostic workup and management of seven critically ill patients who met diagnostic criteria for IPAF. We compared baseline characteristics and clinical outcome of IPAF patients with those of the population of ARDS patients admitted in the same period. Seven consecutive patients with IPAF admitted to intensive care unit for acute respiratory distress syndrome (ARDS) were compared with 78 patients with ARDS secondary to a known risk factor and with eight ARDS patients without recognized risk factors. Five IPAF patients (71%) survived and were discharged alive from ICU: Their survival rate was equal to that of patients with a known risk factor (71%), while the subgroup of patients without risk factors had a markedly lower survival (38%). According to the Berlin definition criteria, ARDS was severe in four IPAF patients and moderate in the remaining three. All had multiple organ dysfunction at presentation. The most frequent autoantibody detected was anti-SSA/Ro52. All patients required prolonged mechanical ventilation (median duration 49 days, range 10-88); four received extracorporeal membrane oxygenation and one received low-flow extracorporeal CO 2 removal. All patients received immunosuppressive therapy. This is the first description of a cohort of critical patients meeting the diagnostic criteria for IPAF presenting with ARDS. This diagnosis should be considered in any critically ill patient with interstitial lung disease of unknown origin. While management is challenging and level of support high, survival appears to be good and comparable to that of patients with ARDS associated with a known clinical insult.

Face features and face configurations both contribute to visual crowding.

PubMed

Sun, Hsin-Mei; Balas, Benjamin

2015-02-01

Crowding refers to the inability to recognize an object in peripheral vision when other objects are presented nearby (Whitney & Levi Trends in Cognitive Sciences, 15, 160-168, 2011). A popular explanation of crowding is that features of the target and flankers are combined inappropriately when they are located within an integration field, thus impairing target recognition (Pelli, Palomares, & Majaj Journal of Vision, 4(12), 12:1136-1169, 2004). However, it remains unclear which features of the target and flankers are combined inappropriately to cause crowding (Levi Vision Research, 48, 635-654, 2008). For example, in a complex stimulus (e.g., a face), to what extent does crowding result from the integration of features at a part-based level or at the level of global processing of the configural appearance? In this study, we used a face categorization task and different types of flankers to examine how much the magnitude of visual crowding depends on the similarity of face parts or of global configurations. We created flankers with face-like features (e.g., the eyes, nose, and mouth) in typical and scrambled configurations to examine the impacts of part appearance and global configuration on the visual crowding of faces. Additionally, we used "electrical socket" flankers that mimicked first-order face configuration but had only schematic features, to examine the extent to which global face geometry impacted crowding. Our results indicated that both face parts and configurations contribute to visual crowding, suggesting that face similarity as realized under crowded conditions includes both aspects of facial appearance.

Saliency image of feature building for image quality assessment

NASA Astrophysics Data System (ADS)

Ju, Xinuo; Sun, Jiyin; Wang, Peng

2011-11-01

The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

Separable spectro-temporal Gabor filter bank features: Reducing the complexity of robust features for automatic speech recognition.

PubMed

Schädler, Marc René; Kollmeier, Birger

2015-04-01

To test if simultaneous spectral and temporal processing is required to extract robust features for automatic speech recognition (ASR), the robust spectro-temporal two-dimensional-Gabor filter bank (GBFB) front-end from Schädler, Meyer, and Kollmeier [J. Acoust. Soc. Am. 131, 4134-4151 (2012)] was de-composed into a spectral one-dimensional-Gabor filter bank and a temporal one-dimensional-Gabor filter bank. A feature set that is extracted with these separate spectral and temporal modulation filter banks was introduced, the separate Gabor filter bank (SGBFB) features, and evaluated on the CHiME (Computational Hearing in Multisource Environments) keywords-in-noise recognition task. From the perspective of robust ASR, the results showed that spectral and temporal processing can be performed independently and are not required to interact with each other. Using SGBFB features permitted the signal-to-noise ratio (SNR) to be lowered by 1.2 dB while still performing as well as the GBFB-based reference system, which corresponds to a relative improvement of the word error rate by 12.8%. Additionally, the real time factor of the spectro-temporal processing could be reduced by more than an order of magnitude. Compared to human listeners, the SNR needed to be 13 dB higher when using Mel-frequency cepstral coefficient features, 11 dB higher when using GBFB features, and 9 dB higher when using SGBFB features to achieve the same recognition performance.

Assessing the impact of representational and contextual problem features on student use of right-hand rules

NASA Astrophysics Data System (ADS)

Kustusch, Mary Bridget

2016-06-01

Students in introductory physics struggle with vector algebra and these challenges are often associated with contextual and representational features of the problems. Performance on problems about cross product direction is particularly poor and some research suggests that this may be primarily due to misapplied right-hand rules. However, few studies have had the resolution to explore student use of right-hand rules in detail. This study reviews literature in several disciplines, including spatial cognition, to identify ten contextual and representational problem features that are most likely to influence performance on problems requiring a right-hand rule. Two quantitative measures of performance (correctness and response time) and two qualitative measures (methods used and type of errors made) were used to explore the impact of these problem features on student performance. Quantitative results are consistent with expectations from the literature, but reveal that some features (such as the type of reasoning required and the physical awkwardness of using a right-hand rule) have a greater impact than others (such as whether the vectors are placed together or separate). Additional insight is gained by the qualitative analysis, including identifying sources of difficulty not previously discussed in the literature and revealing that the use of supplemental methods, such as physically rotating the paper, can mitigate errors associated with certain features.

The addition of STEPPS in the treatment of patients with bipolar disorder and comorbid borderline personality features: a protocol for a randomized controlled trial.

PubMed

Riemann, Georg; Weisscher, Nadine; Goossens, Peter J J; Draijer, Nel; Apenhorst-Hol, Marjolein; Kupka, Ralph W

2014-06-09

Bipolar disorder (BD) and borderline personality disorder (BPD) both are severe and chronic psychiatric disorders. Both disorders have overlapping symptoms, and current research shows that the presence of a BPD has an adverse effect on the course of BD. The limited research available shows an unfavorable illness course, a worse prognosis and response to medication, longer treatment duration, more frequent psychiatric admissions, higher drop-out, increased risk of substance abuse, increased risk of suicide, and more impairment of social and occupational functioning. However, there is no research available on the effect of specific psychotherapeutic treatment for this patients. This paper presents the protocol of a RCT to investigate the presence of borderline personality features in patients treated for BD (study part 1) and the effectiveness of STEPPS (Systems Training for Emotional Predictability and Problem Solving) added to treatment as usual (TAU) for BD compared to TAU in patients with BD and comorbid borderline personality features (study part 2). STEPPS is a validated and effective intervention for BPD. The study population consists of patients treated for BD at specialized outpatient clinics for BD in the Netherlands. At first the prevalence of comorbid borderline personality features in outpatients with BD is investigated. Inclusion criteria for study part 2 is defined as having three or more of the DSM-IV-TR diagnostic criteria of BPD, including impulsivity and anger bursts. Primary outcomes will be the frequency and severity of manic and depressive recurrences as well as severity, course and burden of borderline personality features. Secondary outcomes will be quality of life, utilizing mental healthcare and psychopathologic symptoms not primarily related to BD or BPD. Assessment will be at baseline, at the end of the intervention, and at 12 and 18 months follow-up. This will be the first randomized controlled trial of a specific intervention in patients

The addition of STEPPS in the treatment of patients with bipolar disorder and comorbid borderline personality features: a protocol for a randomized controlled trial

PubMed Central

2014-01-01

Background Bipolar disorder (BD) and borderline personality disorder (BPD) both are severe and chronic psychiatric disorders. Both disorders have overlapping symptoms, and current research shows that the presence of a BPD has an adverse effect on the course of BD. The limited research available shows an unfavorable illness course, a worse prognosis and response to medication, longer treatment duration, more frequent psychiatric admissions, higher drop-out, increased risk of substance abuse, increased risk of suicide, and more impairment of social and occupational functioning. However, there is no research available on the effect of specific psychotherapeutic treatment for this patients. Methods/Design This paper presents the protocol of a RCT to investigate the presence of borderline personality features in patients treated for BD (study part 1) and the effectiveness of STEPPS (Systems Training for Emotional Predictability and Problem Solving) added to treatment as usual (TAU) for BD compared to TAU in patients with BD and comorbid borderline personality features (study part 2). STEPPS is a validated and effective intervention for BPD. The study population consists of patients treated for BD at specialized outpatient clinics for BD in the Netherlands. At first the prevalence of comorbid borderline personality features in outpatients with BD is investigated. Inclusion criteria for study part 2 is defined as having three or more of the DSM-IV-TR diagnostic criteria of BPD, including impulsivity and anger bursts. Primary outcomes will be the frequency and severity of manic and depressive recurrences as well as severity, course and burden of borderline personality features. Secondary outcomes will be quality of life, utilizing mental healthcare and psychopathologic symptoms not primarily related to BD or BPD. Assessment will be at baseline, at the end of the intervention, and at 12 and 18 months follow-up. Discussion This will be the first randomized controlled trial

The first missense mutation of NHS gene in a Tunisian family with clinical features of NHS syndrome including cardiac anomaly

PubMed Central

Chograni, Manèl; Rejeb, Imen; Jemaa, Lamia Ben; Châabouni, Myriam; Bouhamed, Habiba Chaabouni

2011-01-01

Nance-Horan Syndrome (NHS) or X-linked cataract-dental syndrome is a disease of unknown gene action mechanism, characterized by congenital cataract, dental anomalies, dysmorphic features and, in some cases, mental retardation. We performed linkage analysis in a Tunisian family with NHS in which affected males and obligate carrier female share a common haplotype in the Xp22.32-p11.21 region that contains the NHS gene. Direct sequencing of NHS coding exons and flanking intronic sequences allowed us to identify the first missense mutation (P551S) and a reported SNP-polymorphism (L1319F) in exon 6, a reported UTR–SNP (c.7422 C>T) and a novel one (c.8239 T>A) in exon 8. Both variations P551S and c.8239 T>A segregate with NHS phenotype in this family. Although truncations, frame-shift and copy number variants have been reported in this gene, no missense mutations have been found to segregate previously. This is the first report of a missense NHS mutation causing NHS phenotype (including cardiac defects). We hypothesize also that the non-reported UTR–SNP of the exon 8 (3′-UTR) is specific to the Tunisian population. PMID:21559051

The first missense mutation of NHS gene in a Tunisian family with clinical features of NHS syndrome including cardiac anomaly.

PubMed

Chograni, Manèl; Rejeb, Imen; Jemaa, Lamia Ben; Châabouni, Myriam; Bouhamed, Habiba Chaabouni

2011-08-01

Nance-Horan Syndrome (NHS) or X-linked cataract-dental syndrome is a disease of unknown gene action mechanism, characterized by congenital cataract, dental anomalies, dysmorphic features and, in some cases, mental retardation. We performed linkage analysis in a Tunisian family with NHS in which affected males and obligate carrier female share a common haplotype in the Xp22.32-p11.21 region that contains the NHS gene. Direct sequencing of NHS coding exons and flanking intronic sequences allowed us to identify the first missense mutation (P551S) and a reported SNP-polymorphism (L1319F) in exon 6, a reported UTR-SNP (c.7422 C>T) and a novel one (c.8239 T>A) in exon 8. Both variations P551S and c.8239 T>A segregate with NHS phenotype in this family. Although truncations, frame-shift and copy number variants have been reported in this gene, no missense mutations have been found to segregate previously. This is the first report of a missense NHS mutation causing NHS phenotype (including cardiac defects). We hypothesize also that the non-reported UTR-SNP of the exon 8 (3'-UTR) is specific to the Tunisian population.

Clinical and radiological features of Marchiafava–Bignami disease

PubMed Central

Dong, Xiaoyu; Bai, Chaobo; Nao, Jianfei

2018-01-01

Abstract Marchiafava–Bignami disease (MBD) is a rare neurological disease usually associated with chronic alcoholism and characterized by demyelination and necrosis. Our aims were to describe the clinicoradiological features and identify factors that may affect the prognosis of patients with MBD. We examined clinical manifestations, laboratory results, and neuroradiological features of 9 patients with MBD. The patients were classified into 2 subgroups (favorable and poor outcome subgroups) based on the Modified Oxford Handicap Scale (MOSH). In addition, we compared the clinical and neuroimaging features between the 2 subgroups. Nine adult male patients (age of onset range 37–62 years, with a mean age of 47.00 ± 14.50 years) were included in this study. According to MOSH, 4 patients were placed in the poor outcome subgroup (MOHS ≥ 3), 5 patients were placed in the favorable outcome subgroup (MOHS ≤ 2). Relatively high score of MAST-C (≥6) (P = .008), extracallosal lesions (P = .048), GCS (P = .026), cerebral lobe impairment (P = .048) was significantly more common in the poor outcome subgroup. Clinical manifestations of MBD are variable and lack specificity. Early diagnosis by relatively specific performance of bisymmetric lesions in corpus callosum of diffusion-weighted imaging (DWI) may affect the prognosis. The prognosis of patients with severe disturbance of consciousness, heavy alcohol consumption, extracallosal lesions, cerebral lobe impairment is probably unfavorable. PMID:29384842

Mosaic tetraploidy in a liveborn infant with features of the DiGeorge anomaly.

PubMed

Wullich, B; Henn, W; Groterath, E; Ermis, A; Fuchs, S; Zankl, M

1991-11-01

We report on a liveborn male infant with mosaic tetraploidy who presented with multiple congenital anomalies including features of the DiGeorge anomaly (type I truncus arteriosus with other cardiovascular malformations, thymic hypoplasia, hypocalcemia). No structural chromosome aberrations, namely of chromosome 22, were detected. These findings contribute to the variability of symptoms of the polyploid phenotype. Additionally, the cytogenetic studies in our case emphasize the necessity of investigating fibroblasts in order to evaluate the relevant proportion of aberrant cells in mosaicism.

Gynaecomastia as a presenting feature of thyrotoxicosis

PubMed Central

Chan, W; Yeung, V; Chow, C; So, W; Cockram, C

1999-01-01

The association between gynaecomastia and thyrotoxicosis is well recognised. However, the reported frequency of the association is variable, partly depending upon the defining criteria used. Here we report two patients with thyrotoxicosis in whom gynaecomastia was the presenting feature. Both patients had other contributing factors, which are assumed to have predisposed to gynaecomastia. In both patients, the gynaecomastia resolved with successful treatment of the thyrotoxicosis. When gynaecomastia is a presenting, or prominent feature of thyrotoxicosis, the possibility of additional underlying pathology should be considered.


Keywords: gynaecomastia; thyrotoxicosis; sex hormone PMID:10715765

Intrinsic feature-based pose measurement for imaging motion compensation

DOEpatents

Baba, Justin S.; Goddard, Jr., James Samuel

2014-08-19

Systems and methods for generating motion corrected tomographic images are provided. A method includes obtaining first images of a region of interest (ROI) to be imaged and associated with a first time, where the first images are associated with different positions and orientations with respect to the ROI. The method also includes defining an active region in the each of the first images and selecting intrinsic features in each of the first images based on the active region. Second, identifying a portion of the intrinsic features temporally and spatially matching intrinsic features in corresponding ones of second images of the ROI associated with a second time prior to the first time and computing three-dimensional (3D) coordinates for the portion of the intrinsic features. Finally, the method includes computing a relative pose for the first images based on the 3D coordinates.

Rough sets and Laplacian score based cost-sensitive feature selection.

PubMed

Yu, Shenglong; Zhao, Hong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of "good" features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

Modeling crash injury severity by road feature to improve safety.

PubMed

Penmetsa, Praveena; Pulugurtha, Srinivas S

2018-01-02

The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature. Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity. Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway. The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.

Discrimination Enhancement with Transient Feature Analysis of a Graphene Chemical Sensor.

PubMed

Nallon, Eric C; Schnee, Vincent P; Bright, Collin J; Polcha, Michael P; Li, Qiliang

2016-01-19

A graphene chemical sensor is subjected to a set of structurally and chemically similar hydrocarbon compounds consisting of toluene, o-xylene, p-xylene, and mesitylene. The fractional change in resistance of the sensor upon exposure to these compounds exhibits a similar response magnitude among compounds, whereas large variation is observed within repetitions for each compound, causing a response overlap. Therefore, traditional features depending on maximum response change will cause confusion during further discrimination and classification analysis. More robust features that are less sensitive to concentration, sampling, and drift variability would provide higher quality information. In this work, we have explored the advantage of using transient-based exponential fitting coefficients to enhance the discrimination of similar compounds. The advantages of such feature analysis to discriminate each compound is evaluated using principle component analysis (PCA). In addition, machine learning-based classification algorithms were used to compare the prediction accuracies when using fitting coefficients as features. The additional features greatly enhanced the discrimination between compounds while performing PCA and also improved the prediction accuracy by 34% when using linear discrimination analysis.

Learning discriminative functional network features of schizophrenia

NASA Astrophysics Data System (ADS)

Gheiratmand, Mina; Rish, Irina; Cecchi, Guillermo; Brown, Matthew; Greiner, Russell; Bashivan, Pouya; Polosecki, Pablo; Dursun, Serdar

2017-03-01

Associating schizophrenia with disrupted functional connectivity is a central idea in schizophrenia research. However, identifying neuroimaging-based features that can serve as reliable "statistical biomarkers" of the disease remains a challenging open problem. We argue that generalization accuracy and stability of candidate features ("biomarkers") must be used as additional criteria on top of standard significance tests in order to discover more robust biomarkers. Generalization accuracy refers to the utility of biomarkers for making predictions about individuals, for example discriminating between patients and controls, in novel datasets. Feature stability refers to the reproducibility of the candidate features across different datasets. Here, we extracted functional connectivity network features from fMRI data at both high-resolution (voxel-level) and a spatially down-sampled lower-resolution ("supervoxel" level). At the supervoxel level, we used whole-brain network links, while at the voxel level, due to the intractably large number of features, we sampled a subset of them. We compared statistical significance, stability and discriminative utility of both feature types in a multi-site fMRI dataset, composed of schizophrenia patients and healthy controls. For both feature types, a considerable fraction of features showed significant differences between the two groups. Also, both feature types were similarly stable across multiple data subsets. However, the whole-brain supervoxel functional connectivity features showed a higher cross-validation classification accuracy of 78.7% vs. 72.4% for the voxel-level features. Cross-site variability and heterogeneity in the patient samples in the multi-site FBIRN dataset made the task more challenging compared to single-site studies. The use of the above methodology in combination with the fully data-driven approach using the whole brain information have the potential to shed light on "biomarker discovery" in schizophrenia.

Malignant melanoma of sun-protected sites: a review of clinical, histological, and molecular features.

PubMed

Merkel, Emily A; Gerami, Pedram

2017-06-01

In most cases of cutaneous melanoma, ultraviolet (UV) radiation is recognized as a prominent risk factor. Less is known regarding the mechanisms of mutagenesis for melanoma arising in sun-protected sites, such as acral and mucosal melanoma. Acral and mucosal melanoma share many common features, including a late age of onset, a broad radial growth phase with prominent lentiginous growth, the presence of field cancerization cells, and, in most cases, lack of a precursor nevus. In addition to early chromosomal instability, many of the same genes are also involved in these two distinct melanoma subtypes. To better understand non-UV-mediated pathogenesis in melanoma, we conducted a joint literature review of clinical, histological, and molecular features in acral and mucosal melanoma. We also reviewed the current literature regarding aberrations in KIT, PDGFRA, TERT, and other commonly involved genes. By comparing common features of these two subtypes, we suggest potential mechanisms underlying acral and/or mucosal melanoma and offer direction for future investigations.

Ceramic substrate including thin film multilayer surface conductor

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

Wolf, Joseph Ambrose; Peterson, Kenneth A.

2017-05-09

A ceramic substrate comprises a plurality of ceramic sheets, a plurality of inner conductive layers, a plurality of vias, and an upper conductive layer. The ceramic sheets are stacked one on top of another and include a top ceramic sheet. The inner conductive layers include electrically conductive material that forms electrically conductive features on an upper surface of each ceramic sheet excluding the top ceramic sheet. The vias are formed in each of the ceramic sheets with each via being filled with electrically conductive material. The upper conductive layer includes electrically conductive material that forms electrically conductive features on anmore » upper surface of the top ceramic sheet. The upper conductive layer is constructed from a stack of four sublayers. A first sublayer is formed from titanium. A second sublayer is formed from copper. A third sublayer is formed from platinum. A fourth sublayer is formed from gold.« less

qFeature

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

2015-09-14

This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.

Tunable features of magnetoelectric transformers.

PubMed

Dong, Shuxiang; Zhai, Junyi; Priya, Shashank; Li, Jie-Fang; Viehland, Dwight

2009-06-01

We have found that magnetostrictive FeBSiC alloy ribbons laminated with piezoelectric Pb(Zr,Ti)O(3) fiber can act as a tunable transformer when driven under resonant conditions. These composites were also found to exhibit the strongest resonant magnetoelectric voltage coefficient of 750 V/cm-Oe. The tunable features were achieved by applying small dc magnetic biases of -5 features include 1) a high voltage gain of -55 features can be attributed to large changes in the piezomagnetic coefficient and permeability of the magnetostrictive phase under H(dc).

Structural Features of Algebraic Quantum Notations

ERIC Educational Resources Information Center

Gire, Elizabeth; Price, Edward

2015-01-01

The formalism of quantum mechanics includes a rich collection of representations for describing quantum systems, including functions, graphs, matrices, histograms of probabilities, and Dirac notation. The varied features of these representations affect how computations are performed. For example, identifying probabilities of measurement outcomes…

Graphical augmentations to the funnel plot assess the impact of additional evidence on a meta-analysis.

PubMed

Langan, Dean; Higgins, Julian P T; Gregory, Walter; Sutton, Alexander J

2012-05-01

We aim to illustrate the potential impact of a new study on a meta-analysis, which gives an indication of the robustness of the meta-analysis. A number of augmentations are proposed to one of the most widely used of graphical displays, the funnel plot. Namely, 1) statistical significance contours, which define regions of the funnel plot in which a new study would have to be located to change the statistical significance of the meta-analysis; and 2) heterogeneity contours, which show how a new study would affect the extent of heterogeneity in a given meta-analysis. Several other features are also described, and the use of multiple features simultaneously is considered. The statistical significance contours suggest that one additional study, no matter how large, may have a very limited impact on the statistical significance of a meta-analysis. The heterogeneity contours illustrate that one outlying study can increase the level of heterogeneity dramatically. The additional features of the funnel plot have applications including 1) informing sample size calculations for the design of future studies eligible for inclusion in the meta-analysis; and 2) informing the updating prioritization of a portfolio of meta-analyses such as those prepared by the Cochrane Collaboration. Copyright © 2012 Elsevier Inc. All rights reserved.

Prominent feature extraction for review analysis: an empirical study

NASA Astrophysics Data System (ADS)

Agarwal, Basant; Mittal, Namita

2016-05-01

Sentiment analysis (SA) research has increased tremendously in recent times. SA aims to determine the sentiment orientation of a given text into positive or negative polarity. Motivation for SA research is the need for the industry to know the opinion of the users about their product from online portals, blogs, discussion boards and reviews and so on. Efficient features need to be extracted for machine-learning algorithm for better sentiment classification. In this paper, initially various features are extracted such as unigrams, bi-grams and dependency features from the text. In addition, new bi-tagged features are also extracted that conform to predefined part-of-speech patterns. Furthermore, various composite features are created using these features. Information gain (IG) and minimum redundancy maximum relevancy (mRMR) feature selection methods are used to eliminate the noisy and irrelevant features from the feature vector. Finally, machine-learning algorithms are used for classifying the review document into positive or negative class. Effects of different categories of features are investigated on four standard data-sets, namely, movie review and product (book, DVD and electronics) review data-sets. Experimental results show that composite features created from prominent features of unigram and bi-tagged features perform better than other features for sentiment classification. mRMR is a better feature selection method as compared with IG for sentiment classification. Boolean Multinomial Naïve Bayes) algorithm performs better than support vector machine classifier for SA in terms of accuracy and execution time.

Discriminative and informative features for biomolecular text mining with ensemble feature selection.

PubMed

Van Landeghem, Sofie; Abeel, Thomas; Saeys, Yvan; Van de Peer, Yves

2010-09-15

In the field of biomolecular text mining, black box behavior of machine learning systems currently limits understanding of the true nature of the predictions. However, feature selection (FS) is capable of identifying the most relevant features in any supervised learning setting, providing insight into the specific properties of the classification algorithm. This allows us to build more accurate classifiers while at the same time bridging the gap between the black box behavior and the end-user who has to interpret the results. We show that our FS methodology successfully discards a large fraction of machine-generated features, improving classification performance of state-of-the-art text mining algorithms. Furthermore, we illustrate how FS can be applied to gain understanding in the predictions of a framework for biomolecular event extraction from text. We include numerous examples of highly discriminative features that model either biological reality or common linguistic constructs. Finally, we discuss a number of insights from our FS analyses that will provide the opportunity to considerably improve upon current text mining tools. The FS algorithms and classifiers are available in Java-ML (http://java-ml.sf.net). The datasets are publicly available from the BioNLP'09 Shared Task web site (http://www-tsujii.is.s.u-tokyo.ac.jp/GENIA/SharedTask/).

Visualizing complex hydrodynamic features

NASA Astrophysics Data System (ADS)

Kempf, Jill L.; Marshall, Robert E.; Yen, Chieh-Cheng

1990-08-01

The Lake Erie Forecasting System is a cooperative project by university, private and governmental institutions to provide continuous forecasting of three-dimensional structure within the lake. The forecasts will include water velocity and temperature distributions throughout the body of water, as well as water level and wind-wave distributions at the lake's surface. Many hydrodynamic features can be extracted from this data, including coastal jets, large-scale thermocline motion and zones of upwelling and downwelling. A visualization system is being developed that will aid in understanding these features and their interactions. Because of the wide variety of features, they cannot all be adequately represented by a single rendering technique. Particle tracing, surface rendering, and volumetric techniques are all necessary. This visualization effortis aimed towards creating a system that will provide meaningful forecasts for those using the lake for recreational and commercial purposes. For example, the fishing industry needs to know about large-scale thermocline motion in order to find the best fishing areas and power plants need to know water intAke temperatures. The visualization system must convey this information in a manner that is easily understood by these users. Scientists must also be able to use this system to verify their hydrodynamic simulation. The focus of the system, therefore, is to provide the information to serve these diverse interests, without overwhelming any single user with unnecessary data.

An adaptive multi-feature segmentation model for infrared image

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

2016-04-01

Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

PubMed

Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

2014-08-01

Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature

Feature-Selective Attentional Modulations in Human Frontoparietal Cortex.

PubMed

Ester, Edward F; Sutterer, David W; Serences, John T; Awh, Edward

2016-08-03

Control over visual selection has long been framed in terms of a dichotomy between "source" and "site," where top-down feedback signals originating in frontoparietal cortical areas modulate or bias sensory processing in posterior visual areas. This distinction is motivated in part by observations that frontoparietal cortical areas encode task-level variables (e.g., what stimulus is currently relevant or what motor outputs are appropriate), while posterior sensory areas encode continuous or analog feature representations. Here, we present evidence that challenges this distinction. We used fMRI, a roving searchlight analysis, and an inverted encoding model to examine representations of an elementary feature property (orientation) across the entire human cortical sheet while participants attended either the orientation or luminance of a peripheral grating. Orientation-selective representations were present in a multitude of visual, parietal, and prefrontal cortical areas, including portions of the medial occipital cortex, the lateral parietal cortex, and the superior precentral sulcus (thought to contain the human homolog of the macaque frontal eye fields). Additionally, representations in many-but not all-of these regions were stronger when participants were instructed to attend orientation relative to luminance. Collectively, these findings challenge models that posit a strict segregation between sources and sites of attentional control on the basis of representational properties by demonstrating that simple feature values are encoded by cortical regions throughout the visual processing hierarchy, and that representations in many of these areas are modulated by attention. Influential models of visual attention posit a distinction between top-down control and bottom-up sensory processing networks. These models are motivated in part by demonstrations showing that frontoparietal cortical areas associated with top-down control represent abstract or categorical stimulus

Rough sets and Laplacian score based cost-sensitive feature selection

PubMed Central

Yu, Shenglong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of “good” features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms. PMID:29912884

Prostatic adenocarcinoma with glomeruloid features.

PubMed

Pacelli, A; Lopez-Beltran, A; Egan, A J; Bostwick, D G

1998-05-01

A wide variety of architectural patterns of adenocarcinoma may be seen in the prostate. We have recently encountered a hitherto-undescribed pattern of growth characterized by intraluminal ball-like clusters of cancer cells reminiscent of renal glomeruli, which we refer to as prostatic adenocarcinoma with glomeruloid features. To define the architectural features, frequency, and distribution of prostatic adenocarcinoma with glomeruloid features, we reviewed 202 totally embedded radical prostatectomy specimens obtained between October 1992 and April 1994 from the files of the Mayo Clinic. This series was supplemented by 100 consecutive needle biopsies with prostatic cancer from January to February 1996. Prostatic adenocarcinoma with glomeruloid features was characterized by round to oval epithelial tufts growing within malignant acini, often supported by a fibrovascular core. The epithelial cells were sometimes arranged in semicircular concentric rows separated by clefted spaces. In the radical prostatectomy specimens, nine cases (4.5%) had glomeruloid features. The glomeruloid pattern constituted 5% to 20% of each cancer (mean, 8.33%) and was usually located at the apex or in the peripheral zone of the prostate. Seven cases were associated with a high Gleason score (7 or 8), one with a score of 6, and one with a score of 5. All cases were associated with high-grade prostatic intraepithelial neoplasia and extensive perineural invasion. Pathological stages included T2c (three cases), T3b (four cases), and T3c (two cases); one of the T3b cases had lymph node metastases (N1). Three (3%) of 100 consecutive routine needle biopsy specimens with cancer showed glomeruloid features, and this pattern constituted 5% to 10% of each cancer (mean, 6.7%). The Gleason score was 6 for two cases and 8 for one case. Two cases were associated with high-grade prostatic intraepithelial neoplasia, and one case had perineural invasion. Glomeruloid features were not observed in any benign or

A prototype feature system for feature retrieval using relationships

USGS Publications Warehouse

Choi, J.; Usery, E.L.

2009-01-01

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

Ontology patterns for complex topographic feature yypes

USGS Publications Warehouse

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

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

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Comparative evaluation of Populus variants total sugar release and structural features following pretreatment and digestion by two distinct biological systems

DOE PAGES

Thomas, Vanessa A.; Kothari, Ninad; Bhagia, Samarthya; ...

2017-11-30

Populus natural variants have been shown to realize a broad range of sugar yields during saccharification, however, the structural features responsible for higher sugar release from natural variants are not clear. In addition, the sugar release patterns resulting from digestion with two distinct biological systems, fungal enzymes and Clostridium thermocellum, have yet to be evaluated and compared. This study evaluates the effect of structural features of three natural variant Populus lines, which includes the line BESC standard, with respect to the overall process of sugar release for two different biological systems.

Additive Manufacturing Design Considerations for Liquid Engine Components

NASA Technical Reports Server (NTRS)

Whitten, Dave; Hissam, Andy; Baker, Kevin; Rice, Darron

2014-01-01

The Marshall Space Flight Center's Propulsion Systems Department has gained significant experience in the last year designing, building, and testing liquid engine components using additive manufacturing. The department has developed valve, duct, turbo-machinery, and combustion device components using this technology. Many valuable lessons were learned during this process. These lessons will be the focus of this presentation. We will present criteria for selecting part candidates for additive manufacturing. Some part characteristics are 'tailor made' for this process. Selecting the right parts for the process is the first step to maximizing productivity gains. We will also present specific lessons we learned about feature geometry that can and cannot be produced using additive manufacturing machines. Most liquid engine components were made using a two-step process. The base part was made using additive manufacturing and then traditional machining processes were used to produce the final part. The presentation will describe design accommodations needed to make the base part and lessons we learned about which features could be built directly and which require the final machine process. Tolerance capabilities, surface finish, and material thickness allowances will also be covered. Additive Manufacturing can produce internal passages that cannot be made using traditional approaches. It can also eliminate a significant amount of manpower by reducing part count and leveraging model-based design and analysis techniques. Information will be shared about performance enhancements and design efficiencies we experienced for certain categories of engine parts.

Long-term outcomes of adults with features of VACTERL association

PubMed Central

Raam, Manu S.; Pineda-Alvarez, Daniel E.; Hadley, Donald W.; Solomon, Benjamin D.

2010-01-01

VACTERL association involves the presence of specific congenital, multi-organ malformations that tend to co-occur. Clinical and research efforts typically center on pediatric patients, and there is a scarcity of information in the literature regarding VACTERL-related issues and outcomes in adulthood. We describe here 11 adults with features of VACTERL association ascertained through our research study on the condition. In our cohort of adult patients, approximately 25% of medically significant malformations that are component features of VACTERL association, including 40% of vertebral, 50% of cardiac, and 50% of renal anomalies, were not identified during childhood. Additionally, medical sequelae of many of the primary malformations identified in infancy or early childhood persist or are first reported in adulthood. These sequelae can involve challenging medical and surgical management in adulthood. As most adults with VACTERL association are not specifically followed for VACTERL-related issues, a more uniform diagnostic work-up and a low threshold for investigation of medical sequelae of the primary disorder may enhance the quality of clinical management in these patients. PMID:20888933

Dissociative features in posttraumatic stress disorder: A latent profile analysis.

PubMed

Műllerová, Jana; Hansen, Maj; Contractor, Ateka A; Elhai, Jon D; Armour, Cherie

2016-09-01

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) characterizes the dissociative subtype of posttraumatic stress disorder (PTSD) in terms of the individual meeting the criteria for PTSD and additionally reporting symptoms of depersonalization and/or derealization. The current study aimed to examine whether a dissociative PTSD profile may include alternative features of dissociation and whether it could be differentiated from a nondissociative PTSD profile on certain psychopathologies and demographics. Data from 309 trauma-exposed participants, collected through Amazon Mechanical Turk, were subjected to latent profile analysis. Regression analyses were used to examine the predictors of latent classes. Three discrete profiles named Baseline, PTSD, and Dissociative profile were uncovered. All examined features of dissociation were significantly elevated in the Dissociative profile. Anxiety, male sex, being employed, and having a minority racial background significantly predicted the Dissociative profile relative to the PTSD profile. The study points to the importance of alternative symptoms of dissociation in the dissociative PTSD subtype beyond the symptoms of depersonalization and derealization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Food additives

MedlinePlus

... or natural. Natural food additives include: Herbs or spices to add flavor to foods Vinegar for pickling ... Certain colors improve the appearance of foods. Many spices, as well as natural and man-made flavors, ...

Microstructure and Mechanical Properties of Additively Manufactured Parts with Staircase Feature

NASA Astrophysics Data System (ADS)

Keya, Tahmina

This thesis focuses on a part with staircase feature that is made of Inconel 718 and fabricated by SLM process. The objective of the study was to observe build height effect on the microstructure and mechanical properties of the part. Due to the nature of SLM, there is possibility of different microstructure and mechanical properties in different locations depending on the design of the part. The objective was to compare microstructure and mechanical properties from different location and four comparison groups were considered: 1. Effect of thermal cycle; 2. External and internal surfaces; 3. Build height effect and 4. Bottom surfaces. To achieve the goals of this research, standard metallurgical procedure has been performed to prepare samples. Etching was done to reveal the microstructure of SLM processed Inconel 718 parts. Young's modulus and hardness were measured using nanoindentation technique. FEM analysis was performed to simulate nanoindentation. The conclusions drawn from this research are: 1. The microstructure of front and side surface of SLM processed Inconel 718 consists of arc shaped cut ends of melt pools with intermetallic phase at the border of the melt pool; 2. On top surface, melted tracks and scanning patterns can be observed and the average width of melted tracks is 100-150 microm; 3. The microstructure looks similar at different build height; 4. Microstructure on the top of a stair is more defined and organized than the internal surface; 5. The mechanical properties are highest at the bottom. OM images revealed slight difference in microstructure in terms of build height for this specific part, but mechanical properties seem to be vary noticeably. This is something to be kept in mind while designing or determining build orientation. External and internal surfaces of a stair at the same height showed difference in both microstructure and mechanical properties. To minimize that effect and to make it more uniform, gradual elevation can be

Feature selection in feature network models: finding predictive subsets of features with the Positive Lasso.

PubMed

Frank, Laurence E; Heiser, Willem J

2008-05-01

A set of features is the basis for the network representation of proximity data achieved by feature network models (FNMs). Features are binary variables that characterize the objects in an experiment, with some measure of proximity as response variable. Sometimes features are provided by theory and play an important role in the construction of the experimental conditions. In some research settings, the features are not known a priori. This paper shows how to generate features in this situation and how to select an adequate subset of features that takes into account a good compromise between model fit and model complexity, using a new version of least angle regression that restricts coefficients to be non-negative, called the Positive Lasso. It will be shown that features can be generated efficiently with Gray codes that are naturally linked to the FNMs. The model selection strategy makes use of the fact that FNM can be considered as univariate multiple regression model. A simulation study shows that the proposed strategy leads to satisfactory results if the number of objects is less than or equal to 22. If the number of objects is larger than 22, the number of features selected by our method exceeds the true number of features in some conditions.

Physical Features of Visual Images Affect Macaque Monkey’s Preference for These Images

PubMed Central

Funahashi, Shintaro

2016-01-01

Animals exhibit different degrees of preference toward various visual stimuli. In addition, it has been shown that strongly preferred stimuli can often act as a reward. The aim of the present study was to determine what features determine the strength of the preference for visual stimuli in order to examine neural mechanisms of preference judgment. We used 50 color photographs obtained from the Flickr Material Database (FMD) as original stimuli. Four macaque monkeys performed a simple choice task, in which two stimuli selected randomly from among the 50 stimuli were simultaneously presented on a monitor and monkeys were required to choose either stimulus by eye movements. We considered that the monkeys preferred the chosen stimulus if it continued to look at the stimulus for an additional 6 s and calculated a choice ratio for each stimulus. Each monkey exhibited a different choice ratio for each of the original 50 stimuli. They tended to select clear, colorful and in-focus stimuli. Complexity and clarity were stronger determinants of preference than colorfulness. Images that included greater amounts of spatial frequency components were selected more frequently. These results indicate that particular physical features of the stimulus can affect the strength of a monkey’s preference and that the complexity, clarity and colorfulness of the stimulus are important determinants of this preference. Neurophysiological studies would be needed to examine whether these features of visual stimuli produce more activation in neurons that participate in this preference judgment. PMID:27853424

CONTRASTIVE CULTURAL FEATURES IN FL TEACHING.

ERIC Educational Resources Information Center

FISCHER, MILLA

CONTRASTIVE CULTURAL FEATURES SHOULD BE INCLUDED WITHIN THE FRAMEWORK OF THE GRAMMATICAL LESSON AS A MEANS OF COUNTERBALANCING THE GENERALLY UNSATISFACTORY MATERIAL USED FOR RUSSIAN TEXTS. LESSONS FOR AMERICAN STUDENTS LEARNING RUSSIAN SHOULD INCLUDE PHONOLOGICAL DRILLS ON VOWEL LENGTHS, DISTRIBUTION OF VOICED OBSTRUENTS, AND OBSTRUENT CLUSTERS,…

Integrated Education. Feature Issue.

ERIC Educational Resources Information Center

York, Jennifer, Ed.; Vandercook, Terri, Ed.

1988-01-01

This "feature issue" provides various perspectives on a number of integrated education topics, including successful integration practices and strategies, the changing roles of teachers, the appropriate role of research, the history and future of integrated education, and the realization of dreams of life in the mainstream for children with severe…

Genitourinary malformations: an under-recognized feature of ectrodactyly, ectodermal dysplasia and cleft lip/palate syndrome.

PubMed

Hyder, Zerin; Beale, Victoria; O'Connor, Ruth; Clayton-Smith, Jill

2017-04-01

The ectodermal dysplasia and cleft lip/palate (EEC) syndrome describes the association of ectrodactyly, ectodermal dysplasia and orofacial clefting. As with many autosomal dominant disorders, there is variability in expression and not all of these three core features are present in every individual with the condition. Moreover, there may be additional associated features, which are under-recognized. One of these is the presence of genitourinary anomalies, some of which cause significant morbidity. This report details a further two patients with EEC syndrome and genitourinary involvement, including flaccid megacystis with detrusor muscle failure, bilateral hydronephrosis and megaureter, requiring significant renal and urological involvement during their childhood. We go on to review the literature on the diagnosis and management of genitourinary malformations in EEC syndrome.

Formative Assessment: Simply, No Additives

ERIC Educational Resources Information Center

Roskos, Kathleen; Neuman, Susan B.

2012-01-01

Among the types of assessment the closest to daily reading instruction is formative assessment. In contrast to summative assessment, which occurs after instruction, formative assessment involves forming judgments frequently in the flow of instruction. Key features of formative assessment include identifying gaps between where students are and…

On the location of Steve, the mysterious subauroral feature

NASA Astrophysics Data System (ADS)

Gallardo-Lacourt, B.; Nishimura, Y.; Donovan, E.; Gillies, D. M.; Spanswick, E.; Archer, W. E.; MacDonald, E.; Knudsen, D. J.

2017-12-01

Over the past year, there has been an exciting development in auroral research with the finding of a new subauroral phenomenon called Steve. Although Steve has been documented by amateur night sky watchers for decades, this is a new phenomenon about which scientists know very little. From optical observations including images from amateur photographers, Steve is a luminous arc that is narrow in north-south extent, and thousands of kilometers in east-west extent. We use auroral images from the ground-based THEMIS all-sky imagers and the Redline Geospace Observatory (REGO) array to identify Steve events. In addition, we use data from Meridian Scanning Photometers (NORSTAR and FESO) that measure brightness of H-β proton auroral emission at 4861Å. We surveyed data from December 2007 up to May 2017. Our observations suggest that Steve is always located equatorward of the proton aurora, and thus is not a traditional electron auroral arc, a feature which is always poleward of the peak in proton auroral brightness. Further, we have developed a picture of the magnetospheric region which is magnetically conjugate to Steve, and the magnetospheric conditions which give rise to the feature.

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Speech-feature discrimination in children with Asperger syndrome as determined with the multi-feature mismatch negativity paradigm.

PubMed

Kujala, T; Kuuluvainen, S; Saalasti, S; Jansson-Verkasalo, E; von Wendt, L; Lepistö, T

2010-09-01

Asperger syndrome, belonging to the autistic spectrum of disorders, involves deficits in social interaction and prosodic use of language but normal development of formal language abilities. Auditory processing involves both hyper- and hypoactive reactivity to acoustic changes. Responses composed of mismatch negativity (MMN) and obligatory components were recorded for five types of deviations in syllables (vowel, vowel duration, consonant, syllable frequency, syllable intensity) with the multi-feature paradigm from 8-12-year old children with Asperger syndrome. Children with Asperger syndrome had larger MMNs for intensity and smaller MMNs for frequency changes than typically developing children, whereas no MMN group differences were found for the other deviant stimuli. Furthermore, children with Asperger syndrome performed more poorly than controls in Comprehension of Instructions subtest of a language test battery. Cortical speech-sound discrimination is aberrant in children with Asperger syndrome. This is evident both as hypersensitive and depressed neural reactions to speech-sound changes, and is associated with features (frequency, intensity) which are relevant for prosodic processing. The multi-feature MMN paradigm, which includes variation and thereby resembles natural speech hearing circumstances, suggests abnormal pattern of speech discrimination in Asperger syndrome, including both hypo- and hypersensitive responses for speech features. 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

SmaggIce 2.0: Additional Capabilities for Interactive Grid Generation of Iced Airfoils

NASA Technical Reports Server (NTRS)

Kreeger, Richard E.; Baez, Marivell; Braun, Donald C.; Schilling, Herbert W.; Vickerman, Mary B.

2008-01-01

The Surface Modeling and Grid Generation for Iced Airfoils (SmaggIce) software toolkit has been extended to allow interactive grid generation for multi-element iced airfoils. The essential phases of an icing effects study include geometry preparation, block creation and grid generation. SmaggIce Version 2.0 now includes these main capabilities for both single and multi-element airfoils, plus an improved flow solver interface and a variety of additional tools to enhance the efficiency and accuracy of icing effects studies. An overview of these features is given, especially the new multi-element blocking strategy using the multiple wakes method. Examples are given which illustrate the capabilities of SmaggIce for conducting an icing effects study for both single and multi-element airfoils.

Eye movement identification based on accumulated time feature

NASA Astrophysics Data System (ADS)

Guo, Baobao; Wu, Qiang; Sun, Jiande; Yan, Hua

2017-06-01

Eye movement is a new kind of feature for biometrical recognition, it has many advantages compared with other features such as fingerprint, face, and iris. It is not only a sort of static characteristics, but also a combination of brain activity and muscle behavior, which makes it effective to prevent spoofing attack. In addition, eye movements can be incorporated with faces, iris and other features recorded from the face region into multimode systems. In this paper, we do an exploring study on eye movement identification based on the eye movement datasets provided by Komogortsev et al. in 2011 with different classification methods. The time of saccade and fixation are extracted from the eye movement data as the eye movement features. Furthermore, the performance analysis was conducted on different classification methods such as the BP, RBF, ELMAN and SVM in order to provide a reference to the future research in this field.

Global map of eolian features on Mars.

USGS Publications Warehouse

Ward, A.W.; Doyle, K.B.; Helm, P.J.; Weisman, M.K.; Witbeck, N.E.

1985-01-01

Ten basic categories of eolian features on Mars were identified from a survey of Mariner 9 and Viking orbiter images. The ten features mapped are 1) light streaks (including frost streaks), 2) dark streaks, 3) sand sheets or splotches, 4) barchan dunes, 5) transverse dunes, 6) crescentic dunes, 7) anomalous dunes, 8) yardangs, 9) wind grooves, and 10) deflation pits. The features were mapped in groups, not as individual landforms, and recorded according to their geographic positions and orientations on maps of 1:12.5 million or 1:25 million scale. -from Authors

Additive Manufacturing for Cost Efficient Production of Compact Ceramic Heat Exchangers and Recuperators

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

Shulman, Holly; Ross, Nicole

2015-10-30

An additive manufacture technique known as laminated object manufacturing (LOM) was used to fabricate compact ceramic heat exchanger prototypes. LOM uses precision CO2 laser cutting of ceramic green tapes, which are then precision stacked to build a 3D object with fine internal features. Modeling was used to develop prototype designs and predict the thermal response, stress, and efficiency in the ceramic heat exchangers. Build testing and materials analyses were used to provide feedback for the design selection. During this development process, laminated object manufacturing protocols were established. This included laser optimization, strategies for fine feature integrity, lamination fluid control, greenmore » handling, and firing profile. Three full size prototypes were fabricated using two different designs. One prototype was selected for performance testing. During testing, cross talk leakage prevented the application of a high pressure differential, however, the prototype was successful at withstanding the high temperature operating conditions (1300 °F). In addition, analysis showed that the bulk of the part did not have cracks or leakage issues. This led to the development of a module method for next generation LOM heat exchangers. A scale-up cost analysis showed that given a purpose built LOM system, these ceramic heat exchangers would be affordable for the applications.« less

Classification of radiolarian images with hand-crafted and deep features

NASA Astrophysics Data System (ADS)

Keçeli, Ali Seydi; Kaya, Aydın; Keçeli, Seda Uzunçimen

2017-12-01

Radiolarians are planktonic protozoa and are important biostratigraphic and paleoenvironmental indicators for paleogeographic reconstructions. Radiolarian paleontology still remains as a low cost and the one of the most convenient way to obtain dating of deep ocean sediments. Traditional methods for identifying radiolarians are time-consuming and cannot scale to the granularity or scope necessary for large-scale studies. Automated image classification will allow making these analyses promptly. In this study, a method for automatic radiolarian image classification is proposed on Scanning Electron Microscope (SEM) images of radiolarians to ease species identification of fossilized radiolarians. The proposed method uses both hand-crafted features like invariant moments, wavelet moments, Gabor features, basic morphological features and deep features obtained from a pre-trained Convolutional Neural Network (CNN). Feature selection is applied over deep features to reduce high dimensionality. Classification outcomes are analyzed to compare hand-crafted features, deep features, and their combinations. Results show that the deep features obtained from a pre-trained CNN are more discriminative comparing to hand-crafted ones. Additionally, feature selection utilizes to the computational cost of classification algorithms and have no negative effect on classification accuracy.

Text feature extraction based on deep learning: a review.

PubMed

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

Windblown Features on Venus and Geological Mapping

NASA Technical Reports Server (NTRS)

Greeley, Ronald

1999-01-01

The objectives of this study were to: 1) develop a global data base of aeolian features by searching Magellan coverage for possible time-variable wind streaks, 2) analyze the data base to characterize aeolian features and processes on Venus, 3) apply the analysis to assessments of wind patterns near the surface and for comparisons with atmospheric circulation models, 4) analyze shuttle radar data acquired for aeolian features on Earth to determine their radar characteristics, and 5) conduct geological mapping of two quadrangles. Wind, or aeolian, features are observed on Venus and aeolian processes play a role in modifying its surface. Analysis of features resulting from aeolian processes provides insight into characteristics of both the atmosphere and the surface. Wind related features identified on Venus include erosional landforms (yardangs), depositional dune fields, and features resulting from the interaction of the atmosphere and crater ejecta at the time of impact. The most abundant aeolian features are various wind streaks. Their discovery on Venus afforded the opportunity to learn about the interaction of the atmosphere and surface, both for the identification of sediments and in mapping near-surface winds.

Supervised non-negative tensor factorization for automatic hyperspectral feature extraction and target discrimination

NASA Astrophysics Data System (ADS)

Anderson, Dylan; Bapst, Aleksander; Coon, Joshua; Pung, Aaron; Kudenov, Michael

2017-05-01

Hyperspectral imaging provides a highly discriminative and powerful signature for target detection and discrimination. Recent literature has shown that considering additional target characteristics, such as spatial or temporal profiles, simultaneously with spectral content can greatly increase classifier performance. Considering these additional characteristics in a traditional discriminative algorithm requires a feature extraction step be performed first. An example of such a pipeline is computing a filter bank response to extract spatial features followed by a support vector machine (SVM) to discriminate between targets. This decoupling between feature extraction and target discrimination yields features that are suboptimal for discrimination, reducing performance. This performance reduction is especially pronounced when the number of features or available data is limited. In this paper, we propose the use of Supervised Nonnegative Tensor Factorization (SNTF) to jointly perform feature extraction and target discrimination over hyperspectral data products. SNTF learns a tensor factorization and a classification boundary from labeled training data simultaneously. This ensures that the features learned via tensor factorization are optimal for both summarizing the input data and separating the targets of interest. Practical considerations for applying SNTF to hyperspectral data are presented, and results from this framework are compared to decoupled feature extraction/target discrimination pipelines.

Computed Tomography Inspection and Analysis for Additive Manufacturing Components

NASA Technical Reports Server (NTRS)

Beshears, Ronald D.

2017-01-01

Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws and geometric features were inspected using a 2-megavolt linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed to determine the impact of additive manufacturing on inspectability of objects with complex geometries.

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

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

Mahon, R; Weiss, E; Karki, K

Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from themore » delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated

Realistic Free-Spins Features Increase Preference for Slot Machines.

PubMed

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

Clinical features of schizophrenia in a woman with hyperandrogenism.

PubMed Central

Kopala, L C; Lewine, R; Good, K P; Fluker, M; Martzke, J S; Lapointe, J S; Honer, W G

1997-01-01

Ample evidence supports sex differences in the clinical features of schizophrenia. In this regard, estrogen may contribute to later onset and less severe course of illness in women. Direct investigation of hormonal status in schizophrenia is extremely difficult. The present report documents the clinical features of schizophrenia in a young woman with long-standing hyperandrogenism related to polycystic ovarian disease. We postulate that hyperandrogenism contributed to a relatively early onset, olfactory dysfunction, and other clinical features of schizophrenia more commonly associated with men. Additionally, acute estrogen depletion following cessation of oral contraceptives may have precipitated psychosis, while recommencement of oral contraceptives could have contributed to subsequent improvement in symptoms. PMID:9002393

Enhancing facial features by using clear facial features

NASA Astrophysics Data System (ADS)

Rofoo, Fanar Fareed Hanna

2017-09-01

The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2011 CFR

2011-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. No. 35-8, 73 FR 63346, Oct. 24...

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. 35-8, 73 FR 63346, Oct. 24, 2008] ...

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. 35-8, 73 FR 63346, Oct. 24, 2008] ...

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2010 CFR

2010-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. No. 35-8, 73 FR 63346, Oct. 24...

14 CFR 35.7 - Features and characteristics.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have... propeller. The applicant must make changes to the design and conduct additional tests that the Administrator finds necessary to establish the airworthiness of the propeller. [Amdt. 35-8, 73 FR 63346, Oct. 24, 2008] ...

Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization.

PubMed

Adam, Asrul; Shapiai, Mohd Ibrahim; Tumari, Mohd Zaidi Mohd; Mohamad, Mohd Saberi; Mubin, Marizan

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model.

Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization

PubMed Central

Adam, Asrul; Mohd Tumari, Mohd Zaidi; Mohamad, Mohd Saberi

2014-01-01

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that provides the importance of every peak feature in contributing to a good and generalized model. In this study, feature selection and classifier parameters estimation based on particle swarm optimization (PSO) are proposed as a framework for peak detection on EEG signals in time domain analysis. Two versions of PSO are used in the study: (1) standard PSO and (2) random asynchronous particle swarm optimization (RA-PSO). The proposed framework tries to find the best combination of all the available features that offers good peak detection and a high classification rate from the results in the conducted experiments. The evaluation results indicate that the accuracy of the peak detection can be improved up to 99.90% and 98.59% for training and testing, respectively, as compared to the framework without feature selection adaptation. Additionally, the proposed framework based on RA-PSO offers a better and reliable classification rate as compared to standard PSO as it produces low variance model. PMID:25243236

Anxious mood narrows attention in feature space.

PubMed

Wegbreit, Ezra; Franconeri, Steven; Beeman, Mark

2015-01-01

Spatial attention can operate like a spotlight whose scope can vary depending on task demands. Emotional states contribute to the spatial extent of attentional selection, with the spotlight focused more narrowly during anxious moods and more broadly during happy moods. In addition to visual space, attention can also operate over features, and we show here that mood states may also influence attentional scope in feature space. After anxious or happy mood inductions, participants focused their attention to identify a central target while ignoring flanking items. Flankers were sometimes coloured differently than targets, so focusing attention on target colour should lead to relatively less interference. Compared to happy and neutral moods, when anxious, participants showed reduced interference when colour isolated targets from flankers, but showed more interference when flankers and targets were the same colour. This pattern reveals that the anxious mood caused these individuals to attend to the irrelevant feature in both cases, regardless of its benefit or detriment. In contrast, participants showed no effect of colour on interference when happy, suggesting that positive mood did not influence attention in feature space. These mood effects on feature-based attention provide a theoretical bridge between previous findings concerning spatial and conceptual attention.

Instruction of Keyboarding Skills: A Whole Language Approach to Teaching Functional Literacy Skills to Students Who are Blind and Have Additional Disabilities

ERIC Educational Resources Information Center

Stauffer, Mary

2008-01-01

This article describes an unconventional method to teach un-contracted braille reading and writing skills to students who are blind and have additional disabilities. It includes a keyboarding curriculum that focuses on the whole language approach to literacy. A special feature is the keyboard that is adapted with braille symbols. Un-contracted…

Reducing Communication in Algebraic Multigrid Using Additive Variants

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

Vassilevski, Panayot S.; Yang, Ulrike Meier

Algebraic multigrid (AMG) has proven to be an effective scalable solver on many high performance computers. However, its increasing communication complexity on coarser levels has shown to seriously impact its performance on computers with high communication cost. Moreover, additive AMG variants provide not only increased parallelism as well as decreased numbers of messages per cycle but also generally exhibit slower convergence. Here we present various new additive variants with convergence rates that are significantly improved compared to the classical additive algebraic multigrid method and investigate their potential for decreased communication, and improved communication-computation overlap, features that are essential for goodmore » performance on future exascale architectures.« less

Reducing Communication in Algebraic Multigrid Using Additive Variants

DOE PAGES

Vassilevski, Panayot S.; Yang, Ulrike Meier

2014-02-12

Algebraic multigrid (AMG) has proven to be an effective scalable solver on many high performance computers. However, its increasing communication complexity on coarser levels has shown to seriously impact its performance on computers with high communication cost. Moreover, additive AMG variants provide not only increased parallelism as well as decreased numbers of messages per cycle but also generally exhibit slower convergence. Here we present various new additive variants with convergence rates that are significantly improved compared to the classical additive algebraic multigrid method and investigate their potential for decreased communication, and improved communication-computation overlap, features that are essential for goodmore » performance on future exascale architectures.« less

Including granulometric sediment coastal data composition into the Black Sea GIS

NASA Astrophysics Data System (ADS)

Zhuk, Elena; Khaliulin, Alexey; Krylenko, Marina; Krylenko, Viacheslav; Zodiatis, George; Nikolaidis, Marios; Nikolaidis, Andreas

2017-09-01

The module structure of the Black Sea GIS allows the increasing of its functionality, including new data types and defining new procedures accessing them, their visualization and integration with existing data by their conjoint processing and representation. The Black Sea GIS is released as free software; Mapserver is used as a mapping service; MySQL DBMS works with relational data. A new additional feature provided, is the ability of including coastal data obtained in SB SIO RAS. The data represent granulometric composition of the Anapa bay-bar sediments. The Anapa bay-bar is an accumulative sand form (about 50 km long) located on the northwest Russian Black Sea coast. The entire bay-bar and especially its southern part with sand beaches 50-200 m wide is intensively used in recreation. This work is based on the results of field studies of 2010-2014 in the southern part of the Anapa bay-bar researched by scientists of the Shirshov Institute of Oceanology RAS. Since the shore under consideration has no clearly pronounced reference points, "virtual" points located within 1 km distance from each other were selected. Transversal profiles cross these points. The granulometric composition was studied along with 45 profiles. The samples taken in every profile were from the most characteristic morphological parts of the beach. In this study we used shoreline zone samples. Twenty one granule fractions (mm) were separated in the laboratory. The module which processes coastal data allows to select coastal data based on territory/region and granulometric sediment composition. Also, it allows to visualize coastal maps with user-selected features combined with other GIS data.

Featuring the primordial power spectrum: New constraints on interrupted slow-roll from CMB and LRG data

NASA Astrophysics Data System (ADS)

Benetti, Micol; Pandolfi, Stefania; Lattanzi, Massimiliano; Martinelli, Matteo; Melchiorri, Alessandro

2013-01-01

Using the most recent data from the WMAP, ACT and SPT experiments, we update the constraints on models with oscillatory features in the primordial power spectrum of scalar perturbations. This kind of features can appear in models of inflation where slow-roll is interrupted, like multifield models. We also derive constraints for the case in which, in addition to cosmic microwave observations, we also consider the data on the spectrum of luminous red galaxies from the 7th SDSS catalog, and the SNIa Union Compilation 2 data. We have found that: (i) considering a model with features in the primordial power spectrum increases the agreement with data compared to the featureless “vanilla” ΛCDM model by Δχ2=6.7, representing an improvement with respect to the expected value Δχ2=3 for an equivalent model with three additional parameters; (ii) the uncertainty on the determination of the standard parameters is not degraded when features are included; (iii) the best fit for the features model locates the step in the primordial spectrum at a scale k≃0.005Mpc-1, corresponding to the scale where the outliers in the WMAP7 data at ℓ=22 and ℓ=40 are located.; (iv) a distinct, albeit less statistically significant peak is present in the likelihood at smaller scales, whose presence might be related to the WMAP7 preference for a negative value of the running of the scalar spectral index parameter; (v) the inclusion of the LRG-7 data does not change significantly the best fit model, but allows to better constrain the amplitude of the oscillations.

Iris recognition using possibilistic fuzzy matching on local features.

PubMed

Tsai, Chung-Chih; Lin, Heng-Yi; Taur, Jinshiuh; Tao, Chin-Wang

2012-02-01

In this paper, we propose a novel possibilistic fuzzy matching strategy with invariant properties, which can provide a robust and effective matching scheme for two sets of iris feature points. In addition, the nonlinear normalization model is adopted to provide more accurate position before matching. Moreover, an effective iris segmentation method is proposed to refine the detected inner and outer boundaries to smooth curves. For feature extraction, the Gabor filters are adopted to detect the local feature points from the segmented iris image in the Cartesian coordinate system and to generate a rotation-invariant descriptor for each detected point. After that, the proposed matching algorithm is used to compute a similarity score for two sets of feature points from a pair of iris images. The experimental results show that the performance of our system is better than those of the systems based on the local features and is comparable to those of the typical systems.

Ensemble methods with simple features for document zone classification

NASA Astrophysics Data System (ADS)

Obafemi-Ajayi, Tayo; Agam, Gady; Xie, Bingqing

2012-01-01

Document layout analysis is of fundamental importance for document image understanding and information retrieval. It requires the identification of blocks extracted from a document image via features extraction and block classification. In this paper, we focus on the classification of the extracted blocks into five classes: text (machine printed), handwriting, graphics, images, and noise. We propose a new set of features for efficient classifications of these blocks. We present a comparative evaluation of three ensemble based classification algorithms (boosting, bagging, and combined model trees) in addition to other known learning algorithms. Experimental results are demonstrated for a set of 36503 zones extracted from 416 document images which were randomly selected from the tobacco legacy document collection. The results obtained verify the robustness and effectiveness of the proposed set of features in comparison to the commonly used Ocropus recognition features. When used in conjunction with the Ocropus feature set, we further improve the performance of the block classification system to obtain a classification accuracy of 99.21%.

Citing geospatial feature inventories with XML manifests

NASA Astrophysics Data System (ADS)

Bose, R.; McGarva, G.

2006-12-01

Today published scientific papers include a growing number of citations for online information sources that either complement or replace printed journals and books. We anticipate this same trend for cartographic citations used in the geosciences, following advances in web mapping and geographic feature-based services. Instead of using traditional libraries to resolve citations for print material, the geospatial citation life cycle will include requesting inventories of objects or geographic features from distributed geospatial data repositories. Using a case study from the UK Ordnance Survey MasterMap database, which is illustrative of geographic object-based products in general, we propose citing inventories of geographic objects using XML feature manifests. These manifests: (1) serve as a portable listing of sets of versioned features; (2) could be used as citations within the identification portion of an international geospatial metadata standard; (3) could be incorporated into geospatial data transfer formats such as GML; but (4) can be resolved only with comprehensive, curated repositories of current and historic data. This work has implications for any researcher who foresees the need to make or resolve references to online geospatial databases.

Space Object Classification Using Fused Features of Time Series Data

NASA Astrophysics Data System (ADS)

Jia, B.; Pham, K. D.; Blasch, E.; Shen, D.; Wang, Z.; Chen, G.

In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.

Feature selection gait-based gender classification under different circumstances

NASA Astrophysics Data System (ADS)

Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

2014-05-01

This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

Salient object detection method based on multiple semantic features

NASA Astrophysics Data System (ADS)

Wang, Chunyang; Yu, Chunyan; Song, Meiping; Wang, Yulei

2018-04-01

The existing salient object detection model can only detect the approximate location of salient object, or highlight the background, to resolve the above problem, a salient object detection method was proposed based on image semantic features. First of all, three novel salient features were presented in this paper, including object edge density feature (EF), object semantic feature based on the convex hull (CF) and object lightness contrast feature (LF). Secondly, the multiple salient features were trained with random detection windows. Thirdly, Naive Bayesian model was used for combine these features for salient detection. The results on public datasets showed that our method performed well, the location of salient object can be fixed and the salient object can be accurately detected and marked by the specific window.

A Sparsity-Promoted Method Based on Majorization-Minimization for Weak Fault Feature Enhancement

PubMed Central

Hao, Yansong; Song, Liuyang; Tang, Gang; Yuan, Hongfang

2018-01-01

Fault transient impulses induced by faulty components in rotating machinery usually contain substantial interference. Fault features are comparatively weak in the initial fault stage, which renders fault diagnosis more difficult. In this case, a sparse representation method based on the Majorzation-Minimization (MM) algorithm is proposed to enhance weak fault features and extract the features from strong background noise. However, the traditional MM algorithm suffers from two issues, which are the choice of sparse basis and complicated calculations. To address these challenges, a modified MM algorithm is proposed in which a sparse optimization objective function is designed firstly. Inspired by the Basis Pursuit (BP) model, the optimization function integrates an impulsive feature-preserving factor and a penalty function factor. Second, a modified Majorization iterative method is applied to address the convex optimization problem of the designed function. A series of sparse coefficients can be achieved through iterating, which only contain transient components. It is noteworthy that there is no need to select the sparse basis in the proposed iterative method because it is fixed as a unit matrix. Then the reconstruction step is omitted, which can significantly increase detection efficiency. Eventually, envelope analysis of the sparse coefficients is performed to extract weak fault features. Simulated and experimental signals including bearings and gearboxes are employed to validate the effectiveness of the proposed method. In addition, comparisons are made to prove that the proposed method outperforms the traditional MM algorithm in terms of detection results and efficiency. PMID:29597280

A Sparsity-Promoted Method Based on Majorization-Minimization for Weak Fault Feature Enhancement.

PubMed

Ren, Bangyue; Hao, Yansong; Wang, Huaqing; Song, Liuyang; Tang, Gang; Yuan, Hongfang

2018-03-28

Fault transient impulses induced by faulty components in rotating machinery usually contain substantial interference. Fault features are comparatively weak in the initial fault stage, which renders fault diagnosis more difficult. In this case, a sparse representation method based on the Majorzation-Minimization (MM) algorithm is proposed to enhance weak fault features and extract the features from strong background noise. However, the traditional MM algorithm suffers from two issues, which are the choice of sparse basis and complicated calculations. To address these challenges, a modified MM algorithm is proposed in which a sparse optimization objective function is designed firstly. Inspired by the Basis Pursuit (BP) model, the optimization function integrates an impulsive feature-preserving factor and a penalty function factor. Second, a modified Majorization iterative method is applied to address the convex optimization problem of the designed function. A series of sparse coefficients can be achieved through iterating, which only contain transient components. It is noteworthy that there is no need to select the sparse basis in the proposed iterative method because it is fixed as a unit matrix. Then the reconstruction step is omitted, which can significantly increase detection efficiency. Eventually, envelope analysis of the sparse coefficients is performed to extract weak fault features. Simulated and experimental signals including bearings and gearboxes are employed to validate the effectiveness of the proposed method. In addition, comparisons are made to prove that the proposed method outperforms the traditional MM algorithm in terms of detection results and efficiency.

The analysis of image feature robustness using cometcloud

PubMed Central

Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

2012-01-01

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

Relearning To Teach Arithmetic Addition and Subtraction: A Teacher's Study Guide.

ERIC Educational Resources Information Center

Russell, Susan Jo

This package features videotapes and a study guide that are designed to help teachers revisit the operations of addition and subtraction and consider how students can develop meaningful approaches to these operations. The study guides' sessions are on addition, subtraction, the teacher's role, and goals for students and teachers. The readings in…

Expanding the phenotype of alopecia-contractures-dwarfism mental retardation syndrome (ACD syndrome): description of an additional case and review of the literature.

PubMed

Schell-Apacik, Chayim; Hardt, Michael; Ertl-Wagner, Birgit; Klopocki, Eva; Möhrenschlager, Matthias; Heinrich, Uwe; von Voss, Hubertus

2008-09-01

Alopecia-contractures-dwarfism mental retardation syndrome (ACD syndrome; OMIM 203550) is a very rare genetic disorder with distinct features. To our knowledge, there have been four cases documented to date. In addition, another three patients, previously described as having IFAP syndrome (OMIM %308205), may also have ACD syndrome. We report on one patient with short stature, total alopecia, ichthyosis, photophobia, seizures, ectrodactyly, vertebral anomalies, scoliosis, multiple contractures, mental retardation, and striking facial and other features (e.g. microdolichocephaly, missing eyebrows and eyelashes, long nose, large ears) consistent with ACD syndrome. Results of laboratory testing in the literature case reports were normal, although in none of them, array-CGH (microarray-based comparative genomic hybridization) analysis was performed. In conclusion, the combination of specific features, including total alopecia, ichthyosis, mental retardation, and skeletal anomalies are suggestive of ACD syndrome. We propose that children with this syndrome undergo a certain social pediatric protocol including EEG diagnostics, ophthalmological investigation, psychological testing, management of dermatologic and orthopedic problems, and genetic counseling.

Contextual Multi-armed Bandits under Feature Uncertainty

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

Yun, Seyoung; Nam, Jun Hyun; Mo, Sangwoo

We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined NLinRel, having O(T⁷/₈(log(dT)+K√d)) regret bound for T rounds, K actions, and d-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including NLinRel are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has O(T²/₃√log d)regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case,more » we also design a practical variant of NLinRel, coined Universal-NLinRel, for arbitrary feature distributions. It first runs NLinRel for finding the ‘true’ coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of Universal-NLinRel on both synthetic and real-world datasets.« less

Assessing the performance of quantitative image features on early stage prediction of treatment effectiveness for ovary cancer patients: a preliminary investigation

NASA Astrophysics Data System (ADS)

Zargari, Abolfazl; Du, Yue; Thai, Theresa C.; Gunderson, Camille C.; Moore, Kathleen; Mannel, Robert S.; Liu, Hong; Zheng, Bin; Qiu, Yuchen

2018-02-01

The objective of this study is to investigate the performance of global and local features to better estimate the characteristics of highly heterogeneous metastatic tumours, for accurately predicting the treatment effectiveness of the advanced stage ovarian cancer patients. In order to achieve this , a quantitative image analysis scheme was developed to estimate a total of 103 features from three different groups including shape and density, Wavelet, and Gray Level Difference Method (GLDM) features. Shape and density features are global features, which are directly applied on the entire target image; wavelet and GLDM features are local features, which are applied on the divided blocks of the target image. To assess the performance, the new scheme was applied on a retrospective dataset containing 120 recurrent and high grade ovary cancer patients. The results indicate that the three best performed features are skewness, root-mean-square (rms) and mean of local GLDM texture, indicating the importance of integrating local features. In addition, the averaged predicting performance are comparable among the three different categories. This investigation concluded that the local features contains at least as copious tumour heterogeneity information as the global features, which may be meaningful on improving the predicting performance of the quantitative image markers for the diagnosis and prognosis of ovary cancer patients.

Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis.

PubMed

Hu, Shan; Xu, Chao; Guan, Weiqiao; Tang, Yong; Liu, Yana

2014-01-01

Osteosarcoma is the most common malignant bone tumor among children and adolescents. In this study, image texture analysis was made to extract texture features from bone CR images to evaluate the recognition rate of osteosarcoma. To obtain the optimal set of features, Sym4 and Db4 wavelet transforms and gray-level co-occurrence matrices were applied to the image, with statistical methods being used to maximize the feature selection. To evaluate the performance of these methods, a support vector machine algorithm was used. The experimental results demonstrated that the Sym4 wavelet had a higher classification accuracy (93.44%) than the Db4 wavelet with respect to osteosarcoma occurrence in the epiphysis, whereas the Db4 wavelet had a higher classification accuracy (96.25%) for osteosarcoma occurrence in the diaphysis. Results including accuracy, sensitivity, specificity and ROC curves obtained using the wavelets were all higher than those obtained using the features derived from the GLCM method. It is concluded that, a set of texture features can be extracted from the wavelets and used in computer-aided osteosarcoma diagnosis systems. In addition, this study also confirms that multi-resolution analysis is a useful tool for texture feature extraction during bone CR image processing.

Integrating Vocational & Academic Education. A Handbook Featuring Four Demonstration Sites Including Students from Special Populations.

ERIC Educational Resources Information Center

Tindall, Lloyd W.; And Others

This handbook describes the processes and techniques used to develop, implement, and evaluate four integrated vocational and academic learning programs in Wisconsin that included students from special populations. The handbook contains seven chapters. Chapter 1 presents an overview of the project, including the request for proposal process and…

Queensland tick typhus: three cases with unusual clinical features.

PubMed

Wilson, P A; Tierney, L; Lai, K; Graves, S

2013-07-01

Queensland tick typhus (QTT), caused by Rickettsia australis, is usually a relatively mild illness but can occasionally be severe. We describe three cases of probable QTT with unusual clinical features, namely splenic infarction, fulminant myopericarditis and severe leukocytoclastic vasculitis. QTT may present with uncommon clinical features in addition to the more common manifestations. A high index of suspicion enables specific antibiotic therapy that may hasten recovery. © 2013 The Authors; Internal Medicine Journal © 2013 Royal Australasian College of Physicians.

Feature space analysis of MRI

NASA Astrophysics Data System (ADS)

Soltanian-Zadeh, Hamid; Windham, Joe P.; Peck, Donald J.

1997-04-01

This paper presents development and performance evaluation of an MRI feature space method. The method is useful for: identification of tissue types; segmentation of tissues; and quantitative measurements on tissues, to obtain information that can be used in decision making (diagnosis, treatment planning, and evaluation of treatment). The steps of the work accomplished are as follows: (1) Four T2-weighted and two T1-weighted images (before and after injection of Gadolinium) were acquired for ten tumor patients. (2) Images were analyed by two image analysts according to the following algorithm. The intracranial brain tissues were segmented from the scalp and background. The additive noise was suppressed using a multi-dimensional non-linear edge- preserving filter which preserves partial volume information on average. Image nonuniformities were corrected using a modified lowpass filtering approach. The resulting images were used to generate and visualize an optimal feature space. Cluster centers were identified on the feature space. Then images were segmented into normal tissues and different zones of the tumor. (3) Biopsy samples were extracted from each patient and were subsequently analyzed by the pathology laboratory. (4) Image analysis results were compared to each other and to the biopsy results. Pre- and post-surgery feature spaces were also compared. The proposed algorithm made it possible to visualize the MRI feature space and to segment the image. In all cases, the operators were able to find clusters for normal and abnormal tissues. Also, clusters for different zones of the tumor were found. Based on the clusters marked for each zone, the method successfully segmented the image into normal tissues (white matter, gray matter, and CSF) and different zones of the lesion (tumor, cyst, edema, radiation necrosis, necrotic core, and infiltrated tumor). The results agreed with those obtained from the biopsy samples. Comparison of pre- to post-surgery and radiation

Identification of DNA-binding proteins using multi-features fusion and binary firefly optimization algorithm.

PubMed

Zhang, Jian; Gao, Bo; Chai, Haiting; Ma, Zhiqiang; Yang, Guifu

2016-08-26

DNA-binding proteins (DBPs) play fundamental roles in many biological processes. Therefore, the developing of effective computational tools for identifying DBPs is becoming highly desirable. In this study, we proposed an accurate method for the prediction of DBPs. Firstly, we focused on the challenge of improving DBP prediction accuracy with information solely from the sequence. Secondly, we used multiple informative features to encode the protein. These features included evolutionary conservation profile, secondary structure motifs, and physicochemical properties. Thirdly, we introduced a novel improved Binary Firefly Algorithm (BFA) to remove redundant or noisy features as well as select optimal parameters for the classifier. The experimental results of our predictor on two benchmark datasets outperformed many state-of-the-art predictors, which revealed the effectiveness of our method. The promising prediction performance on a new-compiled independent testing dataset from PDB and a large-scale dataset from UniProt proved the good generalization ability of our method. In addition, the BFA forged in this research would be of great potential in practical applications in optimization fields, especially in feature selection problems. A highly accurate method was proposed for the identification of DBPs. A user-friendly web-server named iDbP (identification of DNA-binding Proteins) was constructed and provided for academic use.

Histopathological features of Proteus syndrome.

PubMed

Hoey, S E H; Eastwood, D; Monsell, F; Kangesu, L; Harper, J I; Sebire, N J

2008-05-01

Proteus syndrome is a rare, sporadic overgrowth disorder for which the underlying genetic defect remains unknown. Although the clinical course is well-described there is no systematic histopathological description of the lesional pathology. To describe the histopathological features encountered in a series of patients with Proteus syndrome from a single centre. Patients with Proteus syndrome who had undergone therapeutic surgical resection or biopsy were identified from a database and the histopathological findings were reviewed, with particular regard to descriptive features of the underlying tissue abnormality. There were 18 surgical specimens from nine patients, median age 4 years (range 1-9), classified into four main categories: soft-tissue swellings (lipomatous lesions), vascular anomalies (vascular malformation and haemangioma), macrodactyly (hamartomatous overgrowth) and others (sebaceous naevus and nonspecific features). In all cases, the clinical features of overgrowth were due to increased amounts of disorganized tissue, indicating a hamartomatous-type defect in which normal tissue constituents were present, but with an abnormal distribution and architecture. Vascular malformations represented a prominent category of lesions, accounting for 50% of the specimens, predominantly comprising lymphatic and lymphovascular malformations. No malignancy or cytological atypia was identified in any case. The histopathological features of lesions resected from children with Proteus syndrome predominantly include hamartomatous mixed connective tissue lesions, benign neoplasms such as lipomata, and lymphatic-rich vascular malformations.

Predictive Value of Morphological Features in Patients with Autism versus Normal Controls

ERIC Educational Resources Information Center

Ozgen, H.; Hellemann, G. S.; de Jonge, M. V.; Beemer, F. A.; van Engeland, H.

2013-01-01

We investigated the predictive power of morphological features in 224 autistic patients and 224 matched-pairs controls. To assess the relationship between the morphological features and autism, we used the receiver operator curves (ROC). In addition, we used recursive partitioning (RP) to determine a specific pattern of abnormalities that is…

Qualification of security printing features

NASA Astrophysics Data System (ADS)

Simske, Steven J.; Aronoff, Jason S.; Arnabat, Jordi

2006-02-01

This paper describes the statistical and hardware processes involved in qualifying two related printing features for their deployment in product (e.g. document and package) security. The first is a multi-colored tiling feature that can also be combined with microtext to provide additional forms of security protection. The color information is authenticated automatically with a variety of handheld, desktop and production scanners. The microtext is authenticated either following magnification or manually by a field inspector. The second security feature can also be tile-based. It involves the use of two inks that provide the same visual color, but differ in their transparency to infrared (IR) wavelengths. One of the inks is effectively transparent to IR wavelengths, allowing emitted IR light to pass through. The other ink is effectively opaque to IR wavelengths. These inks allow the printing of a seemingly uniform, or spot, color over a (truly) uniform IR emitting ink layer. The combination converts a uniform covert ink and a spot color to a variable data region capable of encoding identification sequences with high density. Also, it allows the extension of variable data printing for security to ostensibly static printed regions, affording greater security protection while meeting branding and marketing specifications.

Breast Cancer Detection with Reduced Feature Set.

PubMed

Mert, Ahmet; Kılıç, Niyazi; Bilgili, Erdem; Akan, Aydin

2015-01-01

This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%-40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity.

Desired features of smartphone applications promoting physical activity.

PubMed

Rabin, Carolyn; Bock, Beth

2011-12-01

Approximately one-third of adults in the United States are physically inactive. This is a significant public health concern as physical activity (PA) can influence the risk of cardiovascular disease, diabetes, and certain forms of cancer. To minimize these health risks, effective PA interventions must be developed and disseminated to the vast number of individuals who remain sedentary. Smartphone technology presents an exciting opportunity for delivering PA interventions remotely. Although a number of PA applications are currently available for smartphones, these "apps" are not based on established theories of health behavior change and most do not include evidence-based features (e.g., reinforcement and goal setting). Our aim was to collect formative data to develop a smartphone PA app that is empirically and theoretically-based and incorporates user preferences. We recruited 15 sedentary adults to test three currently available PA smartphone apps and provide qualitative and quantitative feedback. Findings indicate that users have a number of specific preferences with regard to PA app features, including that apps provide automatic tracking of PA (e.g., steps taken and calories burned), track progress toward PA goals, and integrate a music feature. Participants also preferred that PA apps be flexible enough to be used with several types of PA, and have well-documented features and user-friendly interfaces (e.g., a one-click main page). When queried by the researcher, most participants endorsed including goal-setting and problem-solving features. These findings provide a blue print for developing a smartphone PA app that incorporates evidence-based components and user preferences.

Segmenting texts from outdoor images taken by mobile phones using color features

NASA Astrophysics Data System (ADS)

Liu, Zongyi; Zhou, Hanning

2011-01-01

Recognizing texts from images taken by mobile phones with low resolution has wide applications. It has been shown that a good image binarization can substantially improve the performances of OCR engines. In this paper, we present a framework to segment texts from outdoor images taken by mobile phones using color features. The framework consists of three steps: (i) the initial process including image enhancement, binarization and noise filtering, where we binarize the input images in each RGB channel, and apply component level noise filtering; (ii) grouping components into blocks using color features, where we compute the component similarities by dynamically adjusting the weights of RGB channels, and merge groups hierachically, and (iii) blocks selection, where we use the run-length features and choose the Support Vector Machine (SVM) as the classifier. We tested the algorithm using 13 outdoor images taken by an old-style LG-64693 mobile phone with 640x480 resolution. We compared the segmentation results with Tsar's algorithm, a state-of-the-art camera text detection algorithm, and show that our algorithm is more robust, particularly in terms of the false alarm rates. In addition, we also evaluated the impacts of our algorithm on the Abbyy's FineReader, one of the most popular commercial OCR engines in the market.

Estimating standard errors in feature network models.

PubMed

Frank, Laurence E; Heiser, Willem J

2007-05-01

Feature network models are graphical structures that represent proximity data in a discrete space while using the same formalism that is the basis of least squares methods employed in multidimensional scaling. Existing methods to derive a network model from empirical data only give the best-fitting network and yield no standard errors for the parameter estimates. The additivity properties of networks make it possible to consider the model as a univariate (multiple) linear regression problem with positivity restrictions on the parameters. In the present study, both theoretical and empirical standard errors are obtained for the constrained regression parameters of a network model with known features. The performance of both types of standard error is evaluated using Monte Carlo techniques.

Facial soft biometric features for forensic face recognition.

PubMed

Tome, Pedro; Vera-Rodriguez, Ruben; Fierrez, Julian; Ortega-Garcia, Javier

2015-12-01

This paper proposes a functional feature-based approach useful for real forensic caseworks, based on the shape, orientation and size of facial traits, which can be considered as a soft biometric approach. The motivation of this work is to provide a set of facial features, which can be understood by non-experts such as judges and support the work of forensic examiners who, in practice, carry out a thorough manual comparison of face images paying special attention to the similarities and differences in shape and size of various facial traits. This new approach constitutes a tool that automatically converts a set of facial landmarks to a set of features (shape and size) corresponding to facial regions of forensic value. These features are furthermore evaluated in a population to generate statistics to support forensic examiners. The proposed features can also be used as additional information that can improve the performance of traditional face recognition systems. These features follow the forensic methodology and are obtained in a continuous and discrete manner from raw images. A statistical analysis is also carried out to study the stability, discrimination power and correlation of the proposed facial features on two realistic databases: MORPH and ATVS Forensic DB. Finally, the performance of both continuous and discrete features is analyzed using different similarity measures. Experimental results show high discrimination power and good recognition performance, especially for continuous features. A final fusion of the best systems configurations achieves rank 10 match results of 100% for ATVS database and 75% for MORPH database demonstrating the benefits of using this information in practice. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A judicious multiple hypothesis tracker with interacting feature extraction

NASA Astrophysics Data System (ADS)

McAnanama, James G.; Kirubarajan, T.

2009-05-01

The multiple hypotheses tracker (mht) is recognized as an optimal tracking method due to the enumeration of all possible measurement-to-track associations, which does not involve any approximation in its original formulation. However, its practical implementation is limited by the NP-hard nature of this enumeration. As a result, a number of maintenance techniques such as pruning and merging have been proposed to bound the computational complexity. It is possible to improve the performance of a tracker, mht or not, using feature information (e.g., signal strength, size, type) in addition to kinematic data. However, in most tracking systems, the extraction of features from the raw sensor data is typically independent of the subsequent association and filtering stages. In this paper, a new approach, called the Judicious Multi Hypotheses Tracker (jmht), whereby there is an interaction between feature extraction and the mht, is presented. The measure of the quality of feature extraction is input into measurement-to-track association while the prediction step feeds back the parameters to be used in the next round of feature extraction. The motivation for this forward and backward interaction between feature extraction and tracking is to improve the performance in both steps. This approach allows for a more rational partitioning of the feature space and removes unlikely features from the assignment problem. Simulation results demonstrate the benefits of the proposed approach.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

PubMed Central

Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

2012-01-01

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

Feature Selection Using Information Gain for Improved Structural-Based Alert Correlation

PubMed Central

Siraj, Maheyzah Md; Zainal, Anazida; Elshoush, Huwaida Tagelsir; Elhaj, Fatin

2016-01-01

Grouping and clustering alerts for intrusion detection based on the similarity of features is referred to as structurally base alert correlation and can discover a list of attack steps. Previous researchers selected different features and data sources manually based on their knowledge and experience, which lead to the less accurate identification of attack steps and inconsistent performance of clustering accuracy. Furthermore, the existing alert correlation systems deal with a huge amount of data that contains null values, incomplete information, and irrelevant features causing the analysis of the alerts to be tedious, time-consuming and error-prone. Therefore, this paper focuses on selecting accurate and significant features of alerts that are appropriate to represent the attack steps, thus, enhancing the structural-based alert correlation model. A two-tier feature selection method is proposed to obtain the significant features. The first tier aims at ranking the subset of features based on high information gain entropy in decreasing order. The‏ second tier extends additional features with a better discriminative ability than the initially ranked features. Performance analysis results show the significance of the selected features in terms of the clustering accuracy using 2000 DARPA intrusion detection scenario-specific dataset. PMID:27893821

Enhanced Exoplanet Biosignature from an Interferometer Addition to Low Resolution Spectrographs

NASA Astrophysics Data System (ADS)

Erskine, D. J.; Muirhead, P. S.; Vanderburg, A. M.; Szentgyorgyi, A.

2017-12-01

The absorption spectral signature of many atmospheric molecules consists of a group of 40 or so lines that are approximately periodic due to the physics of molecular vibration. This is fortuitous for detecting atmospheric features in an exoEarth, since it has a similar periodic nature as an interferometer's transmission, which is sinusoidal. The period (in wavenumbers) of the interferometer is selectable, being inversely proportional to the delay (in cm). We show that the addition of a small interferometer of 0.6 cm delay to an existing dispersive spectrograph can greatly enhance the detection of molecular features, by several orders of magnitude for initially low resolution spectrographs. We simulate the Gemini Planet Imager measuring a telluric spectrum having native resolution of 40 and 70 in the 1.65 micron and 2 micron bands. These low resolutions are insufficient to resolve the fine features of the molecular feature group. However, the addition of a 0.6 cm delay outside the spectrograph and in series with it increases the local amplitude of the signal to a level similar to a R=4400 (at 1.65 micron) or R=3900 (at 2 micron) classical spectrograph. Prepared by LLNL under Contract DE-AC52-07NA27344.

Shielding voices: The modulation of binding processes between voice features and response features by task representations.

PubMed

Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

2017-09-01

Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

Bipolar polygenic loading and bipolar spectrum features in major depressive disorder

PubMed Central

Wiste, Anna; Robinson, Elise B; Milaneschi, Yuri; Meier, Sandra; Ripke, Stephan; Clements, Caitlin C; Fitzmaurice, Garrett M; Rietschel, Marcella; Penninx, Brenda W; Smoller, Jordan W; Perlis, Roy H

2014-01-01

Objectives Family and genetic studies indicate overlapping liability for major depressive disorder and bipolar disorder. The purpose of this study was to determine whether this shared genetic liability influences clinical presentation. Methods A polygenic risk score for bipolar disorder, derived from a large genome-wide association meta-analysis, was generated for each subject of European–American ancestry (n = 1,274) in the Sequential Treatment Alternatives to Relieve Depression study (STAR*D) outpatient major depressive disorder cohort. A hypothesis-driven approach was used to test for association between bipolar disorder risk score and features of depression associated with bipolar disorder in the literature. Follow-up analyses were performed in two additional cohorts. Results A generalized linear mixed model including seven features hypothesized to be associated with bipolar spectrum illness was significantly associated with bipolar polygenic risk score [F = 2.07, degrees of freedom (df) = 7, p = 0.04). Features included early onset, suicide attempt, recurrent depression, atypical depression, subclinical mania, subclinical psychosis, and severity. Post-hoc univariate analyses demonstrated that the major contributors to this omnibus association were onset of illness at age ≤ 18 years [odds ratio (OR) = 1.2, p = 0.003], history of suicide attempt (OR = 1.21, p = 0.03), and presence of at least one manic symptom (OR = 1.16, p = 0.02). The maximal variance in these traits explained by polygenic score ranged from 0.8–1.1%. However, analyses in two replication cohorts testing a five feature model did not support this association. Conclusions Bipolar genetic loading appeared to be associated with bipolar-like presentation in major depressive disorder in the primary analysis. However, results are at most inconclusive because of lack of replication. Replication efforts are challenged by different ascertainment and assessment strategies in the different cohorts

Latent feature decompositions for integrative analysis of multi-platform genomic data

PubMed Central

Gregory, Karl B.; Momin, Amin A.; Coombes, Kevin R.; Baladandayuthapani, Veerabhadran

2015-01-01

Increased availability of multi-platform genomics data on matched samples has sparked research efforts to discover how diverse molecular features interact both within and between platforms. In addition, simultaneous measurements of genetic and epigenetic characteristics illuminate the roles their complex relationships play in disease progression and outcomes. However, integrative methods for diverse genomics data are faced with the challenges of ultra-high dimensionality and the existence of complex interactions both within and between platforms. We propose a novel modeling framework for integrative analysis based on decompositions of the large number of platform-specific features into a smaller number of latent features. Subsequently we build a predictive model for clinical outcomes accounting for both within- and between-platform interactions based on Bayesian model averaging procedures. Principal components, partial least squares and non-negative matrix factorization as well as sparse counterparts of each are used to define the latent features, and the performance of these decompositions is compared both on real and simulated data. The latent feature interactions are shown to preserve interactions between the original features and not only aid prediction but also allow explicit selection of outcome-related features. The methods are motivated by and applied to, a glioblastoma multiforme dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, microRNA, copy number and methylation data. For the glioblastoma data, we find a high concordance between our selected prognostic genes and genes with known associations with glioblastoma. In addition, our model discovers several relevant cross-platform interactions such as copy number variation associated gene dosing and epigenetic regulation through promoter methylation. On simulated data, we show that our proposed method successfully incorporates interactions within and between

Guilt by Association: The 13 Micron Dust Emission Feature and Its Correlation to Other Gas and Dust Features

NASA Astrophysics Data System (ADS)

Sloan, G. C.; Kraemer, Kathleen E.; Goebel, J. H.; Price, Stephan D.

2003-09-01

A study of all full-scan spectra of optically thin oxygen-rich circumstellar dust shells in the database produced by the Short Wavelength Spectrometer on ISO reveals that the strength of several infrared spectral features correlates with the strength of the 13 μm dust feature. These correlated features include dust features at 19.8 and 28.1 μm and the bands produced by warm carbon dioxide molecules (the strongest of which are at 13.9, 15.0, and 16.2 μm). The database does not provide any evidence for a correlation of the 13 μm feature with a dust feature at 32 μm, and it is more likely that a weak emission feature at 16.8 μm arises from carbon dioxide gas rather than dust. The correlated dust features at 13, 20, and 28 μm tend to be stronger with respect to the total dust emission in semiregular and irregular variables associated with the asymptotic giant branch than in Mira variables or supergiants. This family of dust features also tends to be stronger in systems with lower infrared excesses and thus lower mass-loss rates. We hypothesize that the dust features arise from crystalline forms of alumina (13 μm) and silicates (20 and 28 μm). Based on observations with the ISO, a European Space Agency (ESA) project with instruments funded by ESA member states (especially the Principal Investigator countries: France, Germany, the Netherlands, and the United Kingdom) and with the participation of the Institute of Space and Astronautical Science (ISAS) and the National Aeronautics and Space Administration (NASA).

Correlative feature analysis on FFDM

PubMed Central

Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

2008-01-01

Identifying the corresponding images of a lesion in different views is an essential step in improving the diagnostic ability of both radiologists and computer-aided diagnosis (CAD) systems. Because of the nonrigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this pilot study, we present a computerized framework that differentiates between corresponding images of the same lesion in different views and noncorresponding images, i.e., images of different lesions. A dual-stage segmentation method, which employs an initial radial gradient index (RGI) based segmentation and an active contour model, is applied to extract mass lesions from the surrounding parenchyma. Then various lesion features are automatically extracted from each of the two views of each lesion to quantify the characteristics of density, size, texture and the neighborhood of the lesion, as well as its distance to the nipple. A two-step scheme is employed to estimate the probability that the two lesion images from different mammographic views are of the same physical lesion. In the first step, a correspondence metric for each pairwise feature is estimated by a Bayesian artificial neural network (BANN). Then, these pairwise correspondence metrics are combined using another BANN to yield an overall probability of correspondence. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing corresponding pairs from noncorresponding pairs. Using a FFDM database with 123 corresponding image pairs and 82 noncorresponding pairs, the distance feature yielded an area under the ROC curve (AUC) of 0.81±0.02 with leave-one-out (by physical lesion) evaluation, and the feature metric subset, which included distance, gradient texture, and ROI-based correlation, yielded an AUC of 0.87±0.02. The improvement by using multiple feature metrics was statistically

Correlative feature analysis of FFDM images

NASA Astrophysics Data System (ADS)

Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

2008-03-01

Identifying the corresponding image pair of a lesion is an essential step for combining information from different views of the lesion to improve the diagnostic ability of both radiologists and CAD systems. Because of the non-rigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this study, we present a computerized framework that differentiates the corresponding images from different views of a lesion from non-corresponding ones. A dual-stage segmentation method, which employs an initial radial gradient index(RGI) based segmentation and an active contour model, was initially applied to extract mass lesions from the surrounding tissues. Then various lesion features were automatically extracted from each of the two views of each lesion to quantify the characteristics of margin, shape, size, texture and context of the lesion, as well as its distance to nipple. We employed a two-step method to select an effective subset of features, and combined it with a BANN to obtain a discriminant score, which yielded an estimate of the probability that the two images are of the same physical lesion. ROC analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing between corresponding and non-corresponding pairs. By using a FFDM database with 124 corresponding image pairs and 35 non-corresponding pairs, the distance feature yielded an AUC (area under the ROC curve) of 0.8 with leave-one-out evaluation by lesion, and the feature subset, which includes distance feature, lesion size and lesion contrast, yielded an AUC of 0.86. The improvement by using multiple features was statistically significant as compared to single feature performance. (p<0.001)

An Assessment of Nondestructive Evaluation Capability for Complex Additive Manufacturing Aerospace Components

NASA Technical Reports Server (NTRS)

Walker, James; Beshears, Ron; Lambert, Dennis; Tilson, William

2016-01-01

The primary focus of this work is to investigate some of the fundamental relationships between processing, mechanical testing, materials characterization, and NDE for additively manufactured (AM) components using the powder bed fusion direct melt laser sintered process. The goal is to understand the criticality of defects unique to the AM process and then how conventional nondestructive evaluation methods as well as some of the more non-traditional methods such as computed tomography, are effected by the AM material. Specific defects including cracking, porosity and partially/unfused powder will be addressed. Besides line-of-site NDE, as appropriate these inspection capabilities will be put into the context of complex AM geometries where hidden features obscure, or inhibit traditional NDE methods.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

PubMed

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching

PubMed Central

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed. PMID:28542537

THE ROLE OF THE HIPPOCAMPUS IN OBJECT DISCRIMINATION BASED ON VISUAL FEATURES.

PubMed

Levcik, David; Nekovarova, Tereza; Antosova, Eliska; Stuchlik, Ales; Klement, Daniel

2018-06-07

The role of rodent hippocampus has been intensively studied in different cognitive tasks. However, its role in discrimination of objects remains controversial due to conflicting findings. We tested whether the number and type of features available for the identification of objects might affect the strategy (hippocampal-independent vs. hippocampal-dependent) that rats adopt to solve object discrimination tasks. We trained rats to discriminate 2D visual objects presented on a computer screen. The objects were defined either by their shape only or by multiple-features (a combination of filling pattern and brightness in addition to the shape). Our data showed that objects displayed as simple geometric shapes are not discriminated by trained rats after their hippocampi had been bilaterally inactivated by the GABA A -agonist muscimol. On the other hand, objects containing a specific combination of non-geometric features in addition to the shape are discriminated even without the hippocampus. Our results suggest that the involvement of the hippocampus in visual object discrimination depends on the abundance of object's features. Copyright © 2018. Published by Elsevier Inc.

Impact of feature saliency on visual category learning.

PubMed

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the 'essence' of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies.

Impact of feature saliency on visual category learning

PubMed Central

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies. PMID:25954220

Object attributes combine additively in visual search

PubMed Central

Pramod, R. T.; Arun, S. P.

2016-01-01

We perceive objects as containing a variety of attributes: local features, relations between features, internal details, and global properties. But we know little about how they combine. Here, we report a remarkably simple additive rule that governs how these diverse object attributes combine in vision. The perceived dissimilarity between two objects was accurately explained as a sum of (a) spatially tuned local contour-matching processes modulated by part decomposition; (b) differences in internal details, such as texture; (c) differences in emergent attributes, such as symmetry; and (d) differences in global properties, such as orientation or overall configuration of parts. Our results elucidate an enduring question in object vision by showing that the whole object is not a sum of its parts but a sum of its many attributes. PMID:26967014

Object attributes combine additively in visual search.

PubMed

Pramod, R T; Arun, S P

2016-01-01

We perceive objects as containing a variety of attributes: local features, relations between features, internal details, and global properties. But we know little about how they combine. Here, we report a remarkably simple additive rule that governs how these diverse object attributes combine in vision. The perceived dissimilarity between two objects was accurately explained as a sum of (a) spatially tuned local contour-matching processes modulated by part decomposition; (b) differences in internal details, such as texture; (c) differences in emergent attributes, such as symmetry; and (d) differences in global properties, such as orientation or overall configuration of parts. Our results elucidate an enduring question in object vision by showing that the whole object is not a sum of its parts but a sum of its many attributes.

Feature-level sentiment analysis by using comparative domain corpora

NASA Astrophysics Data System (ADS)

Quan, Changqin; Ren, Fuji

2016-06-01

Feature-level sentiment analysis (SA) is able to provide more fine-grained SA on certain opinion targets and has a wider range of applications on E-business. This study proposes an approach based on comparative domain corpora for feature-level SA. The proposed approach makes use of word associations for domain-specific feature extraction. First, we assign a similarity score for each candidate feature to denote its similarity extent to a domain. Then we identify domain features based on their similarity scores on different comparative domain corpora. After that, dependency grammar and a general sentiment lexicon are applied to extract and expand feature-oriented opinion words. Lastly, the semantic orientation of a domain-specific feature is determined based on the feature-oriented opinion lexicons. In evaluation, we compare the proposed method with several state-of-the-art methods (including unsupervised and semi-supervised) using a standard product review test collection. The experimental results demonstrate the effectiveness of using comparative domain corpora.

Structural optimization under overhang constraints imposed by additive manufacturing technologies

NASA Astrophysics Data System (ADS)

Allaire, G.; Dapogny, C.; Estevez, R.; Faure, A.; Michailidis, G.

2017-12-01

This article addresses one of the major constraints imposed by additive manufacturing processes on shape optimization problems - that of overhangs, i.e. large regions hanging over void without sufficient support from the lower structure. After revisiting the 'classical' geometric criteria used in the literature, based on the angle between the structural boundary and the build direction, we propose a new mechanical constraint functional, which mimics the layer by layer construction process featured by additive manufacturing technologies, and thereby appeals to the physical origin of the difficulties caused by overhangs. This constraint, as well as some variants, is precisely defined; their shape derivatives are computed in the sense of Hadamard's method, and numerical strategies are extensively discussed, in two and three space dimensions, to efficiently deal with the appearance of overhang features in the course of shape optimization processes.

Form drag in rivers due to small-scale natural topographic features: 1. Regular sequences

USGS Publications Warehouse

Kean, J.W.; Smith, J.D.

2006-01-01

Small-scale topographic features are commonly found on the boundaries of natural rivers, streams, and floodplains. A simple method for determining the form drag on these features is presented, and the results of this model are compared to laboratory measurements. The roughness elements are modeled as Gaussian-shaped features defined in terms of three parameters: a protrusion height, H; a streamwise length scale, ??; and a spacing between crests, ??. This shape is shown to be a good approximation to a wide variety of natural topographic bank features. The form drag on an individual roughness element embedded in a series of identical elements is determined using the drag coefficient of the individual element and a reference velocity that includes the effects of roughness elements further upstream. In addition to calculating the drag on each element, the model determines the spatially averaged total stress, skin friction stress, and roughness height of the boundary. The effects of bank roughness on patterns of velocity and boundary shear stress are determined by combining the form drag model with a channel flow model. The combined model shows that drag on small-scale topographic features substantially alters the near-bank flow field. These methods can be used to improve predictions of flow resistance in rivers and to form the basis for fully predictive (no empirically adjusted parameters) channel flow models. They also provide a foundation for calculating the near-bank boundary shear stress fields necessary for determining rates of sediment transport and lateral erosion.

Variable developmental delays and characteristic facial features-A novel 7p22.3p22.2 microdeletion syndrome?

PubMed

Yu, Andrea C; Zambrano, Regina M; Cristian, Ingrid; Price, Sue; Bernhard, Birgitta; Zucker, Marc; Venkateswaran, Sunita; McGowan-Jordan, Jean; Armour, Christine M

2017-06-01

Isolated 7p22.3p22.2 deletions are rarely described with only two reports in the literature. Most other reported cases either involve a much larger region of the 7p arm or have an additional copy number variation. Here, we report five patients with overlapping microdeletions at 7p22.3p22.2. The patients presented with variable developmental delays, exhibiting relative weaknesses in expressive language skills and relative strengths in gross, and fine motor skills. The most consistent facial features seen in these patients included a broad nasal root, a prominent forehead a prominent glabella and arched eyebrows. Additional variable features amongst the patients included microcephaly, metopic ridging or craniosynostosis, cleft palate, cardiac defects, and mild hypotonia. Although the patients' deletions varied in size, there was a 0.47 Mb region of overlap which contained 7 OMIM genes: EIP3B, CHST12, LFNG, BRAT1, TTYH3, AMZ1, and GNA12. We propose that monosomy of this region represents a novel microdeletion syndrome. We recommend that individuals with 7p22.3p22.2 deletions should receive a developmental assessment and a thorough cardiac exam, with consideration of an echocardiogram, as part of their initial evaluation. © 2017 Wiley Periodicals, Inc.

ON THE MISALIGNMENT BETWEEN CHROMOSPHERIC FEATURES AND THE MAGNETIC FIELD ON THE SUN

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

Martínez-Sykora, Juan; Pontieu, Bart De; Hansteen, Viggo

2016-11-01

Observations of the upper chromosphere show an enormous amount of intricate fine structure. Much of this comes in the form of linear features, which are most often assumed to be well aligned with the direction of the magnetic field in the low plasma β regime that is thought to dominate the upper chromosphere. We use advanced radiative magnetohydrodynamic simulations, including the effects of ion-neutral interactions (using the generalized Ohm’s law) in the partially ionized chromosphere, to show that the magnetic field is often not well aligned with chromospheric features. This occurs where the ambipolar diffusion is large, i.e., ions andmore » neutral populations decouple as the ion-neutral collision frequency drops, allowing the field to slip through the neutral population; where currents perpendicular to the field are strong; and where thermodynamic timescales are longer than or similar to those of ambipolar diffusion. We find this often happens in dynamic spicule or fibril-like features at the top of the chromosphere. This has important consequences for field extrapolation methods, which increasingly use such upper chromospheric features to help constrain the chromospheric magnetic field: our results invalidate the underlying assumption that these features are aligned with the field. In addition, our results cast doubt on results from 1D hydrodynamic models, which assume that plasma remains on the same field lines. Finally, our simulations show that ambipolar diffusion significantly alters the amount of free energy available in the coronal part of our simulated volume, which is likely to have consequences for studies of flare initiation.« less

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-13

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

2016-01-01

An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features. PMID:26759193

An Evaluation of Feature Learning Methods for High Resolution Image Classification

NASA Astrophysics Data System (ADS)

Tokarczyk, P.; Montoya, J.; Schindler, K.

2012-07-01

Automatic image classification is one of the fundamental problems of remote sensing research. The classification problem is even more challenging in high-resolution images of urban areas, where the objects are small and heterogeneous. Two questions arise, namely which features to extract from the raw sensor data to capture the local radiometry and image structure at each pixel or segment, and which classification method to apply to the feature vectors. While classifiers are nowadays well understood, selecting the right features remains a largely empirical process. Here we concentrate on the features. Several methods are evaluated which allow one to learn suitable features from unlabelled image data by analysing the image statistics. In a comparative study, we evaluate unsupervised feature learning with different linear and non-linear learning methods, including principal component analysis (PCA) and deep belief networks (DBN). We also compare these automatically learned features with popular choices of ad-hoc features including raw intensity values, standard combinations like the NDVI, a few PCA channels, and texture filters. The comparison is done in a unified framework using the same images, the target classes, reference data and a Random Forest classifier.

Diamond field emitter array cathodes and possibilities for employing additive manufacturing for dielectric laser accelerating structures

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

Simakov, Evgenya Ivanovna; Andrews, Heather Lynn; Herman, Matthew Joseph

2016-09-20

These are slides for a presentation at Stanford University. The outline is as follows: Motivation: customers for compact accelerators, LANL's technologies for laser acceleration, DFEA cathodes, and additive manufacturing of micron-size structures. Among the stated conclusions are the following: preliminary study identified DFEA cathodes as promising sources for DLAs--high beam current and small emittance; additive manufacturing with Nanoscribe Professional GT can produce structures with the right scale features for a DLA operating at micron wavelengths (fabrication tolerances need to be studied, DLAs require new materials). Future plans include DLA experiment with a beam produced by the DFEA cathode with fieldmore » emission, demonstration of photoemission from DFEAs, and new structures to print and test.« less

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images.

PubMed

Guo, Shengwen; Lai, Chunren; Wu, Congling; Cen, Guiyin

2017-01-01

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI-cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI-NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI-NC comparison. The best performances obtained by the SVM classifier using the essential features were 5-40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its

FOCUSR: Feature Oriented Correspondence using Spectral Regularization–A Method for Precise Surface Matching

PubMed Central

Lombaert, Herve; Grady, Leo; Polimeni, Jonathan R.; Cheriet, Farida

2013-01-01

Existing methods for surface matching are limited by the trade-off between precision and computational efficiency. Here we present an improved algorithm for dense vertex-to-vertex correspondence that uses direct matching of features defined on a surface and improves it by using spectral correspondence as a regularization. This algorithm has the speed of both feature matching and spectral matching while exhibiting greatly improved precision (distance errors of 1.4%). The method, FOCUSR, incorporates implicitly such additional features to calculate the correspondence and relies on the smoothness of the lowest-frequency harmonics of a graph Laplacian to spatially regularize the features. In its simplest form, FOCUSR is an improved spectral correspondence method that nonrigidly deforms spectral embeddings. We provide here a full realization of spectral correspondence where virtually any feature can be used as additional information using weights on graph edges, but also on graph nodes and as extra embedded coordinates. As an example, the full power of FOCUSR is demonstrated in a real case scenario with the challenging task of brain surface matching across several individuals. Our results show that combining features and regularizing them in a spectral embedding greatly improves the matching precision (to a sub-millimeter level) while performing at much greater speed than existing methods. PMID:23868776

LBT Distributed Archive: Status and Features

NASA Astrophysics Data System (ADS)

Knapic, C.; Smareglia, R.; Thompson, D.; Grede, G.

2011-07-01

After the first release of the LBT Distributed Archive, this successful collaboration is continuing within the LBT corporation. The IA2 (Italian Center for Astronomical Archive) team had updated the LBT DA with new features in order to facilitate user data retrieval while abiding by VO standards. To facilitate the integration of data from any new instruments, we have migrated to a new database, developed new data distribution software, and enhanced features in the LBT User Interface. The DBMS engine has been changed to MySQL. Consequently, the data handling software now uses java thread technology to update and synchronize the main storage archives on Mt. Graham and in Tucson, as well as archives in Trieste and Heidelberg, with all metadata and proprietary data. The LBT UI has been updated with additional features allowing users to search by instrument and some of the more important characteristics of the images. Finally, instead of a simple cone search service over all LBT image data, new instrument specific SIAP and cone search services have been developed. They will be published in the IVOA framework later this fall.

Hemipteran Mitochondrial Genomes: Features, Structures and Implications for Phylogeny

PubMed Central

Wang, Yuan; Chen, Jing; Jiang, Li-Yun; Qiao, Ge-Xia

2015-01-01

The study of Hemipteran mitochondrial genomes (mitogenomes) began with the Chagas disease vector, Triatoma dimidiata, in 2001. At present, 90 complete Hemipteran mitogenomes have been sequenced and annotated. This review examines the history of Hemipteran mitogenomes research and summarizes the main features of them including genome organization, nucleotide composition, protein-coding genes, tRNAs and rRNAs, and non-coding regions. Special attention is given to the comparative analysis of repeat regions. Gene rearrangements are an additional data type for a few families, and most mitogenomes are arranged in the same order to the proposed ancestral insect. We also discuss and provide insights on the phylogenetic analyses of a variety of taxonomic levels. This review is expected to further expand our understanding of research in this field and serve as a valuable reference resource. PMID:26039239

Prediction of lysine ubiquitylation with ensemble classifier and feature selection.

PubMed

Zhao, Xiaowei; Li, Xiangtao; Ma, Zhiqiang; Yin, Minghao

2011-01-01

Ubiquitylation is an important process of post-translational modification. Correct identification of protein lysine ubiquitylation sites is of fundamental importance to understand the molecular mechanism of lysine ubiquitylation in biological systems. This paper develops a novel computational method to effectively identify the lysine ubiquitylation sites based on the ensemble approach. In the proposed method, 468 ubiquitylation sites from 323 proteins retrieved from the Swiss-Prot database were encoded into feature vectors by using four kinds of protein sequences information. An effective feature selection method was then applied to extract informative feature subsets. After different feature subsets were obtained by setting different starting points in the search procedure, they were used to train multiple random forests classifiers and then aggregated into a consensus classifier by majority voting. Evaluated by jackknife tests and independent tests respectively, the accuracy of the proposed predictor reached 76.82% for the training dataset and 79.16% for the test dataset, indicating that this predictor is a useful tool to predict lysine ubiquitylation sites. Furthermore, site-specific feature analysis was performed and it was shown that ubiquitylation is intimately correlated with the features of its surrounding sites in addition to features derived from the lysine site itself. The feature selection method is available upon request.

Prevailing Torque Locking Feature in Threaded Fasteners Using Anaerobic Adhesive

NASA Technical Reports Server (NTRS)

Hernandez, Alan; Hess, Daniel P.

2016-01-01

This paper presents results from tests to assess the use of anaerobic adhesive for providing a prevailing torque locking feature in threaded fasteners. Test procedures are developed and tests are performed on three fastener materials, four anaerobic adhesives, and both unseated assembly conditions. Five to ten samples are tested for each combination. Tests for initial use, reuse without additional adhesive, and reuse with additional adhesive are performed for all samples. A 48-hour cure time was used for all initial use and reuse tests. Test data are presented as removal torque versus removal angle with the specification required prevailing torque range added for performance assessment. Percent specification pass rates for the all combinations of fastener material, adhesive, and assembly condition are tabulated and reveal use of anaerobic adhesive as a prevailing torque locking feature is viable. Although not every possible fastener material and anaerobic adhesive combination provides prevailing torque values within specification, any combination can be assessed using the test procedures presented. Reuse without additional anaerobic adhesive generally provides some prevailing torque, and in some cases within specification. Reuse with additional adhesive often provides comparable removal torque data as in initial use.

Embryonic staging and external features of development of the Chimaeroid fish, Callorhinchus milii (Holocephali, Callorhinchidae).

PubMed

Didier, Dominique A; LeClair, Elizabeth E; Vanbuskirk, Dana R

1998-04-01

The development of Callorhinchus milii, a primitive chondrichthyan fish (Subclass Holocephali) is described in detail based on a complete series of embryos from stage 17 to hatching. The external features of these specimens, in comparison with other chondrichthyan embryos, are used to establish the first staging table for any chimaeroid species. Each stage of C. milii is defined by a suite of morphological characters in addition to total length, including the number of somites, extent of external pigmentation, eye size and shape, head flexure, heart morphology, and size and shape of paired and unpaired fins. Particular attention is given to features of the gill arches and associated structures, including external gill filaments and the opercular flap. Embryos of this species also possess a transient rostral bulb, a feature unique to chimaeroids. Embryological development of Callorhinchus milii is similar to that previously described for sharks and batoids (Subclass Elasmobranchii), including the spiny dogfish, Squalus acanthias, the Japanese bullshark, Heterodontus japonicus, the lesser spotted dogfish, Scyliorhinus canicula, the frill shark, Chlamydoselachus anguineus, the guitarfish, Rhinobatus halavi, and the skate, Raja brachyura. Callorhinchus milii is also similar in overall development to another holocephalan, Hydrolagus colliei. A review of previous staging schemes confirms that early morphological development in all three major chondrichthyan lineages (sharks, batoids, and chimaeras) can be correlated using a common set of stages. A uniform staging system is provided that should prove useful in continuing ontogenetic and phylogenetic studies of this entire clade of fishes. J. Morphol. 236:25-47, 1998. © 1998 Wiley-Liss, Inc. Copyright © 1998 Wiley-Liss, Inc.

Interstitial Features at Chest CT Enhance the Deleterious Effects of Emphysema in the COPDGene Cohort.

PubMed

Ash, Samuel Y; Harmouche, Rola; Ross, James C; Diaz, Alejandro A; Rahaghi, Farbod N; Sanchez-Ferrero, Gonzalo Vegas; Putman, Rachel K; Hunninghake, Gary M; Onieva, Jorge Onieva; Martinez, Fernando J; Choi, Augustine M; Bowler, Russell P; Lynch, David A; Hatabu, Hiroto; Bhatt, Surya P; Dransfield, Mark T; Wells, J Michael; Rosas, Ivan O; San Jose Estepar, Raul; Washko, George R

2018-06-05

Purpose To determine if interstitial features at chest CT enhance the effect of emphysema on clinical disease severity in smokers without clinical pulmonary fibrosis. Materials and Methods In this retrospective cohort study, an objective CT analysis tool was used to measure interstitial features (reticular changes, honeycombing, centrilobular nodules, linear scar, nodular changes, subpleural lines, and ground-glass opacities) and emphysema in 8266 participants in a study of chronic obstructive pulmonary disease (COPD) called COPDGene (recruited between October 2006 and January 2011). Additive differences in patients with emphysema with interstitial features and in those without interstitial features were analyzed by using t tests, multivariable linear regression, and Kaplan-Meier analysis. Multivariable linear and Cox regression were used to determine if interstitial features modified the effect of continuously measured emphysema on clinical measures of disease severity and mortality. Results Compared with individuals with emphysema alone, those with emphysema and interstitial features had a higher percentage predicted forced expiratory volume in 1 second (absolute difference, 6.4%; P < .001), a lower percentage predicted diffusing capacity of lung for carbon monoxide (DLCO) (absolute difference, 7.4%; P = .034), a 0.019 higher right ventricular-to-left ventricular (RVLV) volume ratio (P = .029), a 43.2-m shorter 6-minute walk distance (6MWD) (P < .001), a 5.9-point higher St George's Respiratory Questionnaire (SGRQ) score (P < .001), and 82% higher mortality (P < .001). In addition, interstitial features modified the effect of emphysema on percentage predicted DLCO, RVLV volume ratio, 6WMD, SGRQ score, and mortality (P for interaction < .05 for all). Conclusion In smokers, the combined presence of interstitial features and emphysema was associated with worse clinical disease severity and higher mortality than was emphysema alone. In addition, interstitial features

The newly expanded KSC Visitors Complex features a new ticket plaza, information center, exhibits an

NASA Technical Reports Server (NTRS)

1999-01-01

At the grand opening of the newly expanded KSC Visitor Complex, Center Director Roy Bridges addresses guests and the media. The $13 million addition to the Visitor Complex includes an International Space Station-themed ticket plaza, featuring a structure of overhanging solar panels and astronauts performing assembly tasks, a new information center, films, and exhibits. The KSC Visitor Complex was inaugurated three decades ago and is now one of the top five tourist attractions in Florida. It is located on S.R. 407, east of I-95, within the Merritt Island National Wildlife Refuge.

Mid-Infrared Silicate Dust Features in Seyfert 1 Spectra

NASA Astrophysics Data System (ADS)

Thompson, Grant D.; Levenson, N. A.; Sirocky, M. M.; Uddin, S.

2007-12-01

Silicate dust emission dominates the mid-infrared spectra of galaxies, and the dust produces two spectral features, at 10 and 18 μm. These features' strengths (in emission or absorption) and peak wavelengths reveal the geometry of the dust distribution, and they are sensitive to the dust composition. We examine mid-infrared spectra of 32 Seyfert 1 active galactic nuclei (AGN), observed with the Infrared Spectrograph aboard the Spitzer Space Telescope. In the spectra, we typically find the shorter-wavelength feature in emission, at an average peak wavelength of 10.0 μm, although it is known historically as the "9.7 μm" feature. In addition, peak wavelength increases with feature strength. The 10 and 18 μm feature strengths together are sensitive to the dust geometry surrounding the central heating engine. Numerical calculations of radiative transfer distinguish between clumpy and smooth distributions, and we find that the surroundings of these AGN (the obscuring "tori" of unified AGN schemes) are clumpy. Polycyclic aromatic hydrocarbon (PAH) features are associated with star formation, and we find strong PAH emission (luminosity ≥ 1042 erg/s) in only four sources, three of which show independent evidence for starbursts. We will explore the effects of luminosity on dust geometry and chemistry in a comparison sample of quasars. We acknowledge work supported by the NSF under grant number 0237291.

Radiographic Features of Acute Patellar Tendon Rupture.

PubMed

Fazal, Muhammad Ali; Moonot, Pradeep; Haddad, Fares

2015-11-01

The purpose of our study was to assess soft tissue features of acute patellar tendon rupture on lateral knee radiograph that would facilitate early diagnosis. The participants were divided into two groups of 35 patients each. There were 28 men and seven women with a mean age of 46 years in the control group and 26 men and nine women with a mean age of 47 years in the rupture group. The lateral knee radiograph of each patient was evaluated for Insall-Salvati ratio for patella alta, increased density of the infrapatellar fat pad, appearance of the soft tissue margin of the patellar tendon and bony avulsions. In the rupture group there were three consistent soft tissue radiographic features in addition to patellar alta. These were increased density of infrapatellar fat pad; loss of sharp, well-defined linear margins of the patellar tendon and angulated wavy margin of the patellar tendon while in the control group these features were not observed. The soft tissue radiographic features described in the rupture group are consistent and reliable. When coupled with careful clinical assessment, these will aid in early diagnosis and further imaging will be seldom required. © 2015 Chinese Orthopaedic Association and Wiley Publishing Asia Pty Ltd.

Major depressive disorder discrimination using vocal acoustic features.

PubMed

Taguchi, Takaya; Tachikawa, Hirokazu; Nemoto, Kiyotaka; Suzuki, Masayuki; Nagano, Toru; Tachibana, Ryuki; Nishimura, Masafumi; Arai, Tetsuaki

2018-01-01

The voice carries various information produced by vibrations of the vocal cords and the vocal tract. Though many studies have reported a relationship between vocal acoustic features and depression, including mel-frequency cepstrum coefficients (MFCCs) which applied to speech recognition, there have been few studies in which acoustic features allowed discrimination of patients with depressive disorder. Vocal acoustic features as biomarker of depression could make differential diagnosis of patients with depressive state. In order to achieve differential diagnosis of depression, in this preliminary study, we examined whether vocal acoustic features could allow discrimination between depressive patients and healthy controls. Subjects were 36 patients who met the criteria for major depressive disorder and 36 healthy controls with no current or past psychiatric disorders. Voices of reading out digits before and after verbal fluency task were recorded. Voices were analyzed using OpenSMILE. The extracted acoustic features, including MFCCs, were used for group comparison and discriminant analysis between patients and controls. The second dimension of MFCC (MFCC 2) was significantly different between groups and allowed the discrimination between patients and controls with a sensitivity of 77.8% and a specificity of 86.1%. The difference in MFCC 2 between the two groups reflected an energy difference of frequency around 2000-3000Hz. The MFCC 2 was significantly different between depressive patients and controls. This feature could be a useful biomarker to detect major depressive disorder. Sample size was relatively small. Psychotropics could have a confounding effect on voice. Copyright © 2017 Elsevier B.V. All rights reserved.

Interpretable Topic Features for Post-ICU Mortality Prediction.

PubMed

Luo, Yen-Fu; Rumshisky, Anna

2016-01-01

Electronic health records provide valuable resources for understanding the correlation between various diseases and mortality. The analysis of post-discharge mortality is critical for healthcare professionals to follow up potential causes of death after a patient is discharged from the hospital and give prompt treatment. Moreover, it may reduce the cost derived from readmissions and improve the quality of healthcare. Our work focused on post-discharge ICU mortality prediction. In addition to features derived from physiological measurements, we incorporated ICD-9-CM hierarchy into Bayesian topic model learning and extracted topic features from medical notes. We achieved highest AUCs of 0.835 and 0.829 for 30-day and 6-month post-discharge mortality prediction using baseline and topic proportions derived from Labeled-LDA. Moreover, our work emphasized the interpretability of topic features derived from topic model which may facilitates the understanding and investigation of the complexity between mortality and diseases.

Antisocial features and "faking bad": A critical note.

PubMed

Niesten, Isabella J M; Nentjes, Lieke; Merckelbach, Harald; Bernstein, David P

2015-01-01

We critically review the literature on antisocial personality features and symptom fabrication (i.e., faking bad; e.g., malingering). A widespread assumption is that these constructs are intimately related. Some studies have, indeed, found that antisocial individuals score higher on instruments detecting faking bad, but others have been unable to replicate this pattern. In addition, studies exploring whether antisocial individuals are especially talented in faking bad have generally come up with null results. The notion of an intrinsic link between antisocial features and faking bad is difficult to test and research in this domain is sensitive to selection bias. We argue that research on faking bad would profit from further theoretical articulation. One topic that deserves scrutiny is how antisocial features affect the cognitive dissonance typically induced by faking bad. We illustrate our points with preliminary data and discuss their implications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Infrastructure features outperform environmental variables explaining rabbit abundance around motorways.

PubMed

Planillo, Aimara; Malo, Juan E

2018-01-01

Human disturbance is widespread across landscapes in the form of roads that alter wildlife populations. Knowing which road features are responsible for the species response and their relevance in comparison with environmental variables will provide useful information for effective conservation measures. We sampled relative abundance of European rabbits, a very widespread species, in motorway verges at regional scale, in an area with large variability in environmental and infrastructure conditions. Environmental variables included vegetation structure, plant productivity, distance to water sources, and altitude. Infrastructure characteristics were the type of vegetation in verges, verge width, traffic volume, and the presence of embankments. We performed a variance partitioning analysis to determine the relative importance of two sets of variables on rabbit abundance. Additionally, we identified the most important variables and their effects model averaging after model selection by AICc on hypothesis-based models. As a group, infrastructure features explained four times more variability in rabbit abundance than environmental variables, being the effects of the former critical in motorway stretches located in altered landscapes with no available habitat for rabbits, such as agricultural fields. Model selection and Akaike weights showed that verge width and traffic volume are the most important variables explaining rabbit abundance index, with positive and negative effects, respectively. In the light of these results, the response of species to the infrastructure can be modulated through the modification of motorway features, being some of them manageable in the design phase. The identification of such features leads to suggestions for improvement through low-cost corrective measures and conservation plans. As a general indication, keeping motorway verges less than 10 m wide will prevent high densities of rabbits and avoid the unwanted effects that rabbit populations

Apology in the criminal justice setting: evidence for including apology as an additional component in the legal system.

PubMed

Petrucci, Carrie J

2002-01-01

The criminal justice system has reached unprecedented scope in the United States, with over 6.4 million people under some type of supervision. Remedies that have the potential to reduce this number are continually being sought. This article analyzes an innovative strategy currently being reconsidered in criminal justice: the apology. Despite a legal system that only sporadically acknowledges it, evidence for the use of apology is supported by social science research, current criminal justice theories, case law, and empirical studies. Social psychological, sociological and socio-legal studies pinpoint the elements and function of apology, what makes apologies effective, and concerns about apology if it were implemented in the criminal justice system. Theoretical evidence is examined (including restorative justice, therapeutic jurisprudence, crime, shame, and reintegration) to explore the process of apology in the criminal justice context. Attribution theory and social conduct theory are used to explain the apology process specifically for victims and offenders. A brief examination of case law reveals that though apology has no formal place in criminal law, it has surfaced recently under the federal sentencing guidelines. Finally, empirical evidence in criminal justice settings reveals that offenders want to apologize and victims desire an apology. Moreover, by directly addressing the harmful act, apology may be the link to reduced recidivism for offenders, as well as empowerment for victims. This evidence combined suggests that apology is worthy of further study as a potentially valuable addition to the criminal justice process. Copyright 2002 John Wiley & Sons, Ltd.

Additively Manufactured Combustion Devices Components for LOX/Methane Applications

NASA Technical Reports Server (NTRS)

Greene, Sandra Elam; Protz, Christopher; Garcia, Chance; Goodman, Dwight; Baker, Kevin

2016-01-01

Marshall Space Flight Center (MSFC) has designed, fabricated, and hot-fire tested a variety of successful injectors, chambers, and igniters for potential liquid oxygen (LOX) and methane (CH4) systems since 2005. The most recent efforts have focused on components with additive manufacturing (AM) to include unique design features, minimize joints, and reduce final machining efforts. Inconel and copper alloys have been used with AM processes to produce a swirl coaxial injector and multiple methane cooled thrust chambers. The initial chambers included unique thermocouple ports for measuring local coolant channel temperatures along the length of the chamber. Results from hot-fire testing were used to anchor thermal models and generate a regeneratively cooled thruster for a 4,000 lbf LOX/CH4 engine. The completed thruster will be hot-fire tested in the summer of 2016 at MSFC. The thruster design can also be easily scaled and used on a 25,000 lbf engine. To further support the larger engine design, an AM gas generator injector has been designed. Hot-fire testing on this injector is planned for the summer of 2016 at MSFC.

Feature and Region Selection for Visual Learning.

PubMed

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

Metalinguistic Knowledge of Salient vs. Unsalient Features: Evidence from the Arabic Construct State

ERIC Educational Resources Information Center

Azaz, Mahmoud

2017-01-01

This study examined to what extent English-speaking learners of Arabic demonstrated varied metalinguistic knowledge of a salient feature (head-direction) vs. an unsalient feature (definiteness) in the Arabic construct state. In addition, it examined whether this knowledge was utilized in form-focused task performance. In the target construction,…

Additive Manufactured Product Integrity

NASA Technical Reports Server (NTRS)

Waller, Jess; Wells, Doug; James, Steve; Nichols, Charles

2017-01-01

NASA is providing key leadership in an international effort linking NASA and non-NASA resources to speed adoption of additive manufacturing (AM) to meet NASA's mission goals. Participants include industry, NASA's space partners, other government agencies, standards organizations and academia. Nondestructive Evaluation (NDE) is identified as a universal need for all aspects of additive manufacturing.

The Role of Attention in the Binding of Surface Features to Locations

PubMed Central

Hyun, Joo-seok; Woodman, Geoffrey F.; Luck, Steven J.

2013-01-01

Previous studies have proposed that attention is not necessary for detecting simple features but is necessary for binding them to spatial locations. The present study tested this hypothesis, using the N2pc component of the event-related potential waveform as a measure of the allocation of attention. A simple feature detection condition, in which observers reported whether a target color was present or not, was compared with feature-location binding conditions, in which observers reported the location of the target color. A larger N2pc component was observed in the binding conditions than in the detection condition, indicating that additional attentional resources are needed to bind a feature to a location than to detect the feature independently of its location. This finding supports theories of attention in which attention plays a special role in binding features. PMID:24235876

Functional Additive Mixed Models

PubMed Central

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2014-01-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach. PMID:26347592

Functional Additive Mixed Models.

PubMed

Scheipl, Fabian; Staicu, Ana-Maria; Greven, Sonja

2015-04-01

We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data. Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response. It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund. Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.

Sensorineural Deafness, Distinctive Facial Features and Abnormal Cranial Bones

PubMed Central

Gad, Alona; Laurino, Mercy; Maravilla, Kenneth R.; Matsushita, Mark; Raskind, Wendy H.

2008-01-01

The Waardenburg syndromes (WS) account for approximately 2% of congenital sensorineural deafness. This heterogeneous group of diseases currently can be categorized into four major subtypes (WS types 1-4) on the basis of characteristic clinical features. Multiple genes have been implicated in WS, and mutations in some genes can cause more than one WS subtype. In addition to eye, hair and skin pigmentary abnormalities, dystopia canthorum and broad nasal bridge are seen in WS type 1. Mutations in the PAX3 gene are responsible for the condition in the majority of these patients. In addition, mutations in PAX3 have been found in WS type 3 that is distinguished by musculoskeletal abnormalities, and in a family with a rare subtype of WS, craniofacial-deafness-hand syndrome (CDHS), characterized by dysmorphic facial features, hand abnormalities, and absent or hypoplastic nasal and wrist bones. Here we describe a woman who shares some, but not all features of WS type 3 and CDHS, and who also has abnormal cranial bones. All sinuses were hypoplastic, and the cochlea were small. No sequence alteration in PAX3 was found. These observations broaden the clinical range of WS and suggest there may be genetic heterogeneity even within the CDHS subtype. PMID:18553554

Proscene: A feature-rich framework for interactive environments

NASA Astrophysics Data System (ADS)

Charalambos, Jean Pierre

We introduce Proscene, a feature-rich, open-source framework for interactive environments. The design of Proscene comprises a three-layered onion-like software architecture, promoting different possible development scenarios. The framework innermost layer decouples user gesture parsing from user-defined actions. The in-between layer implements a feature-rich set of widely-used motion actions allowing the selection and manipulation of objects, including the scene viewpoint. The outermost layer exposes those features as a Processing library. The results have shown the feasibility of our approach together with the simplicity and flexibility of the Proscene framework API.

Munitions related feature extraction from LIDAR data.

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

Roberts, Barry L.

2010-06-01

The characterization of former military munitions ranges is critical in the identification of areas likely to contain residual unexploded ordnance (UXO). Although these ranges are large, often covering tens-of-thousands of acres, the actual target areas represent only a small fraction of the sites. The challenge is that many of these sites do not have records indicating locations of former target areas. The identification of target areas is critical in the characterization and remediation of these sites. The Strategic Environmental Research and Development Program (SERDP) and Environmental Security Technology Certification Program (ESTCP) of the DoD have been developing and implementing techniquesmore » for the efficient characterization of large munitions ranges. As part of this process, high-resolution LIDAR terrain data sets have been collected over several former ranges. These data sets have been shown to contain information relating to former munitions usage at these ranges, specifically terrain cratering due to high-explosives detonations. The location and relative intensity of crater features can provide information critical in reconstructing the usage history of a range, and indicate areas most likely to contain UXO. We have developed an automated procedure using an adaptation of the Circular Hough Transform for the identification of crater features in LIDAR terrain data. The Circular Hough Transform is highly adept at finding circular features (craters) in noisy terrain data sets. This technique has the ability to find features of a specific radius providing a means of filtering features based on expected scale and providing additional spatial characterization of the identified feature. This method of automated crater identification has been applied to several former munitions ranges with positive results.« less

Recurrent Deletions and Reciprocal Duplications of 10q11.21q11.23 Including CHAT and SLC18A3 are Likely Mediated by Complex Low-Copy Repeats

PubMed Central

Stankiewicz, Paweł; Kulkarni, Shashikant; Dharmadhikari, Avinash V.; Sampath, Srirangan; Bhatt, Samarth S.; Shaikh, Tamim H.; Xia, Zhilian; Pursley, Amber N.; Cooper, M. Lance; Shinawi, Marwan; Paciorkowski, Alex R.; Grange, Dorothy K.; Noetzel, Michael J.; Saunders, Scott; Simons, Paul; Summar, Marshall; Lee, Brendan; Scaglia, Fernando; Fellmann, Florence; Martinet, Danielle; Beckmann, Jacques S.; Asamoah, Alexander; Platky, Kathryn; Sparks, Susan; Martin, Ann S.; Madan-Khetarpal, Suneeta; Hoover, Jacqueline; Medne, Livija; Bonnemann, Carsten G.; Moeschler, John B.; Vallee, Stephanie E.; Parikh, Sumit; Irwin, Polly; Dalzell, Victoria P.; Smith, Wendy E.; Banks, Valerie C.; Flannery, David B.; Lovell, Carolyn M.; Bellus, Gary A.; Golden-Grant, Kathryn; Gorski, Jerome L.; Kussmann, Jennifer L.; McGregor, Tracy L.; Hamid, Rizwan; Pfotenhauer, Jean; Ballif, Blake C.; Shaw, Chad A.; Kang, Sung-Hae L.; Bacino, Carlos A.; Patel, Ankita; Rosenfeld, Jill A.; Cheung, Sau Wai; Shaffer, Lisa G.

2013-01-01

We report 24 unrelated individuals with deletions and 17 additional cases with duplications at 10q11.21q21.1 identified by chromosomal microarray analysis. The rearrangements range in size from 0.3 to 12 Mb. Nineteen of the deletions and eight duplications are flanked by large, directly oriented segmental duplications of >98% sequence identity, suggesting that nonallelic homologous recombination (NAHR) caused these genomic rearrangements. Nine individuals with deletions and five with duplications have additional copy number changes. Detailed clinical evaluation of 20 patients with deletions revealed variable clinical features, with developmental delay (DD) and/or intellectual disability (ID) as the only features common to a majority of individuals. We suggest that some of the other features present in more than one patient with deletion, including hypotonia, sleep apnea, chronic constipation, gastroesophageal and vesicoureteral refluxes, epilepsy, ataxia, dysphagia, nystagmus, and ptosis may result from deletion of the CHAT gene, encoding choline acetyltransferase, and the SLC18A3 gene, mapping in the first intron of CHAT and encoding vesicular acetylcholine transporter. The phenotypic diversity and presence of the deletion in apparently normal carrier parents suggest that subjects carrying 10q11.21q11.23 deletions may exhibit variable phenotypic expressivity and incomplete penetrance influenced by additional genetic and nongenetic modifiers. PMID:21948486

Cross-Domain Semi-Supervised Learning Using Feature Formulation.

PubMed

Xingquan Zhu

2011-12-01

Semi-Supervised Learning (SSL) traditionally makes use of unlabeled samples by including them into the training set through an automated labeling process. Such a primitive Semi-Supervised Learning (pSSL) approach suffers from a number of disadvantages including false labeling and incapable of utilizing out-of-domain samples. In this paper, we propose a formative Semi-Supervised Learning (fSSL) framework which explores hidden features between labeled and unlabeled samples to achieve semi-supervised learning. fSSL regards that both labeled and unlabeled samples are generated from some hidden concepts with labeling information partially observable for some samples. The key of the fSSL is to recover the hidden concepts, and take them as new features to link labeled and unlabeled samples for semi-supervised learning. Because unlabeled samples are only used to generate new features, but not to be explicitly included in the training set like pSSL does, fSSL overcomes the inherent disadvantages of the traditional pSSL methods, especially for samples not within the same domain as the labeled instances. Experimental results and comparisons demonstrate that fSSL significantly outperforms pSSL-based methods for both within-domain and cross-domain semi-supervised learning.

Additional security features for optically variable foils

NASA Astrophysics Data System (ADS)

Marshall, Allan C.; Russo, Frank

1998-04-01

For thousands of years, man has exploited the attraction and radiance of pure gold to adorn articles of great significance. Today, designers decorate packaging with metallic gold foils to maintain the prestige of luxury items such as perfumes, chocolates, wine and whisky, and to add visible appeal and value to wide range of products. However, today's products do not call for the hand beaten gold leaf of the Ancient Egyptians, instead a rapid production technology exists which makes use of accurately coated thin polymer films and vacuum deposited metallic layers. Stamping Foils Technology is highly versatile since several different layers may be combined into one product, each providing a different function. Not only can a foil bring visual appeal to an article, it can provide physical and chemical resistance properties and also protect an article from human forms of interference, such as counterfeiting, copying or tampering. Stamping foils have proved to be a highly effective vehicle for applying optical devices to items requiring this type of protection. Credit cards, bank notes, personal identification documents and more recently high value packaged items such as software and perfumes are protected by optically variable devices applied using stamping foil technology.

Evaluation of feature selection algorithms for classification in temporal lobe epilepsy based on MR images

NASA Astrophysics Data System (ADS)

Lai, Chunren; Guo, Shengwen; Cheng, Lina; Wang, Wensheng; Wu, Kai

2017-02-01

It's very important to differentiate the temporal lobe epilepsy (TLE) patients from healthy people and localize the abnormal brain regions of the TLE patients. The cortical features and changes can reveal the unique anatomical patterns of brain regions from the structural MR images. In this study, structural MR images from 28 normal controls (NC), 18 left TLE (LTLE), and 21 right TLE (RTLE) were acquired, and four types of cortical feature, namely cortical thickness (CTh), cortical surface area (CSA), gray matter volume (GMV), and mean curvature (MCu), were explored for discriminative analysis. Three feature selection methods, the independent sample t-test filtering, the sparse-constrained dimensionality reduction model (SCDRM), and the support vector machine-recursive feature elimination (SVM-RFE), were investigated to extract dominant regions with significant differences among the compared groups for classification using the SVM classifier. The results showed that the SVM-REF achieved the highest performance (most classifications with more than 92% accuracy), followed by the SCDRM, and the t-test. Especially, the surface area and gray volume matter exhibited prominent discriminative ability, and the performance of the SVM was improved significantly when the four cortical features were combined. Additionally, the dominant regions with higher classification weights were mainly located in temporal and frontal lobe, including the inferior temporal, entorhinal cortex, fusiform, parahippocampal cortex, middle frontal and frontal pole. It was demonstrated that the cortical features provided effective information to determine the abnormal anatomical pattern and the proposed method has the potential to improve the clinical diagnosis of the TLE.

Age and gender-invariant features of handwritten signatures for verification systems

NASA Astrophysics Data System (ADS)

AbdAli, Sura; Putz-Leszczynska, Joanna

2014-11-01

Handwritten signature is one of the most natural biometrics, the study of human physiological and behavioral patterns. Behavioral biometrics includes signatures that may be different due to its owner gender or age because of intrinsic or extrinsic factors. This paper presents the results of the author's research on age and gender influence on verification factors. The experiments in this research were conducted using a database that contains signatures and their associated metadata. The used algorithm is based on the universal forgery feature idea, where the global classifier is able to classify a signature as a genuine one or, as a forgery, without the actual knowledge of the signature template and its owner. Additionally, the reduction of the dimensionality with the MRMR method is discussed.

Semantic data association for planar features in outdoor 6D-SLAM using lidar

NASA Astrophysics Data System (ADS)

Ulas, C.; Temeltas, H.

2013-05-01

Simultaneous Localization and Mapping (SLAM) is a fundamental problem of the autonomous systems in GPS (Global Navigation System) denied environments. The traditional probabilistic SLAM methods uses point features as landmarks and hold all the feature positions in their state vector in addition to the robot pose. The bottleneck of the point-feature based SLAM methods is the data association problem, which are mostly based on a statistical measure. The data association performance is very critical for a robust SLAM method since all the filtering strategies are applied after a known correspondence. For point-features, two different but very close landmarks in the same scene might be confused while giving the correspondence decision when their positions and error covariance matrix are solely taking into account. Instead of using the point features, planar features can be considered as an alternative landmark model in the SLAM problem to be able to provide a more consistent data association. Planes contain rich information for the solution of the data association problem and can be distinguished easily with respect to point features. In addition, planar maps are very compact since an environment has only very limited number of planar structures. The planar features does not have to be large structures like building wall or roofs; the small plane segments can also be used as landmarks like billboards, traffic posts and some part of the bridges in urban areas. In this paper, a probabilistic plane-feature extraction method from 3DLiDAR data and the data association based on the extracted semantic information of the planar features is introduced. The experimental results show that the semantic data association provides very satisfactory result in outdoor 6D-SLAM.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when

Cognitive and noncognitive neurological features of young-onset dementia.

PubMed

Kelley, Brendan J; Boeve, Bradley F; Josephs, Keith A

2009-01-01

The rarity of young-onset dementia (YOD), the broad differential diagnosis and unusual clinical presentations present unique challenges to correctly recognize the condition and establish an accurate diagnosis. Limited data exist regarding clinical features associated with dementia prior to the age of 45. We retrospectively assessed cognitive and noncognitive neurological characteristics of 235 patients who presented for evaluation of YOD to investigate the clinical characteristics of YOD compared to later-onset dementias and to identify clinical features associated with specific etiologies that may aid in the evaluation of YOD. Multiple cognitive domains were affected in most patients, and no significant differences in affected domains existed between groups. Early psychiatric and behavioral features occurred at very high frequencies. Nearly 80% of this YOD cohort had additional noncognitive symptoms or signs as a feature of their disease. Chorea was strongly associated with Huntington disease. Parkinsonism was not seen in patients having an autoimmune/inflammatory etiology. The rarity of YOD and the high frequency of early psychiatric features led to frequent misdiagnosis early in the clinical course. The high frequency of noncognitive symptoms and signs may aid clinicians in distinguishing patients requiring a more extensive evaluation for YOD.

Varying irrelevant phonetic features hinders learning of the feature being trained.

PubMed

Antoniou, Mark; Wong, Patrick C M

2016-01-01

Learning to distinguish nonnative words that differ in a critical phonetic feature can be difficult. Speech training studies typically employ methods that explicitly direct the learner's attention to the relevant nonnative feature to be learned. However, studies on vision have demonstrated that perceptual learning may occur implicitly, by exposing learners to stimulus features, even if they are irrelevant to the task, and it has recently been suggested that this task-irrelevant perceptual learning framework also applies to speech. In this study, subjects took part in a seven-day training regimen to learn to distinguish one of two nonnative features, namely, voice onset time or lexical tone, using explicit training methods consistent with most speech training studies. Critically, half of the subjects were exposed to stimuli that varied not only in the relevant feature, but in the irrelevant feature as well. The results showed that subjects who were trained with stimuli that varied in the relevant feature and held the irrelevant feature constant achieved the best learning outcomes. Varying both features hindered learning and generalization to new stimuli.

Shapes and features of the primordial bispectrum

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

Gong, Jinn-Ouk; Palma, Gonzalo A.; Sypsas, Spyros, E-mail: jinn-ouk.gong@apctp.org, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: s.sypsas@gmail.com

If time-dependent disruptions from slow-roll occur during inflation, the correlation functions of the primordial curvature perturbation should have scale-dependent features, a case which is marginally supported from the cosmic microwave background (CMB) data. We offer a new approach to analyze the appearance of such features in the primordial bispectrum that yields new consistency relations and justifies the search of oscillating patterns modulated by orthogonal and local templates. Under the assumption of sharp features, we find that the cubic couplings of the curvature perturbation can be expressed in terms of the bispectrum in two specific momentum configurations, for example local andmore » equilateral. This allows us to derive consistency relations among different bispectrum shapes, which in principle could be tested in future CMB surveys. Furthermore, based on the form of the consistency relations, we construct new two-parameter templates for features that include all the known shapes.« less

Performance comparison of quantitative semantic features and lung-RADS in the National Lung Screening Trial

NASA Astrophysics Data System (ADS)

Li, Qian; Balagurunathan, Yoganand; Liu, Ying; Schabath, Matthew; Gillies, Robert J.

2016-03-01

Background: Lung-RADS is the new oncology classification guideline proposed by American College of Radiology (ACR), which provides recommendation for further follow up in lung cancer screening. However, only two features (solidity and size) are included in this system. We hypothesize that additional sematic features can be used to better characterize lung nodules and diagnose cancer. Objective: We propose to develop and characterize a systematic methodology based on semantic image traits to more accurately predict occurrence of cancerous nodules. Methods: 24 radiological image traits were systematically scored on a point scale (up to 5) by a trained radiologist, and lung-RADS was independently scored. A linear discriminant model was used on the semantic features to access their performance in predicting cancer status. The semantic predictors were then compared to lung-RADS classification in 199 patients (60 cancers, 139 normal controls) obtained from the National Lung Screening Trial. Result: There were different combinations of semantic features that were strong predictors of cancer status. Of these, contour, border definition, size, solidity, focal emphysema, focal fibrosis and location emerged as top candidates. The performance of two semantic features (short axial diameter and contour) had an AUC of 0.945, and was comparable to that of lung-RADS (AUC: 0.871). Conclusion: We propose that a semantics-based discrimination approach may act as a complement to the lung-RADS to predict cancer status.

Magnetic field feature extraction and selection for indoor location estimation.

PubMed

Galván-Tejada, Carlos E; García-Vázquez, Juan Pablo; Brena, Ramon F

2014-06-20

User indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices, which allows us to exploit not only infrastructures made for everyday use, such as WiFi, but also natural infrastructure, as is the case of natural magnetic field. In this paper we present an extension and improvement of our current indoor localization model based on the feature extraction of 46 magnetic field signal features. The extension adds a feature selection phase to our methodology, which is performed through Genetic Algorithm (GA) with the aim of optimizing the fitness of our current model. In addition, we present an evaluation of the final model in two different scenarios: home and office building. The results indicate that performing a feature selection process allows us to reduce the number of signal features of the model from 46 to 5 regardless the scenario and room location distribution. Further, we verified that reducing the number of features increases the probability of our estimator correctly detecting the user's location (sensitivity) and its capacity to detect false positives (specificity) in both scenarios.

Feature extraction for ultrasonic sensor based defect detection in ceramic components

NASA Astrophysics Data System (ADS)

Kesharaju, Manasa; Nagarajah, Romesh

2014-02-01

High density silicon carbide materials are commonly used as the ceramic element of hard armour inserts used in traditional body armour systems to reduce their weight, while providing improved hardness, strength and elastic response to stress. Currently, armour ceramic tiles are inspected visually offline using an X-ray technique that is time consuming and very expensive. In addition, from X-rays multiple defects are also misinterpreted as single defects. Therefore, to address these problems the ultrasonic non-destructive approach is being investigated. Ultrasound based inspection would be far more cost effective and reliable as the methodology is applicable for on-line quality control including implementation of accept/reject criteria. This paper describes a recently developed methodology to detect, locate and classify various manufacturing defects in ceramic tiles using sub band coding of ultrasonic test signals. The wavelet transform is applied to the ultrasonic signal and wavelet coefficients in the different frequency bands are extracted and used as input features to an artificial neural network (ANN) for purposes of signal classification. Two different classifiers, using artificial neural networks (supervised) and clustering (un-supervised) are supplied with features selected using Principal Component Analysis(PCA) and their classification performance compared. This investigation establishes experimentally that Principal Component Analysis(PCA) can be effectively used as a feature selection method that provides superior results for classifying various defects in the context of ultrasonic inspection in comparison with the X-ray technique.

3D variational brain tumor segmentation on a clustered feature set

NASA Astrophysics Data System (ADS)

Popuri, Karteek; Cobzas, Dana; Jagersand, Martin; Shah, Sirish L.; Murtha, Albert

2009-02-01

Tumor segmentation from MRI data is a particularly challenging and time consuming task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. Our work addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multi-dimensional feature set. Further, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this paper is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to the previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned inside and outside region voxel probabilities in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance, during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters in the ventricles to be in the tumor and hence better disambiguate the tumor from brain tissue. We show the performance of our method on real MRI scans. The experimental dataset includes MRI scans, from patients with difficult instances, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Our method shows good results on these test cases.

Atlas of Radiographic Features of Osteoarthritis of the Ankle and Hindfoot

PubMed Central

Kraus, Virginia Byers; Kilfoil, Terrence M; Hash, Thomas W.; McDaniel, Gary; Renner, Jordan B; Carrino, John A.; Adams, Samuel

2015-01-01

Objective To develop a radiographic atlas of osteoarthritis (OA) for use as a template and guide for standardized scoring of radiographic features of OA of the ankle and hindfoot joints. Method Under Institutional Review Board approval, ankle and hindfoot images were selected from a cohort study and from among cases that underwent ankle radiography during a 6-month period at Duke University Medical Center. Missing OA pathology was obtained through supplementation of cases with the assistance of a foot and ankle specialist in Orthopaedic surgery and a musculoskeletal radiologist. Images were obtained and reviewed without patient identifying information. Images went through multiple rounds of review and final images were selected by consensus of the study team. For intra-rater and inter-rater reliability, the kappa statistic was calculated for two readings by 3 musculoskeletal radiologists, a minimum of two weeks apart, of ankle and hindfoot radiographs from 30 anonymized subjects. Results The atlas demonstrates individual radiographic features (osteophyte and joint space narrowing) and Kellgren Lawrence grade for all aspects of the talocrural (ankle joint proper) and talocalcaneal (subtalar) joints. Reliability of scoring based on the atlas was quite good to excellent for most features indicated. Additional examples of ankle joint findings are illustrated including sclerosis, os trigonum, subchondral cysts and talar tilt. Conclusions It is anticipated that this atlas will assist with standardization of scoring of ankle and hindfoot OA by basic and clinical OA researchers. PMID:26318654

Atlas of radiographic features of osteoarthritis of the ankle and hindfoot.

PubMed

Kraus, V B; Kilfoil, T M; Hash, T W; McDaniel, G; Renner, J B; Carrino, J A; Adams, S

2015-12-01

To develop a radiographic atlas of osteoarthritis (OA) for use as a template and guide for standardized scoring of radiographic features of OA of the ankle and hindfoot joints. Under Institutional Review Board approval, ankle and hindfoot images were selected from a cohort study and from among cases that underwent ankle radiography during a 6-month period at Duke University Medical Center. Missing OA pathology was obtained through supplementation of cases with the assistance of a foot and ankle specialist in Orthopaedic surgery and a musculoskeletal radiologist. Images were obtained and reviewed without patient identifying information. Images went through multiple rounds of review and final images were selected by consensus of the study team. For intra-rater and inter-rater reliability, the kappa statistic was calculated for two readings by three musculoskeletal radiologists, a minimum of two weeks apart, of ankle and hindfoot radiographs from 30 anonymized subjects. The atlas demonstrates individual radiographic features (osteophyte and joint space narrowing (JSN)) and Kellgren-Lawrence grade for all aspects of the talocrural (ankle joint proper) and talocalcaneal (subtalar) joints. Reliability of scoring based on the atlas was quite good to excellent for most features indicated. Additional examples of ankle joint findings are illustrated including sclerosis, os trigonum, subchondral cysts and talar tilt. It is anticipated that this atlas will assist with standardization of scoring of ankle and hindfoot OA by basic and clinical OA researchers. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Recent Development of the Two-Stroke Engine. II - Design Features. 2; Design Features

NASA Technical Reports Server (NTRS)

Zeman, J.

1945-01-01

Completing the first paper dealing with charging methods and arrangements, the present paper discusses the design forms of two-stroke engines. Features which largely influence piston running are: (a) The shape and surface condition of the sliding parts. (b) The cylinder and piston materials. (c) Heat conditions in the piston, and lubrication. There is little essential difference between four-stroke and two-stroke engines with ordinary pistons. In large engines, for example, are always found separately cast or welded frames in which the stresses are taken up by tie rods. Twin piston and timing piston engines often differ from this design. Examples can be found in many engines of German or foreign make. Their methods of operation will be dealt with in the third part of the present paper, which also includes the bibliography. The development of two-stroke engine design is, of course, mainly concerned with such features as are inherently difficult to master; that is, the piston barrel and the design of the gudgeon pin bearing. Designers of four-stroke engines now-a-days experience approximately the same difficulties, since heat stresses have increased to the point of influencing conditions in the piston barrel. Features which notably affect this are: (a) The material. (b) Prevailing heat conditions.

Prevalence of histological features of idiopathic noncirrhotic portal hypertension in general population: a retrospective study of incidental liver biopsies.

PubMed

Zuo, Chunlai; Chumbalkar, Vaibhav; Ells, Peter F; Bonville, Daniel J; Lee, Hwajeong

2017-09-01

Idiopathic noncirrhotic portal hypertension (INCPH) is associated with histologic changes secondary to obliterative portal venopathy without cirrhosis. We studied the prevalence of individual histological features of INCPH in liver biopsies obtained incidentally during unrelated elective procedures and in elective liver biopsies with the diagnosis of fatty liver disease. A total of 53 incidental liver biopsies obtained intraoperatively during unrelated elective procedures and an additional 28 elective biopsies with the diagnosis of fatty liver disease without portal hypertension and cirrhosis were studied. Various histologic features of INCPH were evaluated. Shunt vessel (30%), phlebosclerosis (27%), increased number of portal vessels (19%) and incomplete septa (17%) were common in these liver biopsies after confounding factors such as co-existing fatty liver disease or fibrosis were excluded. At least one feature of INCPH was noted in 90% of the biopsies. Eight (10%) biopsies showed 5-6 features of INCPH. In total, 11 (14%) of 81 patients had risk factors associated with INCPH, including hypercoagulability, autoimmune disease, exposure to drugs, and infections. No patient had portal hypertension at the end of the follow-up. The histologic features of INCPH are seen in incidental liver biopsies and fatty liver disease without portal hypertension. Ten percent of the biopsies show 5-6 features of INCPH without portal hypertension. Interpreting histologic features in the right clinical context is important for proper patient care.

Asymmetric Michael Addition Mediated by Chiral Ionic Liquids.

PubMed

Suzuki, Yumiko

2018-06-01

Chiral ionic liquids with a focus on their applications in asymmetric Michael additions and related reactions were reviewed. The examples were classified on the basis of the mode of asymmetric induction (e.g., external induction/non-covalent interaction or internal induction/covalent bond formation), the roles in reactions (as a solvent or catalyst), and their structural features (e.g., imidazolium-based chiral cations, other chiral oniums; proline derivatives). Most of the reactions with high chiral induction are Michael addition of ketones or aldehydes to chalcones or nitrostyrenes where proline-derived chiral ionic liquids catalyze the reaction through enamine/ iminium formation. Many reports demonstrate the recyclability of ionic liquid-tagged pyrrolidines.

The future of primordial features with large-scale structure surveys

NASA Astrophysics Data System (ADS)

Chen, Xingang; Dvorkin, Cora; Huang, Zhiqi; Namjoo, Mohammad Hossein; Verde, Licia

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopic and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.

The future of primordial features with large-scale structure surveys

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

Chen, Xingang; Namjoo, Mohammad Hossein; Dvorkin, Cora

2016-11-01

Primordial features are one of the most important extensions of the Standard Model of cosmology, providing a wealth of information on the primordial Universe, ranging from discrimination between inflation and alternative scenarios, new particle detection, to fine structures in the inflationary potential. We study the prospects of future large-scale structure (LSS) surveys on the detection and constraints of these features. We classify primordial feature models into several classes, and for each class we present a simple template of power spectrum that encodes the essential physics. We study how well the most ambitious LSS surveys proposed to date, including both spectroscopicmore » and photometric surveys, will be able to improve the constraints with respect to the current Planck data. We find that these LSS surveys will significantly improve the experimental sensitivity on features signals that are oscillatory in scales, due to the 3D information. For a broad range of models, these surveys will be able to reduce the errors of the amplitudes of the features by a factor of 5 or more, including several interesting candidates identified in the recent Planck data. Therefore, LSS surveys offer an impressive opportunity for primordial feature discovery in the next decade or two. We also compare the advantages of both types of surveys.« less

The effects of variations in parameters and algorithm choices on calculated radiomics feature values: initial investigations and comparisons to feature variability across CT image acquisition conditions

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Wahi-Anwar, Muhammad; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael

2018-02-01

Translation of radiomics into clinical practice requires confidence in its interpretations. This may be obtained via understanding and overcoming the limitations in current radiomic approaches. Currently there is a lack of standardization in radiomic feature extraction. In this study we examined a few factors that are potential sources of inconsistency in characterizing lung nodules, such as 1)different choices of parameters and algorithms in feature calculation, 2)two CT image dose levels, 3)different CT reconstruction algorithms (WFBP, denoised WFBP, and Iterative). We investigated the effect of variation of these factors on entropy textural feature of lung nodules. CT images of 19 lung nodules identified from our lung cancer screening program were identified by a CAD tool and contours provided. The radiomics features were extracted by calculating 36 GLCM based and 4 histogram based entropy features in addition to 2 intensity based features. A robustness index was calculated across different image acquisition parameters to illustrate the reproducibility of features. Most GLCM based and all histogram based entropy features were robust across two CT image dose levels. Denoising of images slightly improved robustness of some entropy features at WFBP. Iterative reconstruction resulted in improvement of robustness in a fewer times and caused more variation in entropy feature values and their robustness. Within different choices of parameters and algorithms texture features showed a wide range of variation, as much as 75% for individual nodules. Results indicate the need for harmonization of feature calculations and identification of optimum parameters and algorithms in a radiomics study.

Adversarial Feature Selection Against Evasion Attacks.

PubMed

Zhang, Fei; Chan, Patrick P K; Biggio, Battista; Yeung, Daniel S; Roli, Fabio

2016-03-01

Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on devising adversary-aware classification algorithms to counter evasion attempts, only few authors have considered the impact of using reduced feature sets on classifier security against the same attacks. An interesting, preliminary result is that classifier security to evasion may be even worsened by the application of feature selection. In this paper, we provide a more detailed investigation of this aspect, shedding some light on the security properties of feature selection against evasion attacks. Inspired by previous work on adversary-aware classifiers, we propose a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary's data manipulation strategy. We focus on an efficient, wrapper-based implementation of our approach, and experimentally validate its soundness on different application examples, including spam and malware detection.

Illusory conjunctions in simultanagnosia: coarse coding of visual feature location?

PubMed

McCrea, Simon M; Buxbaum, Laurel J; Coslett, H Branch

2006-01-01

Simultanagnosia is a disorder characterized by an inability to see more than one object at a time. We report a simultanagnosic patient (ED) with bilateral posterior infarctions who produced frequent illusory conjunctions on tasks involving form and surface features (e.g., a red T) and form alone. ED also produced "blend" errors in which features of one familiar perceptual unit appeared to migrate to another familiar perceptual unit (e.g., "RO" read as "PQ"). ED often misread scrambled letter strings as a familiar word (e.g., "hmoe" read as "home"). Finally, ED's success in reporting two letters in an array was inversely related to the distance between the letters. These findings are consistent with the hypothesis that ED's illusory reflect coarse coding of visual feature location that is ameliorated in part by top-down information from object and word recognition systems; the findings are also consistent, however, with Treisman's Feature Integration Theory. Finally, the data provide additional support for the claim that the dorsal parieto-occipital cortex is implicated in the binding of visual feature information.

Local Chromatin Features Including PU.1 and IKAROS Binding and H3K4 Methylation Shape the Repertoire of Immunoglobulin Kappa Genes Chosen for V(D)J Recombination.

PubMed

Matheson, Louise S; Bolland, Daniel J; Chovanec, Peter; Krueger, Felix; Andrews, Simon; Koohy, Hashem; Corcoran, Anne E

2017-01-01

V(D)J recombination is essential for the generation of diverse antigen receptor (AgR) repertoires. In B cells, immunoglobulin kappa ( Igκ ) light chain recombination follows immunoglobulin heavy chain ( Igh ) recombination. We recently developed the DNA-based VDJ-seq assay for the unbiased quantitation of Igh VH and DH repertoires. Integration of VDJ-seq data with genome-wide datasets revealed that two chromatin states at the recombination signal sequence (RSS) of VH genes are highly predictive of recombination in mouse pro-B cells. It is unknown whether local chromatin states contribute to Vκ gene choice during Igκ recombination. Here we adapt VDJ-seq to profile the Igκ VκJκ repertoire and present a comprehensive readout in mouse pre-B cells, revealing highly variable Vκ gene usage. Integration with genome-wide datasets for histone modifications, DNase hypersensitivity, transcription factor binding and germline transcription identified PU.1 binding at the RSS, which was unimportant for Igh , as highly predictive of whether a Vκ gene will recombine or not, suggesting that it plays a binary, all-or-nothing role, priming genes for recombination. Thereafter, the frequency with which these genes recombine was shaped both by the presence and level of enrichment of several other chromatin features, including H3K4 methylation and IKAROS binding. Moreover, in contrast to the Igh locus, the chromatin landscape of the promoter, as well as of the RSS, contributes to Vκ gene recombination. Thus, multiple facets of local chromatin features explain much of the variation in Vκ gene usage. Together, these findings reveal shared and divergent roles for epigenetic features and transcription factors in AgR V(D)J recombination and provide avenues for further investigation of chromatin signatures that may underpin V(D)J-mediated chromosomal translocations.

Local Chromatin Features Including PU.1 and IKAROS Binding and H3K4 Methylation Shape the Repertoire of Immunoglobulin Kappa Genes Chosen for V(D)J Recombination

PubMed Central

Matheson, Louise S.; Bolland, Daniel J.; Chovanec, Peter; Krueger, Felix; Andrews, Simon; Koohy, Hashem; Corcoran, Anne E.

2017-01-01

V(D)J recombination is essential for the generation of diverse antigen receptor (AgR) repertoires. In B cells, immunoglobulin kappa (Igκ) light chain recombination follows immunoglobulin heavy chain (Igh) recombination. We recently developed the DNA-based VDJ-seq assay for the unbiased quantitation of Igh VH and DH repertoires. Integration of VDJ-seq data with genome-wide datasets revealed that two chromatin states at the recombination signal sequence (RSS) of VH genes are highly predictive of recombination in mouse pro-B cells. It is unknown whether local chromatin states contribute to Vκ gene choice during Igκ recombination. Here we adapt VDJ-seq to profile the Igκ VκJκ repertoire and present a comprehensive readout in mouse pre-B cells, revealing highly variable Vκ gene usage. Integration with genome-wide datasets for histone modifications, DNase hypersensitivity, transcription factor binding and germline transcription identified PU.1 binding at the RSS, which was unimportant for Igh, as highly predictive of whether a Vκ gene will recombine or not, suggesting that it plays a binary, all-or-nothing role, priming genes for recombination. Thereafter, the frequency with which these genes recombine was shaped both by the presence and level of enrichment of several other chromatin features, including H3K4 methylation and IKAROS binding. Moreover, in contrast to the Igh locus, the chromatin landscape of the promoter, as well as of the RSS, contributes to Vκ gene recombination. Thus, multiple facets of local chromatin features explain much of the variation in Vκ gene usage. Together, these findings reveal shared and divergent roles for epigenetic features and transcription factors in AgR V(D)J recombination and provide avenues for further investigation of chromatin signatures that may underpin V(D)J-mediated chromosomal translocations. PMID:29204143

A pragmatic approach to the diagnosis and treatment of mixed features in adults with mood disorders.

PubMed

McIntyre, Roger S; Lee, Yena; Mansur, Rodrigo B

2016-12-01

Mixed features specifier (MFS) is a new nosological entity defined and operationalized in the Diagnostic and Statistical Manual of Mental Disorders (DSM), 5th Edition. The impetus to introduce the MFS and supplant mixed states was protean, including the lack of ecological validity, high rates of misdiagnosis, and guideline discordant treatment for mixed states. Mixed features specifier identifies a phenotype in psychiatry with greater illness burden, as evidenced by earlier age at onset, higher episode frequency and chronicity, psychiatric and medical comorbidity, suicidality, and suboptimal response to conventional antidepressants. Mixed features in psychiatry have historical, conceptual, and nosological relevance; MFS according to DSM-5, is inherently neo-Kraepelinian insofar as individuals with either Major Depressive Disorder (MDD) or Bipolar Disorder (BD) may be affected by MFS. Clinicians are encouraged to screen all patients presenting with a major depressive episode (or hypomanic episode) for MFS. Although "overlapping symptoms" were excluded from the diagnostic criteria (eg, agitation, anxiety, irritability, insomnia), clinicians are encouraged to probe for these nonspecific symptoms as a possible proxy of co-existing MFS. In addition to conventional antidepressants, second generation antipsychotics and/or conventional mood stabilizers (eg, lithium) may be considered as first-line therapies for individuals with a depressive episode as part of MDD or BD with mixed features.

Evaluation of certain food additives.

PubMed

2017-01-01

This report represents the conclusions of a Joint FAO/WHO Expert Committee convened to evaluate the safety of various food additives, including flavouring agents, with a view to concluding as to safety concerns and to preparing specifications for identity and purity. The first part of the report contains a general discussion of the principles governing the toxicological evaluation of and assessment of dietary exposure to food additives, including flavouring agents. A summary follows of the Committee’s evaluations of technical, toxicological and dietary exposure data for 10 food additives (Allura Red AC; carob bean gum; lutein esters from Tagetes erecta; octenyl succinic acid (OSA)– modified gum arabic; pectin; Quinoline Yellow; rosemary extract; steviol glycosides; tartrazine; and xanthan gum) and five groups of flavouring agents (alicyclic, alicyclic-fused and aromatic-fused ring lactones; aliphatic and aromatic amines and amides; aliphatic secondary alcohols, ketones and related esters; cinnamyl alcohol and related substances; and tetrahydrofuran and furanone derivatives). Specifications for the following food additives were revised: aspartame; cassia gum; citric and fatty acid esters of glycerol (CITREM); modified starches; octanoic acid; starch sodium octenyl succinate; and total colouring matters. Annexed to the report are tables summarizing the Committee’s recommendations for dietary exposures to and toxicological evaluations of all of the food additives, including flavouring agents, considered at this meeting.

Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review

PubMed Central

Weal, Mark; Morrison, Leanne; Yardley, Lucy

2018-01-01

Background Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects. Objective The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social media features as part of their intervention infrastructure. A taxonomy of social media features is presented to inform the development, description, and evaluation of behavioral interventions. Methods Search terms were used in 8 databases to identify DBCIs that incorporated social media features and targeted tobacco smoking, diet and nutrition, physical activities, or alcohol consumption. The screening and review process was performed by 2 independent researchers. Results A total of 5264 articles were screened, and 143 articles describing a total of 134 studies were retained for full review. The majority of studies (70%) reported positive outcomes, followed by 28% finding no effects with regard to their respective objectives and hypothesis, and 2% of the studies found that their interventions had negative outcomes. Few studies reported on the association between the inclusion of social media features and intervention effect. A taxonomy of social media features used in behavioral interventions has been presented with 36 social media features organized under 7 high-level categories. The taxonomy has been used to guide the analysis of this review. Conclusions Although social media features are commonly included in DBCIs, there is an acute lack of information with respect to their effect on outcomes and a lack of clear guidance to inform the selection process based on the features’ suitability for the different behaviors. The proposed taxonomy along with the set of recommendations included

Filtering of the Radon transform to enhance linear signal features via wavelet pyramid decomposition

NASA Astrophysics Data System (ADS)

Meckley, John R.

1995-09-01

wavelet coefficient energy. The detection algorithm provides an estimate of the line offset, orientation, and length that is then used to index the appropriate filter shape. Additional wavelet pyramid decomposition is performed in areas of high energy to refine the line position estimate. After filtering, the new Radon transform is generated by inverting the wavelet pyramid. The Radon transform is then inverted by filtered backprojection to produce the final 2D signal estimate with the enhanced linear features. The wavelet-based method is compared to both the Fourier and the nonlinear filtering with examples of sparse and dense shapes in imaging, acoustics and medical tomography with test images of noisy concentric lines, a real spectrogram of a blow fish (a very nonstationary spectrum), and the Shepp Logan Computer Tomography phantom image. Both qualitative and derived quantitative measures demonstrate the improvement of wavelet-based filtering. Additional research is suggested based on these results. Open questions include what level(s) to use for detection and filtering because multiple-level representations exist. The lower levels are smoother at reduced spatial resolution, while the higher levels provide better response to edges. Several examples are discussed based on analytical and phenomenological arguments.

Decoding Articulatory Features from fMRI Responses in Dorsal Speech Regions.

PubMed

Correia, Joao M; Jansma, Bernadette M B; Bonte, Milene

2015-11-11

The brain's circuitry for perceiving and producing speech may show a notable level of overlap that is crucial for normal development and behavior. The extent to which sensorimotor integration plays a role in speech perception remains highly controversial, however. Methodological constraints related to experimental designs and analysis methods have so far prevented the disentanglement of neural responses to acoustic versus articulatory speech features. Using a passive listening paradigm and multivariate decoding of single-trial fMRI responses to spoken syllables, we investigated brain-based generalization of articulatory features (place and manner of articulation, and voicing) beyond their acoustic (surface) form in adult human listeners. For example, we trained a classifier to discriminate place of articulation within stop syllables (e.g., /pa/ vs /ta/) and tested whether this training generalizes to fricatives (e.g., /fa/ vs /sa/). This novel approach revealed generalization of place and manner of articulation at multiple cortical levels within the dorsal auditory pathway, including auditory, sensorimotor, motor, and somatosensory regions, suggesting the representation of sensorimotor information. Additionally, generalization of voicing included the right anterior superior temporal sulcus associated with the perception of human voices as well as somatosensory regions bilaterally. Our findings highlight the close connection between brain systems for speech perception and production, and in particular, indicate the availability of articulatory codes during passive speech perception. Sensorimotor integration is central to verbal communication and provides a link between auditory signals of speech perception and motor programs of speech production. It remains highly controversial, however, to what extent the brain's speech perception system actively uses articulatory (motor), in addition to acoustic/phonetic, representations. In this study, we examine the role of

Cytological features of "noninvasive follicular thyroid neoplasm with papillary-like nuclear features" and their correlation with tumor histology.

PubMed

Maletta, Francesca; Massa, Federica; Torregrossa, Liborio; Duregon, Eleonora; Casadei, Gian Piero; Basolo, Fulvio; Tallini, Giovanni; Volante, Marco; Nikiforov, Yuri E; Papotti, Mauro

2016-08-01

Among thyroid papillary carcinomas (PTCs), the follicular variant is the most common and includes encapsulated forms (EFVPTCs). Noninvasive EFVPTCs have very low risk of recurrence or other adverse events and have been recently proposed to be designated as noninvasive follicular thyroid neoplasm with papillary-like nuclear features or NIFTP, thus eliminating the term carcinoma. This proposal is expected to significantly impact the risk of malignancy associated with the currently used diagnostic categories of thyroid cytology. In this study, we analyzed the fine needle aspiration biopsy (FNAB) cytology features of 96 histologically proven NIFTPs and determined how the main nuclear features of NIFTP correlate between cytological and histological samples. Blind review of FNAB cytology from NIFTP nodules yielded the diagnosis of "follicular neoplasm" (Bethesda category IV) in 56% of cases, "suspicious for malignancy" (category V) in 27%, "atypia of undetermined significance/follicular lesion of undetermined significance" (category III) in 15%, and "malignant" (category VI) in 2%. We found good correlation (κ=0.62) of nuclear features between histological and cytological specimens. NIFTP nuclear features (size, irregularities of contours, and chromatin clearing) were significantly different from those of benign nodules but not from those of invasive EFVPTC. Our data indicate that most of the NIFTP nodules yield an indeterminate cytological diagnosis in FNAB cytology and nuclear features found in cytology samples are reproducibly identified in corresponding histology samples. Because of the overlapping nuclear features with invasive EFVPTC, NIFTP cannot be reliably diagnosed preoperatively but should be listed in differential diagnosis of all indeterminate categories of thyroid cytology. Copyright © 2016 Elsevier Inc. All rights reserved.

Coding visual features extracted from video sequences.

PubMed

Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2014-05-01

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

Recognizing human activities using appearance metric feature and kinematics feature

NASA Astrophysics Data System (ADS)

Qian, Huimin; Zhou, Jun; Lu, Xinbiao; Wu, Xinye

2017-05-01

The problem of automatically recognizing human activities from videos through the fusion of the two most important cues, appearance metric feature and kinematics feature, is considered. And a system of two-dimensional (2-D) Poisson equations is introduced to extract the more discriminative appearance metric feature. Specifically, the moving human blobs are first detected out from the video by background subtraction technique to form a binary image sequence, from which the appearance feature designated as the motion accumulation image and the kinematics feature termed as centroid instantaneous velocity are extracted. Second, 2-D discrete Poisson equations are employed to reinterpret the motion accumulation image to produce a more differentiated Poisson silhouette image, from which the appearance feature vector is created through the dimension reduction technique called bidirectional 2-D principal component analysis, considering the balance between classification accuracy and time consumption. Finally, a cascaded classifier based on the nearest neighbor classifier and two directed acyclic graph support vector machine classifiers, integrated with the fusion of the appearance feature vector and centroid instantaneous velocity vector, is applied to recognize the human activities. Experimental results on the open databases and a homemade one confirm the recognition performance of the proposed algorithm.

Modeling process-structure-property relationships for additive manufacturing

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Genetic (idiopathic) epilepsy with photosensitive seizures includes features of both focal and generalized seizures.

PubMed

Xue, Jiao; Gong, Pan; Yang, Haipo; Liu, Xiaoyan; Jiang, Yuwu; Zhang, Yuehua; Yang, Zhixian

2018-04-19

Clinically, some patients having genetic (idiopathic) epilepsy with photosensitive seizures were difficult to be diagnosed. We aimed to discuss whether the genetic (idiopathic) epilepsy with photosensitive seizures is a focal entity, a generalized entity or a continuum. Twenty-two patients with idiopathic epilepsies and photoconvulsive response (PCR) were retrospectively recruited. In the medical records, the seizure types included "generalized tonic-clonic seizures (GTCS)" in 15, "partial secondarily GTCS (PGTCS)" in 3, partial seizures (PS) in 3, myoclonic seizures in 2, eyelid myoclonus in one, and only febrile seizures in one. Seizure types of PCR included GTCS (1/22), PGTCS (6/22), PS (9/22), electrical seizures (ES) (3/22) and GTCS/PGTCS (3/22). Combined the medical history with PCR results, they were diagnosed as: idiopathic (photosensitive) occipital lobe epilepsy (I(P)OE) in 12, genetic (idiopathic) generalized epilepsy (GGE) in one, GGE/I(P)OE in 5, pure photosensitive seizure in one, and epilepsy with undetermined generalized or focal seizure in 3. So, the dichotomy between generalized and focal seizures might have been out of date regarding to pathophysiological advances in epileptology. To some extent, it would be better to recognize the idiopathic epilepsy with photosensitive seizures as a continuum between focal and generalized seizures.

A novel feature extraction approach for microarray data based on multi-algorithm fusion

PubMed Central

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions. PMID:25780277

A novel feature extraction approach for microarray data based on multi-algorithm fusion.

PubMed

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions.

Feature-based attention elicits surround suppression in feature space.

PubMed

Störmer, Viola S; Alvarez, George A

2014-09-08

It is known that focusing attention on a particular feature (e.g., the color red) facilitates the processing of all objects in the visual field containing that feature [1-7]. Here, we show that such feature-based attention not only facilitates processing but also actively inhibits processing of similar, but not identical, features globally across the visual field. We combined behavior and electrophysiological recordings of frequency-tagged potentials in human observers to measure this inhibitory surround in feature space. We found that sensory signals of an attended color (e.g., red) were enhanced, whereas sensory signals of colors similar to the target color (e.g., orange) were suppressed relative to colors more distinct from the target color (e.g., yellow). Importantly, this inhibitory effect spreads globally across the visual field, thus operating independently of location. These findings suggest that feature-based attention comprises an excitatory peak surrounded by a narrow inhibitory zone in color space to attenuate the most distracting and potentially confusable stimuli during visual perception. This selection profile is akin to what has been reported for location-based attention [8-10] and thus suggests that such center-surround mechanisms are an overarching principle of attention across different domains in the human brain. Copyright © 2014 Elsevier Ltd. All rights reserved.

Process Sensitivity, Performance, and Direct Verification Testing of Adhesive Locking Features

NASA Technical Reports Server (NTRS)

Golden, Johnny L.; Leatherwood, Michael D.; Montoya, Michael D.; Kato, Ken A.; Akers, Ed

2012-01-01

Phase I: The use of adhesive locking features or liquid locking compounds (LLCs) (e.g., Loctite) as a means of providing a secondary locking feature has been used on NASA programs since the Apollo program. In many cases Loctite was used as a last resort when (a) self-locking fasteners were no longer functioning per their respective drawing specification, (b) access was limited for removal & replacement, or (c) replacement could not be accomplished without severe impact to schedule. Long-term use of Loctite became inevitable in cases where removal and replacement of worn hardware was not cost effective and Loctite was assumed to be fully cured and working. The NASA Engineering & Safety Center (NESC) and United Space Alliance (USA) recognized the need for more extensive testing of Loctite grades to better understand their capabilities and limitations as a secondary locking feature. These tests, identified as Phase I, were designed to identify processing sensitivities, to determine proper cure time, the correct primer to use on aerospace nutplate, insert and bolt materials such as A286 and MP35N, and the minimum amount of Loctite that is required to achieve optimum breakaway torque values. The .1900-32 was the fastener size tested, due to wide usage in the aerospace industry. Three different grades of Loctite were tested. Results indicate that, with proper controls, adhesive locking features can be successfully used in the repair of locking features and should be considered for design. Phase II: Threaded fastening systems used in aerospace programs typically have a requirement for a redundant locking feature. The primary locking method is the fastener preload and the traditional redundant locking feature is a self-locking mechanical device that may include deformed threads, non-metallic inserts, split beam features, or other methods that impede movement between threaded members. The self-locking resistance of traditional locking features can be directly verified

Novel clinical features of nonconvulsive status epilepticus

PubMed Central

Nagayama, Masao; Yang, Sunghoon; Geocadin, Romergryko G.; Kaplan, Peter W.; Hoshiyama, Eisei; Shiromaru-Sugimoto, Azusa; Kawamura, Mitsuru

2017-01-01

Nonconvulsive status epilepticus (NCSE) has rapidly expanded from classical features such as staring, repetitive blinking, chewing, swallowing, and automatism to include coma, prolonged apnea, cardiac arrest, dementia, and higher brain dysfunction, which were demonstrated mainly after the 2000s by us and other groups. This review details novel clinical features of NCSE as a manifestation of epilepsy, but one that is underdiagnosed, with the best available evidence. Also, we describe the new concept of epilepsy-related organ dysfunction (Epi-ROD) and a novel electrode and headset which enables prompt electroencephalography. PMID:28979770

Frequency of the first feature in action sequences influences feature binding.

PubMed

Mattson, Paul S; Fournier, Lisa R; Behmer, Lawrence P

2012-10-01

We investigated whether binding among perception and action feature codes is a preliminary step toward creating a more durable memory trace of an action event. If so, increasing the frequency of a particular event (e.g., a stimulus requiring a movement with the left or right hand in an up or down direction) should increase the strength and speed of feature binding for this event. The results from two experiments, using a partial-repetition paradigm, confirmed that feature binding increased in strength and/or occurred earlier for a high-frequency (e.g., left hand moving up) than for a low-frequency (e.g., right hand moving down) event. Moreover, increasing the frequency of the first-specified feature in the action sequence alone (e.g., "left" hand) increased the strength and/or speed of action feature binding (e.g., between the "left" hand and movement in an "up" or "down" direction). The latter finding suggests an update to the theory of event coding, as not all features in the action sequence equally determine binding strength. We conclude that action planning involves serial binding of features in the order of action feature execution (i.e., associations among features are not bidirectional but are directional), which can lead to a more durable memory trace. This is consistent with physiological evidence suggesting that serial order is preserved in an action plan executed from memory and that the first feature in the action sequence may be critical in preserving this serial order.

Automatic Feature Extraction from Planetary Images

NASA Technical Reports Server (NTRS)

Troglio, Giulia; Le Moigne, Jacqueline; Benediktsson, Jon A.; Moser, Gabriele; Serpico, Sebastiano B.

2010-01-01

With the launch of several planetary missions in the last decade, a large amount of planetary images has already been acquired and much more will be available for analysis in the coming years. The image data need to be analyzed, preferably by automatic processing techniques because of the huge amount of data. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to planetary data that often present low contrast and uneven illumination characteristics. Different methods have already been presented for crater extraction from planetary images, but the detection of other types of planetary features has not been addressed yet. Here, we propose a new unsupervised method for the extraction of different features from the surface of the analyzed planet, based on the combination of several image processing techniques, including a watershed segmentation and the generalized Hough Transform. The method has many applications, among which image registration and can be applied to arbitrary planetary images.

Novel chromatin texture features for the classification of pap smears

NASA Astrophysics Data System (ADS)

Bejnordi, Babak E.; Moshavegh, Ramin; Sujathan, K.; Malm, Patrik; Bengtsson, Ewert; Mehnert, Andrew

2013-03-01

This paper presents a set of novel structural texture features for quantifying nuclear chromatin patterns in cells on a conventional Pap smear. The features are derived from an initial segmentation of the chromatin into bloblike texture primitives. The results of a comprehensive feature selection experiment, including the set of proposed structural texture features and a range of different cytology features drawn from the literature, show that two of the four top ranking features are structural texture features. They also show that a combination of structural and conventional features yields a classification performance of 0.954±0.019 (AUC±SE) for the discrimination of normal (NILM) and abnormal (LSIL and HSIL) slides. The results of a second classification experiment, using only normal-appearing cells from both normal and abnormal slides, demonstrates that a single structural texture feature measuring chromatin margination yields a classification performance of 0.815±0.019. Overall the results demonstrate the efficacy of the proposed structural approach and that it is possible to detect malignancy associated changes (MACs) in Papanicoloau stain.

Ionic liquids, electrolyte solutions including the ionic liquids, and energy storage devices including the ionic liquids

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

Gering, Kevin L.; Harrup, Mason K.; Rollins, Harry W.

2015-12-08

An ionic liquid including a phosphazene compound that has a plurality of phosphorus-nitrogen units and at least one pendant group bonded to each phosphorus atom of the plurality of phosphorus-nitrogen units. One pendant group of the at least one pendant group comprises a positively charged pendant group. Additional embodiments of ionic liquids are disclosed, as are electrolyte solutions and energy storage devices including the embodiments of the ionic liquid.

Deep-learning derived features for lung nodule classification with limited datasets

NASA Astrophysics Data System (ADS)

Thammasorn, P.; Wu, W.; Pierce, L. A.; Pipavath, S. N.; Lampe, P. D.; Houghton, A. M.; Haynor, D. R.; Chaovalitwongse, W. A.; Kinahan, P. E.

2018-02-01

Only a few percent of indeterminate nodules found in lung CT images are cancer. However, enabling earlier diagnosis is important to avoid invasive procedures or long-time surveillance to those benign nodules. We are evaluating a classification framework using radiomics features derived with a machine learning approach from a small data set of indeterminate CT lung nodule images. We used a retrospective analysis of 194 cases with pulmonary nodules in the CT images with or without contrast enhancement from lung cancer screening clinics. The nodules were contoured by a radiologist and texture features of the lesion were calculated. In addition, sematic features describing shape were categorized. We also explored a Multiband network, a feature derivation path that uses a modified convolutional neural network (CNN) with a Triplet Network. This was trained to create discriminative feature representations useful for variable-sized nodule classification. The diagnostic accuracy was evaluated for multiple machine learning algorithms using texture, shape, and CNN features. In the CT contrast-enhanced group, the texture or semantic shape features yielded an overall diagnostic accuracy of 80%. Use of a standard deep learning network in the framework for feature derivation yielded features that substantially underperformed compared to texture and/or semantic features. However, the proposed Multiband approach of feature derivation produced results similar in diagnostic accuracy to the texture and semantic features. While the Multiband feature derivation approach did not outperform the texture and/or semantic features, its equivalent performance indicates promise for future improvements to increase diagnostic accuracy. Importantly, the Multiband approach adapts readily to different size lesions without interpolation, and performed well with relatively small amount of training data.

Prioritizing causal disease genes using unbiased genomic features.

PubMed

Deo, Rahul C; Musso, Gabriel; Tasan, Murat; Tang, Paul; Poon, Annie; Yuan, Christiana; Felix, Janine F; Vasan, Ramachandran S; Beroukhim, Rameen; De Marco, Teresa; Kwok, Pui-Yan; MacRae, Calum A; Roth, Frederick P

2014-12-03

Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits. To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM. Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature.

The newly expanded KSC Visitors Complex features a new ticket plaza, information center, exhibits an

NASA Technical Reports Server (NTRS)

1999-01-01

The $13 million expansion to KSC's Visitor Complex includes a new International Space Station-themed ticket plaza, featuring a structure of overhanging solar panels and astronauts performing assembly tasks. Other additions are a new information center, a walk-through Robot Scouts exhibit, a wildlife exhibit, and the film Quest for Life in a new 300-seat theater. The KSC Visitor Complex was inaugurated three decades ago and is now one of the top five tourist attractions in Florida. It is located on S.R. 407, east of I-95, within the Merritt Island National Wildlife Refuge.

The newly expanded KSC Visitors Complex features a new ticket plaza, information center, exhibits an

NASA Technical Reports Server (NTRS)

1999-01-01

The $13 million expansion to KSC's Visitor Complex includes a new International Space Station-themed ticket plaza, featuring a structure of overhanging solar panels and astronauts performing assembly tasks. Other additions are the new information center, a walk-through Robot Scouts exhibit, a wildlife exhibit, and the film Quest for Life in a new 300-seat theater. The KSC Visitor Complex was inaugurated three decades ago and is now one of the top five tourist attractions in Florida. It is located on S.R. 407, east of I-95, within the Merritt Island National Wildlife Refuge.

Cardiovascular Disease and 10-Year Mortality in Postmenopausal Women with Clinical Features of Polycystic Ovary Syndrome.

PubMed

Merz, C Noel Bairey; Shaw, Leslee J; Azziz, Ricardo; Stanczyk, Frank Z; Sopko, George; Braunstein, Glenn D; Kelsey, Sheryl F; Kip, Kevin E; Cooper-DeHoff, Rhonda M; Johnson, B Delia; Vaccarino, Viola; Reis, Steven E; Bittner, Vera; Hodgson, T Keta; Rogers, William; Pepine, Carl J

2016-09-01

Women with polycystic ovary syndrome (PCOS) have greater cardiac risk factor clustering but the link with mortality is incompletely described. To evaluate outcomes in 295 postmenopausal women enrolled in the National Institutes of Health-National Heart, Lung, and Blood Institute (NIH-NHLBI) sponsored Women's Ischemia Syndrome Evaluation (WISE) study according to clinical features of PCOS. A total of 25/295 (8%) women had clinical features of PCOS defined by a premenopausal history of irregular menses and current biochemical evidence of hyperandrogenemia, defined as the top quartile of androstenedione (≥701 pg/mL), testosterone (≥30.9 ng/dL), or free testosterone (≥4.5 pg/mL). Cox proportional hazard model estimated death (n = 80). Women with clinical features of PCOS had an earlier menopause (p = 0.01), were more often smokers (p < 0.04), and trended toward more angiographic coronary artery disease (CAD) (p = 0.07) than women without these features. Cumulative 10-year mortality was 28% for women with (n = 25) versus 27% without clinical features of PCOS (n = 270) (p = 0.85). PCOS was not a significant predictor (p = NS) in prognostic models including diabetes, waist circumference, hypertension, and angiographic CAD. From this longer-term follow up of a relatively small cohort of postmenopausal women with suspected ischemia, the prevalence of PCOS is similar to the general population, and clinical features of PCOS are not associated with CAD or mortality. These findings question whether identification of clinical features of PCOS in postmenopausal women who already have known cardiovascular disease provides any additional opportunity for risk factor intervention.

Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.

PubMed

Elaheebocus, Sheik Mohammad Roushdat Ally; Weal, Mark; Morrison, Leanne; Yardley, Lucy

2018-02-22

Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects. The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social media features as part of their intervention infrastructure. A taxonomy of social media features is presented to inform the development, description, and evaluation of behavioral interventions. Search terms were used in 8 databases to identify DBCIs that incorporated social media features and targeted tobacco smoking, diet and nutrition, physical activities, or alcohol consumption. The screening and review process was performed by 2 independent researchers. A total of 5264 articles were screened, and 143 articles describing a total of 134 studies were retained for full review. The majority of studies (70%) reported positive outcomes, followed by 28% finding no effects with regard to their respective objectives and hypothesis, and 2% of the studies found that their interventions had negative outcomes. Few studies reported on the association between the inclusion of social media features and intervention effect. A taxonomy of social media features used in behavioral interventions has been presented with 36 social media features organized under 7 high-level categories. The taxonomy has been used to guide the analysis of this review. Although social media features are commonly included in DBCIs, there is an acute lack of information with respect to their effect on outcomes and a lack of clear guidance to inform the selection process based on the features' suitability for the different behaviors. The proposed taxonomy along with the set of recommendations included in this review will support future research aimed

Modeling Autistic Features in Animals

PubMed Central

Patterson, Paul H.

2011-01-01

A variety of features of autism can be simulated in rodents, including the core behavioral hallmarks of stereotyped and repetitive behaviors, and deficits in social interaction and communication. Other behaviors frequently found in autism spectrum disorders (ASD) such as neophobia, enhanced anxiety, abnormal pain sensitivity and eye blink conditioning, disturbed sleep patterns, seizures, and deficits in sensorimotor gating are also present in some of the animal models. Neuropathology and some characteristic neurochemical changes that are frequently seen in autism, as well as alterations in the immune status in the brain and periphery are also found in some of the models. Several known environmental risk factors for autism have been successfully established in rodents, including maternal infection and maternal valproate administration. Also under investigation are a number of mouse models based on genetic variants associated with autism or on syndromic disorders with autistic features. This review briefly summarizes recent developments in this field, highlighting models with face and/or construct validity, and noting the potential for investigation of pathogenesis and early progress towards clinical testing of potential therapeutics. Wherever possible, reference is made to reviews rather than primary articles. PMID:21289542

Limb/pelvis hypoplasia/aplasia with skull defect (Schinzel phocomelia): distinctive features and prenatal detection.

PubMed

Olney, R S; Hoyme, H E; Roche, F; Ferguson, K; Hintz, S; Madan, A

2001-11-01

Schinzel phocomelia syndrome is characterized by limb/pelvis hypoplasia/aplasia: specifically, intercalary limb deficiencies and absent or hypoplastic pelvic bones. The phenotype is similar to that described in a related multiple malformation syndrome known as Al-Awadi/Raas-Rothschild syndrome. The additional important feature of large parietooccipital skull defects without meningocele, encephalocele, or other brain malformation has thus far been reported only in children with Schinzel phocomelia syndrome. We recently evaluated a boy affected with Schinzel phocomelia born to nonconsanguineous healthy parents of Mexican origin. A third-trimester fetal ultrasound scan showed severe limb deficiencies and an absent pelvis. The infant died shortly after birth. Dysmorphology examination, radiographs, and autopsy revealed quadrilateral intercalary limb deficiencies with preaxial toe polydactyly; an absent pelvis and a 7 x 3-cm skull defect; and extraskeletal anomalies including microtia, telecanthus, micropenis with cryptorchidism, renal cysts, stenosis of the colon, and a cleft alveolar ridge. A normal 46,XY karyotype was demonstrated, and autosomal recessive inheritance was presumed on the basis of previously reported families. This case report emphasizes the importance of recognizing severe pelvic and skull deficiencies (either post- or prenatally) in differentiating infants with Schinzel phocomelia from other multiple malformation syndromes that feature intercalary limb defects, including thalidomide embryopathy and Roberts-SC phocomelia. Copyright 2001 Wiley-Liss, Inc.

Clinico-radiological features of subarachnoid hyperintensity on diffusion-weighted images in patients with meningitis.

PubMed

Kawaguchi, T; Sakurai, K; Hara, M; Muto, M; Nakagawa, M; Tohyama, J; Oguri, T; Mitake, S; Maeda, M; Matsukawa, N; Ojika, K; Shibamoto, Y

2012-04-01

To investigate the clinical and radiological features of meningitis with subarachnoid diffusion-weighted imaging (DWI) hyperintensity. The clinical features, laboratory data, and radiological findings, including the number and distribution of subarachnoid DWI hyperintense lesions and other radiological abnormalities, of 18 patients seen at five institutions were evaluated. The patients consisted of eight males and 10 females, whose ages ranged from 4 months to 82 years (median 65 years). Causative organisms were bacteria in 15 patients, including Haemophilus influenzae, Streptococcus pneumoniae, Streptococcus agalactiae, Staphylococcus aureus, Klebsiella pneumoniae, and Listeria monocytogenes. The remaining three were fungal meningitis caused by Cryptococcus neoformans. Subarachnoid DWI hyperintense lesions were multiple in 16 of the 18 cases (89%) and predominantly distributed around the frontal lobe in 16 of the 18 cases (89%). In addition to subarachnoid abnormality, subdural empyema, cerebral infarction, and intraventricular empyema were found in 50, 39, and 39%, respectively. Compared with paediatric patients, adult patients with bacterial meningitis tended to have poor prognoses (7/10 versus 1/5; p = 0.1). Both bacterial and fungal meningitis could cause subarachnoid hyperintensity on DWI, predominantly around the frontal lobe. This finding is often associated with poor prognosis in adult bacterial meningitis. Copyright © 2011 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Characterizing the effects of feature salience and top-down attention in the early visual system.

PubMed

Poltoratski, Sonia; Ling, Sam; McCormack, Devin; Tong, Frank

2017-07-01

The visual system employs a sophisticated balance of attentional mechanisms: salient stimuli are prioritized for visual processing, yet observers can also ignore such stimuli when their goals require directing attention elsewhere. A powerful determinant of visual salience is local feature contrast: if a local region differs from its immediate surround along one or more feature dimensions, it will appear more salient. We used high-resolution functional MRI (fMRI) at 7T to characterize the modulatory effects of bottom-up salience and top-down voluntary attention within multiple sites along the early visual pathway, including visual areas V1-V4 and the lateral geniculate nucleus (LGN). Observers viewed arrays of spatially distributed gratings, where one of the gratings immediately to the left or right of fixation differed from all other items in orientation or motion direction, making it salient. To investigate the effects of directed attention, observers were cued to attend to the grating to the left or right of fixation, which was either salient or nonsalient. Results revealed reliable additive effects of top-down attention and stimulus-driven salience throughout visual areas V1-hV4. In comparison, the LGN exhibited significant attentional enhancement but was not reliably modulated by orientation- or motion-defined salience. Our findings indicate that top-down effects of spatial attention can influence visual processing at the earliest possible site along the visual pathway, including the LGN, whereas the processing of orientation- and motion-driven salience primarily involves feature-selective interactions that take place in early cortical visual areas. NEW & NOTEWORTHY While spatial attention allows for specific, goal-driven enhancement of stimuli, salient items outside of the current focus of attention must also be prioritized. We used 7T fMRI to compare salience and spatial attentional enhancement along the early visual hierarchy. We report additive effects of

17 CFR 230.408 - Additional information.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 17 Commodity and Securities Exchanges 2 2013-04-01 2013-04-01 false Additional information. 230... RULES AND REGULATIONS, SECURITIES ACT OF 1933 General Requirements § 230.408 Additional information. (a) In addition to the information expressly required to be included in a registration statement, there...

Factors that affect micro-tooling features created by direct printing approach

NASA Astrophysics Data System (ADS)

Kumbhani, Mayur N.

Current market required faster pace production of smaller, better, and improved products in shorter amount of time. Traditional high-rate manufacturing process such as hot embossing, injection molding, compression molding, etc. use tooling to replicate feature on a products. Miniaturization of many product in the field of biomedical, electronics, optical, and microfluidic is occurring on a daily bases. There is a constant need to produce cheaper, and faster tooling, which can be utilize by existing manufacturing processes. Traditionally, in order to manufacture micron size tooling features processes such as micro-machining, Electrical Discharge Machining (EDM), etc. are utilized. Due to a higher difficulty to produce smaller size features, and longer production cycle time, various additive manufacturing approaches are proposed, e.g. selective laser sintering (SLS), inkjet printing (3DP), fused deposition modeling (FDM), etc. were proposed. Most of these approaches can produce net shaped products from different materials such as metal, ceramic, or polymers. Several attempts were made to produce tooling features using additive manufacturing approaches. Most of these produced tooling were not cost effective, and the life cycle of these tooling was reported short. In this research, a method to produce tooling features using direct printing approach, where highly filled feedstock was dispensed on a substrate. This research evaluated different natural binders, such as guar gum, xanthan gum, and sodium carboxymethyl cellulose (NaCMC) and their combinations were evaluated. The best binder combination was then use to evaluate effect of different metal (316L stainless steel (3 mum), 316 stainless steel (45 mum), and 304 stainless steel (45 mum)) particle size on feature quality. Finally, the effect of direct printing process variables such as dispensing tip internal diameter (500 mum, and 333 mum) at different printing speeds were evaluated.

Role of Importance and Distinctiveness of Semantic Features in People with Aphasia: A Replication Study

ERIC Educational Resources Information Center

Mason-Baughman, Mary Beth; Wallace, Sarah E.

2014-01-01

Previous studies suggest that people with aphasia have incomplete lexical-semantic representations with decreased low-importance distinctive (LID) feature knowledge. In addition, decreased LID feature knowledge correlates with ability to discriminate among semantically related words. The current study seeks to replicate and extend previous…

Defeating feature fatigue.

PubMed

Rust, Roland T; Thompson, Debora Viana; Hamilton, Rebecca W

2006-02-01

Consider a coffeemaker that offers 12 drink options, a car with more than 700 features on the dashboard, and a mouse pad that's also a clock, calculator, and FM radio. All are examples of "feature bloat", or "featuritis", the result of an almost irresistible temptation to load products with lots of bells and whistles. The problem is that the more features a product boasts, the harder it is to use. Manufacturers that increase a product's capability--the number of useful functions it can perform--at the expense of its usability are exposing their customers to feature fatigue. The authors have conducted three studies to gain a better understanding of how consumers weigh a product's capability relative to its usability. They found that even though consumers know that products with more features are harder to use, they initially choose high-feature models. They also pile on more features when given the chance to customize a product for their needs. Once consumers have actually worked with a product, however, usability starts to matter more to them than capability. For managers in consumer products companies, these findings present a dilemma: Should they maximize initial sales by designing high-feature models, which consumers consistently choose, or should they limit the number of features in order to enhance the lifetime value of their customers? The authors' analytical model guides companies toward a happy middle ground: maximizing the net present value of the typical customer's profit stream. The authors also advise companies to build simpler products, help consumers learn which products suit their needs, develop products that do one thing very well, and design market research in which consumers use actual products or prototypes.

Comparative study of palm print authentication system using geometric features

NASA Astrophysics Data System (ADS)

Shreyas, Kamath K. M.; Rajeev, Srijith; Panetta, Karen; Agaian, Sos S.

2017-05-01

Biometrics, particularly palm print authentication has been a stimulating research area due to its abundance of features. Stable features and effective matching are the most crucial steps for an authentication system. In conventional palm print authentication systems, matching is based on flexion creases, friction ridges, and minutiae points. Currently, contactless palm print imaging is an emerging technology. However, they tend to involve fluctuations in the image quality and texture loss due to factors such as varying illumination conditions, occlusions, noise, pose, and ghosting. These variations decrease the performance of the authentication systems. Furthermore, real-time palm print authentication in large databases continue to be a challenging task. In order to effectively solve these problems, features which are invariant to these anomalies are required. This paper proposes a robust palm print matching framework by making a comparative study of different local geometric features such as Difference-of-Gaussian, Hessian, Hessian-Laplace, Harris-Laplace, and Multiscale Harris for feature detection. These detectors are coupled with Scale Invariant Feature Transformation (SIFT) descriptor to describe the identified features. Additionally, a two-stage refinement process is carried out to obtain the best stable matches. Computer simulations demonstrate that the accuracy of the system has increased effectively with an EER of 0.86% when Harris-Laplace detector is used on IITD database.

Orofacial manual therapy improves cervical movement impairment associated with headache and features of temporomandibular dysfunction: a randomized controlled trial.

PubMed

von Piekartz, Harry; Hall, Toby

2013-08-01

There is evidence that temporomandibular disorder (TMD) may be a contributing factor to cervicogenic headache (CGH), in part because of the influence of dysfunction of the temporomandibular joint on the cervical spine. The purpose of this randomized controlled trial was to determine whether orofacial treatment in addition to cervical manual therapy, was more effective than cervical manual therapy alone on measures of cervical movement impairment in patients with features of CGH and signs of TMD. In this study, 43 patients (27 women) with headache for more than 3-months and with some features of CGH and signs of TMD were randomly assigned to receive either cervical manual therapy (usual care) or orofacial manual therapy to address TMD in addition to usual care. Subjects were assessed at baseline, after 6 treatment sessions (3-months), and at 6-months follow-up. 38 subjects (25 female) completed all analysis at 6-months follow-up. The outcome criteria were: cervical range of movement (including the C1-2 flexion-rotation test) and manual examination of the upper 3 cervical vertebra. The group that received orofacial treatment in addition to usual care showed significant reduction in all aspects of cervical impairment after the treatment period. These improvements persisted to the 6-month follow-up, but were not observed in the usual care group at any point. These observations together with previous reports indicate that manual therapists should look for features of TMD when examining patients with headache, particularly if treatment fails when directed to the cervical spine. Copyright © 2013. Published by Elsevier Ltd.

Features in Grocery Stores that Motivate Shoppers to Buy Healthier Foods, ConsumerStyles 2014.

PubMed

Moore, Latetia V; Pinard, Courtney A; Yaroch, Amy L

2016-08-01

We examined nine features in grocery stores shoppers reported motivated them to purchase more healthful foods in the past month. Features were compiled from common supermarket practices for each of the 4 Ps of marketing: pricing, placement, promotion, and product. We examined percentages of the features overall and by shopping frequency using Chi square tests from a 2014 cross sectional web-based health attitudes and behaviors survey, ConsumerStyles. The survey was fielded from June to July in 2014. Participants were part of a market research consumer panel that were randomly recruited by probability-based sampling using address-based sampling methods to achieve a sample representative of the U.S. Data from 4242 adults ages 18 and older were analyzed. About 44 % of respondents indicated at least one feature motivated them to purchase more healthful foods. Top choices included in-store coupons or specials (20.1 %), availability of convenient, ready-to-eat more healthful foods (18.8 %), product labels or advertising on packages (15.2 %), and labels or signs on shelves that highlighted more healthful options (14.6 %). Frequent shoppers reported being motivated to purchase more healthful foods by in-store tastings/recipe demonstrations and coupons/specials more often than infrequent shoppers. Enhancing the visibility and appeal of more healthful food items in grocery stores may help improve dietary choices in some populations but additional research is needed to identify the most effective strategies for interventions.

Features in grocery stores that motivate shoppers to buy healthier foods, ConsumerStyles 2014

PubMed Central

Moore, Latetia V; Pinard, Courtney A.; Yaroch, Amy L.

2016-01-01

Objective We examined nine features in grocery stores shoppers reported motivated them to purchase more healthful foods in the past month. Design Features were compiled from common supermarket practices for each of the 4 Ps of marketing: pricing, placement, promotion, and product. We examined percentages of the features overall and by shopping frequency using chi-square tests from a 2014 cross sectional web-based health attitudes and behaviors survey, ConsumerStyles. The survey was fielded from June to July in 2014. Setting Participants were part of a market research consumer panel that were randomly recruited by probability-based sampling using address-based sampling methods to achieve a sample representative of the U.S. population. Subjects Data from 4,242 adults ages 18 and older were analyzed. Results About 44% of respondents indicated at least one feature motivated them to purchase more healthful foods. Top choices included in-store coupons or specials (20.1%), availability of convenient, ready-to-eat more healthful foods (18.8%), product labels or advertising on packages (15.2%), and labels or signs on shelves that highlighted more healthful options (14.6%). Frequent shoppers reported being motivated to purchase more healthful foods by in-store tastings/recipe demonstrations and coupons/specials more often than infrequent shoppers. Conclusions Enhancing the visibility and appeal of more healthful food items in grocery stores may help improve dietary choices in some populations but additional research is needed to identify the most effective strategies for interventions. PMID:26831484

Identification of particle-laden flow features from wavelet decomposition

NASA Astrophysics Data System (ADS)

Jackson, A.; Turnbull, B.

2017-12-01

A wavelet decomposition based technique is applied to air pressure data obtained from laboratory-scale powder snow avalanches. This technique is shown to be a powerful tool for identifying both repeatable and chaotic features at any frequency within the signal. Additionally, this technique is demonstrated to be a robust method for the removal of noise from the signal as well as being capable of removing other contaminants from the signal. Whilst powder snow avalanches are the focus of the experiments analysed here, the features identified can provide insight to other particle-laden gravity currents and the technique described is applicable to a wide variety of experimental signals.

A geographic comparison of selected large-scale planetary surface features

NASA Technical Reports Server (NTRS)

Meszaros, S. P.

1984-01-01

Photographic and cartographic comparisons of geographic features on Mercury, the Moon, Earth, Mars, Ganymede, Callisto, Mimas, and Tethys are presented. Planetary structures caused by impacts, volcanism, tectonics, and other natural forces are included. Each feature is discussed individually and then those of similar origin are compared at the same scale.

A multi-approach feature extractions for iris recognition

NASA Astrophysics Data System (ADS)

Sanpachai, H.; Settapong, M.

2014-04-01

Biometrics is a promising technique that is used to identify individual traits and characteristics. Iris recognition is one of the most reliable biometric methods. As iris texture and color is fully developed within a year of birth, it remains unchanged throughout a person's life. Contrary to fingerprint, which can be altered due to several aspects including accidental damage, dry or oily skin and dust. Although iris recognition has been studied for more than a decade, there are limited commercial products available due to its arduous requirement such as camera resolution, hardware size, expensive equipment and computational complexity. However, at the present time, technology has overcome these obstacles. Iris recognition can be done through several sequential steps which include pre-processing, features extractions, post-processing, and matching stage. In this paper, we adopted the directional high-low pass filter for feature extraction. A box-counting fractal dimension and Iris code have been proposed as feature representations. Our approach has been tested on CASIA Iris Image database and the results are considered successful.

Neocentromeres and epigenetically inherited features of centromeres

PubMed Central

Burrack, Laura S.; Berman, Judith

2012-01-01

Neocentromeres are ectopic sites where new functional kinetochores assemble and permit chromosome segregation. Neocentromeres usually form following genomic alterations that remove or disrupt centromere function. The ability to form neocentromeres is conserved in eukaryotes ranging from fungi to mammals. Neocentromeres that rescue chromosome fragments in cells with gross chromosomal rearrangements are found in several types of human cancers, and in patients with developmental disabilities. In this review, we discuss the importance of neocentromeres to human health and evaluate recently developed model systems to study neocentromere formation, maintenance, and function in chromosome segregation. Additionally, studies of neocentromeres provide insight into native centromeres; analysis of neocentromeres found in human clinical samples and induced in model organisms distinguishes features of centromeres that are dependent on centromere DNA from features that are epigenetically inherited together with the formation of a functional kinetochore. PMID:22723125

Low complexity feature extraction for classification of harmonic signals

NASA Astrophysics Data System (ADS)

William, Peter E.

In this dissertation, feature extraction algorithms have been developed for extraction of characteristic features from harmonic signals. The common theme for all developed algorithms is the simplicity in generating a significant set of features directly from the time domain harmonic signal. The features are a time domain representation of the composite, yet sparse, harmonic signature in the spectral domain. The algorithms are adequate for low-power unattended sensors which perform sensing, feature extraction, and classification in a standalone scenario. The first algorithm generates the characteristic features using only the duration between successive zero-crossing intervals. The second algorithm estimates the harmonics' amplitudes of the harmonic structure employing a simplified least squares method without the need to estimate the true harmonic parameters of the source signal. The third algorithm, resulting from a collaborative effort with Daniel White at the DSP Lab, University of Nebraska-Lincoln, presents an analog front end approach that utilizes a multichannel analog projection and integration to extract the sparse spectral features from the analog time domain signal. Classification is performed using a multilayer feedforward neural network. Evaluation of the proposed feature extraction algorithms for classification through the processing of several acoustic and vibration data sets (including military vehicles and rotating electric machines) with comparison to spectral features shows that, for harmonic signals, time domain features are simpler to extract and provide equivalent or improved reliability over the spectral features in both the detection probabilities and false alarm rate.

Ceres' deformational surface features compared to other planetary bodies.

NASA Astrophysics Data System (ADS)

von der Gathen, Isabel; Jaumann, Ralf; Krohn, Katrin; Buczkowski, Debra L.; Elgner, Stephan; Kersten, Elke; Matz, Klaus-Dieter; Nass, Andrea; Otto, Katharina; Preusker, Frank; Roatsch, Thomas; Schröder, Stefanus E.; Schulzeck, Franziska; Stephan, Katrin; Wagner, Roland; De Sanctis, Maria C.; Schenk, Paul; Scully, Jennifer E. C.; Williams, Dave A.; Raymond, Carol A.

2016-04-01

On March 2015, NASA's Dawn spacecraft arrived at the dwarf planet Ceres and has been providing images of its surface. Based on High Altitude Mapping Orbiter (HAMO) clear filter images (140 m/px res.), a Survey mosaic (~400 m/px) and a series of Low Altitude Mapping Orbiter (LAMO) clear filter images (35 m/px) of the Dawn mission [1], deformational features are identified on the surface of Ceres. In order to further our knowledge about the nature and origin of these features, we start a comparative analysis of similar features on different planetary bodies, like Enceladus, Ganymede and the Moon, based on images provided by the Cassini, Galileo and Lunar Orbiter mission. This study focuses on the small scale fractures, mostly located on Ceres' crater floors, in comparison with crater fractures on the planetary bodies named above. The fractures were analyzed concerning the morphology and shape, the distribution, orientation and possible building mechanisms. On Ceres, two different groups of fractures are distinct. The first one includes fractures, normally arranged in subparallel pattern, which are usually located on crater floors, but also on crater rims. Their sense of direction is relatively uniform but in some cases they get deformed by shearing. The second group consists of joint systems, which spread out of one single location, sometimes arranged concentric to the crater rim. They were likely formed by cooling-melting processes linked to the impact process or up doming material. Fractures located on crater floors are also common on the icy satellite Enceladus [3]. While Enceladus' fractures don't seem to have a lot in common compared to those on Ceres, we assume that similar fracture patterns and therefore similar building mechanism can be found e.g. on Ganymede and especially on the Moon [2]. Further work will include the comparison of the fractures with additional planetary bodies and the trial to explain why fracturing e.g. on Enceladus differs from that on

A Ruby API to query the Ensembl database for genomic features.

PubMed

Strozzi, Francesco; Aerts, Jan

2011-04-01

The Ensembl database makes genomic features available via its Genome Browser. It is also possible to access the underlying data through a Perl API for advanced querying. We have developed a full-featured Ruby API to the Ensembl databases, providing the same functionality as the Perl interface with additional features. A single Ruby API is used to access different releases of the Ensembl databases and is also able to query multi-species databases. Most functionality of the API is provided using the ActiveRecord pattern. The library depends on introspection to make it release independent. The API is available through the Rubygem system and can be installed with the command gem install ruby-ensembl-api.

47 CFR 79.109 - Activating accessibility features.

Code of Federal Regulations, 2014 CFR

2014-10-01

... ACCESSIBILITY OF VIDEO PROGRAMMING Apparatus § 79.109 Activating accessibility features. (a) Requirements... video programming transmitted in digital format simultaneously with sound, including apparatus designed to receive or display video programming transmitted in digital format using Internet protocol, with...

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Robust Feature Selection Technique using Rank Aggregation.

PubMed

Sarkar, Chandrima; Cooley, Sarah; Srivastava, Jaideep

2014-01-01

Although feature selection is a well-developed research area, there is an ongoing need to develop methods to make classifiers more efficient. One important challenge is the lack of a universal feature selection technique which produces similar outcomes with all types of classifiers. This is because all feature selection techniques have individual statistical biases while classifiers exploit different statistical properties of data for evaluation. In numerous situations this can put researchers into dilemma as to which feature selection method and a classifiers to choose from a vast range of choices. In this paper, we propose a technique that aggregates the consensus properties of various feature selection methods to develop a more optimal solution. The ensemble nature of our technique makes it more robust across various classifiers. In other words, it is stable towards achieving similar and ideally higher classification accuracy across a wide variety of classifiers. We quantify this concept of robustness with a measure known as the Robustness Index (RI). We perform an extensive empirical evaluation of our technique on eight data sets with different dimensions including Arrythmia, Lung Cancer, Madelon, mfeat-fourier, internet-ads, Leukemia-3c and Embryonal Tumor and a real world data set namely Acute Myeloid Leukemia (AML). We demonstrate not only that our algorithm is more robust, but also that compared to other techniques our algorithm improves the classification accuracy by approximately 3-4% (in data set with less than 500 features) and by more than 5% (in data set with more than 500 features), across a wide range of classifiers.

A human performance evaluation of graphic symbol-design features.

PubMed

Samet, M G; Geiselman, R E; Landee, B M

1982-06-01

16 subjects learned each of two tactical display symbol sets (conventional symbols and iconic symbols) in turn and were then shown a series of graphic displays containing various symbol configurations. For each display, the subject was asked questions corresponding to different behavioral processes relating to symbol use (identification, search, comparison, pattern recognition). The results indicated that: (a) conventional symbols yielded faster pattern-recognition performance than iconic symbols, and iconic symbols did not yield faster identification than conventional symbols, and (b) the portrayal of additional feature information (through the use of perimeter density or vector projection coding) slowed processing of the core symbol information in four tasks, but certain symbol-design features created less perceptual interference and had greater correspondence with the portrayal of specific tactical concepts than others. The results were discussed in terms of the complexities involved in the selection of symbol design features for use in graphic tactical displays.

Estimating Missing Features to Improve Multimedia Information Retrieval

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

Bagherjeiran, A; Love, N S; Kamath, C

Retrieval in a multimedia database usually involves combining information from different modalities of data, such as text and images. However, all modalities of the data may not be available to form the query. The retrieval results from such a partial query are often less than satisfactory. In this paper, we present an approach to complete a partial query by estimating the missing features in the query. Our experiments with a database of images and their associated captions show that, with an initial text-only query, our completion method has similar performance to a full query with both image and text features.more » In addition, when we use relevance feedback, our approach outperforms the results obtained using a full query.« less

New Features in the ADS Abstract Service

NASA Astrophysics Data System (ADS)

Eichhorn, G.; Accomazzi, A.; Grant, C. S.; Kurtz, M. J.; ReyBacaicoa, V.; Murray, S. S.

2001-11-01

The ADS Abstract Service contains over 2.3 million references in four databases: Astronomy/Astrophysics/Planetary Sciences, Instrumentation, Physics/Geophysics, and Preprints. We provide abstracts and articles free to the astronomical community for all major and many smaller astronomy journals, PhD theses, conference proceedings, and technical reports. These four databases can be queried either separately of jointly. The ADS also has scanned 1.3 million pages in 180,000 articles in the ADS Article Service. This literature archive contains all major Astronomy journals and many smaller journals, as well as conference proceedings, including the abstract books from all the LPSCs back to volume 2. A new feature gives our users the ability to see list of articles that were also read by the readers of a given article. This is a powerful tool to find out what current articles are relevant in a particular field of study. We have recently expanded the citation and reference query capabilities. It allows our users to select papers for which they want to see references or citations and then retrieve these citations/references. Another new capability is the ability to sort a list of articles by their citation count. As usual, users should be reminded that the citations in ADS are incomplete because we do not obtain reference lists from all publishers. In addition, we cannot match all references (e.g. in press, private communications, author errors, some conference papers, etc.). Anyone using the citations for analysis of publishing records should keep this in mind. More work on expanding the citation and reference features is planned over the next year. ADS Home Page http://ads.harvard.edu/

Asymmetric Michael Addition Mediated by Chiral Ionic Liquids

PubMed Central

Suzuki, Yumiko

2018-01-01

Chiral ionic liquids with a focus on their applications in asymmetric Michael additions and related reactions were reviewed. The examples were classified on the basis of the mode of asymmetric induction (e.g., external induction/non-covalent interaction or internal induction/covalent bond formation), the roles in reactions (as a solvent or catalyst), and their structural features (e.g., imidazolium-based chiral cations, other chiral oniums; proline derivatives). Most of the reactions with high chiral induction are Michael addition of ketones or aldehydes to chalcones or nitrostyrenes where proline-derived chiral ionic liquids catalyze the reaction through enamine/ iminium formation. Many reports demonstrate the recyclability of ionic liquid-tagged pyrrolidines. PMID:29861702

Ultrasonic assessment of additive manufactured Ti-6Al-4V

NASA Astrophysics Data System (ADS)

Schehl, Norman; Kramb, Vicki; Dierken, Josiah; Aldrin, John; Schwalbach, Edwin; John, Reji

2018-04-01

Additive Manufacturing (AM) processes offer the potential for manufacturing cost savings and rapid insertion into service through production of near net shape components for complicated structures. Use of these parts in high reliability applications such as those in the aerospace industry will require nondestructive characterization methods to ensure post-process material quality in as-built condition. Ultrasonic methods can be used for this quality verification. Depending on the application, the service life of AM components can be sensitive to the part surface condition. The surface roughness and layered structure inherent to the electron-beam powder-bed fusion process necessitates new approaches to evaluate subsurface material integrity in its presence. Experimental methods and data analytics may improve the evaluation of as-built additively manufactured materials. This paper discusses the assessment of additively manufactured EBM Ti-6Al-4V panels using ultrasonic methods and the data analytics applied to evaluate material integrity. The assessment was done as an exploratory study as the discontinuities of interest in these test samples were not known when the measurements were performed. Water immersion ultrasonic techniques, including pulse-echo and through transmission with 10 MHz focused transducers, were used to explore the material integrity of as-built plates. Subsequent destructive mechanical tests of specimens extracted from the plates provided fracture locations indicating critical flaws. To further understand the effect of surface-roughness, an evaluation of ultrasonic response in the presence of as-built surfaces and with the surface removed was performed. The assessment of additive manufactured EBM Ti-6Al-4V panels with ultrasonic techniques indicated that ultrasonic energy was attenuated by the as-built surface roughness. In addition, feature detection was shown to be sensitive to experimental ultrasonic parameters and flaw morphology.

Which ante mortem clinical features predict progressive supranuclear palsy pathology?

PubMed

Respondek, Gesine; Kurz, Carolin; Arzberger, Thomas; Compta, Yaroslau; Englund, Elisabet; Ferguson, Leslie W; Gelpi, Ellen; Giese, Armin; Irwin, David J; Meissner, Wassilios G; Nilsson, Christer; Pantelyat, Alexander; Rajput, Alex; van Swieten, John C; Troakes, Claire; Josephs, Keith A; Lang, Anthony E; Mollenhauer, Brit; Müller, Ulrich; Whitwell, Jennifer L; Antonini, Angelo; Bhatia, Kailash P; Bordelon, Yvette; Corvol, Jean-Christophe; Colosimo, Carlo; Dodel, Richard; Grossman, Murray; Kassubek, Jan; Krismer, Florian; Levin, Johannes; Lorenzl, Stefan; Morris, Huw; Nestor, Peter; Oertel, Wolfgang H; Rabinovici, Gil D; Rowe, James B; van Eimeren, Thilo; Wenning, Gregor K; Boxer, Adam; Golbe, Lawrence I; Litvan, Irene; Stamelou, Maria; Höglinger, Günter U

2017-07-01

Progressive supranuclear palsy (PSP) is a neuropathologically defined disease presenting with a broad spectrum of clinical phenotypes. To identify clinical features and investigations that predict or exclude PSP pathology during life, aiming at an optimization of the clinical diagnostic criteria for PSP. We performed a systematic review of the literature published since 1996 to identify clinical features and investigations that may predict or exclude PSP pathology. We then extracted standardized data from clinical charts of patients with pathologically diagnosed PSP and relevant disease controls and calculated the sensitivity, specificity, and positive predictive value of key clinical features for PSP in this cohort. Of 4166 articles identified by the database inquiry, 269 met predefined standards. The literature review identified clinical features predictive of PSP, including features of the following 4 functional domains: ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. No biomarker or genetic feature was found reliably validated to predict definite PSP. High-quality original natural history data were available from 206 patients with pathologically diagnosed PSP and from 231 pathologically diagnosed disease controls (54 corticobasal degeneration, 51 multiple system atrophy with predominant parkinsonism, 53 Parkinson's disease, 73 behavioral variant frontotemporal dementia). We identified clinical features that predicted PSP pathology, including phenotypes other than Richardson's syndrome, with varying sensitivity and specificity. Our results highlight the clinical variability of PSP and the high prevalence of phenotypes other than Richardson's syndrome. The features of variant phenotypes with high specificity and sensitivity should serve to optimize clinical diagnosis of PSP. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Enterocolic lymphocytic phlebitis: clinicopathologic features and review of the literature.

PubMed

Ngo, Nyethane; Chang, Fuju

2007-07-01

Enterocolic lymphocytic phlebitis (ELP) is a recently described entity and is of unknown etiology and pathogenesis. It is characterized by phlebitis of the bowel wall and mesentery, without arterial involvement or evidence of systemic vasculitis. The clinical presentation of ELP is varied, but it most commonly manifests with signs of an acute abdomen. Clinical, radiologic, and endoscopic findings are often conflicting and misdiagnosis is common as venous thrombosis is not suspected. The diagnosis of ELP is obtained histologically. There is a spectrum of histologic features associated with ELP, which includes lymphocytic phlebitis, necrotizing phlebitis, granulomatous phlebitis, and myointimal hyperplasia. Other features include venous thrombi and acute ischemic changes of the intestine. Surgical resection of the affected bowel is usually curative and recurrences are rare. The clinical and histopathologic features of ELP are reviewed.

Nanoparticles for Cardiovascular Imaging and Therapeutic Delivery, Part 1: Compositions and Features.

PubMed

Stendahl, John C; Sinusas, Albert J

2015-10-01

Imaging agents made from nanoparticles are functionally versatile and have unique properties that may translate to clinical utility in several key cardiovascular imaging niches. Nanoparticles exhibit size-based circulation, biodistribution, and elimination properties different from those of small molecules and microparticles. In addition, nanoparticles provide versatile platforms that can be engineered to create both multimodal and multifunctional imaging agents with tunable properties. With these features, nanoparticulate imaging agents can facilitate fusion of high-sensitivity and high-resolution imaging modalities and selectively bind tissues for targeted molecular imaging and therapeutic delivery. Despite their intriguing attributes, nanoparticulate imaging agents have thus far achieved only limited clinical use. The reasons for this restricted advancement include an evolving scope of applications, the simplicity and effectiveness of existing small-molecule agents, pharmacokinetic limitations, safety concerns, and a complex regulatory environment. This review describes general features of nanoparticulate imaging agents and therapeutics and discusses challenges associated with clinical translation. A second, related review to appear in a subsequent issue of JNM highlights nuclear-based nanoparticulate probes in preclinical cardiovascular imaging. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Subsurface structures of buried features in the lunar Procellarum region

NASA Astrophysics Data System (ADS)

Wang, Wenrui; Heki, Kosuke

2017-07-01

The Gravity Recovery and Interior Laboratory (GRAIL) mission unraveled numbers of features showing strong gravity anomalies without prominent topographic signatures in the lunar Procellarum region. These features, located in different geologic units, are considered to have complex subsurface structures reflecting different evolution processes. By using the GRAIL level-1 data, we estimated the free-air and Bouguer gravity anomalies in several selected regions including such intriguing features. With the three-dimensional inversion technique, we recovered subsurface density structures in these regions.

Image processing tool for automatic feature recognition and quantification

DOEpatents

Chen, Xing; Stoddard, Ryan J.

2017-05-02

A system for defining structures within an image is described. The system includes reading of an input file, preprocessing the input file while preserving metadata such as scale information and then detecting features of the input file. In one version the detection first uses an edge detector followed by identification of features using a Hough transform. The output of the process is identified elements within the image.

Seismic features of Winnipegosis mounds in Saskatchewan

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

Gendzwill, D.J.

1988-07-01

The Winnipegosis Formation of southern Saskatchewan is characterized by reefs or reeflike mounds in its upper member. Several characteristic features of the mounds permit their identification from seismic-reflection data. These features include reflections from the flanks of the mound, a change in the reflection continuity in the middle and base of the mound, a velocity pullup under the mound, and subsidence of strata over the mound. Dissolution of the salt which surrounds the mounds sometimes occurs, resulting in a drape structure. Some or all of these features may be present at the correct seismic stratigraphic level for Winnipegosis mounds, dependingmore » on the local conditions. Subsidence of strata over the mounds indicates compaction and porosity loss from the original mound or possibly the degree of dolomitization or pressure dissolution. Salt-removal features over or adjacent to the mounds indicate fluid movements. Approximate ages can be estimated from stratigraphic thinning and thickening relationships above such features. Complications in identifying Winnipegosis mounds may arise from thin-bed effects if the mounds are not very thick compared to a seismic wavelength. Confusion may also arise from anhydrite, which may encase the mounds or which may form a thick horizontal layer at the tops of the mounds, causing an interfering signal.« less

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder

PubMed Central

Taniguchi, Tadahiro; Takenaka, Kazuhito; Bando, Takashi

2018-01-01

Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant information can be expected to complicate the data analysis, e.g., more factors need to be analyzed; even varying the levels of redundancy can influence the results of the analysis. We assume that the measured multi-dimensional sensor time-series data of driving behavior are generated from low-dimensional data shared by the many types of one-dimensional data of which multi-dimensional time-series data are composed. Meanwhile, sensor time-series data may be defective because of sensor failure. Therefore, another important function is to reduce the negative effect of defective data when extracting low-dimensional time-series data. This study proposes a defect-repairable feature extraction method based on a deep sparse autoencoder (DSAE) to extract low-dimensional time-series data. In the experiments, we show that DSAE provides high-performance latent feature extraction for driving behavior, even for defective sensor time-series data. In addition, we show that the negative effect of defects on the driving behavior segmentation task could be reduced using the latent features extracted by DSAE. PMID:29462931

Aging and Developmental Disabilities. Feature Issue.

ERIC Educational Resources Information Center

Anderson, Deborah, Ed.; And Others

1993-01-01

This feature issue of a bulletin on community integration points out the challenge of making service systems more familiar with and responsive to the needs of older adults with developmental disabilities and their families. It includes articles with the following titles and authors: "Living on the Edge" (Arthur Campbell, Jr.); "Aging and…