The myositis autoantibody phenotypes of the juvenile idiopathic inflammatory myopathies.

PubMed

Rider, Lisa G; Shah, Mona; Mamyrova, Gulnara; Huber, Adam M; Rice, Madeline Murguia; Targoff, Ira N; Miller, Frederick W

2013-07-01

The juvenile idiopathic inflammatory myopathies (JIIM) are systemic autoimmune diseases characterized by skeletal muscle weakness, characteristic rashes, and other systemic features. In follow-up to our study defining the major clinical subgroup phenotypes of JIIM, we compared demographics, clinical features, laboratory measures, and outcomes among myositis-specific autoantibody (MSA) subgroups, as well as with published data on adult idiopathic inflammatory myopathy patients enrolled in a separate natural history study. In the present study, of 430 patients enrolled in a nationwide registry study who had serum tested for myositis autoantibodies, 374 had either a single specific MSA (n = 253) or no identified MSA (n = 121) and were the subject of the present report. Following univariate analysis, we used random forest classification and exact logistic regression modeling to compare autoantibody subgroups. Anti-p155/140 autoantibodies were the most frequent subgroup, present in 32% of patients with juvenile dermatomyositis (JDM) or overlap myositis with JDM, followed by anti-MJ autoantibodies, which were seen in 20% of JIIM patients, primarily in JDM. Other MSAs, including anti-synthetase, anti-signal recognition particle (SRP), and anti-Mi-2, were present in only 10% of JIIM patients. Features that characterized the anti-p155/140 autoantibody subgroup included Gottron papules, malar rash, "shawl-sign" rash, photosensitivity, cuticular overgrowth, lowest creatine kinase (CK) levels, and a predominantly chronic illness course. The features that differed for patients with anti-MJ antibodies included muscle cramps, dysphonia, intermediate CK levels, a high frequency of hospitalization, and a monocyclic disease course. Patients with anti-synthetase antibodies had higher frequencies of interstitial lung disease, arthralgia, and "mechanic's hands," and had an older age at diagnosis. The anti-SRP group, which had exclusively juvenile polymyositis, was characterized by high frequencies of black race, severe onset, distal weakness, falling episodes, Raynaud phenomenon, cardiac involvement, high CK levels, chronic disease course, frequent hospitalization, and wheelchair use. Characteristic features of the anti-Mi-2 subgroup included Hispanic ethnicity, classic dermatomyositis and malar rashes, high CK levels, and very low mortality. Finally, the most common features of patients without any currently defined MSA or myositis-associated autoantibodies included linear extensor erythema, arthralgia, and a monocyclic disease course. Several demographic and clinical features were shared between juvenile and adult idiopathic inflammatory myopathy subgroups, but with several important differences. We conclude that juvenile myositis is a heterogeneous group of illnesses with distinct autoantibody phenotypes defined by varying clinical and demographic characteristics, laboratory features, and outcomes.

The Myositis Autoantibody Phenotypes of the Juvenile Idiopathic Inflammatory Myopathies

PubMed Central

Shah, Mona; Mamyrova, Gulnara; Huber, Adam M.; Rice, Madeline Murguia; Targoff, Ira N.; Miller, Frederick W.

2013-01-01

Abstract The juvenile idiopathic inflammatory myopathies (JIIM) are systemic autoimmune diseases characterized by skeletal muscle weakness, characteristic rashes, and other systemic features. In follow-up to our study defining the major clinical subgroup phenotypes of JIIM, we compared demographics, clinical features, laboratory measures, and outcomes among myositis-specific autoantibody (MSA) subgroups, as well as with published data on adult idiopathic inflammatory myopathy patients enrolled in a separate natural history study. In the present study, of 430 patients enrolled in a nationwide registry study who had serum tested for myositis autoantibodies, 374 had either a single specific MSA (n = 253) or no identified MSA (n = 121) and were the subject of the present report. Following univariate analysis, we used random forest classification and exact logistic regression modeling to compare autoantibody subgroups. Anti-p155/140 autoantibodies were the most frequent subgroup, present in 32% of patients with juvenile dermatomyositis (JDM) or overlap myositis with JDM, followed by anti-MJ autoantibodies, which were seen in 20% of JIIM patients, primarily in JDM. Other MSAs, including anti-synthetase, anti-signal recognition particle (SRP), and anti-Mi-2, were present in only 10% of JIIM patients. Features that characterized the anti-p155/140 autoantibody subgroup included Gottron papules, malar rash, “shawl-sign” rash, photosensitivity, cuticular overgrowth, lowest creatine kinase (CK) levels, and a predominantly chronic illness course. The features that differed for patients with anti-MJ antibodies included muscle cramps, dysphonia, intermediate CK levels, a high frequency of hospitalization, and a monocyclic disease course. Patients with anti-synthetase antibodies had higher frequencies of interstitial lung disease, arthralgia, and “mechanic’s hands,” and had an older age at diagnosis. The anti-SRP group, which had exclusively juvenile polymyositis, was characterized by high frequencies of black race, severe onset, distal weakness, falling episodes, Raynaud phenomenon, cardiac involvement, high CK levels, chronic disease course, frequent hospitalization, and wheelchair use. Characteristic features of the anti-Mi-2 subgroup included Hispanic ethnicity, classic dermatomyositis and malar rashes, high CK levels, and very low mortality. Finally, the most common features of patients without any currently defined MSA or myositis-associated autoantibodies included linear extensor erythema, arthralgia, and a monocyclic disease course. Several demographic and clinical features were shared between juvenile and adult idiopathic inflammatory myopathy subgroups, but with several important differences. We conclude that juvenile myositis is a heterogeneous group of illnesses with distinct autoantibody phenotypes defined by varying clinical and demographic characteristics, laboratory features, and outcomes. PMID:23877355

WND-CHARM: Multi-purpose image classification using compound image transforms

PubMed Central

Orlov, Nikita; Shamir, Lior; Macura, Tomasz; Johnston, Josiah; Eckley, D. Mark; Goldberg, Ilya G.

2008-01-01

We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classification accuracy comparable to state-of-the-art task-specific image classifiers. The proposed image classifier first extracts a large set of 1025 image features including polynomial decompositions, high contrast features, pixel statistics, and textures. These features are computed on the raw image, transforms of the image, and transforms of transforms of the image. The feature values are then used to classify test images into a set of pre-defined image classes. This classifier was tested on several different problems including biological image classification and face recognition. Although we cannot make a claim of universality, our experimental results show that this classifier performs as well or better than classifiers developed specifically for these image classification tasks. Our classifier’s high performance on a variety of classification problems is attributed to (i) a large set of features extracted from images; and (ii) an effective feature selection and weighting algorithm sensitive to specific image classification problems. The algorithms are available for free download from openmicroscopy.org. PMID:18958301

Progress in nanoscale dry processes for fabrication of high-aspect-ratio features: How can we control critical dimension uniformity at the bottom?

NASA Astrophysics Data System (ADS)

Ishikawa, Kenji; Karahashi, Kazuhiro; Ishijima, Tatsuo; Cho, Sung Il; Elliott, Simon; Hausmann, Dennis; Mocuta, Dan; Wilson, Aaron; Kinoshita, Keizo

2018-06-01

In this review, we discuss the progress of emerging dry processes for nanoscale fabrication of high-aspect-ratio features, including emerging design technology for manufacturability. Experts in the fields of plasma processing have contributed to addressing the increasingly challenging demands of nanoscale deposition and etching technologies for high-aspect-ratio features. The discussion of our atomic-scale understanding of physicochemical reactions involving ion bombardment and neutral transport presents the major challenges shared across the plasma science and technology community. Focus is placed on advances in fabrication technology that control surface reactions on three-dimensional features, as well as state-of-the-art techniques used in semiconductor manufacturing with a brief summary of future challenges.

Image-Based 3D Face Modeling System

NASA Astrophysics Data System (ADS)

Park, In Kyu; Zhang, Hui; Vezhnevets, Vladimir

2005-12-01

This paper describes an automatic system for 3D face modeling using frontal and profile images taken by an ordinary digital camera. The system consists of four subsystems including frontal feature detection, profile feature detection, shape deformation, and texture generation modules. The frontal and profile feature detection modules automatically extract the facial parts such as the eye, nose, mouth, and ear. The shape deformation module utilizes the detected features to deform the generic head mesh model such that the deformed model coincides with the detected features. A texture is created by combining the facial textures augmented from the input images and the synthesized texture and mapped onto the deformed generic head model. This paper provides a practical system for 3D face modeling, which is highly automated by aggregating, customizing, and optimizing a bunch of individual computer vision algorithms. The experimental results show a highly automated process of modeling, which is sufficiently robust to various imaging conditions. The whole model creation including all the optional manual corrections takes only 2[InlineEquation not available: see fulltext.]3 minutes.

High-Sensitivity Ionization Trace-Species Detector

NASA Technical Reports Server (NTRS)

Bernius, Mark T.; Chutjian, Ara

1990-01-01

Features include high ion-extraction efficiency, compactness, and light weight. Improved version of previous ionization detector features in-line geometry that enables extraction of almost every ion from region of formation. Focusing electrodes arranged and shaped into compact system of space-charge-limited reversal electron optics and ion-extraction optics. Provides controllability of ionizing electron energies, greater efficiency of ionization, and nearly 100 percent ion-collection efficiency.

The World's Largest Photovoltaic Concentrator System.

ERIC Educational Resources Information Center

Smith, Harry V.

1982-01-01

The Mississippi County Community College large-scale energy experiment, featuring the emerging high technology of solar electricity, is described. The project includes a building designed for solar electricity and a power plant consisting of a total energy photovoltaic system, and features two experimental developments. (MLW)

What to do with thyroid nodules showing benign cytology and BRAF(V600E) mutation? A study based on clinical and radiologic features using a highly sensitive analytic method.

PubMed

Kim, Soo-Yeon; Kim, Eun-Kyung; Kwak, Jin Young; Moon, Hee Jung; Yoon, Jung Hyun

2015-02-01

BRAF(V600E) mutation analysis has been used as a complementary diagnostic tool to ultrasonography-guided, fine-needle aspiration (US-FNA) in the diagnosis of thyroid nodule with high specificity reported up to 100%. When highly sensitive analytic methods are used, however, false-positive results of BRAF(V600E) mutation analysis have been reported. In this study, we investigated the clinical, US features, and outcome of patients with thyroid nodules with benign cytology but positive BRAF(V600E) mutation using highly sensitive analytic methods from US-FNA. This study included 22 nodules in 22 patients (3 men, 19 women; mean age, 53 years) with benign cytology but positive BRAF(V600E) mutation from US-FNA. US features were categorized according to the internal components, echogenicity, margin, calcifications, and shape. Suspicious US features included markedly hypoechogenicity, noncircumscribed margins, micro or mixed calcifications, and nonparallel shape. Nodules were considered to have either concordant or discordant US features to benign cytology. Medical records and imaging studies were reviewed for final cytopathology results and outcomes during follow-up. Among the 22 nodules, 17 nodules were reviewed. Fifteen of 17 nodules were malignant, and 2 were benign. The benign nodules were confirmed as adenomatous hyperplasia with underlying lymphocytic thyroiditis and a fibrotic nodule with dense calcification. Thirteen of the 15 malignant nodules had 2 or more suspicious US features, and all 15 nodules were considered to have discordant cytology considering suspicious US features. Five nodules had been followed with US or US-FNA without resection, and did not show change in size or US features on follow-up US examinations. BRAF(V600E) mutation analysis is a highly sensitive diagnostic tool in the diagnosis of papillary thyroid carcinomas. In the management of thyroid nodules with benign cytology but positive BRAF(V600E) mutation, thyroidectomy should be considered in nodules which have 2 or more suspicious US features and are considered discordant on image-cytology correlation. Copyright © 2015 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Reverse engineering the face space: Discovering the critical features for face identification.

PubMed

Abudarham, Naphtali; Yovel, Galit

2016-01-01

How do we identify people? What are the critical facial features that define an identity and determine whether two faces belong to the same person or different people? To answer these questions, we applied the face space framework, according to which faces are represented as points in a multidimensional feature space, such that face space distances are correlated with perceptual similarities between faces. In particular, we developed a novel method that allowed us to reveal the critical dimensions (i.e., critical features) of the face space. To that end, we constructed a concrete face space, which included 20 facial features of natural face images, and asked human observers to evaluate feature values (e.g., how thick are the lips). Next, we systematically and quantitatively changed facial features, and measured the perceptual effects of these manipulations. We found that critical features were those for which participants have high perceptual sensitivity (PS) for detecting differences across identities (e.g., which of two faces has thicker lips). Furthermore, these high PS features vary minimally across different views of the same identity, suggesting high PS features support face recognition across different images of the same face. The methods described here set an infrastructure for discovering the critical features of other face categories not studied here (e.g., Asians, familiar) as well as other aspects of face processing, such as attractiveness or trait inferences.

Encoding properties of haltere neurons enable motion feature detection in a biological gyroscope

PubMed Central

Fox, Jessica L.; Fairhall, Adrienne L.; Daniel, Thomas L.

2010-01-01

The halteres of dipteran insects are essential sensory organs for flight control. They are believed to detect Coriolis and other inertial forces associated with body rotation during flight. Flies use this information for rapid flight control. We show that the primary afferent neurons of the haltere’s mechanoreceptors respond selectively with high temporal precision to multiple stimulus features. Although we are able to identify many stimulus features contributing to the response using principal component analysis, predictive models using only two features, common across the cell population, capture most of the cells’ encoding activity. However, different sensitivity to these two features permits each cell to respond to sinusoidal stimuli with a different preferred phase. This feature similarity, combined with diverse phase encoding, allows the haltere to transmit information at a high rate about numerous inertial forces, including Coriolis forces. PMID:20133721

Breast cancer Ki67 expression preoperative discrimination by DCE-MRI radiomics features

NASA Astrophysics Data System (ADS)

Ma, Wenjuan; Ji, Yu; Qin, Zhuanping; Guo, Xinpeng; Jian, Xiqi; Liu, Peifang

2018-02-01

To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are associated with Ki67 expression of breast cancer. In this institutional review board approved retrospective study, we collected 377 cases Chinese women who were diagnosed with invasive breast cancer in 2015. This cohort included 53 low-Ki67 expression (Ki67 proliferation index less than 14%) and 324 cases with high-Ki67 expression (Ki67 proliferation index more than 14%). A binary-classification of low- vs. high- Ki67 expression was performed. A set of 52 quantitative radiomics features, including morphological, gray scale statistic, and texture features, were extracted from the segmented lesion area. Three most common machine learning classification methods, including Naive Bayes, k-Nearest Neighbor and support vector machine with Gaussian kernel, were employed for the classification and the least absolute shrink age and selection operator (LASSO) method was used to select most predictive features set for the classifiers. Classification performance was evaluated by the area under receiver operating characteristic curve (AUC), accuracy, sensitivity and specificity. The model that used Naive Bayes classification method achieved the best performance than the other two methods, yielding 0.773 AUC value, 0.757 accuracy, 0.777 sensitivity and 0.769 specificity. Our study showed that quantitative radiomics imaging features of breast tumor extracted from DCE-MRI are associated with breast cancer Ki67 expression. Future larger studies are needed in order to further evaluate the findings.

Advanced RF and microwave functions based on an integrated optical frequency comb source.

PubMed

Xu, Xingyuan; Wu, Jiayang; Nguyen, Thach G; Shoeiby, Mehrdad; Chu, Sai T; Little, Brent E; Morandotti, Roberto; Mitchell, Arnan; Moss, David J

2018-02-05

We demonstrate advanced transversal radio frequency (RF) and microwave functions based on a Kerr optical comb source generated by an integrated micro-ring resonator. We achieve extremely high performance for an optical true time delay aimed at tunable phased array antenna applications, as well as reconfigurable microwave photonic filters. Our results agree well with theory. We show that our true time delay would yield a phased array antenna with features that include high angular resolution and a wide range of beam steering angles, while the microwave photonic filters feature high Q factors, wideband tunability, and highly reconfigurable filtering shapes. These results show that our approach is a competitive solution to implementing reconfigurable, high performance and potentially low cost RF and microwave signal processing functions for applications including radar and communication systems.

Space station power semiconductor package

NASA Technical Reports Server (NTRS)

Balodis, Vilnis; Berman, Albert; Devance, Darrell; Ludlow, Gerry; Wagner, Lee

1987-01-01

A package of high-power switching semiconductors for the space station have been designed and fabricated. The package includes a high-voltage (600 volts) high current (50 amps) NPN Fast Switching Power Transistor and a high-voltage (1200 volts), high-current (50 amps) Fast Recovery Diode. The package features an isolated collector for the transistors and an isolated anode for the diode. Beryllia is used as the isolation material resulting in a thermal resistance for both devices of .2 degrees per watt. Additional features include a hermetical seal for long life -- greater than 10 years in a space environment. Also, the package design resulted in a low electrical energy loss with the reduction of eddy currents, stray inductances, circuit inductance, and capacitance. The required package design and device parameters have been achieved. Test results for the transistor and diode utilizing the space station package is given.

A Real-Time Infrared Ultra-Spectral Signature Classification Method via Spatial Pyramid Matching

PubMed Central

Mei, Xiaoguang; Ma, Yong; Li, Chang; Fan, Fan; Huang, Jun; Ma, Jiayi

2015-01-01

The state-of-the-art ultra-spectral sensor technology brings new hope for high precision applications due to its high spectral resolution. However, it also comes with new challenges, such as the high data dimension and noise problems. In this paper, we propose a real-time method for infrared ultra-spectral signature classification via spatial pyramid matching (SPM), which includes two aspects. First, we introduce an infrared ultra-spectral signature similarity measure method via SPM, which is the foundation of the matching-based classification method. Second, we propose the classification method with reference spectral libraries, which utilizes the SPM-based similarity for the real-time infrared ultra-spectral signature classification with robustness performance. Specifically, instead of matching with each spectrum in the spectral library, our method is based on feature matching, which includes a feature library-generating phase. We calculate the SPM-based similarity between the feature of the spectrum and that of each spectrum of the reference feature library, then take the class index of the corresponding spectrum having the maximum similarity as the final result. Experimental comparisons on two publicly-available datasets demonstrate that the proposed method effectively improves the real-time classification performance and robustness to noise. PMID:26205263

Teacher Explanation of Physics Concepts: A Video Study

ERIC Educational Resources Information Center

Geelan, David

2013-01-01

Video recordings of Year 11 physics lessons were analyzed to identify key features of teacher explanations. Important features of the explanations used included teachers' ability to move between qualitative and quantitative modes of discussion, attention to what students require to succeed in high stakes examinations, thoughtful use of…

Activity Participation and Sensory Features among Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

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

2015-01-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

Mobile Phone Apps to Improve Medication Adherence: A Systematic Stepwise Process to Identify High-Quality Apps.

PubMed

Santo, Karla; Richtering, Sarah S; Chalmers, John; Thiagalingam, Aravinda; Chow, Clara K; Redfern, Julie

2016-12-02

There are a growing number of mobile phone apps available to support people in taking their medications and to improve medication adherence. However, little is known about how these apps differ in terms of features, quality, and effectiveness. We aimed to systematically review the medication reminder apps available in the Australian iTunes store and Google Play to assess their features and their quality in order to identify high-quality apps. This review was conducted in a similar manner to a systematic review by using a stepwise approach that included (1) a search strategy; (2) eligibility assessment; (3) app selection process through an initial screening of all retrieved apps and full app review of the included apps; (4) data extraction using a predefined set of features considered important or desirable in medication reminder apps; (5) analysis by classifying the apps as basic and advanced medication reminder apps and scoring and ranking them; and (6) a quality assessment by using the Mobile App Rating Scale (MARS), a reliable tool to assess mobile health apps. We identified 272 medication reminder apps, of which 152 were found only in Google Play, 87 only in iTunes, and 33 in both app stores. Apps found in Google Play had more customer reviews, higher star ratings, and lower cost compared with apps in iTunes. Only 109 apps were available for free and 124 were recently updated in 2015 or 2016. Overall, the median number of features per app was 3.0 (interquartile range 4.0) and only 18 apps had ≥9 of the 17 desirable features. The most common features were flexible scheduling that was present in 56.3% (153/272) of the included apps, medication tracking history in 54.8% (149/272), snooze option in 34.9% (95/272), and visual aids in 32.4% (88/272). We classified 54.8% (149/272) of the included apps as advanced medication reminder apps and 45.2% (123/272) as basic medication reminder apps. The advanced apps had a higher number of features per app compared with the basic apps. Using the MARS instrument, we were able to identify high-quality apps that were rated as being very interesting and entertaining, highly interactive and customizable, intuitive, and easy to use and to navigate as well as having a high level of visual appeal and good-quality information. Many medication reminder apps are available in the app stores; however, the majority of them did not have many of the desirable features and were, therefore, considered low quality. Through a systematic stepwise process, we were able to identify high-quality apps to be tested in a future study that will provide evidence on the use of medication reminder apps to improve medication adherence. ©Karla Santo, Sarah S Richtering, John Chalmers, Aravinda Thiagalingam, Clara K Chow, Julie Redfern. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 02.12.2016.

Mobile Phone Apps to Improve Medication Adherence: A Systematic Stepwise Process to Identify High-Quality Apps

PubMed Central

Richtering, Sarah S; Chalmers, John; Thiagalingam, Aravinda; Chow, Clara K; Redfern, Julie

2016-01-01

Background There are a growing number of mobile phone apps available to support people in taking their medications and to improve medication adherence. However, little is known about how these apps differ in terms of features, quality, and effectiveness. Objective We aimed to systematically review the medication reminder apps available in the Australian iTunes store and Google Play to assess their features and their quality in order to identify high-quality apps. Methods This review was conducted in a similar manner to a systematic review by using a stepwise approach that included (1) a search strategy; (2) eligibility assessment; (3) app selection process through an initial screening of all retrieved apps and full app review of the included apps; (4) data extraction using a predefined set of features considered important or desirable in medication reminder apps; (5) analysis by classifying the apps as basic and advanced medication reminder apps and scoring and ranking them; and (6) a quality assessment by using the Mobile App Rating Scale (MARS), a reliable tool to assess mobile health apps. Results We identified 272 medication reminder apps, of which 152 were found only in Google Play, 87 only in iTunes, and 33 in both app stores. Apps found in Google Play had more customer reviews, higher star ratings, and lower cost compared with apps in iTunes. Only 109 apps were available for free and 124 were recently updated in 2015 or 2016. Overall, the median number of features per app was 3.0 (interquartile range 4.0) and only 18 apps had ≥9 of the 17 desirable features. The most common features were flexible scheduling that was present in 56.3% (153/272) of the included apps, medication tracking history in 54.8% (149/272), snooze option in 34.9% (95/272), and visual aids in 32.4% (88/272). We classified 54.8% (149/272) of the included apps as advanced medication reminder apps and 45.2% (123/272) as basic medication reminder apps. The advanced apps had a higher number of features per app compared with the basic apps. Using the MARS instrument, we were able to identify high-quality apps that were rated as being very interesting and entertaining, highly interactive and customizable, intuitive, and easy to use and to navigate as well as having a high level of visual appeal and good-quality information. Conclusions Many medication reminder apps are available in the app stores; however, the majority of them did not have many of the desirable features and were, therefore, considered low quality. Through a systematic stepwise process, we were able to identify high-quality apps to be tested in a future study that will provide evidence on the use of medication reminder apps to improve medication adherence. PMID:27913373

CT of abdominal tuberculosis

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

Epstein, B.M.; Mann, J.H.

1982-11-01

Intraabdominal tuberculosis (TB) presents with a wide variety of clinical and radiologic features. Besides the reported computed tomographic (CT) finding of high-density ascites in tuberculous peritonitis, this report describes additional CT features highly suggestive of abdominal tuberculosis in eight cases: (1) irregular soft-tissue densities in the omental area; (2) low-density masses surrounded by thick solid rims; (3) a disorganized appearance of soft-tissue densities, fluid, and bowel loops forming a poorly defined mass; (4) low-density lymph nodes with a multilocular appearance after intravenous contrast administration; and (5) possibly high-density ascites. The differential diagnosis of these features include lymphoma, various forms ofmore » peritonitis, peritoneal carcinomatosis, and peritoneal mesothelioma. It is important that the CT features of intraabdominal tuberculosis be recognized in order that laparotomy be avoided and less invasive procedures (e.g., laparoscopy, biopsy, or a trial of antituberculous therapy) be instituted.« less

Clinicopathological features of gastric mucosa associated lymphoid tissue (MALT) lymphomas: high grade transformation and comparison with diffuse large B cell lymphomas without MALT lymphoma features

PubMed Central

Yoshino, T.; Omonishi, K.; Kobayashi, K.; Mannami, T.; Okada, H.; Mizuno, M.; Yamadori, I.; Kondo, E.; Akagi, T.

2000-01-01

Aims—To investigate the clinicopathological differences among gastric low grade MALT lymphomas (low MALT), large B cell lymphomas with low grade components (secondary high grade MALT lymphomas, high MALT), and diffuse large B cell lymphomas without low grade features (primary high grade MALT lymphomas, DLL). Methods—Clinicopathological and morphological characters of 126 gastric lymphoma cases were studied: 82 cases of low MALT lymphoma including 40 that were surgically resected, 17 cases of high MALT lymphoma including 13 surgically resected, and 27 cases of DLL including 12 surgically resected. Results—Age ranges were as follows: low MALT lymphoma, 34 to 85 years (mean 59.9); high MALT lymphoma, 53 to 88 years (mean 68.5); DLL, 29 to 83 years (mean 62.3). The average age for low and high MALT lymphomas was significantly different (p < 0.05), but there were no differences in other comparisons. There was a female predominance of low MALT lymphoma patients (female to male ratio, 47/35), while for high MALT patients the ratio was almost even (8/9), and for DLL patients there was a male predominance (11/16). Examination of surgically resected material showed that MALT lymphomas had a wider distribution in the gastric wall than DLL. Conclusions—The findings suggest that at least some of the high grade gastric lymphomas, especially in patients younger than the fifth decade, do not originate from high grade transformation of low MALT lymphomas. It seems to take about one decade at least for high grade transformation of low MALT lymphomas. Key Words: MALT lymphoma • stomach • transformation PMID:10823136

High temperature, high intensity solar array. [for Venus Radar Mapper mission

NASA Technical Reports Server (NTRS)

Smith, B. S.; Brooks, G. R.; Pinkerton, R.

1985-01-01

The solar array for the Venus Radar Mapper mission will operate in the high temperature, high intensity conditions of a low Venus orbit environment. To fulfill the performance requirements in this environment at minimum cost and mass while maximizing power density and packing factor on the panel surface, several features were introduced into the design. These features included the use of optical surface reflectors (OSR's) to reduce the operating temperature; new adhesives for conductive bonding of OSR's to avoid electrostatic discharges; custom-designed large area cells and novel shunt diode circuit and panel power harness configurations.

Slippery liquid-infused porous surfaces having improved stability

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

Aizenberg, Joanna; Vogel, Nicolas

Methods and articles disclosed herein relate to liquid repellant surfaces having selective wetting and transport properties. An article having a repellant surface includes a substrate comprising surface features with re-entrant curvature and an immobilized layer of lubricating liquid wetting over the surface features. The surface features with re-entrant curvature can be designed to provide high repellency even after failure or removal of the immobilized layer of lubricating liquid under certain operating conditions.

Feature weight estimation for gene selection: a local hyperlinear learning approach

PubMed Central

2014-01-01

Background Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried in high-dimensional irrelevant noises. RELIEF is a popular and widely used approach for feature selection owing to its low computational cost and high accuracy. However, RELIEF based methods suffer from instability, especially in the presence of noisy and/or high-dimensional outliers. Results We propose an innovative feature weighting algorithm, called LHR, to select informative genes from highly noisy data. LHR is based on RELIEF for feature weighting using classical margin maximization. The key idea of LHR is to estimate the feature weights through local approximation rather than global measurement, which is typically used in existing methods. The weights obtained by our method are very robust in terms of degradation of noisy features, even those with vast dimensions. To demonstrate the performance of our method, extensive experiments involving classification tests have been carried out on both synthetic and real microarray benchmark datasets by combining the proposed technique with standard classifiers, including the support vector machine (SVM), k-nearest neighbor (KNN), hyperplane k-nearest neighbor (HKNN), linear discriminant analysis (LDA) and naive Bayes (NB). Conclusion Experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed feature selection method combined with supervised learning in three aspects: 1) high classification accuracy, 2) excellent robustness to noise and 3) good stability using to various classification algorithms. PMID:24625071

SU-F-R-30: Interscanner Variability of Radiomics Features in Computed Tomography (CT) Using a Standard ACR Phantom

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

Shafiq ul Hassan, M; Zhang, G; Moros, E

2016-06-15

Purpose: A simple approach to investigate Interscanner variability of Radiomics features in computed tomography (CT) using a standard ACR phantom. Methods: The standard ACR phantom was scanned on CT scanners from three different manufacturers. Scanning parameters of 120 KVp, 200 mA were used while slice thickness of 3.0 mm on two scanners and 3.27 mm on third scanner was used. Three spherical regions of interest (ROI) from water, medium density and high density inserts were contoured. Ninety four Radiomics features were extracted using an in-house program. These features include shape (11), intensity (22), GLCM (26), GLZSM (11), RLM (11), andmore » NGTDM (5) and 8 fractal dimensions features. To evaluate the Interscanner variability across three scanners, a coefficient of variation (COV) is calculated for each feature group. Each group is further classified according to the COV- by calculating the percentage of features in each of the following categories: COV less than 2%, between 2 and 10% and greater than 10%. Results: For all feature groups, similar trend was observed for three different inserts. Shape features were the most robust for all scanners as expected. 70% of the shape features had COV <2%. For intensity feature group, 2% COV varied from 9 to 32% for three scanners. All features in four groups GLCM, GLZSM, RLM and NGTDM were found to have Interscanner variability ≥2%. The fractal dimensions dependence for medium and high density inserts were similar while it was different for water inserts. Conclusion: We concluded that even for similar scanning conditions, Interscanner variability across different scanners was significant. The texture features based on GLCM, GLZSM, RLM and NGTDM are highly scanner dependent. Since the inserts of the ACR Phantom are not heterogeneous in HU values suggests that matrix based 2nd order features are highly affected by variation in noise. Research partly funded by NIH/NCI R01CA190105-01.« less

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

LROC Observations of Geologic Features in the Marius Hills

NASA Astrophysics Data System (ADS)

Lawrence, S.; Stopar, J. D.; Hawke, R. B.; Denevi, B. W.; Robinson, M. S.; Giguere, T.; Jolliff, B. L.

2009-12-01

Lunar volcanic cones, domes, and their associated geologic features are important objects of study for the LROC science team because they represent possible volcanic endmembers that may yield important insights into the history of lunar volcanism and are potential sources of lunar resources. Several hundred domes, cones, and associated volcanic features are currently targeted for high-resolution LROC Narrow Angle Camera [NAC] imagery[1]. The Marius Hills, located in Oceanus Procellarum (centered at ~13.4°N, -55.4°W), represent the largest concentration of these volcanic features on the Moon including sinuous rilles, volcanic cones, domes, and depressions [e.g., 2-7]. The Marius region is thus a high priority for future human lunar exploration, as signified by its inclusion in the Project Constellation list of notional future human lunar exploration sites [8], and will be an intense focus of interest for LROC science investigations. Previous studies of the Marius Hills have utilized telescopic, Lunar Orbiter, Apollo, and Clementine imagery to study the morphology and composition of the volcanic features in the region. Complementary LROC studies of the Marius region will focus on high-resolution NAC images of specific features for studies of morphology (including flow fronts, dome/cone structure, and possible layering) and topography (using stereo imagery). Preliminary studies of the new high-resolution images of the Marius Hills region reveal small-scale features in the sinuous rilles including possible outcrops of bedrock and lobate lava flows from the domes. The observed Marius Hills are characterized by rough surface textures, including the presence of large boulders at the summits (~3-5m diameter), which is consistent with the radar-derived conclusions of [9]. Future investigations will involve analysis of LROC stereo photoclinometric products and coordinating NAC images with the multispectral images collected by the LROC WAC, especially the ultraviolet data, to enable measurements of color variations within and amongst deposits and provide possible compositional insights, including the location of possibly related pyroclastic deposits. References: [1] J. D. Stopar et al. (2009), LRO Science Targeting Meeting, Abs. 6039 [2] Greeley R (1971) Moon, 3, 289-314 [3] Guest J. E. (1971) Geol. and Phys. of the Moon, p. 41-53. [4] McCauley J. F. (1967) USGS Geologic Atlas of the Moon, Sheet I-491 [5] Weitz C. M. and Head J. W. (1999) JGR, 104, 18933-18956 [6] Heather D. J. et al. (2003) JGR, doi:10.1029/2002JE001938 [7] Whitford-Stark, J. L., and J. W. Head (1977) Proc. LSC 8th, 2705-2724 [8] Gruener J. and Joosten B. K. (2009) LRO Science Targeting Meeting, Abs. 6036 [9] Campbell B. A. et al. (2009) JGR, doi:10.1029/2008JE003253.

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.

Characterizing Arctic sea ice topography and atmospheric form drag using high-resolution IceBridge data

NASA Astrophysics Data System (ADS)

Petty, A.; Tsamados, M.; Kurtz, N. T.; Farrell, S. L.; Newman, T.; Harbeck, J.; Feltham, D. L.; Richter-Menge, J.

2015-12-01

Here we present a detailed analysis of Arctic sea ice topography using high resolution, three-dimensional surface elevation data from the NASA Operation IceBridge Airborne Topographic Mapper (ATM) laser altimeter. We derive novel ice topography statistics from 2009-2014 across both first-year and multiyear ice regimes - including the height, area coverage, orientation and spacing of distinct surface features. The sea ice topography exhibits strong spatial variability, including increased surface feature (e.g. pressure ridge) height and area coverage within the multi-year ice regions. The ice topography also shows a strong coastal dependency, with the feature height and area coverage increasing as a function of proximity to the nearest coastline, especially north of Greenland and the Canadian Archipelago. The ice topography data have also been used to explicitly calculate atmospheric drag coefficients over Arctic sea ice; utilizing existing relationships regarding ridge geometry and their impact on form drag. The results are being used to calibrate the recent drag parameterization scheme included in the sea ice model CICE.

Application Of Empirical Phase Diagrams For Multidimensional Data Visualization Of High Throughput Microbatch Crystallization Experiments.

PubMed

Klijn, Marieke E; Hubbuch, Jürgen

2018-04-27

Protein phase diagrams are a tool to investigate cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphological features, such as crystal size, as well as kinetic features, such as crystal growth time. Common used data visualization techniques include individual line graphs or symbols-based phase diagrams. These techniques have limitations in terms of handling large datasets, comprehensiveness or completeness. To eliminate these limitations, morphological and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram (EPD) method. Morphological features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the EPD method can support high throughput crystallization experiments in its data amount as well as its data complexity. Copyright © 2018. Published by Elsevier Inc.

Reducing breast biopsies by ultrasonographic analysis and a modified self-organizing map

NASA Astrophysics Data System (ADS)

Zheng, Yi; Greenleaf, James F.; Gisvold, John J.

1997-05-01

Recent studies suggest that visual evaluation of ultrasound images could decrease negative biopsies of breast cancer diagnosis. However, visual evaluation requires highly experienced breast sonographers. The objective of this study is to develop computerized radiologist assistant to reduce breast biopsies needed for evaluating suspected breast cancer. The approach of this study utilizes a neural network and tissue features extracted from digital sonographic breast images. The features include texture parameters of breast images: characteristics of echoes within and around breast lesions, and geometrical information of breast tumors. Clusters containing only benign lesions in the feature space are then identified by a modified self- organizing map. This newly developed neural network objectively segments population distributions of lesions and accurately establishes benign and equivocal regions.t eh method was applied to high quality breast sonograms of a large number of patients collected with a controlled procedure at Mayo Clinic. The study showed that the number of biopsies in this group of women could be decreased by 40 percent to 59 percent with high confidence and that no malignancies would have been included in the nonbiopsied group. The advantages of this approach are that it is robust, simple, and effective and does not require highly experienced sonographers.

Incorporating High-Frequency Physiologic Data Using Computational Dictionary Learning Improves Prediction of Delayed Cerebral Ischemia Compared to Existing Methods.

PubMed

Megjhani, Murad; Terilli, Kalijah; Frey, Hans-Peter; Velazquez, Angela G; Doyle, Kevin William; Connolly, Edward Sander; Roh, David Jinou; Agarwal, Sachin; Claassen, Jan; Elhadad, Noemie; Park, Soojin

2018-01-01

Accurate prediction of delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) can be critical for planning interventions to prevent poor neurological outcome. This paper presents a model using convolution dictionary learning to extract features from physiological data available from bedside monitors. We develop and validate a prediction model for DCI after SAH, demonstrating improved precision over standard methods alone. 488 consecutive SAH admissions from 2006 to 2014 to a tertiary care hospital were included. Models were trained on 80%, while 20% were set aside for validation testing. Modified Fisher Scale was considered the standard grading scale in clinical use; baseline features also analyzed included age, sex, Hunt-Hess, and Glasgow Coma Scales. An unsupervised approach using convolution dictionary learning was used to extract features from physiological time series (systolic blood pressure and diastolic blood pressure, heart rate, respiratory rate, and oxygen saturation). Classifiers (partial least squares and linear and kernel support vector machines) were trained on feature subsets of the derivation dataset. Models were applied to the validation dataset. The performances of the best classifiers on the validation dataset are reported by feature subset. Standard grading scale (mFS): AUC 0.54. Combined demographics and grading scales (baseline features): AUC 0.63. Kernel derived physiologic features: AUC 0.66. Combined baseline and physiologic features with redundant feature reduction: AUC 0.71 on derivation dataset and 0.78 on validation dataset. Current DCI prediction tools rely on admission imaging and are advantageously simple to employ. However, using an agnostic and computationally inexpensive learning approach for high-frequency physiologic time series data, we demonstrated that we could incorporate individual physiologic data to achieve higher classification accuracy.

Scalable topographies to support proliferation and Oct4 expression by human induced pluripotent stem cells

PubMed Central

Reimer, Andreas; Vasilevich, Aliaksei; Hulshof, Frits; Viswanathan, Priyalakshmi; van Blitterswijk, Clemens A.; de Boer, Jan; Watt, Fiona M.

2016-01-01

It is well established that topographical features modulate cell behaviour, including cell morphology, proliferation and differentiation. To define the effects of topography on human induced pluripotent stem cells (iPSC), we plated cells on a topographical library containing over 1000 different features in medium lacking animal products (xeno-free). Using high content imaging, we determined the effect of each topography on cell proliferation and expression of the pluripotency marker Oct4 24 h after seeding. Features that maintained Oct4 expression also supported proliferation and cell-cell adhesion at 24 h, and by 4 days colonies of Oct4-positive, Sox2-positive cells had formed. Computational analysis revealed that small feature size was the most important determinant of pluripotency, followed by high wave number and high feature density. Using this information we correctly predicted whether any given topography within our library would support the pluripotent state at 24 h. This approach not only facilitates the design of substrates for optimal human iPSC expansion, but also, potentially, identification of topographies with other desirable characteristics, such as promoting differentiation. PMID:26757610

Scalable topographies to support proliferation and Oct4 expression by human induced pluripotent stem cells.

PubMed

Reimer, Andreas; Vasilevich, Aliaksei; Hulshof, Frits; Viswanathan, Priyalakshmi; van Blitterswijk, Clemens A; de Boer, Jan; Watt, Fiona M

2016-01-13

It is well established that topographical features modulate cell behaviour, including cell morphology, proliferation and differentiation. To define the effects of topography on human induced pluripotent stem cells (iPSC), we plated cells on a topographical library containing over 1000 different features in medium lacking animal products (xeno-free). Using high content imaging, we determined the effect of each topography on cell proliferation and expression of the pluripotency marker Oct4 24 h after seeding. Features that maintained Oct4 expression also supported proliferation and cell-cell adhesion at 24 h, and by 4 days colonies of Oct4-positive, Sox2-positive cells had formed. Computational analysis revealed that small feature size was the most important determinant of pluripotency, followed by high wave number and high feature density. Using this information we correctly predicted whether any given topography within our library would support the pluripotent state at 24 h. This approach not only facilitates the design of substrates for optimal human iPSC expansion, but also, potentially, identification of topographies with other desirable characteristics, such as promoting differentiation.

New features in Saturn's atmosphere revealed by high-resolution thermal infrared images

NASA Technical Reports Server (NTRS)

Gezari, D. Y.; Mumma, M. J.; Espenak, F.; Deming, D.; Bjoraker, G.; Woods, L.; Folz, W.

1989-01-01

Observations of the stratospheric IR emission structure on Saturn are presented. The high-spatial-resolution global images show a variety of new features, including a narrow equatorial belt of enhanced emission at 7.8 micron, a prominent symmetrical north polar hotspot at all three wavelengths, and a midlatitude structure which is asymmetrically brightened at the east limb. The results confirm the polar brightening and reversal in position predicted by recent models for seasonal thermal variations of Saturn's stratosphere.

Microtopographic characterization of ice-wedge polygon landscape in Barrow, Alaska: a digital map of troughs, rims, centers derived from high resolution (0.25 m) LiDAR data

DOE Data Explorer

Gangodagamage, Chandana; Wullschleger, Stan

2014-07-03

The dataset represents microtopographic characterization of the ice-wedge polygon landscape in Barrow, Alaska. Three microtopographic features are delineated using 0.25 m high resolution digital elevation dataset derived from LiDAR. The troughs, rims, and centers are the three categories in this classification scheme. The polygon troughs are the surface expression of the ice-wedges that are in lower elevations than the interior polygon. The elevated shoulders of the polygon interior immediately adjacent to the polygon troughs are the polygon rims for the low center polygons. In case of high center polygons, these features are the topographic highs. In this classification scheme, both topographic highs and rims are considered as polygon rims. The next version of the dataset will include more refined classification scheme including separate classes for rims ad topographic highs. The interior part of the polygon just adjacent to the polygon rims are the polygon centers.

Pap-tests with non-hyperchromatic dyskariosis are often associated with squamous intraepithelial lesions of the cervix uteri with eosinophilic features.

PubMed

Bellisano, Giulia; Ambrosini-Spaltro, Andrea; Faa, Gavino; Ravarino, Alberto; Piccin, Andrea; Peer, Irmgard; Kasal, Armin; Vittadello, Fabio; Negri, Giovanni

2016-10-01

Squamous intraepithelial lesions of the cervix uteri with eosinophilic features (eosinophilic dysplasia, ED) are a peculiar type of dysplasia with metaplastic phenotype which was described in histological specimens. The cytological features of these lesions have not been studied yet. Histological samples from 66 women with features of ED and positive p16(INK4a) staining were included in the study. Within the previous year, all women had at least one pap-test, whose features were recorded and compared with 31 control samples with high-grade dysplasia of usual type. The previous pap-test showed high-grade dysplastic cells with non-hyperchromatic nuclei in 56/66 (84.8%) cases and metaplastic features in 60/66 (90.9%) cases. Conversely, the dysplastic cells of the usual lesions showed non-hyperchromatic nuclei in 6/31 (19.4%) and metaplastic features in 4/31 (12.9%) cases. Statistical analysis showed significant differences in distribution of the non-hyperchromatic nuclei (P < 0.001), metaplastic features (P < 0.001), presence of both non-hyperchromatic nuclei and metaplastic features (P < 0.001) and usual dysplastic features (P < 0.001) among the study and control groups. A high-grade squamous intraepithelial lesion with non-hyperchromatic nuclei or metaplastic features is often found in the pap-test previous to the histological diagnosis of ED and may represent the cytologic correlate of this particular type of dysplasia. Diagn. Cytopathol. 2016;44:783-786. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

Dialogic and Hortatory Features in the Writing of Chinese Candidates for the IELTS Test

ERIC Educational Resources Information Center

Mayor, Barbara M.

2006-01-01

Research conducted in the context of the IELTS Research Program indicates that there are recurrent features in the writing under test conditions of candidates from Chinese language backgrounds, particularly in terms of interpersonal tenor. These include a high level of interpersonal reference, combined with a heavily dialogic and hortatory style.…

Maritime English Vocabulary in Feature Films: "The Perfect Storm" (2000) and "Master and Commander" (2003)

ERIC Educational Resources Information Center

Jurkovic, Violeta

2016-01-01

The teaching content of Maritime English is dictated by the 1995 International Convention on Standards of Training, Certification, and Watchkeeping, as amended, which sets qualification standards for masters, officers, and officers of the watch on merchant ships, including a high proficiency level in maritime English. Feature films have an…

The Effectiveness of Reason Racer, a Game Designed to Engage Middle School Students in Scientific Argumentation

ERIC Educational Resources Information Center

Ault, Marilyn; Craig-Hare, Jana; Frey, Bruce; Ellis, James D.; Bulgren, Janis

2015-01-01

Reason Racer is an online, rate-based, multiplayer game that applies specific game features in order to engage middle school students in introductory knowledge of and thinking related to scientific argumentation. Game features include rapid and competitive play, timed performance, immediate feedback, and high rates of response across many…

Validation of Preoperative Risk Grouping of the Selection of Patients Most Likely to Benefit From Neoadjuvant Chemotherapy Before Radical Cystectomy.

PubMed

Moschini, Marco; Soria, Francesco; Klatte, Tobias; Wirth, Gregory J; Özsoy, Mehmet; Gust, Killian; Briganti, Alberto; Roupret, Morgan; Susani, Martin; Haitel, Andrea; Shariat, Shahrokh F

2017-04-01

The aim of this study was to validate the value of preoperative patient characteristics in prognosticating survival after radical cystectomy (RC) to guide treatment decisions regarding neoadjuvant systemic treatment. We evaluated a single cohort of 449 consecutive patients treated with RC for bladder cancer. Patients treated with neoadjuvant therapy were excluded from the study cohort (n = 24). Patients were stratified based on preoperative characteristics into 2 risk groups. The high-risk group included patients harboring clinically non-organ-confined disease (≥ cT3), hydroureteronephrosis, lymphovascular invasion, or variant histology (micropapillary, neuroendocrine, sarcomatoid, or plasmacytoid variants on transurethral resection). The low-risk group included patients with cT2 disease without any of the aforementioned features. Survival expectancies after surgery were evaluated using competing risk and Kaplan-Meier analyses. We identified 153 (44.6%) low-risk and 190 (55.4%) high-risk patients. The majority of high-risk patients had only 1 high-risk feature (n = 111; 58.4%); the most common high-risk feature was preoperative hydroureteronephrosis (n = 107; 56.3%). The majority of low-risk patients were upstaged at time of RC (n = 118; 70.6%), whereas a pathologic downstage occurred only in 27 high-risk patients (14.2%). Cancer-specific mortality-free rates at 5 years after RC were 77.4% versus 64.4% for low-risk versus high-risk patients, respectively. We confirm that preoperative risk features can stratify patients with muscle-invasive bladder cancer into differential risk groups regarding survival. Decision-making regarding neoadjuvant systemic therapy administration is likely to be improved by integrating clinical stage, lymphovascular invasion, variant histology, and hydroureteronephrosis. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study.

PubMed

Mazzarini, Lorenzo; Kotzalidis, Georgios D; Piacentino, Daria; Rizzato, Salvatore; Angst, Jules; Azorin, Jean-Michel; Bowden, Charles L; Mosolov, Sergey; Young, Allan H; Vieta, Eduard; Girardi, Paolo; Perugi, Giulio

2018-03-15

Current classifications separate Bipolar (BD) from Major Depressive Disorder (MDD) based on polarity rather than recurrence. We aimed to determine bipolar/mixed feature frequency in a large MDD multinational sample with (High-Rec) and without (Low-Rec) >3 recurrences, comparing the two subsamples. We measured frequency of bipolarity/hypomanic features during current depressive episodes (MDEs) in 2347 MDD patients from the BRIDGE-II-mix database, comparing High-Rec with Low-Rec. We used Bonferroni-corrected Student's t-test for continuous, and chi-squared test, for categorical variables. Logistic regression estimated the size of the association between clinical characteristics and High-Rec MDD. Compared to Low-Rec (n = 1084, 46.2%), High-Rec patients (n = 1263, 53.8%) were older, with earlier depressive onset, had more family history of BD, more atypical features, suicide attempts, hospitalisations, and treatment resistance and (hypo)manic switches when treated with antidepressants, higher comorbidity with borderline personality disorder, and more hypomanic symptoms during current MDE, resulting in higher rates of mixed depression according to both DSM-5 and research-based diagnostic (RBDC) criteria. Logistic regression showed age at first symptoms < 30 years, current MDE duration ≤ 1 month, hypomania/mania among first-degree relatives, past suicide attempts, treatment-resistance, antidepressant-induced swings, and atypical, mixed, or psychotic features during MDE to associate with High-Rec. Number of MDEs for defining recurrence was arbitrary; cross-sectionality did not allow assessment of conversion from MDD to BD. High-Rec MDD differed from Low-Rec group for several clinical/epidemiological variables, including bipolar/mixed features. Bipolarity specifier and RBDC were more sensitive than DSM-5 criteria in detecting bipolar and mixed features in MDD. Copyright © 2017. Published by Elsevier B.V.

Introducing Standardized EFL/ESL Exams

ERIC Educational Resources Information Center

Laborda, Jesus Garcia

2007-01-01

This article presents the features, and a brief comparison, of some of the most well-known high-stakes exams. They are classified in the following fashion: tests that only include multiple-choice questions, tests that include writing and multiple-choice questions, and tests that include speaking questions. The tests reviewed are: BULATS, IELTS,…

Wavelet Packet Feature Assessment for High-Density Myoelectric Pattern Recognition and Channel Selection toward Stroke Rehabilitation.

PubMed

Wang, Dongqing; Zhang, Xu; Gao, Xiaoping; Chen, Xiang; Zhou, Ping

2016-01-01

This study presents wavelet packet feature assessment of neural control information in paretic upper limb muscles of stroke survivors for myoelectric pattern recognition, taking advantage of high-resolution time-frequency representations of surface electromyogram (EMG) signals. On this basis, a novel channel selection method was developed by combining the Fisher's class separability index and the sequential feedforward selection analyses, in order to determine a small number of appropriate EMG channels from original high-density EMG electrode array. The advantages of the wavelet packet features and the channel selection analyses were further illustrated by comparing with previous conventional approaches, in terms of classification performance when identifying 20 functional arm/hand movements implemented by 12 stroke survivors. This study offers a practical approach including paretic EMG feature extraction and channel selection that enables active myoelectric control of multiple degrees of freedom with paretic muscles. All these efforts will facilitate upper limb dexterity restoration and improved stroke rehabilitation.

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.

Tip Characterization Method using Multi-feature Characterizer for CD-AFM

PubMed Central

Orji, Ndubuisi G.; Itoh, Hiroshi; Wang, Chumei; Dixson, Ronald G.; Walecki, Peter S.; Schmidt, Sebastian W.; Irmer, Bernd

2016-01-01

In atomic force microscopy (AFM) metrology, the tip is a key source of uncertainty. Images taken with an AFM show a change in feature width and shape that depends on tip geometry. This geometric dilation is more pronounced when measuring features with high aspect ratios, and makes it difficult to obtain absolute dimensions. In order to accurately measure nanoscale features using an AFM, the tip dimensions should be known with a high degree of precision. We evaluate a new AFM tip characterizer, and apply it to critical dimension AFM (CD-AFM) tips used for high aspect ratio features. The characterizer is made up of comb-shaped lines and spaces, and includes a series of gratings that could be used as an integrated nanoscale length reference. We also demonstrate a simulation method that could be used to specify what range of tip sizes and shapes the characterizer can measure. Our experiments show that for non re-entrant features, the results obtained with this characterizer are consistent to 1 nm with the results obtained by using widely accepted but slower methods that are common practice in CD-AFM metrology. A validation of the integrated length standard using displacement interferometry indicates a uniformity of better than 0.75%, suggesting that the sample could be used as highly accurate and SI traceable lateral scale for the whole evaluation process. PMID:26720439

Health System Features That Enhance Access to Comprehensive Primary Care for Women Living with HIV in High-Income Settings: A Systematic Mixed Studies Review.

PubMed

O'Brien, Nadia; Hong, Quan Nha; Law, Susan; Massoud, Sarah; Carter, Allison; Kaida, Angela; Loutfy, Mona; Cox, Joseph; Andersson, Neil; de Pokomandy, Alexandra

2018-04-01

Women living with HIV in high-income settings continue to experience modifiable barriers to care. We sought to determine the features of care that facilitate access to comprehensive primary care, inclusive of HIV, comorbidity, and sexual and reproductive healthcare. Using a systematic mixed studies review design, we reviewed qualitative, mixed methods, and quantitative studies identified in Ovid MEDLINE, EMBASE, and CINAHL databases (January 2000 to August 2017). Eligibility criteria included women living with HIV; high-income countries; primary care; and healthcare accessibility. We performed a thematic synthesis using NVivo. After screening 3466 records, we retained 44 articles and identified 13 themes. Drawing on a social-ecological framework on engagement in HIV care, we situated the themes across three levels of the healthcare system: care providers, clinical care environments, and social and institutional factors. At the care provider level, features enhancing access to comprehensive primary care included positive patient-provider relationships and availability of peer support, case managers, and/or nurse navigators. Within clinical care environments, facilitators to care were appointment reminder systems, nonidentifying clinic signs, women and family spaces, transportation services, and coordination of care to meet women's HIV, comorbidity, and sexual and reproductive healthcare needs. Finally, social and institutional factors included healthcare insurance, patient and physician education, and dispelling HIV-related stigma. This review highlights several features of care that are particularly relevant to the care-seeking experience of women living with HIV. Improving their health through comprehensive care requires a variety of strategies at the provider, clinic, and greater social and institutional levels.

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 premalignant lesions, including hyperplasia and intraepithelial neoplasia. Glomeruloid structures in the prostate represent an uncommon but distinctive pattern of growth that is specific for malignancy. Glomeruloid features may be a useful diagnostic clue for malignancy, particularly in some challenging needle biopsy specimens. This pattern of growth is usually seen in high-grade adenocarcinoma, often with extraprostatic extension. Further investigations are required to determine its independent predictive value and correlation with stage and Gleason score.

Structure and origin of Australian ring and dome features with reference to the search for asteroid impact events

NASA Astrophysics Data System (ADS)

Glikson, Andrew

2018-01-01

Ring, dome and crater features on the Australian continent and shelf include (A) 38 structures of confirmed or probable asteroid and meteorite impact origin and (B) numerous buried and exposed ring, dome and crater features of undefined origin. A large number of the latter include structural and geophysical elements consistent with impact structures, pending test by field investigations and/or drilling. This paper documents and briefly describes 43 ring and dome features with the aim of appraising their similarities and differences from those of impact structures. Discrimination between impact structures and igneous plugs, volcanic caldera and salt domes require field work and/or drilling. Where crater-like morphological patterns intersect pre-existing linear structural features and contain central morphological highs and unique thrust and fault patterns an impact connection needs to tested in the field. Hints of potential buried impact structures may be furnished by single or multi-ring TMI patterns, circular TMI quiet zones, corresponding gravity patterns, low velocity and non-reflective seismic zones.

Interactive classification and content-based retrieval of tissue images

NASA Astrophysics Data System (ADS)

Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

2002-11-01

We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

High-resolution 3-T MRI of the triangular fibrocartilage complex in the wrist: injury pattern and MR features.

PubMed

Zhan, Huili; Zhang, Huibo; Bai, Rongjie; Qian, Zhanhua; Liu, Yue; Zhang, Heng; Yin, Yuming

2017-12-01

To investigate if using high-resolution 3-T MRI can identify additional injuries of the triangular fibrocartilage complex (TFCC) beyond the Palmer classification. Eighty-six patients with surgically proven TFCC injury were included in this study. All patients underwent high-resolution 3-T MRI of the injured wrist. The MR imaging features of TFCC were analyzed according to the Palmer classification. According to the Palmer classification, 69 patients could be classified as having Palmer injuries (52 had traumatic tears and 17 had degenerative tears). There were 17 patients whose injuries could not be classified according to the Palmer classification: 13 had volar or dorsal capsular TFC detachment and 4 had a horizontal tear of the articular disk. Using high-resolution 3-T MRI, we have not only found all the TFCC injuries described in the Palmer classification, additional injury types were found in this study, including horizontal tear of the TFC and capsular TFC detachment. We propose the modified Palmer classification and add the injury types that were not included in the original Palmer classification.

The Effects of High School Organization on Dropping Out: An Exploratory Investigation.

ERIC Educational Resources Information Center

Bryk, Anthony S.; Thum, Yeow Meng

1989-01-01

A hierarchical linear model analysis investigated the effects of structural and normative features of schools on absenteeism and the probability of dropping out. Subjects included 4,450 sophomores in 160 Catholic and public high schools from the High School and Beyond 1980 cohort. (SLD)

High-temperature pump-motor assembly

NASA Technical Reports Server (NTRS)

Colker, C.; Waldron, W.

1971-01-01

Assembly pumps liquid sodium-potassium /NaK/ eutectic at 950 K for up to 20,000 hours. Design features include - high operating-temperature capability, zero leakage, process fluid lubricant/coolant, insulation system compatible with ionizing radiation environments, and reliability and long life without maintenance.

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811

The Myszkow porphyry copper-molybdenum deposit, Poland

USGS Publications Warehouse

Chaffee, M.A.; Eppinger, R.G.; Lason, K.; Slosarz, J.; Podemski, M.

1994-01-01

The porphyry copper-molybdenum deposit at Myszkow, south-central Poland, lies in the Cracow-Silesian orogenic belt, in the vicinity of a Paleozoic boundary between two tectonic plates. The deposit is hosted in a complex that includes early Paleozoic metasedimentary rocks intruded in the late Paleozoic by a predominantly granodioritic pluton. This deposit exhibits many features that are typical of porphyry copper deposits associated with calc-alkaline intrusive rocks, including ore- and alteration-mineral suites, zoning of ore and alteration minerals, fluid-inclusion chemistry, tectonic setting, and structural style of veining. Unusual features of the Myszkow deposit include high concentrations of tungsten and the late Paleozoic (Variscan) age. -Authors

Automated analysis of free speech predicts psychosis onset in high-risk youths

PubMed Central

Bedi, Gillinder; Carrillo, Facundo; Cecchi, Guillermo A; Slezak, Diego Fernández; Sigman, Mariano; Mota, Natália B; Ribeiro, Sidarta; Javitt, Daniel C; Copelli, Mauro; Corcoran, Cheryl M

2015-01-01

Background/Objectives: Psychiatry lacks the objective clinical tests routinely used in other specializations. Novel computerized methods to characterize complex behaviors such as speech could be used to identify and predict psychiatric illness in individuals. AIMS: In this proof-of-principle study, our aim was to test automated speech analyses combined with Machine Learning to predict later psychosis onset in youths at clinical high-risk (CHR) for psychosis. Methods: Thirty-four CHR youths (11 females) had baseline interviews and were assessed quarterly for up to 2.5 years; five transitioned to psychosis. Using automated analysis, transcripts of interviews were evaluated for semantic and syntactic features predicting later psychosis onset. Speech features were fed into a convex hull classification algorithm with leave-one-subject-out cross-validation to assess their predictive value for psychosis outcome. The canonical correlation between the speech features and prodromal symptom ratings was computed. Results: Derived speech features included a Latent Semantic Analysis measure of semantic coherence and two syntactic markers of speech complexity: maximum phrase length and use of determiners (e.g., which). These speech features predicted later psychosis development with 100% accuracy, outperforming classification from clinical interviews. Speech features were significantly correlated with prodromal symptoms. Conclusions: Findings support the utility of automated speech analysis to measure subtle, clinically relevant mental state changes in emergent psychosis. Recent developments in computer science, including natural language processing, could provide the foundation for future development of objective clinical tests for psychiatry. PMID:27336038

Borderline Personality Features in Childhood: The Role of Subtype, Developmental Timing and Chronicity of Child Maltreatment

PubMed Central

Hecht, Kathryn F.; Cicchetti, Dante; Rogosch, Fred A.; Crick, Nicki

2014-01-01

Child maltreatment has been established as a risk factor for borderline personality disorder (BPD), yet few studies consider how maltreatment influences the development of BPD features through childhood and adolescence. Subtype, developmental timing and chronicity of child maltreatment were examined as factors in the development of borderline personality features in childhood. Children (M age = 11.30, SD = 0.94), including 314 maltreated and 285 nonmaltreated children from comparable low socioeconomic backgrounds, provided self-reports of developmentally salient borderline personality traits. Maltreated children had higher overall borderline feature scores, higher scores on each individual subscale and were more likely to be identified as at high risk for development of BPD through raised scores on all 4 subscales. Chronicity of maltreatment predicted higher overall borderline feature scores and patterns of onset and recency of maltreatment significantly predicted whether a participant would meet criteria for the high-risk group. Implications of findings and recommendations for intervention are discussed. PMID:25047300

Borderline personality features in childhood: the role of subtype, developmental timing, and chronicity of child maltreatment.

PubMed

Hecht, Kathryn F; Cicchetti, Dante; Rogosch, Fred A; Crick, Nicki R

2014-08-01

Child maltreatment has been established as a risk factor for borderline personality disorder (BPD), yet few studies consider how maltreatment influences the development of BPD features through childhood and adolescence. Subtype, developmental timing, and chronicity of child maltreatment were examined as factors in the development of borderline personality features in childhood. Children (M age = 11.30, SD = 0.94), including 314 maltreated and 285 nonmaltreated children from comparable low socioeconomic backgrounds, provided self-reports of developmentally salient borderline personality traits. Maltreated children had higher overall borderline feature scores, had higher scores on each individual subscale, and were more likely to be identified as at high risk for development of BPD through raised scores on all four subscales. Chronicity of maltreatment predicted higher overall borderline feature scores, and patterns of onset and recency of maltreatment significantly predicted whether a participant would meet criteria for the high-risk group. Implications of findings and recommendations for intervention are discussed.

Cyclic development of igneous features and their relationship to high-temperature hydrothermal features in the Henderson porphyry molybdenum deposit, Colorado

USGS Publications Warehouse

Carten, R.B.; Geraghty, E.P.; Walker, B.M.

1988-01-01

The Henderson porphyry molybdenum deposit was formed by the superposition of coupled alteration and mineralization events, of varying intensity and size, that were associated with each of at least 11 intrusions. Deposition of molybdenite was accompanied by time-equivalent silicic and potassic alteration. High-temperature alteration and mineralization are spatially and temporally linked to the crystallization of compositionally zoned magma in the apex of stocks. Differences in hydrothermal features associated with each intrusion (e.g., mass of ore, orientation and type of veins, density of veins, and intensity of alteration) correlate with differences in primary igneous features (e.g., composition, texture, morphology, and size). The systematic relations between hydrothermal and magmatic features suggest that primary magma compositions, including volatile contents, largely control the geometry, volume, level of emplacement, and mechanisms of crystallization of stocks. These elements in turn govern the orientations and densities of fractures, which ultimately determine the distribution patterns of hydrothermal alteration and mineralization. -from Authors

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

MRI Features of Hepatocellular Carcinoma Related to Biologic Behavior

PubMed Central

Cho, Eun-Suk

2015-01-01

Imaging studies including magnetic resonance imaging (MRI) play a crucial role in the diagnosis and staging of hepatocellular carcinoma (HCC). Several recent studies reveal a large number of MRI features related to the prognosis of HCC. In this review, we discuss various MRI features of HCC and their implications for the diagnosis and prognosis as imaging biomarkers. As a whole, the favorable MRI findings of HCC are small size, encapsulation, intralesional fat, high apparent diffusion coefficient (ADC) value, and smooth margins or hyperintensity on the hepatobiliary phase of gadoxetic acid-enhanced MRI. Unfavorable findings include large size, multifocality, low ADC value, non-smooth margins or hypointensity on hepatobiliary phase images. MRI findings are potential imaging biomarkers in patients with HCC. PMID:25995679

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

TH-E-BRF-05: Comparison of Survival-Time Prediction Models After Radiotherapy for High-Grade Glioma Patients Based On Clinical and DVH Features

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

Magome, T; Haga, A; Igaki, H

Purpose: Although many outcome prediction models based on dose-volume information have been proposed, it is well known that the prognosis may be affected also by multiple clinical factors. The purpose of this study is to predict the survival time after radiotherapy for high-grade glioma patients based on features including clinical and dose-volume histogram (DVH) information. Methods: A total of 35 patients with high-grade glioma (oligodendroglioma: 2, anaplastic astrocytoma: 3, glioblastoma: 30) were selected in this study. All patients were treated with prescribed dose of 30–80 Gy after surgical resection or biopsy from 2006 to 2013 at The University of Tokyomore » Hospital. All cases were randomly separated into training dataset (30 cases) and test dataset (5 cases). The survival time after radiotherapy was predicted based on a multiple linear regression analysis and artificial neural network (ANN) by using 204 candidate features. The candidate features included the 12 clinical features (tumor location, extent of surgical resection, treatment duration of radiotherapy, etc.), and the 192 DVH features (maximum dose, minimum dose, D95, V60, etc.). The effective features for the prediction were selected according to a step-wise method by using 30 training cases. The prediction accuracy was evaluated by a coefficient of determination (R{sup 2}) between the predicted and actual survival time for the training and test dataset. Results: In the multiple regression analysis, the value of R{sup 2} between the predicted and actual survival time was 0.460 for the training dataset and 0.375 for the test dataset. On the other hand, in the ANN analysis, the value of R{sup 2} was 0.806 for the training dataset and 0.811 for the test dataset. Conclusion: Although a large number of patients would be needed for more accurate and robust prediction, our preliminary Result showed the potential to predict the outcome in the patients with high-grade glioma. This work was partly supported by the JSPS Core-to-Core Program(No. 23003) and Grant-in-aid from the JSPS Fellows.« less

ANALYSIS OF CLINICAL AND DERMOSCOPIC FEATURES FOR BASAL CELL CARCINOMA NEURAL NETWORK CLASSIFICATION

PubMed Central

Cheng, Beibei; Stanley, R. Joe; Stoecker, William V; Stricklin, Sherea M.; Hinton, Kristen A.; Nguyen, Thanh K.; Rader, Ryan K.; Rabinovitz, Harold S.; Oliviero, Margaret; Moss, Randy H.

2012-01-01

Background Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in the United States. In this research, we examine four different feature categories used for diagnostic decisions, including patient personal profile (patient age, gender, etc.), general exam (lesion size and location), common dermoscopic (blue-gray ovoids, leaf-structure dirt trails, etc.), and specific dermoscopic lesion (white/pink areas, semitranslucency, etc.). Specific dermoscopic features are more restricted versions of the common dermoscopic features. Methods Combinations of the four feature categories are analyzed over a data set of 700 lesions, with 350 BCCs and 350 benign lesions, for lesion discrimination using neural network-based techniques, including Evolving Artificial Neural Networks and Evolving Artificial Neural Network Ensembles. Results Experiment results based on ten-fold cross validation for training and testing the different neural network-based techniques yielded an area under the receiver operating characteristic curve as high as 0.981 when all features were combined. The common dermoscopic lesion features generally yielded higher discrimination results than other individual feature categories. Conclusions Experimental results show that combining clinical and image information provides enhanced lesion discrimination capability over either information source separately. This research highlights the potential of data fusion as a model for the diagnostic process. PMID:22724561

Builders Challenge High Performance Builder Spotlight: Artistic Homes, Albuquerque, New Mexico

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

None

2009-12-22

Building America Builders Challenge fact sheet on Artistic Homes of Albuquerque, New Mexico. Standard features of their homes include advanced framed 2x6 24-inch on center walls, R-21 blown insulation in the walls, and high-efficiency windows.

Automatic Correction Algorithm of Hyfrology Feature Attribute in National Geographic Census

NASA Astrophysics Data System (ADS)

Li, C.; Guo, P.; Liu, X.

2017-09-01

A subset of the attributes of hydrologic features data in national geographic census are not clear, the current solution to this problem was through manual filling which is inefficient and liable to mistakes. So this paper proposes an automatic correction algorithm of hydrologic features attribute. Based on the analysis of the structure characteristics and topological relation, we put forward three basic principles of correction which include network proximity, structure robustness and topology ductility. Based on the WJ-III map workstation, we realize the automatic correction of hydrologic features. Finally, practical data is used to validate the method. The results show that our method is highly reasonable and efficient.

On application of kernel PCA for generating stimulus features for fMRI during continuous music listening.

PubMed

Tsatsishvili, Valeri; Burunat, Iballa; Cong, Fengyu; Toiviainen, Petri; Alluri, Vinoo; Ristaniemi, Tapani

2018-06-01

There has been growing interest towards naturalistic neuroimaging experiments, which deepen our understanding of how human brain processes and integrates incoming streams of multifaceted sensory information, as commonly occurs in real world. Music is a good example of such complex continuous phenomenon. In a few recent fMRI studies examining neural correlates of music in continuous listening settings, multiple perceptual attributes of music stimulus were represented by a set of high-level features, produced as the linear combination of the acoustic descriptors computationally extracted from the stimulus audio. NEW METHOD: fMRI data from naturalistic music listening experiment were employed here. Kernel principal component analysis (KPCA) was applied to acoustic descriptors extracted from the stimulus audio to generate a set of nonlinear stimulus features. Subsequently, perceptual and neural correlates of the generated high-level features were examined. The generated features captured musical percepts that were hidden from the linear PCA features, namely Rhythmic Complexity and Event Synchronicity. Neural correlates of the new features revealed activations associated to processing of complex rhythms, including auditory, motor, and frontal areas. Results were compared with the findings in the previously published study, which analyzed the same fMRI data but applied linear PCA for generating stimulus features. To enable comparison of the results, methodology for finding stimulus-driven functional maps was adopted from the previous study. Exploiting nonlinear relationships among acoustic descriptors can lead to the novel high-level stimulus features, which can in turn reveal new brain structures involved in music processing. Copyright © 2018 Elsevier B.V. All rights reserved.

All about High/Scope: Practical Summaries of High/Scope's History, Educational Approach, and Curriculum. Numbers 1-10.

ERIC Educational Resources Information Center

Epstein, Ann S.

This document is comprised of 10 High/Scope fact sheets for parents, detailing the history of the High/Scope educational approach and describing its educational practice and curriculum. The major topic for each four-page fact sheet follows: (1) educational approach, including goals for young children and features of the High/Scope approach to…

Object-Based Arctic Sea Ice Feature Extraction through High Spatial Resolution Aerial photos

NASA Astrophysics Data System (ADS)

Miao, X.; Xie, H.

2015-12-01

High resolution aerial photographs used to detect and classify sea ice features can provide accurate physical parameters to refine, validate, and improve climate models. However, manually delineating sea ice features, such as melt ponds, submerged ice, water, ice/snow, and pressure ridges, is time-consuming and labor-intensive. An object-based classification algorithm is developed to automatically extract sea ice features efficiently from aerial photographs taken during the Chinese National Arctic Research Expedition in summer 2010 (CHINARE 2010) in the MIZ near the Alaska coast. The algorithm includes four steps: (1) the image segmentation groups the neighboring pixels into objects based on the similarity of spectral and textural information; (2) the random forest classifier distinguishes four general classes: water, general submerged ice (GSI, including melt ponds and submerged ice), shadow, and ice/snow; (3) the polygon neighbor analysis separates melt ponds and submerged ice based on spatial relationship; and (4) pressure ridge features are extracted from shadow based on local illumination geometry. The producer's accuracy of 90.8% and user's accuracy of 91.8% are achieved for melt pond detection, and shadow shows a user's accuracy of 88.9% and producer's accuracies of 91.4%. Finally, pond density, pond fraction, ice floes, mean ice concentration, average ridge height, ridge profile, and ridge frequency are extracted from batch processing of aerial photos, and their uncertainties are estimated.

Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals.

PubMed

Rosenkrantz, Andrew B; Doshi, Ankur M; Ginocchio, Luke A; Aphinyanaphongs, Yindalon

2016-12-01

This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Inference of physical/biological dynamics from synthetic ocean colour images

NASA Technical Reports Server (NTRS)

Eert, J.; Holloway, G.; Gower, J. F. R.; Denman, K.; Abbott, M.

1987-01-01

High resolution numerical experiments with well resolved eddies are performed including advection of a biologically active plankton field. Shelf wave propagation and bottom topographic features are included. The resulting synthetic ocean color fields are examined for sensitivity to the (known) underlying physical dynamics.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Visual Saliency Detection Based on Multiscale Deep CNN Features.

PubMed

Guanbin Li; Yizhou Yu

2016-11-01

Visual saliency is a fundamental problem in both cognitive and computational sciences, including computer vision. In this paper, we discover that a high-quality visual saliency model can be learned from multiscale features extracted using deep convolutional neural networks (CNNs), which have had many successes in visual recognition tasks. For learning such saliency models, we introduce a neural network architecture, which has fully connected layers on top of CNNs responsible for feature extraction at three different scales. The penultimate layer of our neural network has been confirmed to be a discriminative high-level feature vector for saliency detection, which we call deep contrast feature. To generate a more robust feature, we integrate handcrafted low-level features with our deep contrast feature. To promote further research and evaluation of visual saliency models, we also construct a new large database of 4447 challenging images and their pixelwise saliency annotations. Experimental results demonstrate that our proposed method is capable of achieving the state-of-the-art performance on all public benchmarks, improving the F-measure by 6.12% and 10%, respectively, on the DUT-OMRON data set and our new data set (HKU-IS), and lowering the mean absolute error by 9% and 35.3%, respectively, on these two data sets.

Kevlar: Transitioning Helix for Research to Practice

DTIC Science & Technology

2016-03-01

entropy randomization techniques, automated program repairs leveraging highly-optimized virtual machine technology, and developing a novel framework...attacker from exploiting residual vulnerabilities in a wide variety of classes. Helix/Kevlar uses novel, fine-grained, high- entropy diversification...the Air Force, and IARPA). Salient features of Helix/Kevlar include developing high- entropy randomization techniques, automated program repairs

Data-Mining-Based Intelligent Differential Relaying for Transmission Lines Including UPFC and Wind Farms.

PubMed

Jena, Manas Kumar; Samantaray, Subhransu Ranjan

2016-01-01

This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.

EXFILE: A program for compiling irradiation data on UN and UC fuel pins

NASA Technical Reports Server (NTRS)

Mayer, J. T.; Smith, R. L.; Weinstein, M. B.; Davison, H. W.

1973-01-01

A FORTRAN-4 computer program for handling fuel pin data is described. Its main features include standardized output, easy access for data manipulation, and tabulation of important material property data. An additional feature allows simplified preparation of input decks for a fuel swelling computer code (CYGRO-2). Data from over 300 high temperature nitride and carbide based fuel pin irradiations are listed.

TFE3 break-apart FISH has a higher sensitivity for Xp11.2 translocation-associated renal cell carcinoma compared with TFE3 or cathepsin K immunohistochemical staining alone: expanding the morphologic spectrum.

PubMed

Rao, Qiu; Williamson, Sean R; Zhang, Shaobo; Eble, John N; Grignon, David J; Wang, Mingsheng; Zhou, Xiao-Jun; Huang, Wenbin; Tan, Puay-Hoon; Maclennan, Gregory T; Cheng, Liang

2013-06-01

Renal cell carcinoma (RCC) associated with Xp11.2 translocation is uncommon, characterized by several different translocations involving the TFE3 gene. We assessed the utility of break-apart fluorescence in situ hybridization (FISH) in establishing the diagnosis for suspected or unclassified cases with negative or equivocal TFE3 immunostaining by analyzing 24 renal cancers with break-apart TFE3 FISH and comparing the molecular findings with the results of TFE3 and cathepsin K immunostaining in the same tumors. Ten tumors were originally diagnosed as Xp11.2 RCC on the basis of positive TFE3 immunostaining, and 14 were originally considered unclassified RCCs with negative or equivocal TFE3 staining, but with a range of features suspicious for Xp11.2 RCC. Seventeen cases showed TFE3 rearrangement associated with Xp11.2 translocation by FISH, including all 13 tumors with moderate or strong TFE3 (n=10) or cathepsin K (n=7) immunoreactivity. FISH-positive cases showed negative or equivocal immunoreactivity for TFE3 or cathepsin K in 7 and 10 tumors, respectively (both=3). None had positive immunohistochemistry but negative FISH. Morphologic features were typical for Xp11.2 RCC in 10/17 tumors. Unusual features included 1 melanotic Xp11.2 renal cancer, 1 tumor with mixed features of Xp11.2 RCC and clear cell RCC, and other tumors mimicking clear cell RCC, multilocular cystic RCC, or high-grade urothelial carcinoma. Morphology mimicking high-grade urothelial carcinoma has not been previously reported in these tumors. Psammoma bodies, hyalinized stroma, and intracellular pigment were preferentially identified in FISH-positive cases compared with FISH-negative cases. Our results support the clinical application of a TFE3 break-apart FISH assay for diagnosis and confirmation of Xp11.2 RCC and further expand the histopathologic spectrum of these neoplasms to include tumors with unusual features. A renal tumor with pathologic or clinical features highly suggestive of translocation-associated RCC but exhibiting negative or equivocal TFE3 immunostaining should be evaluated by TFE3 FISH assay to fully assess this possibility.

Pattern classification approach to characterizing solitary pulmonary nodules imaged on high-resolution computed tomography

NASA Astrophysics Data System (ADS)

McNitt-Gray, Michael F.; Hart, Eric M.; Goldin, Jonathan G.; Yao, Chih-Wei; Aberle, Denise R.

1996-04-01

The purpose of our study was to characterize solitary pulmonary nodules (SPN) as benign or malignant based on pattern classification techniques using size, shape, density and texture features extracted from HRCT images. HRCT images of patients with a SPN are acquired, routed through a PACS and displayed on a thoracic radiology workstation. Using the original data, the SPN is semiautomatically contoured using a nodule/background threshold. The contour is used to calculate size and several shape parameters, including compactness and bending energy. Pixels within the interior of the contour are used to calculate several features including: (1) nodule density-related features, such as representative Hounsfield number and moment of inertia, and (2) texture measures based on the spatial gray level dependence matrix and fractal dimension. The true diagnosis of the SPN is established by histology from biopsy or, in the case of some benign nodules, extended follow-up. Multi-dimensional analyses of the features are then performed to determine which features can discriminate between benign and malignant nodules. When a sufficient number of cases are obtained two pattern classifiers, a linear discriminator and a neural network, are trained and tested using a select subset of features. Preliminary data from nine (9) nodule cases have been obtained and several features extracted. While the representative CT number is a reasonably good indicator, it is an inconclusive predictor of SPN diagnosis when considered by itself. Separation between benign and malignant nodules improves when other features, such as the distribution of density as measured by moment of inertia, are included in the analysis. Software has been developed and preliminary results have been obtained which show that individual features may not be sufficient to discriminate between benign and malignant nodules. However, combinations of these features may be able to discriminate between these two classes. With additional cases and more features, we will be able to perform a feature selection procedure and ultimately to train and test pattern classifiers in this discrimination task.

Processing technology for high efficiency silicon solar cells

NASA Technical Reports Server (NTRS)

Spitzer, M. B.; Keavney, C. J.

1985-01-01

Recent advances in silicon solar cell processing have led to attainment of conversion efficiency approaching 20%. The basic cell design is investigated and features of greatest importance to achievement of 20% efficiency are indicated. Experiments to separately optimize high efficiency design features in test structures are discussed. The integration of these features in a high efficiency cell is examined. Ion implantation has been used to achieve optimal concentrations of emitter dopant and junction depth. The optimization reflects the trade-off between high sheet conductivity, necessary for high fill factor, and heavy doping effects, which must be minimized for high open circuit voltage. A second important aspect of the design experiments is the development of a passivation process to minimize front surface recombination velocity. The manner in which a thin SiO2 layer may be used for this purpose is indicated without increasing reflection losses, if the antireflection coating is properly designed. Details are presented of processing intended to reduce recombination at the contact/Si interface. Data on cell performance (including CZ and ribbon) and analysis of loss mechanisms are also presented.

PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.

PubMed

Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar

2014-01-01

Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.

Fast and efficient indexing approach for object recognition

NASA Astrophysics Data System (ADS)

Hefnawy, Alaa; Mashali, Samia A.; Rashwan, Mohsen; Fikri, Magdi

1999-08-01

This paper introduces a fast and efficient indexing approach for both 2D and 3D model-based object recognition in the presence of rotation, translation, and scale variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A list of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

NASA Technical Reports Server (NTRS)

Penaloza, Mauel A.; Welch, Ronald M.

1996-01-01

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

Remembering Complex Objects in Visual Working Memory: Do Capacity Limits Restrict Objects or Features?

PubMed Central

Hardman, Kyle; Cowan, Nelson

2014-01-01

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli which possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results, but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. PMID:25089739

New Infrared Emission Features and Spectral Variations in Ngc 7023

NASA Technical Reports Server (NTRS)

Werner, M. W.; Uchida, K. I.; Sellgren, K.; Marengo, M.; Gordon, K. D.; Morris, P. W.; Houck, J. R.; Stansberry, J. A.

2004-01-01

We observed the reflection nebula NGC 7023, with the Short-High module and the long-slit Short-Low and Long-Low modules of the Infrared Spectrograph on the Spitzer Space Telescope. We also present Infrared Array Camera (IRAC) and Multiband Imaging Photometer for Spitzer (MIPS) images of NGC 7023 at 3.6, 4.5, 8.0, and 24 m. We observe the aromatic emission features (AEFs) at 6.2, 7.7, 8.6, 11.3, and 12.7 m, plus a wealth of weaker features. We find new unidentified interstellar emission features at 6.7, 10.1, 15.8, 17.4, and 19.0 m. Possible identifications include aromatic hydrocarbons or nanoparticles of unknown mineralogy. We see variations in relative feature strengths, central wavelengths, and feature widths, in the AEFs and weaker emission features, depending on both distance from the star and nebular position (southeast vs. northwest).

Ship Detection Based on Multiple Features in Random Forest Model for Hyperspectral Images

NASA Astrophysics Data System (ADS)

Li, N.; Ding, L.; Zhao, H.; Shi, J.; Wang, D.; Gong, X.

2018-04-01

A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in the range of near infrared or short-wave infrared spectrum, is used to segment land and sea on Otsu threshold segmentation method. Secondly, multiple features that include spectral and texture features are extracted from hyperspectral images. Principal components analysis (PCA) is used to extract spectral features, the Grey Level Co-occurrence Matrix (GLCM) is used to extract texture features. Finally, Random Forest (RF) model is introduced to detect ships based on the extracted features. To illustrate the effectiveness of the method, we carry out experiments over the EO-1 data by comparing single feature and different multiple features. Compared with the traditional single feature method and Support Vector Machine (SVM) model, the proposed method can stably achieve the target detection of ships under complex background and can effectively improve the detection accuracy of ships.

Automatic identification of high impact articles in PubMed to support clinical decision making.

PubMed

Bian, Jiantao; Morid, Mohammad Amin; Jonnalagadda, Siddhartha; Luo, Gang; Del Fiol, Guilherme

2017-09-01

The practice of evidence-based medicine involves integrating the latest best available evidence into patient care decisions. Yet, critical barriers exist for clinicians' retrieval of evidence that is relevant for a particular patient from primary sources such as randomized controlled trials and meta-analyses. To help address those barriers, we investigated machine learning algorithms that find clinical studies with high clinical impact from PubMed®. Our machine learning algorithms use a variety of features including bibliometric features (e.g., citation count), social media attention, journal impact factors, and citation metadata. The algorithms were developed and evaluated with a gold standard composed of 502 high impact clinical studies that are referenced in 11 clinical evidence-based guidelines on the treatment of various diseases. We tested the following hypotheses: (1) our high impact classifier outperforms a state-of-the-art classifier based on citation metadata and citation terms, and PubMed's® relevance sort algorithm; and (2) the performance of our high impact classifier does not decrease significantly after removing proprietary features such as citation count. The mean top 20 precision of our high impact classifier was 34% versus 11% for the state-of-the-art classifier and 4% for PubMed's® relevance sort (p=0.009); and the performance of our high impact classifier did not decrease significantly after removing proprietary features (mean top 20 precision=34% vs. 36%; p=0.085). The high impact classifier, using features such as bibliometrics, social media attention and MEDLINE® metadata, outperformed previous approaches and is a promising alternative to identifying high impact studies for clinical decision support. Copyright © 2017 Elsevier Inc. All rights reserved.

A fully-coupled discontinuous Galerkin spectral element method for two-phase flow in petroleum reservoirs

NASA Astrophysics Data System (ADS)

Taneja, Ankur; Higdon, Jonathan

2018-01-01

A high-order spectral element discontinuous Galerkin method is presented for simulating immiscible two-phase flow in petroleum reservoirs. The governing equations involve a coupled system of strongly nonlinear partial differential equations for the pressure and fluid saturation in the reservoir. A fully implicit method is used with a high-order accurate time integration using an implicit Rosenbrock method. Numerical tests give the first demonstration of high order hp spatial convergence results for multiphase flow in petroleum reservoirs with industry standard relative permeability models. High order convergence is shown formally for spectral elements with up to 8th order polynomials for both homogeneous and heterogeneous permeability fields. Numerical results are presented for multiphase fluid flow in heterogeneous reservoirs with complex geometric or geologic features using up to 11th order polynomials. Robust, stable simulations are presented for heterogeneous geologic features, including globally heterogeneous permeability fields, anisotropic permeability tensors, broad regions of low-permeability, high-permeability channels, thin shale barriers and thin high-permeability fractures. A major result of this paper is the demonstration that the resolution of the high order spectral element method may be exploited to achieve accurate results utilizing a simple cartesian mesh for non-conforming geological features. Eliminating the need to mesh to the boundaries of geological features greatly simplifies the workflow for petroleum engineers testing multiple scenarios in the face of uncertainty in the subsurface geology.

Castable high-temperature Ce-modified Al alloys

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

Rios, Orlando; King, Alexander H.; McCall, Scott K.

2018-05-08

A cast alloy includes aluminum and from about 5 to about 30 weight percent of at least one material selected from the group consisting of cerium, lanthanum, and mischmetal. The cast alloy has a strengthening Al 11X 3 intermetallic phase in an amount in the range of from about 5 to about 30 weight percent, wherein X is at least one of cerium, lanthanum, and mischmetal. The Al 11X 3 intermetallic phase has a microstructure that includes at least one of lath features and rod morphological features. The morphological features have an average thickness of no more than 700 ummore » and an average spacing of no more than 10 um, the microstructure further comprising an eutectic microconstituent that comprises more than about 10 volume percent of the microstructure.« less

The Fisher-Markov selector: fast selecting maximally separable feature subset for multiclass classification with applications to high-dimensional data.

PubMed

Cheng, Qiang; Zhou, Hongbo; Cheng, Jie

2011-06-01

Selecting features for multiclass classification is a critically important task for pattern recognition and machine learning applications. Especially challenging is selecting an optimal subset of features from high-dimensional data, which typically have many more variables than observations and contain significant noise, missing components, or outliers. Existing methods either cannot handle high-dimensional data efficiently or scalably, or can only obtain local optimum instead of global optimum. Toward the selection of the globally optimal subset of features efficiently, we introduce a new selector--which we call the Fisher-Markov selector--to identify those features that are the most useful in describing essential differences among the possible groups. In particular, in this paper we present a way to represent essential discriminating characteristics together with the sparsity as an optimization objective. With properly identified measures for the sparseness and discriminativeness in possibly high-dimensional settings, we take a systematic approach for optimizing the measures to choose the best feature subset. We use Markov random field optimization techniques to solve the formulated objective functions for simultaneous feature selection. Our results are noncombinatorial, and they can achieve the exact global optimum of the objective function for some special kernels. The method is fast; in particular, it can be linear in the number of features and quadratic in the number of observations. We apply our procedure to a variety of real-world data, including mid--dimensional optical handwritten digit data set and high-dimensional microarray gene expression data sets. The effectiveness of our method is confirmed by experimental results. In pattern recognition and from a model selection viewpoint, our procedure says that it is possible to select the most discriminating subset of variables by solving a very simple unconstrained objective function which in fact can be obtained with an explicit expression.

Neural networks: Application to medical imaging

NASA Technical Reports Server (NTRS)

Clarke, Laurence P.

1994-01-01

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

EPAs DSSTox Chemical Database: A Resource for the Non-Targeted Testing Community (EPA NTA workshop)

EPA Science Inventory

EPA’s DSSTox database project, which includes coverage of the ToxCast and Tox21 high-throughput testing inventories, provides high-quality chemical-structure files for inventories of toxicological and environmental relevance. A feature of the DSSTox project, which differentiates ...

Red Spot Spotted by Juno

NASA Image and Video Library

2016-06-30

NASA's Juno spacecraft obtained this color view on June 28, 2016, at a distance of 3.9 million miles (6.2 million kilometers) from Jupiter. As Juno nears its destination, features on the giant planet are increasingly visible, including the Great Red Spot. The spacecraft is approaching over Jupiter's north pole, providing a unique perspective on the Jupiter system, including its four large moons. The scene was captured by the mission's imaging camera, called JunoCam, which is designed to acquire high resolution views of features in Jupiter's atmosphere from very close to the planet. http://photojournal.jpl.nasa.gov/catalog/PIA20705

Hydrogeomorphic features mediate the effects of land use/cover on reservoir productivity and food webs

USGS Publications Warehouse

Bremigan, M.T.; Soranno, P.A.; Gonzalez, M.J.; Bunnell, D.B.; Arend, K.K.; Renwick, W.H.; Stein, R.A.; Vanni, M.J.

2008-01-01

Although effects of land use/cover on nutrient concentrations in aquatic systems are well known, half or more of the variation in nutrient concentration remains unexplained by land use/cover alone. Hydrogeomorphic (HGM) landscape features can explain much remaining variation and influence food web interactions. To explore complex linkages among land use/cover, HGM features, reservoir productivity, and food webs, we sampled 11 Ohio reservoirs, ranging broadly in agricultural catchment land use/cover, for 3 years. We hypothesized that HGM features mediate the bottom-up effects of land use/cover on reservoir productivity, chlorophyll a, zooplankton, and recruitment of gizzard shad, an omnivorous fish species common throughout southeastern U.S. reservoirs and capable of exerting strong effects on food web and nutrient dynamics. We tested specific hypotheses using a model selection approach. Percent variation explained was highest for total nitrogen (R2 = 0.92), moderately high for total phosphorus, chlorophyll a, and rotifer biomass (R2 = 0.57 to 0.67), relatively low for crustacean zooplankton biomass and larval gizzard shad hatch abundance (R2 = 0.43 and 0.42), and high for larval gizzard shad survivor abundance (R2 = 0.79). The trophic status models included agricultural land use/cover and an HGM predictor, whereas the zooplankton models had few HGM predictors. The larval gizzard shad models had the highest complexity, including more than one HGM feature and food web components. We demonstrate the importance of integrating land use/cover, HGM features, and food web interactions to investigate critical interactions and feedbacks among physical, chemical, and biological components of linked land-water ecosystems.

Establishment and Biological Characterization of a Panel of Glioblastoma Multiforme (GBM) and GBM Variant Oncosphere Cell Lines.

PubMed

Binder, Zev A; Wilson, Kelli M; Salmasi, Vafi; Orr, Brent A; Eberhart, Charles G; Siu, I-Mei; Lim, Michael; Weingart, Jon D; Quinones-Hinojosa, Alfredo; Bettegowda, Chetan; Kassam, Amin B; Olivi, Alessandro; Brem, Henry; Riggins, Gregory J; Gallia, Gary L

2016-01-01

Human tumor cell lines form the basis of the majority of present day laboratory cancer research. These models are vital to studying the molecular biology of tumors and preclinical testing of new therapies. When compared to traditional adherent cell lines, suspension cell lines recapitulate the genetic profiles and histologic features of glioblastoma multiforme (GBM) with higher fidelity. Using a modified neural stem cell culture technique, here we report the characterization of GBM cell lines including GBM variants. Tumor tissue samples were obtained intra-operatively and cultured in neural stem cell conditions containing growth factors. Tumor lines were characterized in vitro using differentiation assays followed by immunostaining for lineage-specific markers. In vivo tumor formation was assayed by orthotopic injection in nude mice. Genetic uniqueness was confirmed via short tandem repeat (STR) DNA profiling. Thirteen oncosphere lines derived from GBM and GBM variants, including a GBM with PNET features and a GBM with oligodendroglioma component, were established. All unique lines showed distinct genetic profiles by STR profiling. The lines assayed demonstrated a range of in vitro growth rates. Multipotency was confirmed using in vitro differentiation. Tumor formation demonstrated histologic features consistent with high grade gliomas, including invasion, necrosis, abnormal vascularization, and high mitotic rate. Xenografts derived from the GBM variants maintained histopathological features of the primary tumors. We have generated and characterized GBM suspension lines derived from patients with GBMs and GBM variants. These oncosphere cell lines will expand the resources available for preclinical study.

Microbial mats in playa lakes and other saline habitats: Early Mars analog?

NASA Technical Reports Server (NTRS)

Bauld, John

1989-01-01

Microbial mats are cohesive benthic microbial communities which inhabit various Terra (Earth-based) environments including the marine littoral and both permanent and ephemeral (playa) saline lakes. Certain geomorphological features of Mars, such as the Margaritifer Sinus, were interpreted as ancient, dried playa lakes, presumably formed before or during the transition to the present Mars climate. Studies of modern Terran examples suggest that microbial mats on early Mars would have had the capacity to survive and propagate under environmental constraints that would have included irregularly fluctuating regimes of water activity and high ultraviolet flux. Assuming that such microbial communities did indeed inhabit early Mars, their detection during the Mars Rover Sample Return (MRSR) mission depends upon the presence of features diagnostic of the prior existence of these communities or their component microbes or, as an aid to choosing suitable landing, local exploration or sampling sites, geomorphological, sedimentological or chemical features characteristic of their playa lake habitats. Examination of modern Terran playas (e.g., the Lake Eyre basin) shows that these features span several orders of magnitude in size. While stromatolites are commonly centimeter-meter scale features, bioherms or fields of individuals may extend to larger scales. Preservation of organic matter (mats and microbes) would be favored in topographic lows such as channels or ponds of high salinity, particularly those receiving silica-rich groundwaters. These areas are likely to be located near former zones of groundwater emergence and/or where flood channels entered the paleo-playa. Fossil playa systems which may aid in assessing the applicability of this particular Mars analog include the Cambrian Observatory Hill Beds of the Officer Basin and the Eocene Wilkins Peak Member of the Green River Formation.

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.

Characterising smoking cessation smartphone applications in terms of behaviour change techniques, engagement and ease-of-use features.

PubMed

Ubhi, Harveen Kaur; Michie, Susan; Kotz, Daniel; van Schayck, Onno C P; Selladurai, Abiram; West, Robert

2016-09-01

The aim of this study was to assess whether or not behaviour change techniques (BCTs) as well as engagement and ease-of-use features used in smartphone applications (apps) to aid smoking cessation can be identified reliably. Apps were coded for presence of potentially effective BCTs, and engagement and ease-of-use features. Inter-rater reliability for this coding was assessed. Inter-rater agreement for identifying presence of potentially effective BCTs ranged from 66.8 to 95.1 % with 'prevalence and bias adjusted kappas' (PABAK) ranging from 0.35 to 0.90 (p < 0.001). The intra-class correlation coefficients between the two coders for scores denoting the proportions of (a) a set of engagement features and (b) a set of ease-of-use features, which were included, were 0.77 and 0.75, respectively (p < 0.001). Prevalence estimates for BCTs ranged from <10 % for medication advice to >50 % for rewarding abstinence. The average proportions of specified engagement and ease-of-use features included in the apps were 69 and 83 %, respectively. The study found that it is possible to identify potentially effective BCTs, and engagement and ease-of-use features in smoking cessation apps with fair to high inter-rater reliability.

Association between mammogram density and background parenchymal enhancement of breast MRI

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Danala, Gopichandh; Wang, Yunzhi; Zarafshani, Ali; Qian, Wei; Liu, Hong; Zheng, Bin

2018-02-01

Breast density has been widely considered as an important risk factor for breast cancer. The purpose of this study is to examine the association between mammogram density results and background parenchymal enhancement (BPE) of breast MRI. A dataset involving breast MR images was acquired from 65 high-risk women. Based on mammography density (BIRADS) results, the dataset was divided into two groups of low and high breast density cases. The Low-Density group has 15 cases with mammographic density (BIRADS 1 and 2), while the High-density group includes 50 cases, which were rated by radiologists as mammographic density BIRADS 3 and 4. A computer-aided detection (CAD) scheme was applied to segment and register breast regions depicted on sequential images of breast MRI scans. CAD scheme computed 20 global BPE features from the entire two breast regions, separately from the left and right breast region, as well as from the bilateral difference between left and right breast regions. An image feature selection method namely, CFS method, was applied to remove the most redundant features and select optimal features from the initial feature pool. Then, a logistic regression classifier was built using the optimal features to predict the mammogram density from the BPE features. Using a leave-one-case-out validation method, the classifier yields the accuracy of 82% and area under ROC curve, AUC=0.81+/-0.09. Also, the box-plot based analysis shows a negative association between mammogram density results and BPE features in the MRI images. This study demonstrated a negative association between mammogram density and BPE of breast MRI images.

Seismic imaging of the upper mantle beneath the northern Central Andean Plateau: Implications for surface topography

NASA Astrophysics Data System (ADS)

Ward, K. M.; Zandt, G.; Beck, S. L.; Wagner, L. S.

2015-12-01

Extending over 1,800 km along the active South American Cordilleran margin, the Central Andean Plateau (CAP) as defined by the 3 km elevation contour is second only to the Tibetan Plateau in geographic extent. The uplift history of the 4 km high Plateau remains uncertain with paleoelevation studies along the CAP suggesting a complex, non-uniform uplift history. As part of the Central Andean Uplift and the Geodynamics of High Topography (CAUGHT) project, we use surface waves measured from ambient noise and two-plane wave tomography to image the S-wave velocity structure of the crust and upper mantle to investigate the upper mantle component of plateau uplift. We observe three main features in our S-wave velocity model including (1), a high velocity slab (2), a low velocity anomaly above the slab where the slab changes dip from near horizontal to a normal dip, and (3), a high-velocity feature in the mantle above the slab that extends along the length of the Altiplano from the base of the Moho to a depth of ~120 km with the highest velocities observed under Lake Titicaca. A strong spatial correlation exists between the lateral extent of this high-velocity feature beneath the Altiplano and the lower elevations of the Altiplano basin suggesting a potential relationship. Non-uniqueness in our seismic models preclude uniquely constraining this feature as an uppermost mantle feature bellow the Moho or as a connected eastward dipping feature extending up to 300 km in the mantle as seen in deeper mantle tomography studies. Determining if the high velocity feature represents a small lithospheric root or a delaminating lithospheric root extending ~300 km into the mantle requires more integration of observations, but either interpretation shows a strong geodynamic connection with the uppermost mantle and the current topography of the northern CAP.

Validating continuous digital light processing (cDLP) additive manufacturing accuracy and tissue engineering utility of a dye-initiator package.

PubMed

Wallace, Jonathan; Wang, Martha O; Thompson, Paul; Busso, Mallory; Belle, Vaijayantee; Mammoser, Nicole; Kim, Kyobum; Fisher, John P; Siblani, Ali; Xu, Yueshuo; Welter, Jean F; Lennon, Donald P; Sun, Jiayang; Caplan, Arnold I; Dean, David

2014-03-01

This study tested the accuracy of tissue engineering scaffold rendering via the continuous digital light processing (cDLP) light-based additive manufacturing technology. High accuracy (i.e., <50 µm) allows the designed performance of features relevant to three scale spaces: cell-scaffold, scaffold-tissue, and tissue-organ interactions. The biodegradable polymer poly (propylene fumarate) was used to render highly accurate scaffolds through the use of a dye-initiator package, TiO2 and bis (2,4,6-trimethylbenzoyl)phenylphosphine oxide. This dye-initiator package facilitates high accuracy in the Z dimension. Linear, round, and right-angle features were measured to gauge accuracy. Most features showed accuracies between 5.4-15% of the design. However, one feature, an 800 µm diameter circular pore, exhibited a 35.7% average reduction of patency. Light scattered in the x, y directions by the dye may have reduced this feature's accuracy. Our new fine-grained understanding of accuracy could be used to make further improvements by including corrections in the scaffold design software. Successful cell attachment occurred with both canine and human mesenchymal stem cells (MSCs). Highly accurate cDLP scaffold rendering is critical to the design of scaffolds that both guide bone regeneration and that fully resorb. Scaffold resorption must occur for regenerated bone to be remodeled and, thereby, achieve optimal strength.

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 in this review will support future research aimed at isolating and reporting the effects of social media features on DBCIs, cross-study comparisons, and evaluations. PMID:29472174

HOW 1967 AWARD WINNING SCHOOLS COMPARE.

ERIC Educational Resources Information Center

1968

THIS IS A 30 PAGE PORTFOLIO OF PHOTOS, FLOOR PLANS, AND COMPARATIVE STATISTICS ON 24 TREND-SETTING SCHOOLS. SCHOOLS INCLUDED WERE GIVEN DISTINGUISHED DESIGN AWARDS BY THE AMERICAN ASSOCIATION OF SCHOOL ADMINISTRATORS AND STATE CHAPTERS OF THE AMERICAN INSTITUTE OF ARCHITECTS. TWELVE JUNIOR AND SENIOR HIGH SCHOOLS INCLUDED HAVE SUCH FEATURES AS THE…

Temporal Features of Word-Initial /s/+Stop Clusters in Bilingual Mandarin-English Children and Monolingual English Children and Adults

ERIC Educational Resources Information Center

Yang, Jing

2018-01-01

This study investigated the durational features of English word-initial /s/+stop clusters produced by bilingual Mandarin (L1)-English (L2) children and monolingual English children and adults. The participants included two groups of five- to six-year-old bilingual children: low proficiency in the L2 (Bi-low) and high proficiency in the L2…

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing

PubMed Central

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery. PMID:27711246

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

PubMed

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery.

Testing Map Features Designed to Convey the Uncertainty of Cancer Risk: Insights Gained From Assessing Judgments of Information Adequacy and Communication Goals

PubMed Central

Severtson, Dolores J.

2015-01-01

Barriers to communicating the uncertainty of environmental health risks include preferences for certain information and low numeracy. Map features designed to communicate the magnitude and uncertainty of estimated cancer risk from air pollution were tested among 826 participants to assess how map features influenced judgments of adequacy and the intended communication goals. An uncertain versus certain visual feature was judged as less adequate but met both communication goals and addressed numeracy barriers. Expressing relative risk using words communicated uncertainty and addressed numeracy barriers but was judged as highly inadequate. Risk communication and visual cognition concepts were applied to explain findings. PMID:26412960

Testing Map Features Designed to Convey the Uncertainty of Cancer Risk: Insights Gained From Assessing Judgments of Information Adequacy and Communication Goals.

PubMed

Severtson, Dolores J

2015-02-01

Barriers to communicating the uncertainty of environmental health risks include preferences for certain information and low numeracy. Map features designed to communicate the magnitude and uncertainty of estimated cancer risk from air pollution were tested among 826 participants to assess how map features influenced judgments of adequacy and the intended communication goals. An uncertain versus certain visual feature was judged as less adequate but met both communication goals and addressed numeracy barriers. Expressing relative risk using words communicated uncertainty and addressed numeracy barriers but was judged as highly inadequate. Risk communication and visual cognition concepts were applied to explain findings.

Photonic integrated circuits: new challenges for lithography

NASA Astrophysics Data System (ADS)

Bolten, Jens; Wahlbrink, Thorsten; Prinzen, Andreas; Porschatis, Caroline; Lerch, Holger; Giesecke, Anna Lena

2016-10-01

In this work routes towards the fabrication of photonic integrated circuits (PICs) and the challenges their fabrication poses on lithography, such as large differences in feature dimension of adjacent device features, non-Manhattan-type features, high aspect ratios and significant topographic steps as well as tight lithographic requirements with respect to critical dimension control, line edge roughness and other key figures of merit not only for very small but also for relatively large features, are highlighted. Several ways those challenges are faced in today's low-volume fabrication of PICs, including the concept multi project wafer runs and mix and match approaches, are presented and possible paths towards a real market uptake of PICs are discussed.

Personality disorders among patients with panic disorder and individuals with high anxiety sensitivity.

PubMed

Osma, Jorge; García-Palacios, Azucena; Botella, Cristina; Barrada, Juan Ramón

2014-05-01

No studies have been found that compared the psychopathology features, including personality disorders, of Panic Disorder (PD) and Panic Disorder with Agoraphobia (PDA), and a nonclinical sample with anxiety vulnerability. The total sample included 152 participants, 52 in the PD/PDA, 45 in the high anxiety sensitivity (AS) sample, and 55 in the nonclinical sample. The participants in PD/PDA sample were evaluated with the structured interview ADIS-IV. The Brief Symptom Inventory and the MCMI-III were used in all three samples. Statistically significant differences were found between the PD/PDA and the nonclinical sample in all MCMI-III scales except for antisocial and compulsive. No significant differences were found between PD/PDA and the sample with high scores in AS. Phobic Anxiety and Paranoid Ideation were the only scales where there were significant differences between the PD/PDA sample and the high AS sample. Our findings showed that people who scored high on AS, despite not having a diagnosis of PD/PDA, were similar in regard to psychopathology features and personality to individuals with PD/PDA.

Nanoscale platinum printing on insulating substrates.

PubMed

O'Connell, C D; Higgins, M J; Sullivan, R P; Jamali, S S; Moulton, S E; Wallace, G G

2013-12-20

The deposition of noble metals on soft and/or flexible substrates is vital for several emerging applications including flexible electronics and the fabrication of soft bionic implants. In this paper, we describe a new strategy for the deposition of platinum electrodes on a range of materials, including insulators and flexible polymers. The strategy is enabled by two principle advances: (1) the introduction of a novel, low temperature strategy for reducing chloroplatinic acid to platinum using nitrogen plasma; (2) the development of a chloroplatinic acid based liquid ink formulation, utilizing ethylene glycol as both ink carrier and reducing agent, for versatile printing at nanoscale resolution using dip-pen nanolithography (DPN). The ink formulation has been printed and reduced upon Si, glass, ITO, Ge, PDMS, and Parylene C. The plasma treatment effects reduction of the precursor patterns in situ without subjecting the substrate to destructively high temperatures. Feature size is controlled via dwell time and degree of ink loading, and platinum features with 60 nm dimensions could be routinely achieved on Si. Reduction of the ink to platinum was confirmed by energy dispersive x-ray spectroscopy (EDS) elemental analysis and x-ray diffraction (XRD) measurements. Feature morphology was characterized by optical microscopy, SEM and AFM. The high electrochemical activity of individually printed Pt features was characterized using scanning electrochemical microscopy (SECM).

Assessing the Pathogenicity of Insertion and Deletion Variants with the Variant Effect Scoring Tool (VEST-Indel).

PubMed

Douville, Christopher; Masica, David L; Stenson, Peter D; Cooper, David N; Gygax, Derek M; Kim, Rick; Ryan, Michael; Karchin, Rachel

2016-01-01

Insertion/deletion variants (indels) alter protein sequence and length, yet are highly prevalent in healthy populations, presenting a challenge to bioinformatics classifiers. Commonly used features--DNA and protein sequence conservation, indel length, and occurrence in repeat regions--are useful for inference of protein damage. However, these features can cause false positives when predicting the impact of indels on disease. Existing methods for indel classification suffer from low specificities, severely limiting clinical utility. Here, we further develop our variant effect scoring tool (VEST) to include the classification of in-frame and frameshift indels (VEST-indel) as pathogenic or benign. We apply 24 features, including a new "PubMed" feature, to estimate a gene's importance in human disease. When compared with four existing indel classifiers, our method achieves a drastically reduced false-positive rate, improving specificity by as much as 90%. This approach of estimating gene importance might be generally applicable to missense and other bioinformatics pathogenicity predictors, which often fail to achieve high specificity. Finally, we tested all possible meta-predictors that can be obtained from combining the four different indel classifiers using Boolean conjunctions and disjunctions, and derived a meta-predictor with improved performance over any individual method. © 2015 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Clinical Features and Associated Likelihood of Primary Ciliary Dyskinesia in Children and Adolescents.

PubMed

Leigh, Margaret W; Ferkol, Thomas W; Davis, Stephanie D; Lee, Hye-Seung; Rosenfeld, Margaret; Dell, Sharon D; Sagel, Scott D; Milla, Carlos; Olivier, Kenneth N; Sullivan, Kelli M; Zariwala, Maimoona A; Pittman, Jessica E; Shapiro, Adam J; Carson, Johnny L; Krischer, Jeffrey; Hazucha, Milan J; Knowles, Michael R

2016-08-01

Primary ciliary dyskinesia (PCD), a genetically heterogeneous, recessive disorder of motile cilia, is associated with distinct clinical features. Diagnostic tests, including ultrastructural analysis of cilia, nasal nitric oxide measurements, and molecular testing for mutations in PCD genes, have inherent limitations. To define a statistically valid combination of systematically defined clinical features that strongly associates with PCD in children and adolescents. Investigators at seven North American sites in the Genetic Disorders of Mucociliary Clearance Consortium prospectively and systematically assessed individuals (aged 0-18 yr) referred due to high suspicion for PCD. The investigators defined specific clinical questions for the clinical report form based on expert opinion. Diagnostic testing was performed using standardized protocols and included nasal nitric oxide measurement, ciliary biopsy for ultrastructural analysis of cilia, and molecular genetic testing for PCD-associated genes. Final diagnoses were assigned as "definite PCD" (hallmark ultrastructural defects and/or two mutations in a PCD-associated gene), "probable/possible PCD" (no ultrastructural defect or genetic diagnosis, but compatible clinical features and nasal nitric oxide level in PCD range), and "other diagnosis or undefined." Criteria were developed to define early childhood clinical features on the basis of responses to multiple specific queries. Each defined feature was tested by logistic regression. Sensitivity and specificity analyses were conducted to define the most robust set of clinical features associated with PCD. From 534 participants 18 years of age and younger, 205 were identified as having "definite PCD" (including 164 with two mutations in a PCD-associated gene), 187 were categorized as "other diagnosis or undefined," and 142 were defined as having "probable/possible PCD." Participants with "definite PCD" were compared with the "other diagnosis or undefined" group. Four criteria-defined clinical features were statistically predictive of PCD: laterality defect; unexplained neonatal respiratory distress; early-onset, year-round nasal congestion; and early-onset, year-round wet cough (adjusted odds ratios of 7.7, 6.6, 3.4, and 3.1, respectively). The sensitivity and specificity based on the number of criteria-defined clinical features were four features, 0.21 and 0.99, respectively; three features, 0.50 and 0.96, respectively; and two features, 0.80 and 0.72, respectively. Systematically defined early clinical features could help identify children, including infants, likely to have PCD. Clinical trial registered with ClinicalTrials.gov (NCT00323167).

Influences of Altered River Geomorphology on Channel-Floodplain Mass and Momentum Transfer

NASA Astrophysics Data System (ADS)

Byrne, C. F.; Stone, M. C.

2017-12-01

River management strategies, including both river engineering and restoration, have altered river geomorphology and associated lateral channel-floodplain connectivity throughout the world. This altered connectivity is known to drive changes in ecologic and geomorphic processes during floods, however, quantification of altered connectivity is difficult due to the highly dynamic spatial and temporal nature of flood wave conditions. The objective of this research was to quantify the physical processes of lateral mass and momentum transfer at the channel-floodplain interface. The objective was achieved with the implementation of novel scripting and high-resolution, two-dimensional hydrodynamic modeling techniques under unsteady flow conditions. The process-based analysis focused on three geomorphic feature types within the Middle Rio Grande, New Mexico, USA: (1) historical floodplain surfaces, (2) inset floodplain surfaces formed as a result of channel training and hydrologic alteration, and (3) mechanically restored floodplain surfaces. Results suggest that inset floodplain feature types are not only subject to greater mass and momentum transfer magnitudes, but those connections are also more heterogeneous in nature compared with historical feature types. While restored floodplain feature types exhibit transfer magnitudes and heterogeneity comparable to inset feature types, the surfaces are not of great enough spatial extent to substantially influence total channel-floodplain mass and momentum transfer. Mass and momentum transfer also displayed differing characteristic changes as a result of increased flood magnitude, indicating that linked hydrodynamic processes can be altered differently as a result of geomorphic and hydrologic change. The results display the potential of high-resolution modeling strategies in capturing the spatial and temporal complexities of river processes. In addition, the results have implications for other fields of river science including biogeochemical exchange at the channel-floodplain interface and quantification of process associated with environmental flow and river restoration strategies.

SU-F-R-24: Identifying Prognostic Imaging Biomarkers in Early Stage Lung Cancer Using Radiomics

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

Zeng, X; Wu, J; Cui, Y

2016-06-15

Purpose: Patients diagnosed with early stage lung cancer have favorable outcomes when treated with surgery or stereotactic radiotherapy. However, a significant proportion (∼20%) of patients will develop metastatic disease and eventually die of the disease. The purpose of this work is to identify quantitative imaging biomarkers from CT for predicting overall survival in early stage lung cancer. Methods: In this institutional review board-approved HIPPA-compliant retrospective study, we retrospectively analyzed the diagnostic CT scans of 110 patients with early stage lung cancer. Data from 70 patients were used for training/discovery purposes, while those of remaining 40 patients were used for independentmore » validation. We extracted 191 radiomic features, including statistical, histogram, morphological, and texture features. Cox proportional hazard regression model, coupled with the least absolute shrinkage and selection operator (LASSO), was used to predict overall survival based on the radiomic features. Results: The optimal prognostic model included three image features from the Law’s feature and wavelet texture. In the discovery cohort, this model achieved a concordance index or CI=0.67, and it separated the low-risk from high-risk groups in predicting overall survival (hazard ratio=2.72, log-rank p=0.007). In the independent validation cohort, this radiomic signature achieved a CI=0.62, and significantly stratified the low-risk and high-risk groups in terms of overall survival (hazard ratio=2.20, log-rank p=0.042). Conclusion: We identified CT imaging characteristics associated with overall survival in early stage lung cancer. If prospectively validated, this could potentially help identify high-risk patients who might benefit from adjuvant systemic therapy.« less

SPOT satellite mapping of Ice Stream B

NASA Technical Reports Server (NTRS)

Merry, Carolyn J.

1993-01-01

Numerous features of glaciological significance appear on two adjoining SPOT High Resolution Visible (HRV) images that cover the onset region of ice stream B. Many small-scale features, such as crevasses and drift plumes, have been previously observed in aerial photography. Subtle features, such as long flow traces that have not been mapped previously, are also clear in the satellite imagery. Newly discovered features include ladder-like runners and rungs within certain shear margins, flow traces that are parallel to ice flow, unusual crevasse patterns, and flow traces originating within shear margins. An objective of our work is to contribute to an understanding of the genesis of the features observed in satellite imagery. The genetic possibilities for flow traces, other lineations, bands of transverse crevasses, shear margins, mottles, and lumps and warps are described.

Inventory and analysis of natural vegetation and related resources from space and high altitude photography

NASA Technical Reports Server (NTRS)

Poulton, C. E.; Faulkner, D. P.; Johnson, J. R.; Mouat, D. A.; Schrumpf, B. J.

1971-01-01

A high altitude photomosaic resource map of Site 29 was produced which provided an opportunity to test photo interpretation accuracy of natural vegetation resource features when mapped at a small (1:133,400) scale. Helicopter reconnaissance over 144 previously selected test points revealed a highly adequate level of photo interpretation accuracy. In general, the reasons for errors could be accounted for. The same photomosaic resource map enabled construction of interpretive land use overlays. Based on features of the landscape, including natural vegetation types, judgements for land use suitability were made and have been presented for two types of potential land use. These two, agriculture and urbanization, represent potential land use conflicts.

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

Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions.

PubMed

Aksu, Yaman; Miller, David J; Kesidis, George; Yang, Qing X

2010-05-01

Feature selection for classification in high-dimensional spaces can improve generalization, reduce classifier complexity, and identify important, discriminating feature "markers." For support vector machine (SVM) classification, a widely used technique is recursive feature elimination (RFE). We demonstrate that RFE is not consistent with margin maximization, central to the SVM learning approach. We thus propose explicit margin-based feature elimination (MFE) for SVMs and demonstrate both improved margin and improved generalization, compared with RFE. Moreover, for the case of a nonlinear kernel, we show that RFE assumes that the squared weight vector 2-norm is strictly decreasing as features are eliminated. We demonstrate this is not true for the Gaussian kernel and, consequently, RFE may give poor results in this case. MFE for nonlinear kernels gives better margin and generalization. We also present an extension which achieves further margin gains, by optimizing only two degrees of freedom--the hyperplane's intercept and its squared 2-norm--with the weight vector orientation fixed. We finally introduce an extension that allows margin slackness. We compare against several alternatives, including RFE and a linear programming method that embeds feature selection within the classifier design. On high-dimensional gene microarray data sets, University of California at Irvine (UCI) repository data sets, and Alzheimer's disease brain image data, MFE methods give promising results.

An audiovisual emotion recognition system

NASA Astrophysics Data System (ADS)

Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

2007-12-01

Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

Histopathologic grading of anaplasia in retinoblastoma.

PubMed

Mendoza, Pia R; Specht, Charles S; Hubbard, G Baker; Wells, Jill R; Lynn, Michael J; Zhang, Qing; Kong, Jun; Grossniklaus, Hans E

2015-04-01

To determine whether the degree of tumor anaplasia has prognostic value by evaluating its correlation with high-risk histopathologic features and clinical outcomes in a series of retinoblastoma patients. Retrospective clinicopathologic study. The clinical and pathologic findings in 266 patients who underwent primary enucleation for retinoblastoma were reviewed. The histologic degree of anaplasia was graded as retinocytoma, mild, moderate, or severe as defined by increasing cellular pleomorphism, number of mitoses, nuclear size, and nuclear hyperchromatism. Nuclear morphometric characteristics were measured. The clinical and pathologic data of 125 patients were compared using Kaplan-Meier estimates of survival. Fisher exact test and multivariate regression were used to analyze the association between anaplasia grade and high-risk histologic features. Increasing grade of anaplasia was associated with decreased overall survival (P = .003) and increased risk of metastasis (P = .0007). Histopathologic features that were associated with anaplasia included optic nerve invasion (P < .0001), choroidal invasion (P < .0001), and anterior segment invasion (P = .04). Multivariate analysis considering high-risk histopathology and anaplasia grading as predictors of distant metastasis and death showed that high-risk histopathology was statistically significant as an independent predictor (P = .01 for metastasis, P = .03 for death) but anaplasia was not (P = .63 for metastasis, P = .30 for death). In the absence of high-risk features, however, severe anaplasia identified an additional risk for metastasis (P = .0004) and death (P = .01). Grading of anaplasia may be a useful adjunct to standard histopathologic criteria in identifying retinoblastoma patients who do not have high-risk histologic features but still have an increased risk of metastasis and may need adjuvant therapy. Copyright © 2015 Elsevier Inc. All rights reserved.

Beyond the Revitalizing High School Libraries Initiative

ERIC Educational Resources Information Center

Marczynski, Paula Townsend

2009-01-01

In 2003 the Public Education Network developed the pilot Revitalizing High School Libraries (RHSL) initiative, funded by The New York Life Foundation. Based on the Library Power Program, it included many of the same features--collaborative planning, flexible scheduling, collection development, and facility renovation--with a focus on how this…

Identifying Objective Physiological Markers and Modifiable Behaviors for Self-Reported Stress and Mental Health Status Using Wearable Sensors and Mobile Phones: Observational Study.

PubMed

Sano, Akane; Taylor, Sara; McHill, Andrew W; Phillips, Andrew Jk; Barger, Laura K; Klerman, Elizabeth; Picard, Rosalind

2018-06-08

Wearable and mobile devices that capture multimodal data have the potential to identify risk factors for high stress and poor mental health and to provide information to improve health and well-being. We developed new tools that provide objective physiological and behavioral measures using wearable sensors and mobile phones, together with methods that improve their data integrity. The aim of this study was to examine, using machine learning, how accurately these measures could identify conditions of self-reported high stress and poor mental health and which of the underlying modalities and measures were most accurate in identifying those conditions. We designed and conducted the 1-month SNAPSHOT study that investigated how daily behaviors and social networks influence self-reported stress, mood, and other health or well-being-related factors. We collected over 145,000 hours of data from 201 college students (age: 18-25 years, male:female=1.8:1) at one university, all recruited within self-identified social groups. Each student filled out standardized pre- and postquestionnaires on stress and mental health; during the month, each student completed twice-daily electronic diaries (e-diaries), wore two wrist-based sensors that recorded continuous physical activity and autonomic physiology, and installed an app on their mobile phone that recorded phone usage and geolocation patterns. We developed tools to make data collection more efficient, including data-check systems for sensor and mobile phone data and an e-diary administrative module for study investigators to locate possible errors in the e-diaries and communicate with participants to correct their entries promptly, which reduced the time taken to clean e-diary data by 69%. We constructed features and applied machine learning to the multimodal data to identify factors associated with self-reported poststudy stress and mental health, including behaviors that can be possibly modified by the individual to improve these measures. We identified the physiological sensor, phone, mobility, and modifiable behavior features that were best predictors for stress and mental health classification. In general, wearable sensor features showed better classification performance than mobile phone or modifiable behavior features. Wearable sensor features, including skin conductance and temperature, reached 78.3% (148/189) accuracy for classifying students into high or low stress groups and 87% (41/47) accuracy for classifying high or low mental health groups. Modifiable behavior features, including number of naps, studying duration, calls, mobility patterns, and phone-screen-on time, reached 73.5% (139/189) accuracy for stress classification and 79% (37/47) accuracy for mental health classification. New semiautomated tools improved the efficiency of long-term ambulatory data collection from wearable and mobile devices. Applying machine learning to the resulting data revealed a set of both objective features and modifiable behavioral features that could classify self-reported high or low stress and mental health groups in a college student population better than previous studies and showed new insights into digital phenotyping. ©Akane Sano, Sara Taylor, Andrew W McHill, Andrew JK Phillips, Laura K Barger, Elizabeth Klerman, Rosalind Picard. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 08.06.2018.

Quantitative coronary plaque analysis predicts high-risk plaque morphology on coronary computed tomography angiography: results from the ROMICAT II trial.

PubMed

Liu, Ting; Maurovich-Horvat, Pál; Mayrhofer, Thomas; Puchner, Stefan B; Lu, Michael T; Ghemigian, Khristine; Kitslaar, Pieter H; Broersen, Alexander; Pursnani, Amit; Hoffmann, Udo; Ferencik, Maros

2018-02-01

Semi-automated software can provide quantitative assessment of atherosclerotic plaques on coronary CT angiography (CTA). The relationship between established qualitative high-risk plaque features and quantitative plaque measurements has not been studied. We analyzed the association between quantitative plaque measurements and qualitative high-risk plaque features on coronary CTA. We included 260 patients with plaque who underwent coronary CTA in the Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography (ROMICAT) II trial. Quantitative plaque assessment and qualitative plaque characterization were performed on a per coronary segment basis. Quantitative coronary plaque measurements included plaque volume, plaque burden, remodeling index, and diameter stenosis. In qualitative analysis, high-risk plaque was present if positive remodeling, low CT attenuation plaque, napkin-ring sign or spotty calcium were detected. Univariable and multivariable logistic regression analyses were performed to assess the association between quantitative and qualitative high-risk plaque assessment. Among 888 segments with coronary plaque, high-risk plaque was present in 391 (44.0%) segments by qualitative analysis. In quantitative analysis, segments with high-risk plaque had higher total plaque volume, low CT attenuation plaque volume, plaque burden and remodeling index. Quantitatively assessed low CT attenuation plaque volume (odds ratio 1.12 per 1 mm 3 , 95% CI 1.04-1.21), positive remodeling (odds ratio 1.25 per 0.1, 95% CI 1.10-1.41) and plaque burden (odds ratio 1.53 per 0.1, 95% CI 1.08-2.16) were associated with high-risk plaque. Quantitative coronary plaque characteristics (low CT attenuation plaque volume, positive remodeling and plaque burden) measured by semi-automated software correlated with qualitative assessment of high-risk plaque features.

Alcohol marketing in televised international football: frequency analysis.

PubMed

Adams, Jean; Coleman, James; White, Martin

2014-05-20

Alcohol marketing includes sponsorship of individuals, organisations and sporting events. Football (soccer) is one of the most popular spectator sports worldwide. No previous studies have quantified the frequency of alcohol marketing in a high profile international football tournament. The aims were to determine: the frequency and nature of visual references to alcohol in a representative sample of EURO2012 matches broadcast in the UK; and if frequency or nature varied between matches broadcast on public service and commercial channels, or between matches that did and did not feature England. Eight matches selected by stratified random sampling were recorded. All visual references to alcohol were identified using a tool with high inter-rater reliability. 1846 visual references to alcohol were identified over 1487 minutes of broadcast--an average of 1.24 references per minute. The mean number of references per minute was higher in matches that did vs did not feature England (p = 0.004), but did not differ between matches broadcast on public service vs commercial channels (p = 0.92). The frequency of visual references to alcohol was universally high and higher in matches featuring the only UK home team--England--suggesting that there may be targeting of particularly highly viewed matches. References were embedded in broadcasts, and not particular to commercial channels including paid-for advertising. New UK codes-of-conduct on alcohol marketing at sporting events will not reduce the level of marketing reported here.

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

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.

Hydrovolcanic features on Mars: Preliminary observations from the first Mars year of HiRISE imaging

USGS Publications Warehouse

Keszthelyi, L.P.; Jaeger, W.L.; Dundas, C.M.; Martinez-Alonso, S.; McEwen, A.S.; Milazzo, M.P.

2010-01-01

We provide an overview of features indicative of the interaction between water and lava and/or magma on Mars as seen by the High Resolution Imaging Science Experiment (HiRISE) camera during the Primary Science Phase of the Mars Reconnaissance Orbiter (MRO) mission. The ability to confidently resolve meter-scale features from orbit has been extremely useful in the study of the most pristine examples. In particular, HiRISE has allowed the documentation of previously undescribed features associated with phreatovolcanic cones (formed by the interaction of lava and groundwater) on rapidly emplaced flood lavas. These include "moats" and "wakes" that indicate that the lava crust was thin and mobile, respectively [Jaeger, W.L., Keszthelyi, L.P., McEwen, A.S., Dundas, C.M., Russel, P.S., 2007. Science 317, 1709-1711]. HiRISE has also discovered entablature-style jointing in lavas that is indicative of water-cooling [Milazzo, M.P., Keszthelyi, L.P., Jaeger, W.L., Rosiek, M., Mattson, S., Verba, C., Beyer, R.A., Geissler, P.E., McEwen, A.S., and the HiRISE Team, 2009. Geology 37, 171-174]. Other observations strongly support the idea of extensive volcanic mudflows (lahars). Evidence for other forms of hydrovolcanism, including glaciovolcanic interactions, is more equivocal. This is largely because most older and high-latitude terrains have been extensively modified, masking any earlier 1-10 m scale features. Much like terrestrial fieldwork, the prerequisite for making full use of HiRISE's capabilities is finding good outcrops.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Cold-water refuges for climate resilience in Oregon coastal ...

EPA Pesticide Factsheets

Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effects of warm waters include impacts to salmon and steelhead populations that may already be stressed by habitat alteration, disease, predation, and fishing pressures. Thermal refuges may help mitigate the effects of increasing temperatures. In this presentation, we define cold-water refuges as areas buffered from regional climate effects by groundwater, physical habitat heterogeneity, or other watershed attributes. Processes forming these features include groundwater-surface water interactions, and hyporheic exchange at a range of spatial and temporal scales. Patterns associated with these processes may provide useful indicators for mapping and predicting the locations and extent of these features. Fish may congregate at high densities within cold-water refuges during critical periods of thermal stress, but there may be trade-offs associated with refuge use including predation, disease risk, and reduced foraging opportunities. These factors all contribute to determining refuge effectiveness. Watershed management and restoration strategies could consider these features and their potential utility to cold-water fish, and we conclude with examples of types of watershed restoration actions that might help foster cold-water refuge creation and maintenance.M Many rivers and streams in the Pacific Nort

[Image Feature Extraction and Discriminant Analysis of Xinjiang Uygur Medicine Based on Color Histogram].

PubMed

Hamit, Murat; Yun, Weikang; Yan, Chuanbo; Kutluk, Abdugheni; Fang, Yang; Alip, Elzat

2015-06-01

Image feature extraction is an important part of image processing and it is an important field of research and application of image processing technology. Uygur medicine is one of Chinese traditional medicine and researchers pay more attention to it. But large amounts of Uygur medicine data have not been fully utilized. In this study, we extracted the image color histogram feature of herbal and zooid medicine of Xinjiang Uygur. First, we did preprocessing, including image color enhancement, size normalizition and color space transformation. Then we extracted color histogram feature and analyzed them with statistical method. And finally, we evaluated the classification ability of features by Bayes discriminant analysis. Experimental results showed that high accuracy for Uygur medicine image classification was obtained by using color histogram feature. This study would have a certain help for the content-based medical image retrieval for Xinjiang Uygur medicine.

Generic decoding of seen and imagined objects using hierarchical visual features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-05-22

Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a set of features rendered invariant through hierarchical processing. We show that visual features, including those derived from a deep convolutional neural network, can be predicted from fMRI patterns, and that greater accuracy is achieved for low-/high-level features with lower-/higher-level visual areas, respectively. Predicted features are used to identify seen/imagined object categories (extending beyond decoder training) from a set of computed features for numerous object images. Furthermore, decoding of imagined objects reveals progressive recruitment of higher-to-lower visual representations. Our results demonstrate a homology between human and machine vision and its utility for brain-based information retrieval.

[EEG-correlates of pilots' functional condition in simulated flight dynamics].

PubMed

Kiroy, V N; Aslanyan, E V; Bakhtin, O M; Minyaeva, N R; Lazurenko, D M

2015-01-01

The spectral characteristics of the EEG recorded on two professional pilots in the simulator TU-154 aircraft in flight dynamics, including takeoff, landing and horizontal flight (in particular during difficult conditions) were analyzed. EEG recording was made with frequency band 0.1-70 Hz continuously from 15 electrodes. The EEG recordings were evaluated using analysis of variance and discriminant analysis. Statistical significant of the identified differences and the influence of the main factors and their interactions were evaluated using Greenhouse - Gaiser corrections. It was shown that the spectral characteristics of the EEG are highly informative features of the state of the pilots, reflecting the different flight phases. High validity ofthe differences including individual characteristic, indicates their non-random nature and the possibility of constructing a system of pilots' state control during all phases of flight, based on EEG features.

Robust and Effective Component-based Banknote Recognition for the Blind

PubMed Central

Hasanuzzaman, Faiz M.; Yang, Xiaodong; Tian, YingLi

2012-01-01

We develop a novel camera-based computer vision technology to automatically recognize banknotes for assisting visually impaired people. Our banknote recognition system is robust and effective with the following features: 1) high accuracy: high true recognition rate and low false recognition rate, 2) robustness: handles a variety of currency designs and bills in various conditions, 3) high efficiency: recognizes banknotes quickly, and 4) ease of use: helps blind users to aim the target for image capture. To make the system robust to a variety of conditions including occlusion, rotation, scaling, cluttered background, illumination change, viewpoint variation, and worn or wrinkled bills, we propose a component-based framework by using Speeded Up Robust Features (SURF). Furthermore, we employ the spatial relationship of matched SURF features to detect if there is a bill in the camera view. This process largely alleviates false recognition and can guide the user to correctly aim at the bill to be recognized. The robustness and generalizability of the proposed system is evaluated on a dataset including both positive images (with U.S. banknotes) and negative images (no U.S. banknotes) collected under a variety of conditions. The proposed algorithm, achieves 100% true recognition rate and 0% false recognition rate. Our banknote recognition system is also tested by blind users. PMID:22661884

Mass loss, levitation, accretion, and the sharp-lined features in hot white dwarfs

NASA Technical Reports Server (NTRS)

Bruhweiler, F. C.; Kondo, Y.

1983-01-01

A study has been conducted of eight white dwarfs, including seven DA and one He-rich types. The study is based on high-resolution observations conducted with the aid of the International Ultraviolet Explorer. Four of the dwarfs show features related to heavy elements which are not interstellar in origin. It is tentatively suggested that, at least in the hottest low-gravity DA white dwarfs, the observed narrow-lined features are formed in expanding halos or winds associated with the white dwarfs. Theoretically, stable white dwarf halos should actually be coronae with temperatures in excess of 1,000,000 K. However, the observed narrow-lined features do not suggest such high temperatures. The observed radial velocities suggest weak stellar winds in two hot white dwarfs, namely, G191-B2B and 2111+49. It is tentatively proposed that radiative levitation can explain the appearance of the observed metallic lines in the hot DA white dwarfs.

Special Features of Induction Annealing of Friction Stir Welded Joints of Medium-Alloy Steels

NASA Astrophysics Data System (ADS)

Priymak, E. Yu.; Stepanchukova, A. V.; Bashirova, E. V.; Fot, A. P.; Firsova, N. V.

2018-01-01

Welded joints of medium-alloy steels XJY750 and 40KhN2MA are studied in the initial condition and after different variants of annealing. Special features of the phase transformations occurring in the welded steels are determined. Optimum modes of annealing are recommended for the studied welded joints of drill pipes, which provide a high level of mechanical properties including the case of impact loading.

A genome-wide association scan in admixed Latin Americans identifies loci influencing facial and scalp hair features

PubMed Central

Adhikari, Kaustubh; Fontanil, Tania; Cal, Santiago; Mendoza-Revilla, Javier; Fuentes-Guajardo, Macarena; Chacón-Duque, Juan-Camilo; Al-Saadi, Farah; Johansson, Jeanette A.; Quinto-Sanchez, Mirsha; Acuña-Alonzo, Victor; Jaramillo, Claudia; Arias, William; Barquera Lozano, Rodrigo; Macín Pérez, Gastón; Gómez-Valdés, Jorge; Villamil-Ramírez, Hugo; Hunemeier, Tábita; Ramallo, Virginia; Silva de Cerqueira, Caio C.; Hurtado, Malena; Villegas, Valeria; Granja, Vanessa; Gallo, Carla; Poletti, Giovanni; Schuler-Faccini, Lavinia; Salzano, Francisco M.; Bortolini, Maria-Cátira; Canizales-Quinteros, Samuel; Rothhammer, Francisco; Bedoya, Gabriel; Gonzalez-José, Rolando; Headon, Denis; López-Otín, Carlos; Tobin, Desmond J.; Balding, David; Ruiz-Linares, Andrés

2016-01-01

We report a genome-wide association scan in over 6,000 Latin Americans for features of scalp hair (shape, colour, greying, balding) and facial hair (beard thickness, monobrow, eyebrow thickness). We found 18 signals of association reaching genome-wide significance (P values 5 × 10−8 to 3 × 10−119), including 10 novel associations. These include novel loci for scalp hair shape and balding, and the first reported loci for hair greying, monobrow, eyebrow and beard thickness. A newly identified locus influencing hair shape includes a Q30R substitution in the Protease Serine S1 family member 53 (PRSS53). We demonstrate that this enzyme is highly expressed in the hair follicle, especially the inner root sheath, and that the Q30R substitution affects enzyme processing and secretion. The genome regions associated with hair features are enriched for signals of selection, consistent with proposals regarding the evolution of human hair. PMID:26926045

Use of MRI in Differentiation of Papillary Renal Cell Carcinoma Subtypes: Qualitative and Quantitative Analysis.

PubMed

Doshi, Ankur M; Ream, Justin M; Kierans, Andrea S; Bilbily, Matthew; Rusinek, Henry; Huang, William C; Chandarana, Hersh

2016-03-01

The purpose of this study was to determine whether qualitative and quantitative MRI feature analysis is useful for differentiating type 1 from type 2 papillary renal cell carcinoma (PRCC). This retrospective study included 21 type 1 and 17 type 2 PRCCs evaluated with preoperative MRI. Two radiologists independently evaluated various qualitative features, including signal intensity, heterogeneity, and margin. For the quantitative analysis, a radiology fellow and a medical student independently drew 3D volumes of interest over the entire tumor on T2-weighted HASTE images, apparent diffusion coefficient parametric maps, and nephrographic phase contrast-enhanced MR images to derive first-order texture metrics. Qualitative and quantitative features were compared between the groups. For both readers, qualitative features with greater frequency in type 2 PRCC included heterogeneous enhancement, indistinct margin, and T2 heterogeneity (all, p < 0.035). Indistinct margins and heterogeneous enhancement were independent predictors (AUC, 0.822). Quantitative analysis revealed that apparent diffusion coefficient, HASTE, and contrast-enhanced entropy were greater in type 2 PRCC (p < 0.05; AUC, 0.682-0.716). A combined quantitative and qualitative model had an AUC of 0.859. Qualitative features within the model had interreader concordance of 84-95%, and the quantitative data had intraclass coefficients of 0.873-0.961. Qualitative and quantitative features can help discriminate between type 1 and type 2 PRCC. Quantitative analysis may capture useful information that complements the qualitative appearance while benefiting from high interobserver agreement.

High Availability in Optical Networks

NASA Astrophysics Data System (ADS)

Grover, Wayne D.; Wosinska, Lena; Fumagalli, Andrea

2005-09-01

Call for Papers: High Availability in Optical Networks Submission Deadline: 1 January 2006 The Journal of Optical Networking (JON) is soliciting papers for a feature Issue pertaining to all aspects of reliable components and systems for optical networks and concepts, techniques, and experience leading to high availability of services provided by optical networks. Most nations now recognize that telecommunications in all its forms -- including voice, Internet, video, and so on -- are "critical infrastructure" for the society, commerce, government, and education. Yet all these services and applications are almost completely dependent on optical networks for their realization. "Always on" or apparently unbreakable communications connectivity is the expectation from most users and for some services is the actual requirement as well. Achieving the desired level of availability of services, and doing so with some elegance and efficiency, is a meritorious goal for current researchers. This requires development and use of high-reliability components and subsystems, but also concepts for active reconfiguration and capacity planning leading to high availability of service through unseen fast-acting survivability mechanisms. The feature issue is also intended to reflect some of the most important current directions and objectives in optical networking research, which include the aspects of integrated design and operation of multilevel survivability and realization of multiple Quality-of-Protection service classes. Dynamic survivable service provisioning, or batch re-provisioning is an important current theme, as well as methods that achieve high availability at far less investment in spare capacity than required by brute force service path duplication or 100% redundant rings, which is still the surprisingly prevalent practice. Papers of several types are envisioned in the feature issue, including outlook and forecasting types of treatments, optimization and analysis, new concepts for survivability, or papers on availability analysis methods or results. Customer, vendor, and researcher viewpoints and priorities will all be given consideration. Especially valuable to the community would be papers that include or provide measured data on actual reliability and availability performance of optical networking components or systems. The scope of the papers includes, but is not limited to, the following topics: Reliability and availability measurement techniques specific to optical network devices or services. Data on SRLG statistics and frequency of different actual failure causes. Real-life accounts or data on failure and repair rates or projected values for use in availability analysis. Availability analysis methods, especially for survivable networks with reconfigurable or adaptive failure-specific responses. Availability analysis and comparisons of basic schemes for survivability. Differentiated availability schemes. Design for Multiple Quality of Protection. Different schemes for on-demand survivable service provisioning. Basic comparisons or proposals of new survivability mechanisms and architectures. Concepts yielding higher than 1+1 protection switching availability at less than 100% redundancy. Survivable service provisioning in domains of optical transparency: dealing with signal impairments. To submit to this special issue, follow the normal procedure for submission to JON, indicating "Feature Issue: Optical Network Availability" in the "Comments" field of the online submission form. For all other questions relating to this feature issue, please send an e-mail to jon@osa.org, subject line "Feature Issue: Optical Network Availability." Additional information can be found on the JON website: http://www.osa-jon.org/submission/

Social Justice Training in School Psychology: Applying Principles of Organizational Consultation to Facilitate Change in Graduate Programs

ERIC Educational Resources Information Center

Grapin, Sally L.

2017-01-01

Scholars and professional organizations have called for an increased emphasis on social justice training in applied psychology graduate programs, including school psychology programs (SPPs). During the past decade, emerging research has identified some features of high-quality social justice education, including a clear program mission statement…

Opportunities and barriers to establishing a cell therapy programme in South Africa

PubMed Central

2013-01-01

The establishment of a cell therapy programme in South Africa has the potential to contribute to the alleviation of the country’s high disease burden and also to contribute to economic growth. South Africa has various positive attributes that favour the establishment of such a high-profile venture; however, there are also significant obstacles which need to be overcome. We discuss the positive and negative features of the current health biotechnology sector. The positive factors include a strong market pull and a highly innovative scientific and medical community, while the most problematic features include the lack of human resources and education and limited funding. The South African Government has undertaken to strengthen the biotechnology sector in general, but a focus on cell therapy is lacking. The next important step would be to provide financial, legal/ethical and other support for groups that are active and productive in this field through the development of a local cell therapy programme. PMID:23719318

Evidence for recent groundwater seepage and surface runoff on Mars.

PubMed

Malin, M C; Edgett, K S

2000-06-30

Relatively young landforms on Mars, seen in high-resolution images acquired by the Mars Global Surveyor Mars Orbiter Camera since March 1999, suggest the presence of sources of liquid water at shallow depths beneath the martian surface. Found at middle and high martian latitudes (particularly in the southern hemisphere), gullies within the walls of a very small number of impact craters, south polar pits, and two of the larger martian valleys display geomorphic features that can be explained by processes associated with groundwater seepage and surface runoff. The relative youth of the landforms is indicated by the superposition of the gullies on otherwise geologically young surfaces and by the absence of superimposed landforms or cross-cutting features, including impact craters, small polygons, and eolian dunes. The limited size and geographic distribution of the features argue for constrained source reservoirs.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

Remembering complex objects in visual working memory: do capacity limits restrict objects or features?

PubMed

Hardman, Kyle O; Cowan, Nelson

2015-03-01

Visual working memory stores stimuli from our environment as representations that can be accessed by high-level control processes. This study addresses a longstanding debate in the literature about whether storage limits in visual working memory include a limit to the complexity of discrete items. We examined the issue with a number of change-detection experiments that used complex stimuli that possessed multiple features per stimulus item. We manipulated the number of relevant features of the stimulus objects in order to vary feature load. In all of our experiments, we found that increased feature load led to a reduction in change-detection accuracy. However, we found that feature load alone could not account for the results but that a consideration of the number of relevant objects was also required. This study supports capacity limits for both feature and object storage in visual working memory. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Noise Gating Solar Images

NASA Astrophysics Data System (ADS)

DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

2017-08-01

I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO/AIA , SDO/HMI, STEREO/SECCHI, and GOES-R/SUVI) that explore the benefits and limits of the technique.

Improving Reading in Every Class: A Sourcebook for Teachers.

ERIC Educational Resources Information Center

Thomas, Ellen Lamar; Robinson, H. Alan

This sourcebook for high school teachers suggests procedures not only for teaching the fundamental process of reading, but also for teaching reading in all of the high school content areas. It features motivating activities, a subject-area index, and guide sheets and work sheets. Chapters include "How to Use This Book,""Building Vocabulary and…

Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases

PubMed Central

Nixon, Mark S.; Komogortsev, Oleg V.

2017-01-01

We introduce the intraclass correlation coefficient (ICC) to the biometric community as an index of the temporal persistence, or stability, of a single biometric feature. It requires, as input, a feature on an interval or ratio scale, and which is reasonably normally distributed, and it can only be calculated if each subject is tested on 2 or more occasions. For a biometric system, with multiple features available for selection, the ICC can be used to measure the relative stability of each feature. We show, for 14 distinct data sets (1 synthetic, 8 eye-movement-related, 2 gait-related, and 2 face-recognition-related, and one brain-structure-related), that selecting the most stable features, based on the ICC, resulted in the best biometric performance generally. Analyses based on using only the most stable features produced superior Rank-1-Identification Rate (Rank-1-IR) performance in 12 of 14 databases (p = 0.0065, one-tailed), when compared to other sets of features, including the set of all features. For Equal Error Rate (EER), using a subset of only high-ICC features also produced superior performance in 12 of 14 databases (p = 0. 0065, one-tailed). In general, then, for our databases, prescreening potential biometric features, and choosing only highly reliable features yields better performance than choosing lower ICC features or than choosing all features combined. We also determined that, as the ICC of a group of features increases, the median of the genuine similarity score distribution increases and the spread of this distribution decreases. There was no statistically significant similar relationships for the impostor distributions. We believe that the ICC will find many uses in biometric research. In case of the eye movement-driven biometrics, the use of reliable features, as measured by ICC, allowed to us achieve the authentication performance with EER = 2.01%, which was not possible before. PMID:28575030

Method to assess the temporal persistence of potential biometric features: Application to oculomotor, gait, face and brain structure databases.

PubMed

Friedman, Lee; Nixon, Mark S; Komogortsev, Oleg V

2017-01-01

We introduce the intraclass correlation coefficient (ICC) to the biometric community as an index of the temporal persistence, or stability, of a single biometric feature. It requires, as input, a feature on an interval or ratio scale, and which is reasonably normally distributed, and it can only be calculated if each subject is tested on 2 or more occasions. For a biometric system, with multiple features available for selection, the ICC can be used to measure the relative stability of each feature. We show, for 14 distinct data sets (1 synthetic, 8 eye-movement-related, 2 gait-related, and 2 face-recognition-related, and one brain-structure-related), that selecting the most stable features, based on the ICC, resulted in the best biometric performance generally. Analyses based on using only the most stable features produced superior Rank-1-Identification Rate (Rank-1-IR) performance in 12 of 14 databases (p = 0.0065, one-tailed), when compared to other sets of features, including the set of all features. For Equal Error Rate (EER), using a subset of only high-ICC features also produced superior performance in 12 of 14 databases (p = 0. 0065, one-tailed). In general, then, for our databases, prescreening potential biometric features, and choosing only highly reliable features yields better performance than choosing lower ICC features or than choosing all features combined. We also determined that, as the ICC of a group of features increases, the median of the genuine similarity score distribution increases and the spread of this distribution decreases. There was no statistically significant similar relationships for the impostor distributions. We believe that the ICC will find many uses in biometric research. In case of the eye movement-driven biometrics, the use of reliable features, as measured by ICC, allowed to us achieve the authentication performance with EER = 2.01%, which was not possible before.

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 at isolating and reporting the effects of social media features on DBCIs, cross-study comparisons, and evaluations. ©Sheik Mohammad Roushdat Ally Elaheebocus, Mark Weal, Leanne Morrison, Lucy Yardley. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.02.2018.

Classification of high-resolution multispectral satellite remote sensing images using extended morphological attribute profiles and independent component analysis

NASA Astrophysics Data System (ADS)

Wu, Yu; Zheng, Lijuan; Xie, Donghai; Zhong, Ruofei

2017-07-01

In this study, the extended morphological attribute profiles (EAPs) and independent component analysis (ICA) were combined for feature extraction of high-resolution multispectral satellite remote sensing images and the regularized least squares (RLS) approach with the radial basis function (RBF) kernel was further applied for the classification. Based on the major two independent components, the geometrical features were extracted using the EAPs method. In this study, three morphological attributes were calculated and extracted for each independent component, including area, standard deviation, and moment of inertia. The extracted geometrical features classified results using RLS approach and the commonly used LIB-SVM library of support vector machines method. The Worldview-3 and Chinese GF-2 multispectral images were tested, and the results showed that the features extracted by EAPs and ICA can effectively improve the accuracy of the high-resolution multispectral image classification, 2% larger than EAPs and principal component analysis (PCA) method, and 6% larger than APs and original high-resolution multispectral data. Moreover, it is also suggested that both the GURLS and LIB-SVM libraries are well suited for the multispectral remote sensing image classification. The GURLS library is easy to be used with automatic parameter selection but its computation time may be larger than the LIB-SVM library. This study would be helpful for the classification application of high-resolution multispectral satellite remote sensing images.

Analysis of Web Spam for Non-English Content: Toward More Effective Language-Based Classifiers

PubMed Central

Alsaleh, Mansour; Alarifi, Abdulrahman

2016-01-01

Web spammers aim to obtain higher ranks for their web pages by including spam contents that deceive search engines in order to include their pages in search results even when they are not related to the search terms. Search engines continue to develop new web spam detection mechanisms, but spammers also aim to improve their tools to evade detection. In this study, we first explore the effect of the page language on spam detection features and we demonstrate how the best set of detection features varies according to the page language. We also study the performance of Google Penguin, a newly developed anti-web spamming technique for their search engine. Using spam pages in Arabic as a case study, we show that unlike similar English pages, Google anti-spamming techniques are ineffective against a high proportion of Arabic spam pages. We then explore multiple detection features for spam pages to identify an appropriate set of features that yields a high detection accuracy compared with the integrated Google Penguin technique. In order to build and evaluate our classifier, as well as to help researchers to conduct consistent measurement studies, we collected and manually labeled a corpus of Arabic web pages, including both benign and spam pages. Furthermore, we developed a browser plug-in that utilizes our classifier to warn users about spam pages after clicking on a URL and by filtering out search engine results. Using Google Penguin as a benchmark, we provide an illustrative example to show that language-based web spam classifiers are more effective for capturing spam contents. PMID:27855179

Analysis of Web Spam for Non-English Content: Toward More Effective Language-Based Classifiers.

PubMed

Alsaleh, Mansour; Alarifi, Abdulrahman

2016-01-01

Web spammers aim to obtain higher ranks for their web pages by including spam contents that deceive search engines in order to include their pages in search results even when they are not related to the search terms. Search engines continue to develop new web spam detection mechanisms, but spammers also aim to improve their tools to evade detection. In this study, we first explore the effect of the page language on spam detection features and we demonstrate how the best set of detection features varies according to the page language. We also study the performance of Google Penguin, a newly developed anti-web spamming technique for their search engine. Using spam pages in Arabic as a case study, we show that unlike similar English pages, Google anti-spamming techniques are ineffective against a high proportion of Arabic spam pages. We then explore multiple detection features for spam pages to identify an appropriate set of features that yields a high detection accuracy compared with the integrated Google Penguin technique. In order to build and evaluate our classifier, as well as to help researchers to conduct consistent measurement studies, we collected and manually labeled a corpus of Arabic web pages, including both benign and spam pages. Furthermore, we developed a browser plug-in that utilizes our classifier to warn users about spam pages after clicking on a URL and by filtering out search engine results. Using Google Penguin as a benchmark, we provide an illustrative example to show that language-based web spam classifiers are more effective for capturing spam contents.

Stress assessment based on EEG univariate features and functional connectivity measures.

PubMed

Alonso, J F; Romero, S; Ballester, M R; Antonijoan, R M; Mañanas, M A

2015-07-01

The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Temporal features of word-initial /s/+stop clusters in bilingual Mandarin-English children and monolingual English children and adults.

PubMed

Yang, Jing

2018-03-01

This study investigated the durational features of English word-initial /s/+stop clusters produced by bilingual Mandarin (L1)-English (L2) children and monolingual English children and adults. The participants included two groups of five- to six-year-old bilingual children: low proficiency in the L2 (Bi-low) and high proficiency in the L2 (Bi-high), one group of age-matched English children, and one group of English adults. Each participant produced a list of English words containing /sp, st, sk/ at the word-initial position followed by /a, i, u/, respectively. The absolute durations of the clusters and cluster elements and the durational proportions of elements to the overall cluster were measured. The results revealed that Bi-high children behaved similarly to the English monolinguals whereas Bi-low children used a different strategy of temporal organization to coordinate the cluster components in comparison to the English monolinguals and Bi-high children. The influence of language experience and continuing development of temporal features in children were discussed.

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

Moroz, P.E.

A new stellarator configuration, the Double-Helix Stellarator (DHS), is introduced. This novel configuration features a double-helix center post as the only helical element of the stellarator coil system. The DHS configuration has many unique characteristics. One of them is the extreme low plasma aspect ratio, A {approx} 1--1.2. Other advantages include a high enclosed volume, appreciable rotational transform, and a possibility of extreme-high-{beta} MHD equilibria. Moreover, the DHS features improved transport characteristics caused by the absence of the magnetic field ripple on the outboard of the torus. Compactness, simplicity and modularity of the coil system add to the DHS advantagesmore » for fusion applications.« less

Recent progress of carbon nanotube field emitters and their application.

PubMed

Seelaboyina, Raghunandan; Choi, Wonbong

2007-01-01

The potential of utilizing carbon nanotube field emission properties is an attractive feature for future vacuum electronic devices including: high power microwave, miniature x-ray, backlight for liquid crystal displays and flat panel displays. Their high emission current, nano scale geometry, chemical inertness and low threshold voltage for emission are attractive features for the field emission applications. In this paper we review the recent developments of carbon nanotube field emitters and their device applications. We also discuss the latest results on field emission current amplification achieved with an electron multiplier microchannel plate, and emission performance of multistage field emitter based on oxide nanowire operated in poor vacuum.

Laboratory simulation of infrared astrophysical features. Ph.D. Thesis; [emission spectra of comets

NASA Technical Reports Server (NTRS)

Rose, L. A.

1977-01-01

Intermediate resolution emission spectroscopy was used to study a group of 9 terrestrial silicates, 1 synthetic silicate, 6 meteorites and 2 lunar soils; comparisons were made with the intermediate resolution spectra of Comet Kohoutek in order to determine which materials best simulate the 10um astrophysical feature. Mixtures of silicates which would yield spectra matching the spectrum of the comet in the 10um region include: (1) A hydrous layer lattice silicate in combination with a high temperature condensate; (2) an amorphous magnesium silicate in combination with a high temperature condensate and (3) glassy olivine and glassy anorthite in approximately equal proportions.

Histopathologic Grading of Anaplasia in Retinoblastoma

PubMed Central

Mendoza, Pia R.; Specht, Charles S.; Hubbard, G. Baker; Wells, Jill R.; Lynn, Michael J.; Zhang, Qing; Kong, Jun; Grossniklaus, Hans E.

2014-01-01

Purpose To determine whether the degree of tumor anaplasia has prognostic value by evaluating its correlation with high-risk histopathologic features and clinical outcomes in a series of retinoblastoma patients. Design Retrospective clinicopathologic study. Methods The clinical and pathologic findings in 266 patients who underwent primary enucleation for retinoblastoma were reviewed. The histologic degree of anaplasia was graded as retinocytoma, mild, moderate, or severe as defined by increasing cellular pleomorphism, number of mitoses, nuclear size, and nuclear hyperchromatism. Nuclear morphometric characteristics were measured. The clinical and pathologic data of 125 patients were compared using Kaplan-Meier estimates of survival. Fisher's exact test and multivariate regression were used to analyze the association between anaplasia grade and high-risk histologic features. Results Increasing grade of anaplasia was associated with decreased overall survival (p=0.003) and increased risk of metastasis (p=0.0007). Histopathologic features that were associated with anaplasia included optic nerve invasion (p<0.0001), choroidal invasion (p=<0.0001), and anterior segment invasion (p=0.04). Multivariate analysis considering high-risk histopathology and anaplasia grading as predictors of distant metastasis and death showed that high-risk histopathology was statistically significant as an independent predictor (p=0.01 for metastasis, p=0.03 for death) but anaplasia was not (p=0.63 for metastasis, p=0.30 for death). In the absence of high-risk features, however, severe anaplasia identified an additional risk for metastasis (p=0.0004) and death (p=0.01). Conclusion Grading of anaplasia may be a useful adjunct to standard histopathologic criteria in identifying retinoblastoma patients who do not have high-risk histologic features but still have an increased risk of metastasis and may need adjuvant therapy. PMID:25528954

MRI differentiation of low-grade from high-grade appendicular chondrosarcoma.

PubMed

Douis, Hassan; Singh, Leanne; Saifuddin, Asif

2014-01-01

To identify magnetic resonance imaging (MRI) features which differentiate low-grade chondral lesions (atypical cartilaginous tumours/grade 1 chondrosarcoma) from high-grade chondrosarcomas (grade 2, grade 3 and dedifferentiated chondrosarcoma) of the major long bones. We identified all patients treated for central atypical cartilaginous tumours and central chondrosarcoma of major long bones (humerus, femur, tibia) over a 13-year period. The MRI studies were assessed for the following features: bone marrow oedema, soft tissue oedema, bone expansion, cortical thickening, cortical destruction, active periostitis, soft tissue mass and tumour length. The MRI-features were compared with the histopathological tumour grading using univariate, multivariate logistic regression and receiver operating characteristic curve (ROC) analyses. One hundred and seventy-nine tumours were included in this retrospective study. There were 28 atypical cartilaginous tumours, 79 grade 1 chondrosarcomas, 36 grade 2 chondrosarcomas, 13 grade 3 chondrosarcomas and 23 dedifferentiated chondrosarcomas. Multivariate analysis demonstrated that bone expansion (P = 0.001), active periostitis (P = 0.001), soft tissue mass (P < 0.001) and tumour length (P < 0.001) were statistically significant differentiating factors between low-grade and high-grade chondral lesions with an area under the ROC curve of 0.956. On MRI, bone expansion, active periostitis, soft tissue mass and tumour length can reliably differentiate high-grade chondrosarcomas from low-grade chondral lesions of the major long bones. • Accurate differentiation of low-grade from high-grade chondrosarcomas is essential before surgery • MRI can reliably differentiate high-grade from low-grade chondrosarcomas of long bone • Differentiating features are bone expansion, periostitis, soft tissue mass and tumour length • Presence of these four MRI features demonstrated a diagnostic accuracy (AUC) of 95.6 % • The findings may result in more accurate diagnosis before definitive surgery.

Liver transplant patients have a similar risk of progression as sporadic patients with branch duct intraductal papillary mucinous neoplasms

PubMed Central

Lennon, Anne Marie; Victor, David; Zaheer, Atif; Ostovaneh, Mohammad Reza; Jeh, Jessica; Law, Joanna K.; Rezaee, Neda; Molin, Marco Dal; Ahn, Young Joon; Wu, Wenchuan; Khashab, Mouen A.; Girotra, Mohit; Ahuja, Nita; Makary, Martin A.; Weiss, Matthew J.; Hirose, Kenzo; Goggins, Michael; Hruban, Ralph H.; Cameron, Andrew; Wolfgang, Christopher L.; Singh, Vikesh K.; Gurakar, Ahmet

2015-01-01

Background Intraductal papillary mucinous neoplasms (IPMNs) have malignant potential, and can progress from low- to high-grade dysplasia to invasive adenocarcinoma. The management of patients with IPMNs is dependent on their risk of malignant progression, with surgical resection recommended for patients with branch duct-IPMN (BD-IPMN) who develop high-risk features. There is increasing evidence that liver transplant patients are at increased risk of extra-hepatic malignancy. However there are few data regarding the risk of progression of BD-IPMNs in liver transplant recipients. The aim of this study was to determine if liver transplant recipients with BD-IPMNs are at higher risk of developing high-risk features than patients with BD-IPMNs who did not receive a transplant. Methods Consecutive patients who underwent a liver transplant with BD-IPMNs were included. Patients with BD-IPMNs with no history of immunosuppression were used as controls. Progression of the BD-IPMNs was defined as development of a high-risk feature (jaundice, dilated main pancreatic duct, mural nodule, cytology suspicious or diagnostic for malignancy, cyst diameter ≥3cm). Results Twenty three liver transplant patients with BD-IPMN were compared with 274 control patients. The median length of follow-up was 53.7 and 24 months in liver transplant and control groups respectively. Four (17.4%) liver transplant patients and 45 (16.4%) controls developed high-risk features (p=0.99). In multivariate analysis, progression of BD-IPMNs was associated with age at diagnosis but not with liver transplantation. Conclusion There was no statistically significant difference in the risk of developing high-risk features between the liver transplant and control groups. PMID:25155689

Exploring ESASky

NASA Astrophysics Data System (ADS)

De Marchi, Guido; ESASky Team

2017-06-01

ESASky is a science-driven discovery portal for all ESA space astronomy missions. It also includes missions from international partners such as Suzaku and Chandra. The first public release of ESASky features interfaces for sky exploration and for single and multiple target searches. Using the application requires no prior-knowledge of any of the missions involved and gives users world-wide simplified access to high-level science-ready data products from space-based Astronomy missions, plus a number of ESA-produced source catalogues, including the Gaia Data Release 1 catalogue. We highlight here the latest features to be developed, including one that allows the user to project onto the sky the footprints of the JWST instruments, at any chosen position and orientation. This tool has been developed to aid JWST astronomers when they are defining observing proposals. We aim to include other missions and instruments in the near future.

A TV Camera System Which Extracts Feature Points For Non-Contact Eye Movement Detection

NASA Astrophysics Data System (ADS)

Tomono, Akira; Iida, Muneo; Kobayashi, Yukio

1990-04-01

This paper proposes a highly efficient camera system which extracts, irrespective of background, feature points such as the pupil, corneal reflection image and dot-marks pasted on a human face in order to detect human eye movement by image processing. Two eye movement detection methods are sugested: One utilizing face orientation as well as pupil position, The other utilizing pupil and corneal reflection images. A method of extracting these feature points using LEDs as illumination devices and a new TV camera system designed to record eye movement are proposed. Two kinds of infra-red LEDs are used. These LEDs are set up a short distance apart and emit polarized light of different wavelengths. One light source beams from near the optical axis of the lens and the other is some distance from the optical axis. The LEDs are operated in synchronization with the camera. The camera includes 3 CCD image pick-up sensors and a prism system with 2 boundary layers. Incident rays are separated into 2 wavelengths by the first boundary layer of the prism. One set of rays forms an image on CCD-3. The other set is split by the half-mirror layer of the prism and forms an image including the regularly reflected component by placing a polarizing filter in front of CCD-1 or another image not including the component by not placing a polarizing filter in front of CCD-2. Thus, three images with different reflection characteristics are obtained by three CCDs. Through the experiment, it is shown that two kinds of subtraction operations between the three images output from CCDs accentuate three kinds of feature points: the pupil and corneal reflection images and the dot-marks. Since the S/N ratio of the subtracted image is extremely high, the thresholding process is simple and allows reducting the intensity of the infra-red illumination. A high speed image processing apparatus using this camera system is decribed. Realtime processing of the subtraction, thresholding and gravity position calculation of the feature points is possible.

Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning

NASA Astrophysics Data System (ADS)

Vetrivel, Anand; Gerke, Markus; Kerle, Norman; Nex, Francesco; Vosselman, George

2018-06-01

Oblique aerial images offer views of both building roofs and façades, and thus have been recognized as a potential source to detect severe building damages caused by destructive disaster events such as earthquakes. Therefore, they represent an important source of information for first responders or other stakeholders involved in the post-disaster response process. Several automated methods based on supervised learning have already been demonstrated for damage detection using oblique airborne images. However, they often do not generalize well when data from new unseen sites need to be processed, hampering their practical use. Reasons for this limitation include image and scene characteristics, though the most prominent one relates to the image features being used for training the classifier. Recently features based on deep learning approaches, such as convolutional neural networks (CNNs), have been shown to be more effective than conventional hand-crafted features, and have become the state-of-the-art in many domains, including remote sensing. Moreover, often oblique images are captured with high block overlap, facilitating the generation of dense 3D point clouds - an ideal source to derive geometric characteristics. We hypothesized that the use of CNN features, either independently or in combination with 3D point cloud features, would yield improved performance in damage detection. To this end we used CNN and 3D features, both independently and in combination, using images from manned and unmanned aerial platforms over several geographic locations that vary significantly in terms of image and scene characteristics. A multiple-kernel-learning framework, an effective way for integrating features from different modalities, was used for combining the two sets of features for classification. The results are encouraging: while CNN features produced an average classification accuracy of about 91%, the integration of 3D point cloud features led to an additional improvement of about 3% (i.e. an average classification accuracy of 94%). The significance of 3D point cloud features becomes more evident in the model transferability scenario (i.e., training and testing samples from different sites that vary slightly in the aforementioned characteristics), where the integration of CNN and 3D point cloud features significantly improved the model transferability accuracy up to a maximum of 7% compared with the accuracy achieved by CNN features alone. Overall, an average accuracy of 85% was achieved for the model transferability scenario across all experiments. Our main conclusion is that such an approach qualifies for practical use.

Design of an energy conservation building

NASA Astrophysics Data System (ADS)

Jensen, R. N.

1981-11-01

The concepts in designing and predicting energy consumption in a low energy use building are summarized. The building will use less than 30,000 Btu/sq.ft./yr. of boarder energy. The building's primary energy conservation features include heavy concrete walls with external insulation, a highly insulated ceiling, and large amounts of glass for natural lighting. A solar collector air system is integrated into the south wall. Calculations for energy conservation features were performed using NASA's NECAP Energy Program.

Design of an energy conservation building

NASA Technical Reports Server (NTRS)

Jensen, R. N.

1981-01-01

The concepts in designing and predicting energy consumption in a low energy use building are summarized. The building will use less than 30,000 Btu/sq.ft./yr. of boarder energy. The building's primary energy conservation features include heavy concrete walls with external insulation, a highly insulated ceiling, and large amounts of glass for natural lighting. A solar collector air system is integrated into the south wall. Calculations for energy conservation features were performed using NASA's NECAP Energy Program.

Entropy-Based Adaptive Nuclear Texture Features are Independent Prognostic Markers in a Total Population of Uterine Sarcomas

PubMed Central

Nielsen, Birgitte; Hveem, Tarjei Sveinsgjerd; Kildal, Wanja; Abeler, Vera M; Kristensen, Gunnar B; Albregtsen, Fritz; Danielsen, Håvard E; Rohde, Gustavo K

2015-01-01

Nuclear texture analysis measures the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image and is a promising quantitative tool for prognosis of cancer. The aim of this study was to evaluate the prognostic value of entropy-based adaptive nuclear texture features in a total population of 354 uterine sarcomas. Isolated nuclei (monolayers) were prepared from 50 µm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices, and two superior adaptive texture features were calculated from each matrix. The 5-year crude survival was significantly higher (P < 0.001) for patients with high texture feature values (72%) than for patients with low feature values (36%). When combining DNA ploidy classification (diploid/nondiploid) and texture (high/low feature value), the patients could be stratified into three risk groups with 5-year crude survival of 77, 57, and 34% (Hazard Ratios (HR) of 1, 2.3, and 4.1, P < 0.001). Entropy-based adaptive nuclear texture was an independent prognostic marker for crude survival in multivariate analysis including relevant clinicopathological features (HR = 2.1, P = 0.001), and should therefore be considered as a potential prognostic marker in uterine sarcomas. © The Authors. Published 2014 International Society for Advancement of Cytometry PMID:25483227

Spike detection, characterization, and discrimination using feature analysis software written in LabVIEW.

PubMed

Stewart, C M; Newlands, S D; Perachio, A A

2004-12-01

Rapid and accurate discrimination of single units from extracellular recordings is a fundamental process for the analysis and interpretation of electrophysiological recordings. We present an algorithm that performs detection, characterization, discrimination, and analysis of action potentials from extracellular recording sessions. The program was entirely written in LabVIEW (National Instruments), and requires no external hardware devices or a priori information about action potential shapes. Waveform events are detected by scanning the digital record for voltages that exceed a user-adjustable trigger. Detected events are characterized to determine nine different time and voltage levels for each event. Various algebraic combinations of these waveform features are used as axis choices for 2-D Cartesian plots of events. The user selects axis choices that generate distinct clusters. Multiple clusters may be defined as action potentials by manually generating boundaries of arbitrary shape. Events defined as action potentials are validated by visual inspection of overlain waveforms. Stimulus-response relationships may be identified by selecting any recorded channel for comparison to continuous and average cycle histograms of binned unit data. The algorithm includes novel aspects of feature analysis and acquisition, including higher acquisition rates for electrophysiological data compared to other channels. The program confirms that electrophysiological data may be discriminated with high-speed and efficiency using algebraic combinations of waveform features derived from high-speed digital records.

Quasi-continuum photoluminescence: Unusual broad spectral and temporal characteristics found in defective surfaces of silica and other materials

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

Laurence, Ted A., E-mail: laurence2@llnl.gov; Bude, Jeff D.; Shen, Nan

2014-02-28

We previously reported a novel photoluminescence (PL) with a distribution of fast decay times in fused silica surface flaws that is correlated with damage propensity by high fluence lasers. The source of the PL was not attributable to any known silica point defect. Due to its broad spectral and temporal features, we here give this PL the name quasi-continuum PL (QC-PL) and describe the features of QC-PL in more detail. The primary features of QC-PL include broad excitation and emission spectra, a broad distribution of PL lifetimes from 20 ps to 5 ns, continuous shifts in PL lifetime distributions with respectmore » to emission wavelength, and a propensity to photo-bleach and photo-brighten. We found similar PL characteristics in surface flaws of other optical materials, including CaF{sub 2}, DKDP, and quartz. Based on the commonality of the features in different optical materials and the proximity of QC-PL to surfaces, we suggest that these properties arise from interactions associated with high densities of defects, rather than a distribution over a large number of types of defects and is likely found in a wide variety of structures from nano-scale composites to bulk structures as well as in both broad and narrow band materials from dielectrics to semiconductors.« less

Clinical Features and Associated Likelihood of Primary Ciliary Dyskinesia in Children and Adolescents

PubMed Central

Ferkol, Thomas W.; Davis, Stephanie D.; Lee, Hye-Seung; Rosenfeld, Margaret; Dell, Sharon D.; Sagel, Scott D.; Milla, Carlos; Olivier, Kenneth N.; Sullivan, Kelli M.; Zariwala, Maimoona A.; Pittman, Jessica E.; Shapiro, Adam J.; Carson, Johnny L.; Krischer, Jeffrey; Hazucha, Milan J.

2016-01-01

Rationale: Primary ciliary dyskinesia (PCD), a genetically heterogeneous, recessive disorder of motile cilia, is associated with distinct clinical features. Diagnostic tests, including ultrastructural analysis of cilia, nasal nitric oxide measurements, and molecular testing for mutations in PCD genes, have inherent limitations. Objectives: To define a statistically valid combination of systematically defined clinical features that strongly associates with PCD in children and adolescents. Methods: Investigators at seven North American sites in the Genetic Disorders of Mucociliary Clearance Consortium prospectively and systematically assessed individuals (aged 0–18 yr) referred due to high suspicion for PCD. The investigators defined specific clinical questions for the clinical report form based on expert opinion. Diagnostic testing was performed using standardized protocols and included nasal nitric oxide measurement, ciliary biopsy for ultrastructural analysis of cilia, and molecular genetic testing for PCD-associated genes. Final diagnoses were assigned as “definite PCD” (hallmark ultrastructural defects and/or two mutations in a PCD-associated gene), “probable/possible PCD” (no ultrastructural defect or genetic diagnosis, but compatible clinical features and nasal nitric oxide level in PCD range), and “other diagnosis or undefined.” Criteria were developed to define early childhood clinical features on the basis of responses to multiple specific queries. Each defined feature was tested by logistic regression. Sensitivity and specificity analyses were conducted to define the most robust set of clinical features associated with PCD. Measurements and Main Results: From 534 participants 18 years of age and younger, 205 were identified as having “definite PCD” (including 164 with two mutations in a PCD-associated gene), 187 were categorized as “other diagnosis or undefined,” and 142 were defined as having “probable/possible PCD.” Participants with “definite PCD” were compared with the “other diagnosis or undefined” group. Four criteria-defined clinical features were statistically predictive of PCD: laterality defect; unexplained neonatal respiratory distress; early-onset, year-round nasal congestion; and early-onset, year-round wet cough (adjusted odds ratios of 7.7, 6.6, 3.4, and 3.1, respectively). The sensitivity and specificity based on the number of criteria-defined clinical features were four features, 0.21 and 0.99, respectively; three features, 0.50 and 0.96, respectively; and two features, 0.80 and 0.72, respectively. Conclusions: Systematically defined early clinical features could help identify children, including infants, likely to have PCD. Clinical trial registered with ClinicalTrials.gov (NCT00323167). PMID:27070726

Special Feature: Teaching about High Tech.

ERIC Educational Resources Information Center

Kopf, Michael; And Others

1992-01-01

Includes four articles: "Virtual Reality" (Kopf), description of its uses in computer-assisted design, architecture, and technical training; "SME (Society of Manufacturing Engineers) Robotics Contest Opens Doors to Future" (Wagner); "Superconductivity" (Canady), description of classroom demonstrations and experiments;…

Balanced pressure gerotor fuel pump

DOEpatents

Raney, Michael Raymond; Maier, Eugen

2004-08-03

A gerotor pump for pressurizing gasoline fuel is capable of developing pressures up to 2.0 MPa with good mechanical and volumetric efficiency and satisfying the durability requirements for an automotive fuel pump. The pump has been designed with optimized clearances and by including features that promote the formation of lubricating films of pressurized fuel. Features of the improved pump include the use of a shadow port in the side plate opposite the outlet port to promote balancing of high fuel pressures on the opposite sides of the rotors. Inner and outer rotors have predetermined side clearances with the clearances of the outer rotor being greater than those of the inner rotor in order to promote fuel pressure balance on the sides of the outer rotor. Support of the inner rotor and a drive shaft on a single bushing with bearing sleeves maintains concentricity. Additional features are disclosed.

Satellite services system analysis study. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1981-01-01

Service requirements are considered. Topics include development of on-orbit operations scenarios, service equipment summary, crew interaction, and satellite features facilitating servicing. Service equipment concepts are considered. Topics include payload deployment, close proximity retrieval, on-orbit servicing, backup/contingency, delivery/retrieval of high energy payloads, Earth return, optional service, and advanced capabilities. Program requirements are assessed.

NASA aeronautics research and technology

NASA Technical Reports Server (NTRS)

1986-01-01

The technical accomplishments and research highlights of 1986 are featured, along with information on possible areas of future research. These include hypersonic, supersonic, high performance, subsonic, and rotorcraft vehicle technology. Fundamental disciplinary research areas discussed include aerodynamics, propulsion, materials and structures, information sciences and human factors, and flight systems/safety. A description of the NASA organization and facilities is given.

High-order graph matching based feature selection for Alzheimer's disease identification.

PubMed

Liu, Feng; Suk, Heung-Il; Wee, Chong-Yaw; Chen, Huafu; Shen, Dinggang

2013-01-01

One of the main limitations of l1-norm feature selection is that it focuses on estimating the target vector for each sample individually without considering relations with other samples. However, it's believed that the geometrical relation among target vectors in the training set may provide useful information, and it would be natural to expect that the predicted vectors have similar geometric relations as the target vectors. To overcome these limitations, we formulate this as a graph-matching feature selection problem between a predicted graph and a target graph. In the predicted graph a node is represented by predicted vector that may describe regional gray matter volume or cortical thickness features, and in the target graph a node is represented by target vector that include class label and clinical scores. In particular, we devise new regularization terms in sparse representation to impose high-order graph matching between the target vectors and the predicted ones. Finally, the selected regional gray matter volume and cortical thickness features are fused in kernel space for classification. Using the ADNI dataset, we evaluate the effectiveness of the proposed method and obtain the accuracies of 92.17% and 81.57% in AD and MCI classification, respectively.

Pulmonary nodule characterization, including computer analysis and quantitative features.

PubMed

Bartholmai, Brian J; Koo, Chi Wan; Johnson, Geoffrey B; White, Darin B; Raghunath, Sushravya M; Rajagopalan, Srinivasan; Moynagh, Michael R; Lindell, Rebecca M; Hartman, Thomas E

2015-03-01

Pulmonary nodules are commonly detected in computed tomography (CT) chest screening of a high-risk population. The specific visual or quantitative features on CT or other modalities can be used to characterize the likelihood that a nodule is benign or malignant. Visual features on CT such as size, attenuation, location, morphology, edge characteristics, and other distinctive "signs" can be highly suggestive of a specific diagnosis and, in general, be used to determine the probability that a specific nodule is benign or malignant. Change in size, attenuation, and morphology on serial follow-up CT, or features on other modalities such as nuclear medicine studies or MRI, can also contribute to the characterization of lung nodules. Imaging analytics can objectively and reproducibly quantify nodule features on CT, nuclear medicine, and magnetic resonance imaging. Some quantitative techniques show great promise in helping to differentiate benign from malignant lesions or to stratify the risk of aggressive versus indolent neoplasm. In this article, we (1) summarize the visual characteristics, descriptors, and signs that may be helpful in management of nodules identified on screening CT, (2) discuss current quantitative and multimodality techniques that aid in the differentiation of nodules, and (3) highlight the power, pitfalls, and limitations of these various techniques.

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.

Alcohol marketing in televised international football: frequency analysis

PubMed Central

2014-01-01

Background Alcohol marketing includes sponsorship of individuals, organisations and sporting events. Football (soccer) is one of the most popular spectator sports worldwide. No previous studies have quantified the frequency of alcohol marketing in a high profile international football tournament. The aims were to determine: the frequency and nature of visual references to alcohol in a representative sample of EURO2012 matches broadcast in the UK; and if frequency or nature varied between matches broadcast on public service and commercial channels, or between matches that did and did not feature England. Methods Eight matches selected by stratified random sampling were recorded. All visual references to alcohol were identified using a tool with high inter-rater reliability. Results 1846 visual references to alcohol were identified over 1487 minutes of broadcast - an average of 1.24 references per minute. The mean number of references per minute was higher in matches that did vs did not feature England (p = 0.004), but did not differ between matches broadcast on public service vs commercial channels (p = 0.92). Conclusions The frequency of visual references to alcohol was universally high and higher in matches featuring the only UK home team - England - suggesting that there may be targeting of particularly highly viewed matches. References were embedded in broadcasts, and not particular to commercial channels including paid-for advertising. New UK codes-of-conduct on alcohol marketing at sporting events will not reduce the level of marketing reported here. PMID:24885718

Application of an Upwind High Resolution Finite-Differencing Scheme and Multigrid Method in Steady-State Incompressible Flow Simulations

NASA Technical Reports Server (NTRS)

Yang, Cheng I.; Guo, Yan-Hu; Liu, C.- H.

1996-01-01

The analysis and design of a submarine propulsor requires the ability to predict the characteristics of both laminar and turbulent flows to a higher degree of accuracy. This report presents results of certain benchmark computations based on an upwind, high-resolution, finite-differencing Navier-Stokes solver. The purpose of the computations is to evaluate the ability, the accuracy and the performance of the solver in the simulation of detailed features of viscous flows. Features of interest include flow separation and reattachment, surface pressure and skin friction distributions. Those features are particularly relevant to the propulsor analysis. Test cases with a wide range of Reynolds numbers are selected; therefore, the effects of the convective and the diffusive terms of the solver can be evaluated separately. Test cases include flows over bluff bodies, such as circular cylinders and spheres, at various low Reynolds numbers, flows over a flat plate with and without turbulence effects, and turbulent flows over axisymmetric bodies with and without propulsor effects. Finally, to enhance the iterative solution procedure, a full approximation scheme V-cycle multigrid method is implemented. Preliminary results indicate that the method significantly reduces the computational effort.

Automated quantification of surface water inundation in wetlands using optical satellite imagery

USGS Publications Warehouse

DeVries, Ben; Huang, Chengquan; Lang, Megan W.; Jones, John W.; Huang, Wenli; Creed, Irena F.; Carroll, Mark L.

2017-01-01

We present a fully automated and scalable algorithm for quantifying surface water inundation in wetlands. Requiring no external training data, our algorithm estimates sub-pixel water fraction (SWF) over large areas and long time periods using Landsat data. We tested our SWF algorithm over three wetland sites across North America, including the Prairie Pothole Region, the Delmarva Peninsula and the Everglades, representing a gradient of inundation and vegetation conditions. We estimated SWF at 30-m resolution with accuracies ranging from a normalized root-mean-square-error of 0.11 to 0.19 when compared with various high-resolution ground and airborne datasets. SWF estimates were more sensitive to subtle inundated features compared to previously published surface water datasets, accurately depicting water bodies, large heterogeneously inundated surfaces, narrow water courses and canopy-covered water features. Despite this enhanced sensitivity, several sources of errors affected SWF estimates, including emergent or floating vegetation and forest canopies, shadows from topographic features, urban structures and unmasked clouds. The automated algorithm described in this article allows for the production of high temporal resolution wetland inundation data products to support a broad range of applications.

Using multiscale texture and density features for near-term breast cancer risk analysis

PubMed Central

Sun, Wenqing; Tseng, Tzu-Liang (Bill); Qian, Wei; Zhang, Jianying; Saltzstein, Edward C.; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

2015-01-01

Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. Methods: The authors’ dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the “prior” screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. Results: From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). Conclusions: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations. PMID:26127038

What vehicle features are considered important when buying an automobile? An examination of driver preferences by age and gender.

PubMed

Vrkljan, Brenda H; Anaby, Dana

2011-02-01

Certain vehicle features can help drivers avoid collisions and/or protect occupants in the event of a crash, and therefore, might play an important role when deciding which vehicle to purchase. The objective of this study was to examine the importance attributed to key vehicle features (including safety) that drivers consider when buying a car and its association with age and gender. A sample of 2,002 Canadian drivers aged 18 years and older completed a survey that asked them to rank the importance of eight vehicle features if they were to purchase a vehicle (storage, mileage, safety, price, comfort, performance, design, and reliability). ANOVA tests were performed to: (a) determine if there were differences in the level of importance between features and; (b) examine the effect of age and gender on the importance attributed to these features. Of the features examined, safety and reliability were the most highly rated in terms of importance, whereas design and performance had the lowest rating. Differences in safety and performance across age groups were dependent on gender. This effect was most evident in the youngest and oldest age groups. Safety and reliability were considered the most important features. Age and gender play a significant role in explaining the importance of certain features. Targeted efforts for translating safety-related information to the youngest and oldest consumers should be emphasized due to their high collision, injury, and fatality rates. Copyright © 2011 National Safety Council and Elsevier Ltd. All rights reserved.

Elevated hardness of peripheral gland on real-time elastography is an independent marker for high-risk prostate cancers.

PubMed

Zhang, Qi; Yao, Jing; Cai, Yehua; Zhang, Limin; Wu, Yishuo; Xiong, Jingyu; Shi, Jun; Wang, Yuanyuan; Wang, Yi

2017-12-01

To examine the role of quantitative real-time elastography (RTE) features on differentiation between high-risk prostate cancer (PCA) and non-high-risk prostatic diseases in the initial transperineal biopsy setting. We retrospectively included 103 patients with suspicious PCA who underwent both RTE and initial transperineal prostate biopsy. Patients were grouped into high-risk and non-high-risk categories according to the D'Amico's risk stratification. With computer assistance based on MATLAB programming, three features were extracted from RTE, i.e., the median hardness within peripheral gland (PG) (H med ), the ratio of the median hardness within PG to that outside PG (H ratio ), and the ratio of the hard area within PG to the total PG area (H ar ). A multiple regression model incorporating an RTE feature, age, transrectal ultrasound finding, and prostate volume was used to identify markers for high-risk PCA. Forty-seven patients (45.6%) were diagnosed with PCA and 34 (33.0%) were diagnosed with high-risk PCA. Three RTE features were all statistically higher in high-risk PCA than in non-high-risk diseases (p < 0.001), indicating that the PGs in high-risk PCA patients were harder than those in non-high-risk patients. A high H ratio , high age, and low prostate volume were found to be independent markers for PCAs (p < 0.05), among which the high H ratio was the only independent marker for high-risk PCAs (p = 0.012). When predicting high-risk PCAs, the multiple regression achieved an area under receiver operating characteristic curve of 0.755, sensitivity of 73.5%, and specificity of 71.0%. The elevated hardness of PG identified high-risk PCA and served as an independent marker of high-risk PCA. As a non-invasive imaging modality, the RTE could be potentially used in routine clinical practice for the detection of high-risk PCA to decrease unnecessary biopsies and reduce overtreatment.

FRICTION STIR LAP WELDING OF ALUMINUM - POLYMER USING SCRIBE TECHNOLOGY

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

Upadhyay, Piyush; Hovanski, Yuri; Fifield, Leonard S.

2015-02-16

Friction Stir Scribe (FSS) technology is a relatively new variant of Friction Stir Welding (FSW) which enables lap joining of dissimilar material with very different melting points and different high temperature flow behaviors. The cutter scribe attached at the tip of FSW tool pin effectively cuts the high melting point material such that a mechanically interlocking feature is created between the dissimilar materials. The geometric shape of this interlocking feature determines the shear strength attained by the lap joint. This work presents first use of scribe technology in joining polymers to aluminum alloy. Details of the several runs of scribemore » welding performed in lap joining of ~3.175mm thick polymers including HDPE, filled and unfilled Nylon 66 to 2mm thick AA5182 are presented. The effect of scribe geometry and length on weld interlocking features is presented along with lap shear strength evaluations.« less

A discontinuous Galerkin method for gravity-driven viscous fingering instabilities in porous media

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

Scovazzi, G.; Gerstenberger, A.; Collis, S. S.

2013-01-01

We present a new approach to the simulation of gravity-driven viscous fingering instabilities in porous media flow. These instabilities play a very important role during carbon sequestration processes in brine aquifers. Our approach is based on a nonlinear implementation of the discontinuous Galerkin method, and possesses a number of key features. First, the method developed is inherently high order, and is therefore well suited to study unstable flow mechanisms. Secondly, it maintains high-order accuracy on completely unstructured meshes. The combination of these two features makes it a very appealing strategy in simulating the challenging flow patterns and very complex geometriesmore » of actual reservoirs and aquifers. This article includes an extensive set of verification studies on the stability and accuracy of the method, and also features a number of computations with unstructured grids and non-standard geometries.« less

Thin-film filament-based solar cells and modules

NASA Astrophysics Data System (ADS)

Tuttle, J. R.; Cole, E. D.; Berens, T. A.; Alleman, J.; Keane, J.

1997-04-01

This concept paper describes a patented, novel photovoltaic (PV) technology that is capable of achieving near-term commercialization and profitability based upon design features that maximize product performance while minimizing initial and future manufacturing costs. DayStar Technologies plans to exploit these features and introduce a product to the market based upon these differential positions. The technology combines the demonstrated performance and reliability of existing thin-film PV product with a cell and module geometry that cuts material usage by a factor of 5, and enhances performance and manufacturability relative to standard flat-plate designs. The target product introduction price is 1.50/Watt-peak (Wp). This is approximately one-half the cost of the presently available PV product. Additional features include: increased efficiency through low-level concentration, no scribe or grid loss, simple series interconnect, high voltage, light weight, high-throughput manufacturing, large area immediate demonstration, flexibility, modularity.

The Impact of Solid Surface Features on Fluid-Fluid Interface Configuration

NASA Astrophysics Data System (ADS)

Araujo, J. B.; Brusseau, M. L. L.

2017-12-01

Pore-scale fluid processes in geological media are critical for a broad range of applications such as radioactive waste disposal, carbon sequestration, soil moisture distribution, subsurface pollution, land stability, and oil and gas recovery. The continued improvement of high-resolution image acquisition and processing have provided a means to test the usefulness of theoretical models developed to simulate pore-scale fluid processes, through the direct quantification of interfaces. High-resolution synchrotron X-ray microtomography is used in combination with advanced visualization tools to characterize fluid distributions in natural geologic media. The studies revealed the presence of fluid-fluid interface associated with macroscopic features on the surfaces of the solids such as pits and crevices. These features and respective fluid interfaces, which are not included in current theoretical or computational models, may have a significant impact on accurate simulation and understanding of multi-phase flow, energy, heat and mass transfer processes.

A Social Competence Intervention for Young Children with High Functioning Autism and Asperger Syndrome: A Pilot Study

ERIC Educational Resources Information Center

Minne, Elizabeth Portman; Semrud-Clikeman, Margaret

2012-01-01

The key features of Asperger Syndrome (AS) and high functioning autism (HFA) include marked and sustained impairment in social interactions. A multi-session, small group program was developed to increase social perception based on the assumption perceptual or interpretive problems underlying these social difficulties. Additionally, the group…

Videos for Teachers: Successful Teaching Strategies in Middle and High School Classrooms. [CD-ROM].

ERIC Educational Resources Information Center

Teachers Network, New York, NY.

This CD-ROM presents six videos that feature veteran middle and high school teachers in action in their classrooms. Each video offers links to supplemental education resources, including innovative lesson plans. The six videos are: "Monsters and Myths" (a humanities unit for middle school students); "The Bleeding Edge" (a thematic…

Normalized distance aggregation of discriminative features for person reidentification

NASA Astrophysics Data System (ADS)

Hou, Li; Han, Kang; Wan, Wanggen; Hwang, Jenq-Neng; Yao, Haiyan

2018-03-01

We propose an effective person reidentification method based on normalized distance aggregation of discriminative features. Our framework is built on the integration of three high-performance discriminative feature extraction models, including local maximal occurrence (LOMO), feature fusion net (FFN), and a concatenation of LOMO and FFN called LOMO-FFN, through two fast and discriminant metric learning models, i.e., cross-view quadratic discriminant analysis (XQDA) and large-scale similarity learning (LSSL). More specifically, we first represent all the cross-view person images using LOMO, FFN, and LOMO-FFN, respectively, and then apply each extracted feature representation to train XQDA and LSSL, respectively, to obtain the optimized individual cross-view distance metric. Finally, the cross-view person matching is computed as the sum of the optimized individual cross-view distance metric through the min-max normalization. Experimental results have shown the effectiveness of the proposed algorithm on three challenging datasets (VIPeR, PRID450s, and CUHK01).

An evaluation of object-oriented image analysis techniques to identify motorized vehicle effects in semi-arid to arid ecosystems of the American West

USGS Publications Warehouse

Mladinich, C.

2010-01-01

Human disturbance is a leading ecosystem stressor. Human-induced modifications include transportation networks, areal disturbances due to resource extraction, and recreation activities. High-resolution imagery and object-oriented classification rather than pixel-based techniques have successfully identified roads, buildings, and other anthropogenic features. Three commercial, automated feature-extraction software packages (Visual Learning Systems' Feature Analyst, ENVI Feature Extraction, and Definiens Developer) were evaluated by comparing their ability to effectively detect the disturbed surface patterns from motorized vehicle traffic. Each package achieved overall accuracies in the 70% range, demonstrating the potential to map the surface patterns. The Definiens classification was more consistent and statistically valid. Copyright ?? 2010 by Bellwether Publishing, Ltd. All rights reserved.

Autonomous navigation of structured city roads

NASA Astrophysics Data System (ADS)

Aubert, Didier; Kluge, Karl C.; Thorpe, Chuck E.

1991-03-01

Autonomous road following is a domain which spans a range of complexity from poorly defined unmarked dirt roads to well defined well marked highly struc-. tured highways. The YARF system (for Yet Another Road Follower) is designed to operate in the middle of this range of complexity driving on urban streets. Our research program has focused on the use of feature- and situation-specific segmentation techniques driven by an explicit model of the appearance and geometry of the road features in the environment. We report results in robust detection of white and yellow painted stripes fitting a road model to detected feature locations to determine vehicle position and local road geometry and automatic location of road features in an initial image. We also describe our planned extensions to include intersection navigation.

Satellite observations of mesoscale features in lower Cook Inlet and Shelikof Strait, Gulf of Alaska

NASA Technical Reports Server (NTRS)

Schumacher, James D.; Barber, Willard E.; Holt, Benjamin; Liu, Antony K.

1991-01-01

The Seasat satellite launched in Summer 1978 carried a synthetic aperture radar (SAR). Although Seasat failed after 105 days in orbit, it provided observations that demonstrate the potential to examine and monitor upper oceanic processes. Seasat made five passes over lower Cook Inlet and Shelikof Strait, Alaska, during Summer 1978. SAR images from the passes show oceanographic features, including a meander in a front, a pair of mesoscale eddies, and internal waves. These features are compared with contemporary and representative images from a satellite-borne Advanced Very High Resolution Radiometer (AVHRR) and Coastal Zone Color Scanner (CZCS), with water property data, and with current observations from moored instruments. The results indicate that SAR data can be used to monitor mesoscale oceanographic features.

Women's Heart Disease: Cindy Parsons and Follow the Fifty

MedlinePlus

... this page please turn JavaScript on. Feature: Women's Heart Disease Cindy Parsons and Follow the Fifty Past Issues / ... Program, knowing that her personal risk factors for heart disease, including family history, were high. She watched her ...

Communicator, 1998.

ERIC Educational Resources Information Center

Bortolussi, Vicki, Ed.

1998-01-01

The CAG "Communicator" focuses on serving gifted students in California. This document consists of the four issues of "Communicator" issued during 1998. Featured articles include: (1) "Underachievement for Some--Dropping Out with Dignity for Others" (Sally Reis); (2) "When Gifted High School Students Fail"…

Ocular Manifestations of Noonan Syndrome: A Prospective Clinical and Genetic Study of 25 Patients.

PubMed

van Trier, Dorothée C; Vos, Anna M C; Draaijer, Renske W; van der Burgt, Ineke; Draaisma, Jos M Th; Cruysberg, Johannes R M

2016-10-01

To determine the full spectrum of ocular manifestations in patients with Noonan syndrome (NS). Prospective cross-sectional clinical and genetic study in a tertiary referral center. Twenty-five patients with NS (mean age, 14 years; range, 8 months-25 years) clinically diagnosed by validated criteria. All patients were examined by the same team following a detailed study protocol. Genetic analyses were performed in 23 patients. Ocular abnormalities of vision and refraction, external ocular features, ocular position and motility, anterior segment, posterior segment, and intraocular pressure. Ocular features of vision and refraction were amblyopia (32%), myopia (40%), and astigmatism (52%). External ocular features were epicanthic folds (84%), hypertelorism (68%), ptosis (56%), high upper eyelid crease (64%), lower eyelid retraction (60%), abnormal upward slanting palpebral fissures (36%), downward slanting palpebral fissures (32%), and lagophthalmos (28%). Orthoptic abnormalities included strabismus (40%), abnormal stereopsis (44%), and limited ocular motility (40%). Anterior segment abnormalities included prominent corneal nerves (72%) and posterior embryotoxon (32%). Additional ocular features were found, including nonglaucomatous optic disc excavation (20%), relatively low (<10 mmHg) intraocular pressure (22%), and optic nerve hypoplasia (4%). Mutations were established in 22 patients: 19 PTPN11 mutations (76%), 1 SOS1 mutation, 1 BRAF mutation, and 1 KRAS mutation. The patient with the highest number of prominent corneal nerves had an SOS1 mutation. The patient with the lowest visual acuity, associated with bilateral optic nerve hypoplasia, had a BRAF mutation. Patients with severe ptosis and nearly total absence of levator muscle function had PTPN11 mutations. All patients showed at least 3 ocular features (range, 3-13; mean, 7), including at least 1 external ocular feature in more than 95% of the patients. Noonan syndrome is a clinical diagnosis with multiple genetic bases associated with an extensive variety of congenital ocular abnormalities. Ocular features of NS are characterized by 1 or more developmental anomalies of the eyelids (involving the position, opening, and closure) associated with various other ocular abnormalities in childhood, including amblyopia, myopia, astigmatism, strabismus, limited ocular motility, prominent corneal nerves, and posterior embryotoxon. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed ADF features can effectively improve the accuracy of urban scene classification, with a significant increase in overall accuracy (3.8-11.7%) compared to using the spectral bands alone. Furthermore, the results indicated the superiority of the proposed ADFs in distinguishing between the spectrally similar and complex man-made classes, including roads and various types of buildings (e.g., high buildings, urban villages, and residential apartments).

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

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

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

Some unique surface patterns on ignimbrites on Earth: A "bird's eye" view as a guide for planetary mappers

NASA Astrophysics Data System (ADS)

de Silva, Shanaka L.; Bailey, John E.

2017-08-01

Observations of terrestrial analogs are critical to aiding planetary mappers in interpreting surface lithologies on other planets. For instance, the presence of ignimbrites on Mars has been debated for over three decades and is supported by analogy with deposits on Earth. Critical evidence includes the geomorphic and surface expression of the deposits, and those in the Central Andes of South America are amongst the most-cited analogs. Herein we describe some prominent surface textures and patterns seen in ignimbrites on the scale of high-resolution remotely sensed data (10-1 m per pixel). These include pervasive joints and fractures that contribute to yardang form and development as well as prominent mounds, fissures, and fracture networks ("spiders", "bugs", "boxworks") on ignimbrite surfaces. While all these features are related to intrinsic cooling and degassing processes, the involvement of external water buried by hot pyroclastic flows enhances fumarolic activity, advective cooling, and joint development. Observations of these geomorphic expressions using remote sensing are only possible with the highest resolution data and limited surface erosion. For Mars, where similarly high resolution datasets are available (for example, the High Resolution Imaging Sensor Experiment or HiRISE) extensive dust cover may limit the recognition of similar features there. However significant relief on some of these features on Earth indicate they might still be detectable on Mars.

Loss of the Cyclin-Dependent Kinase Inhibitor 1 in the Context of Brachyury-Mediated Phenotypic Plasticity Drives Tumor Resistance to Immune Attack.

PubMed

Hamilton, Duane H; McCampbell, Kristen K; Palena, Claudia

2018-01-01

The acquisition of mesenchymal features by carcinoma cells is now recognized as a driver of metastasis and tumor resistance to a range of anticancer therapeutics, including chemotherapy, radiation, and certain small-molecule targeted therapies. With the recent successful implementation of immunotherapies for the treatment of various types of cancer, there is growing interest in understanding whether an immunological approach could be effective at eradicating carcinoma cells bearing mesenchymal features. Recent studies, however, demonstrated that carcinoma cells that have acquired mesenchymal features may also exhibit decreased susceptibility to lysis mediated by immune effector cells, including antigen-specific CD8 + T cells, innate natural killer (NK), and lymphokine-activated killer (LAK) cells. Here, we investigated the mechanism involved in the immune resistance of carcinoma cells that express very high levels of the transcription factor brachyury, a molecule previously shown to drive the acquisition of mesenchymal features by carcinoma cells. Our results demonstrate that very high levels of brachyury expression drive the loss of the cyclin-dependent kinase inhibitor 1 (p21CIP1, p21), an event that results in decreased tumor susceptibility to immune-mediated lysis. We show here that reconstitution of p21 expression markedly increases the lysis of brachyury-high tumor cells mediated by antigen-specific CD8 + T cells, NK, and LAK cells, TNF-related apoptosis-inducing ligand, and chemotherapy. Several reports have now demonstrated a role for p21 loss in cancer as an inducer of the epithelial-mesenchymal transition. The results from the present study situate p21 as a central player in many of the aspects of the phenomenon of brachyury-mediated mesenchymalization of carcinomas, including resistance to chemotherapy and immune-mediated cytotoxicity. We also demonstrate here that the defects in tumor cell death described in association with very high levels of brachyury could be alleviated via the use of a WEE1 inhibitor. Several vaccine platforms targeting brachyury have been developed and are undergoing clinical evaluation. These studies provide further rationale for the use of WEE1 inhibition in combination with brachyury-based immunotherapeutic approaches.

Loss of the Cyclin-Dependent Kinase Inhibitor 1 in the Context of Brachyury-Mediated Phenotypic Plasticity Drives Tumor Resistance to Immune Attack

PubMed Central

Hamilton, Duane H.; McCampbell, Kristen K.; Palena, Claudia

2018-01-01

The acquisition of mesenchymal features by carcinoma cells is now recognized as a driver of metastasis and tumor resistance to a range of anticancer therapeutics, including chemotherapy, radiation, and certain small-molecule targeted therapies. With the recent successful implementation of immunotherapies for the treatment of various types of cancer, there is growing interest in understanding whether an immunological approach could be effective at eradicating carcinoma cells bearing mesenchymal features. Recent studies, however, demonstrated that carcinoma cells that have acquired mesenchymal features may also exhibit decreased susceptibility to lysis mediated by immune effector cells, including antigen-specific CD8+ T cells, innate natural killer (NK), and lymphokine-activated killer (LAK) cells. Here, we investigated the mechanism involved in the immune resistance of carcinoma cells that express very high levels of the transcription factor brachyury, a molecule previously shown to drive the acquisition of mesenchymal features by carcinoma cells. Our results demonstrate that very high levels of brachyury expression drive the loss of the cyclin-dependent kinase inhibitor 1 (p21CIP1, p21), an event that results in decreased tumor susceptibility to immune-mediated lysis. We show here that reconstitution of p21 expression markedly increases the lysis of brachyury-high tumor cells mediated by antigen-specific CD8+ T cells, NK, and LAK cells, TNF-related apoptosis-inducing ligand, and chemotherapy. Several reports have now demonstrated a role for p21 loss in cancer as an inducer of the epithelial–mesenchymal transition. The results from the present study situate p21 as a central player in many of the aspects of the phenomenon of brachyury-mediated mesenchymalization of carcinomas, including resistance to chemotherapy and immune-mediated cytotoxicity. We also demonstrate here that the defects in tumor cell death described in association with very high levels of brachyury could be alleviated via the use of a WEE1 inhibitor. Several vaccine platforms targeting brachyury have been developed and are undergoing clinical evaluation. These studies provide further rationale for the use of WEE1 inhibition in combination with brachyury-based immunotherapeutic approaches. PMID:29774202

3D for Geosciences: Interactive Tangibles and Virtual Models

NASA Astrophysics Data System (ADS)

Pippin, J. E.; Matheney, M.; Kitsch, N.; Rosado, G.; Thompson, Z.; Pierce, S. A.

2016-12-01

Point cloud processing provides a method of studying and modelling geologic features relevant to geoscience systems and processes. Here, software including Skanect, MeshLab, Blender, PDAL, and PCL are used in conjunction with 3D scanning hardware, including a Structure scanner and a Kinect camera, to create and analyze point cloud images of small scale topography, karst features, tunnels, and structures at high resolution. This project successfully scanned internal karst features ranging from small stalactites to large rooms, as well as an external waterfall feature. For comparison purposes, multiple scans of the same object were merged into single object files both automatically, using commercial software, and manually using open source libraries and code. Files with format .ply were manually converted into numeric data sets to be analyzed for similar regions between files in order to match them together. We can assume a numeric process would be more powerful and efficient than the manual method, however it could lack other useful features that GUI's may have. The digital models have applications in mining as efficient means of replacing topography functions such as measuring distances and areas. Additionally, it is possible to make simulation models such as drilling templates and calculations related to 3D spaces. Advantages of using methods described here for these procedures include the relatively quick time to obtain data and the easy transport of the equipment. With regard to openpit mining, obtaining 3D images of large surfaces and with precision would be a high value tool by georeferencing scan data to interactive maps. The digital 3D images obtained from scans may be saved as printable files to create physical 3D-printable models to create tangible objects based on scientific information, as well as digital "worlds" able to be navigated virtually. The data, models, and algorithms explored here can be used to convey complex scientific ideas to a range of professionals and audiences.

Extracting and identifying concrete structural defects in GPR images

NASA Astrophysics Data System (ADS)

Ye, Qiling; Jiao, Liangbao; Liu, Chuanxin; Cao, Xuehong; Huston, Dryver; Xia, Tian

2018-03-01

Traditionally most GPR data interpretations are performed manually. With the advancement of computing technologies, how to automate GPR data interpretation to achieve high efficiency and accuracy has become an active research subject. In this paper, analytical characterizations of major defects in concrete structures, including delamination, air void and moisture in GPR images, are performed. In the study, the image features of different defects are compared. Algorithms are developed for defect feature extraction and identification. For validations, both simulation results and field test data are utilized.

Geochemical features of the utilization of buried wastes of the Tyrnyauz Tungsten-Molybdenum Plant using acid leaching

NASA Astrophysics Data System (ADS)

Vinokurov, S. F.; Gurbanov, A. G.; Bogatikov, O. A.; Sychkova, V. A.; Shevchenko, A. V.; Lexin, A. B.; Dudarov, Z. I.

2016-10-01

The decontamination of buried wastes of the Tyrnyauz Tungsten-Molybdenum Plant is complicated by the geochemical features of the waste composition: low sulfide and high carbonate content, polyelemental composition, and considerable amounts of technogenic admixtures (kerosene, oils, soda, and soluble glasses). These circumstances result in sufficient complication of the suggested technology of waste treatment, including the sulfuric-acid leaching and separate sorption recovery of hazardous and useful elements from the working solution.

ADX: A high Power Density, Advanced RF-Driven Divertor Test Tokamak for PMI studies

NASA Astrophysics Data System (ADS)

Whyte, Dennis; ADX Team

2015-11-01

The MIT PSFC and collaborators are proposing an advanced divertor experiment, ADX; a divertor test tokamak dedicated to address critical gaps in plasma-material interactions (PMI) science, and the world fusion research program, on the pathway to FNSF/DEMO. Basic ADX design features are motivated and discussed. In order to assess the widest range of advanced divertor concepts, a large fraction (>50%) of the toroidal field volume is purpose-built with innovative magnetic topology control and flexibility for assessing different surfaces, including liquids. ADX features high B-field (>6 Tesla) and high global power density (P/S ~ 1.5 MW/m2) in order to access the full range of parallel heat flux and divertor plasma pressures foreseen for reactors, while simultaneously assessing the effect of highly dissipative divertors on core plasma/pedestal. Various options for efficiently achieving high field are being assessed including the use of Alcator technology (cryogenic cooled copper) and high-temperature superconductors. The experimental platform would also explore advanced lower hybrid current drive and ion-cyclotron range of frequency actuators located at the high-field side; a location which is predicted to greatly reduce the PMI effects on the launcher while minimally perturbing the core plasma. The synergistic effects of high-field launchers with high total B on current and flow drive can thus be studied in reactor-relevant boundary plasmas.

Machine-assisted verification of latent fingerprints: first results for nondestructive contact-less optical acquisition techniques with a CWL sensor

NASA Astrophysics Data System (ADS)

Hildebrandt, Mario; Kiltz, Stefan; Krapyvskyy, Dmytro; Dittmann, Jana; Vielhauer, Claus; Leich, Marcus

2011-11-01

A machine-assisted analysis of traces from crime scenes might be possible with the advent of new high-resolution non-destructive contact-less acquisition techniques for latent fingerprints. This requires reliable techniques for the automatic extraction of fingerprint features from latent and exemplar fingerprints for matching purposes using pattern recognition approaches. Therefore, we evaluate the NIST Biometric Image Software for the feature extraction and verification of contact-lessly acquired latent fingerprints to determine potential error rates. Our exemplary test setup includes 30 latent fingerprints from 5 people in two test sets that are acquired from different surfaces using a chromatic white light sensor. The first test set includes 20 fingerprints on two different surfaces. It is used to determine the feature extraction performance. The second test set includes one latent fingerprint on 10 different surfaces and an exemplar fingerprint to determine the verification performance. This utilized sensing technique does not require a physical or chemical visibility enhancement of the fingerprint residue, thus the original trace remains unaltered for further investigations. No particular feature extraction and verification techniques have been applied to such data, yet. Hence, we see the need for appropriate algorithms that are suitable to support forensic investigations.

Feature Selection Methods for Zero-Shot Learning of Neural Activity.

PubMed

Caceres, Carlos A; Roos, Matthew J; Rupp, Kyle M; Milsap, Griffin; Crone, Nathan E; Wolmetz, Michael E; Ratto, Christopher R

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

Diversity and Community Can Coexist.

PubMed

Stivala, Alex; Robins, Garry; Kashima, Yoshihisa; Kirley, Michael

2016-03-01

We examine the (in)compatibility of diversity and sense of community by means of agent-based models based on the well-known Schelling model of residential segregation and Axelrod model of cultural dissemination. We find that diversity and highly clustered social networks, on the assumptions of social tie formation based on spatial proximity and homophily, are incompatible when agent features are immutable, and this holds even for multiple independent features. We include both mutable and immutable features into a model that integrates Schelling and Axelrod models, and we find that even for multiple independent features, diversity and highly clustered social networks can be incompatible on the assumptions of social tie formation based on spatial proximity and homophily. However, this incompatibility breaks down when cultural diversity can be sufficiently large, at which point diversity and clustering need not be negatively correlated. This implies that segregation based on immutable characteristics such as race can possibly be overcome by sufficient similarity on mutable characteristics based on culture, which are subject to a process of social influence, provided a sufficiently large "scope of cultural possibilities" exists. © Society for Community Research and Action 2016.

Patient-derived xenografts as preclinical neuroblastoma models.

PubMed

Braekeveldt, Noémie; Bexell, Daniel

2018-05-01

The prognosis for children with high-risk neuroblastoma is often poor and survivors can suffer from severe side effects. Predictive preclinical models and novel therapeutic strategies for high-risk disease are therefore a clinical imperative. However, conventional cancer cell line-derived xenografts can deviate substantially from patient tumors in terms of their molecular and phenotypic features. Patient-derived xenografts (PDXs) recapitulate many biologically and clinically relevant features of human cancers. Importantly, PDXs can closely parallel clinical features and outcome and serve as excellent models for biomarker and preclinical drug development. Here, we review progress in and applications of neuroblastoma PDX models. Neuroblastoma orthotopic PDXs share the molecular characteristics, neuroblastoma markers, invasive properties and tumor stroma of aggressive patient tumors and retain spontaneous metastatic capacity to distant organs including bone marrow. The recent identification of genomic changes in relapsed neuroblastomas opens up opportunities to target treatment-resistant tumors in well-characterized neuroblastoma PDXs. We highlight and discuss the features and various sources of neuroblastoma PDXs, methodological considerations when establishing neuroblastoma PDXs, in vitro 3D models, current limitations of PDX models and their application to preclinical drug testing.

A clinically useful self-report measure of the DSM-5 mixed features specifier of major depressive disorder.

PubMed

Zimmerman, Mark; Chelminski, Iwona; Young, Diane; Dalrymple, Kristy; Martinez, Jennifer H

2014-10-01

To acknowledge the clinical significance of manic features in depressed patients, DSM-5 included criteria for a mixed features specifier for major depressive disorder (MDD). In the present report from the Rhode Island Methods to Improve Diagnostic Assessment and Services (MIDAS) project we modified our previously published depression scale to include a subscale assessing the DSM-5 mixed features specifier. More than 1100 psychiatric outpatients with MDD or bipolar disorder completed the Clinically Useful Depression Outcome Scale (CUDOS) supplemented with questions for the DSM-5 mixed features specifier (CUDOS-M). To examine discriminant and convergent validity the patients were rated on clinician severity indices of depression, anxiety, agitation, and irritability. Discriminant and convergent validity was further examined in a subset of patients who completed other self-report symptom severity scales. Test-retest reliability was examined in a subset who completed the CUDOS-M twice. We compared CUDOS-M scores in patients with MDD, bipolar depression, and hypomania. The CUDOS-M subscale had high internal consistency and test-retest reliability, was more highly correlated with another self-report measure of mania than with measures of depression, anxiety, substance use problems, eating disorders, and anger, and was more highly correlated with clinician severity ratings of agitation and irritability than anxiety and depression. CUDOS-M scores were significantly higher in hypomanic patients than depressed patients, and patients with bipolar depression than patients with MDD. The study was cross-sectional, thus we did not examine whether the CUDOS-M detects emerging mixed symptoms when depressed patients are followed over time. Also, while we examined the correlation between the CUDOS-M and clinician ratings of agitation and irritability, we did not examine the association with a clinician measure of manic symptomatology such as the Young Mania Rating Scale In the present study of a large sample of psychiatric outpatients, the CUDOS-M was a reliable and valid measure of the DSM-5 mixed features specifier for MDD. Copyright © 2014 Elsevier B.V. All rights reserved.

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

PubMed

Guo, Hao; Wu, Danni; An, Jubai

2017-08-09

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

Five-class differential diagnostics of neurodegenerative diseases using random undersampling boosting.

PubMed

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

2017-01-01

Differentiating between different types of neurodegenerative diseases is not only crucial in clinical practice when treatment decisions have to be made, but also has a significant potential for the enrichment of clinical trials. The purpose of this study is to develop a classification framework for distinguishing the four most common neurodegenerative diseases, including Alzheimer's disease, frontotemporal lobe degeneration, Dementia with Lewy bodies and vascular dementia, as well as patients with subjective memory complaints. Different biomarkers including features from images (volume features, region-wise grading features) and non-imaging features (CSF measures) were extracted for each subject. In clinical practice, the prevalence of different dementia types is imbalanced, posing challenges for learning an effective classification model. Therefore, we propose the use of the RUSBoost algorithm in order to train classifiers and to handle the class imbalance training problem. Furthermore, a multi-class feature selection method based on sparsity is integrated into the proposed framework to improve the classification performance. It also provides a way for investigating the importance of different features and regions. Using a dataset of 500 subjects, the proposed framework achieved a high accuracy of 75.2% with a balanced accuracy of 69.3% for the five-class classification using ten-fold cross validation, which is significantly better than the results using support vector machine or random forest, demonstrating the feasibility of the proposed framework to support clinical decision making.

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN

PubMed Central

An, Jubai

2017-01-01

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features. PMID:28792477

High Energy Computed Tomographic Inspection of Munitions

DTIC Science & Technology

2016-11-01

this collection of information is estimated to av erage 1 hour per response, including the time for rev iewing instructions, searching existing data... estimate or any other aspect of this collection of information, including suggestions for reducing the burden to Department of Defense, Washington...UNCLASSIFIED i CONTENTS Page System Background 1 Unique Features 3 Scattering Estimating Device 3 Distortion and Geometric Calibration

The new 34-meter antenna

NASA Technical Reports Server (NTRS)

Pompa, M. F.

1986-01-01

The new 34-m high efficiency Azimuth - Elevation antenna configuration, including its features, dynamic characteristics and performance at 8.4-GHz frequencies is described. The current-technology features of this antenna produce a highly reliable configuration by incorporation of a main wheel and track azimuth support, central pintle pivot bearing, close tolerance surface panels and all-welded construction. Also described are basic drive controls that, as slaved to three automatic microprocessors, provide accurate and safe control of the antenna's steering tasks. At this time antenna installations are completed at Goldstone and Canberra and have operationally supported the Voyager - Uranus encounter. A third installation is being constructed currently in Madrid and is scheduled for completion in late 1986.

Geospatial analysis based on GIS integrated with LADAR.

PubMed

Fetterman, Matt R; Freking, Robert; Fernandez-Cull, Christy; Hinkle, Christopher W; Myne, Anu; Relyea, Steven; Winslow, Jim

2013-10-07

In this work, we describe multi-layered analyses of a high-resolution broad-area LADAR data set in support of expeditionary activities. High-level features are extracted from the LADAR data, such as the presence and location of buildings and cars, and then these features are used to populate a GIS (geographic information system) tool. We also apply line-of-sight (LOS) analysis to develop a path-planning module. Finally, visualization is addressed and enhanced with a gesture-based control system that allows the user to navigate through the enhanced data set in a virtual immersive experience. This work has operational applications including military, security, disaster relief, and task-based robotic path planning.

Magnetic resonance imaging-guided core needle breast biopsies resulting in high-risk histopathologic findings: upstage frequency and lesion characteristics.

PubMed

Weinfurtner, R Jared; Patel, Bhavika; Laronga, Christine; Lee, Marie C; Falcon, Shannon L; Mooney, Blaise P; Yue, Binglin; Drukteinis, Jennifer S

2015-06-01

Analysis of magnetic resonance imaging-guided breast biopsies yielding high-risk histopathologic features at a single institution found an overall upstage rate to malignancy of 14% at surgical excision. All upstaged lesions were associated with atypical ductal hyperplasia. Flat epithelial atypia and atypical lobular hyperplasia alone or with lobular carcinoma in situ were not associated with an upstage to malignancy. The purpose of the present study w as to determine the malignancy upstage rates and imaging features of high-risk histopathologic findings resulting from magnetic resonance imaging (MRI)-guided core needle breast biopsies. These features include atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), flat epithelial atypia (FEA), and lobular carcinoma in situ (LCIS). A retrospective medical record review was performed on all MRI-guided core needle breast biopsies at a single institution from June 1, 2007 to December 1, 2013 to select biopsies yielding high-risk histopathologic findings. The patient demographics, MRI lesion characteristics, and histopathologic features at biopsy and surgical excision were analyzed. A total of 257 MRI-guided biopsies had been performed, and 50 yielded high-risk histopathologic features (19%). Biopsy site and surgical excision site correlation was confirmed in 29 of 50 cases. Four of 29 lesions (14%) were upstaged: 1 case to invasive ductal carcinoma and 3 cases to ductal carcinoma in situ. ADH alone had an overall upstage rate of 7% (1 of 14), mixed ADH/ALH a rate of 75% (3 of 4), ALH alone or with LCIS a rate of 0% (0 of 7), and FEA a rate of 0% (0 of 4). Only mixed ADH/ALH had a statistically significant upstage rate to malignancy compared with the other high-risk histopathologic subtypes combined. No specific imaging characteristics on MRI were associated with an upstage to malignancy on the statistical analysis. MRI-guided breast biopsies yielding high-risk histopathologic features were associated with an overall upstage to malignancy rate of 14% at surgical excision. All upstaged lesions were associated with ADH. FEA and ALH alone or with LCIS were not associated with an upstage to malignancy. Copyright © 2015 Elsevier Inc. All rights reserved.

Feature: Special Needs.

ERIC Educational Resources Information Center

Flores, Miguel R.; And Others

1993-01-01

Includes "Filling in the Cracks" (Flores) about an intarsia class for at-risk students; "Closing the Gap--Women in Technology" (Husher) about summer camps for junior high girls; "Work Force of the Future--Multi-Ethnic, Multicultural" (Hall) about vocational education for culturally diverse students;…

Agreement among Magnetic Resonance Imaging/Magnetic Resonance Cholangiopancreatography (MRI-MRCP) and Endoscopic Ultrasound (EUS) in the evaluation of morphological features of Branch Duct Intraductal Papillary Mucinous Neoplasm (BD-IPMN).

PubMed

Uribarri-Gonzalez, Laura; Keane, Margaret G; Pereira, Stephen P; Iglesias-García, Julio; Dominguez-Muñoz, J Enrique; Lariño-Noia, Jose

2018-03-01

To evaluate the agreement between the imaging modalities MRI-MRCP and EUS in cystic lesions of the pancreas which were thought to be a BD-IPMN. Multicenter retrospective study included all patients between 2010 and 2015 with a suspected BD-IPMN who underwent an EUS and MRI-MRCP within 6 months or less of each other. Location, number, size, worrisome features and high-risk stigmata were evaluated. Interobserver agreement was evaluated by Kappa score. 173 patients were included (97 UHSC, 76 UCLH-RFH), mean age 65 (range 25-87 years), 66 males. When comparing both modalities there was good agreement for the location of the cyst. The median lesion size was larger by MRI-MRCP than EUS although it was not significant. With regards to worrisome features, there was moderate agreement for main PD of 5-9 mm and abrupt change (k = 0.45 and 0.52). Fair agreement was seen for the cyst wall thickening (k = 0.25). No agreement was seen between the presence of non-enhanced mural nodules or lymphadenopathy (k < 0). With regards to high-risk stigmata, poor agreement was obtained for the detection of an enhanced solid component (k = 0.12). No agreement was observed for main PD > 10 mm (k < 0). In this multicentre study of patients with a BD-IPMN under active surveillance, most disagreement between these modalities was seen in the proximal pancreas. There was generally only minimal concordance between the imaging findings of EUS and MRI-MRCP for the detection of high-risk stigmata and worrisome features. Copyright © 2018 IAP and EPC. All rights reserved.

Visual perception as retrospective Bayesian decoding from high- to low-level features

PubMed Central

Ding, Stephanie; Cueva, Christopher J.; Tsodyks, Misha; Qian, Ning

2017-01-01

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. PMID:29073108

Dynamical scattering in coherent hard x-ray nanobeam Bragg diffraction

NASA Astrophysics Data System (ADS)

Pateras, A.; Park, J.; Ahn, Y.; Tilka, J. A.; Holt, M. V.; Kim, H.; Mawst, L. J.; Evans, P. G.

2018-06-01

Unique intensity features arising from dynamical diffraction arise in coherent x-ray nanobeam diffraction patterns of crystals having thicknesses larger than the x-ray extinction depth or exhibiting combinations of nanoscale and mesoscale features. We demonstrate that dynamical scattering effects can be accurately predicted using an optical model combined with the Darwin theory of dynamical x-ray diffraction. The model includes the highly divergent coherent x-ray nanobeams produced by Fresnel zone plate focusing optics and accounts for primary extinction, multiple scattering, and absorption. The simulation accurately reproduces the dynamical scattering features of experimental diffraction patterns acquired from a GaAs/AlGaAs epitaxial heterostructure on a GaAs (001) substrate.

Intratumor heterogeneity of DCE-MRI reveals Ki-67 proliferation status in breast cancer

NASA Astrophysics Data System (ADS)

Cheng, Hu; Fan, Ming; Zhang, Peng; Liu, Bin; Shao, Guoliang; Li, Lihua

2018-03-01

Breast cancer is a highly heterogeneous disease both biologically and clinically, and certain pathologic parameters, i.e., Ki67 expression, are useful in predicting the prognosis of patients. The aim of the study is to identify intratumor heterogeneity of breast cancer for predicting Ki-67 proliferation status in estrogen receptor (ER)-positive breast cancer patients. A dataset of 77 patients was collected who underwent dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) examination. Of these patients, 51 were high-Ki-67 expression and 26 were low-Ki-67 expression. We partitioned the breast tumor into subregions using two methods based on the values of time to peak (TTP) and peak enhancement rate (PER). Within each tumor subregion, image features were extracted including statistical and morphological features from DCE-MRI. The classification models were applied on each region separately to assess whether the classifiers based on features extracted from various subregions features could have different performance for prediction. An area under a receiver operating characteristic curve (AUC) was computed using leave-one-out cross-validation (LOOCV) method. The classifier using features related with moderate time to peak achieved best performance with AUC of 0.826 than that based on the other regions. While using multi-classifier fusion method, the AUC value was significantly (P=0.03) increased to 0.858+/-0.032 compare to classifier with AUC of 0.778 using features from the entire tumor. The results demonstrated that features reflect heterogeneity in intratumoral subregions can improve the classifier performance to predict the Ki-67 proliferation status than the classifier using features from entire tumor alone.

The multigenic nature of the differences in pathogenicity of H5N1 highly pathogenic avian influenza viruses in domestic ducks

USDA-ARS?s Scientific Manuscript database

The Eurasian H5N1 highly pathogenic avian influenza (HPAI) viruses have evolved into many genetic lineages. The divergent strains that have arisen express distinct pathobiological features and increased virulence for many bird species including domestic waterfowl. The pathogenicity of H5N1 HPAI vi...

You Know You Have a Rockin' Artroom When...

ERIC Educational Resources Information Center

Stevens, Lori

2006-01-01

Lori Stevens teaches in the art department of Orland High School, a small high school of 600 students in Orland, California. Her program includes Art 1, Studio Art, and Advanced Placement all in one room, with one budget, and one teacher. She has been teaching art in this setting for twenty years. This article features a color photo of her class…

Advanced Range Safety System for High Energy Vehicles

NASA Technical Reports Server (NTRS)

Claxton, Jeffrey S.; Linton, Donald F.

2002-01-01

The advanced range safety system project is a collaboration between the National Aeronautics and Space Administration and the United States Air Force to develop systems that would reduce costs and schedule for safety approval for new classes of unmanned high-energy vehicles. The mission-planning feature for this system would yield flight profiles that satisfy the mission requirements for the user while providing an increased quality of risk assessment, enhancing public safety. By improving the speed and accuracy of predicting risks to the public, mission planners would be able to expand flight envelopes significantly. Once in place, this system is expected to offer the flexibility of handling real-time risk management for the high-energy capabilities of hypersonic vehicles including autonomous return-from-orbit vehicles and extended flight profiles over land. Users of this system would include mission planners of Space Launch Initiative vehicles, space planes, and other high-energy vehicles. The real-time features of the system could make extended flight of a malfunctioning vehicle possible, in lieu of an immediate terminate decision. With this improved capability, the user would have more time for anomaly resolution and potential recovery of a malfunctioning vehicle.

Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods.

PubMed

Liang, Ja-Der; Ping, Xiao-Ou; Tseng, Yi-Ju; Huang, Guan-Tarn; Lai, Feipei; Yang, Pei-Ming

2014-12-01

Recurrence of hepatocellular carcinoma (HCC) is an important issue despite effective treatments with tumor eradication. Identification of patients who are at high risk for recurrence may provide more efficacious screening and detection of tumor recurrence. The aim of this study was to develop recurrence predictive models for HCC patients who received radiofrequency ablation (RFA) treatment. From January 2007 to December 2009, 83 newly diagnosed HCC patients receiving RFA as their first treatment were enrolled. Five feature selection methods including genetic algorithm (GA), simulated annealing (SA) algorithm, random forests (RF) and hybrid methods (GA+RF and SA+RF) were utilized for selecting an important subset of features from a total of 16 clinical features. These feature selection methods were combined with support vector machine (SVM) for developing predictive models with better performance. Five-fold cross-validation was used to train and test SVM models. The developed SVM-based predictive models with hybrid feature selection methods and 5-fold cross-validation had averages of the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the ROC curve as 67%, 86%, 82%, 69%, 90%, and 0.69, respectively. The SVM derived predictive model can provide suggestive high-risk recurrent patients, who should be closely followed up after complete RFA treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2015-06-01

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

Identification of features of electronic prescribing systems to support quality and safety in primary care using a modified Delphi process.

PubMed

Sweidan, Michelle; Williamson, Margaret; Reeve, James F; Harvey, Ken; O'Neill, Jennifer A; Schattner, Peter; Snowdon, Teri

2010-04-15

Electronic prescribing is increasingly being used in primary care and in hospitals. Studies on the effects of e-prescribing systems have found evidence for both benefit and harm. The aim of this study was to identify features of e-prescribing software systems that support patient safety and quality of care and that are useful to the clinician and the patient, with a focus on improving the quality use of medicines. Software features were identified by a literature review, key informants and an expert group. A modified Delphi process was used with a 12-member multidisciplinary expert group to reach consensus on the expected impact of the features in four domains: patient safety, quality of care, usefulness to the clinician and usefulness to the patient. The setting was electronic prescribing in general practice in Australia. A list of 114 software features was developed. Most of the features relate to the recording and use of patient data, the medication selection process, prescribing decision support, monitoring drug therapy and clinical reports. The expert group rated 78 of the features (68%) as likely to have a high positive impact in at least one domain, 36 features (32%) as medium impact, and none as low or negative impact. Twenty seven features were rated as high positive impact across 3 or 4 domains including patient safety and quality of care. Ten features were considered "aspirational" because of a lack of agreed standards and/or suitable knowledge bases. This study defines features of e-prescribing software systems that are expected to support safety and quality, especially in relation to prescribing and use of medicines in general practice. The features could be used to develop software standards, and could be adapted if necessary for use in other settings and countries.

Identification of features of electronic prescribing systems to support quality and safety in primary care using a modified Delphi process

PubMed Central

2010-01-01

Background Electronic prescribing is increasingly being used in primary care and in hospitals. Studies on the effects of e-prescribing systems have found evidence for both benefit and harm. The aim of this study was to identify features of e-prescribing software systems that support patient safety and quality of care and that are useful to the clinician and the patient, with a focus on improving the quality use of medicines. Methods Software features were identified by a literature review, key informants and an expert group. A modified Delphi process was used with a 12-member multidisciplinary expert group to reach consensus on the expected impact of the features in four domains: patient safety, quality of care, usefulness to the clinician and usefulness to the patient. The setting was electronic prescribing in general practice in Australia. Results A list of 114 software features was developed. Most of the features relate to the recording and use of patient data, the medication selection process, prescribing decision support, monitoring drug therapy and clinical reports. The expert group rated 78 of the features (68%) as likely to have a high positive impact in at least one domain, 36 features (32%) as medium impact, and none as low or negative impact. Twenty seven features were rated as high positive impact across 3 or 4 domains including patient safety and quality of care. Ten features were considered "aspirational" because of a lack of agreed standards and/or suitable knowledge bases. Conclusions This study defines features of e-prescribing software systems that are expected to support safety and quality, especially in relation to prescribing and use of medicines in general practice. The features could be used to develop software standards, and could be adapted if necessary for use in other settings and countries. PMID:20398294

Histopathologic Distinguishing Features Between Lupus and Lichenoid Keratosis on the Face.

PubMed

Marsch, Amanda F; Dacso, Mara; High, Whitney A; Junkins-Hopkins, Jacqueline M

2015-12-01

The occurrence of lichenoid keratosis (LK) on the face is not well characterized, and the histopathologic distinction between LK and lupus erythematosus (LE) occurring on the face is often indeterminate. The authors aimed to describe differences between LE and LK occurring on the face by hematoxylin and eosin alone. Cases of LK and LE were obtained using computer-driven queries. Clinical correlation was obtained for each lupus case. Other diagnoses were excluded for the LK cases. Hematoxylin and eosin-stained sections were reviewed. Forty-five cases of LK and 30 cases of LE occurring on the face were identified. Shared features included follicular involvement, epidermal atrophy, pigment incontinence, paucity of eosinophils, and basket-weave orthokeratosis. Major differences between LK and LE, respectively, included perivascular inflammation (11%, 90%), high Civatte bodies (44%, 7%), solar elastosis (84%, 33%), a predominate pattern of cell-poor vacuolar interface dermatitis (7%, 73%), compact follicular plugging (11%, 50%), hemorrhage (22%, 70%), mucin (0%, 77%), hypergranulosis (44%, 17%), and edema (7%, 60%). A predominate pattern of band-like lichenoid interface was seen more commonly in LK as compared with LE (93% vs. 27%). The authors established the occurrence of LK on the face and identified features to help distinguish LK from LE. Follicular involvement, basket-weave orthokeratosis, pigment incontinence, paucity of eosinophils, and epidermal atrophy were not reliable distinguishing features. Perivascular inflammation, cell-poor vacuolar interface, compact follicular plugging, mucin, hemorrhage, and edema favored LE. High Civatte bodies, band-like lichenoid interface, and solar elastosis favored LK.

Experimental apparatus with full optical access for combustion experiments with laminar flames from a single circular nozzle at elevated pressures.

PubMed

Joo, Peter H; Gao, Jinlong; Li, Zhongshan; Aldén, Marcus

2015-03-01

The design and features of a high pressure chamber and burner that is suitable for combustion experiments at elevated pressures are presented. The high pressure combustion apparatus utilizes a high pressure burner that is comprised of a chamber burner module and an easily accessible interchangeable burner module to add to its flexibility. The burner is well suited to study both premixed and non-premixed flames. The optical access to the chamber is provided through four viewports for direct visual observations and optical-based diagnostic techniques. Auxiliary features include numerous access ports and electrical connections and as a result, the combustion apparatus is also suitable to work with plasmas and liquid fuels. Images of methane flames at elevated pressures up to 25 atm and preliminary results of optical-based measurements demonstrate the suitability of the high pressure experimental apparatus for combustion experiments.

A SVM framework for fault detection of the braking system in a high speed train

NASA Astrophysics Data System (ADS)

Liu, Jie; Li, Yan-Fu; Zio, Enrico

2017-03-01

In April 2015, the number of operating High Speed Trains (HSTs) in the world has reached 3603. An efficient, effective and very reliable braking system is evidently very critical for trains running at a speed around 300 km/h. Failure of a highly reliable braking system is a rare event and, consequently, informative recorded data on fault conditions are scarce. This renders the fault detection problem a classification problem with highly unbalanced data. In this paper, a Support Vector Machine (SVM) framework, including feature selection, feature vector selection, model construction and decision boundary optimization, is proposed for tackling this problem. Feature vector selection can largely reduce the data size and, thus, the computational burden. The constructed model is a modified version of the least square SVM, in which a higher cost is assigned to the error of classification of faulty conditions than the error of classification of normal conditions. The proposed framework is successfully validated on a number of public unbalanced datasets. Then, it is applied for the fault detection of braking systems in HST: in comparison with several SVM approaches for unbalanced datasets, the proposed framework gives better results.

Dynamic adaptive learning for decision-making supporting systems

NASA Astrophysics Data System (ADS)

He, Haibo; Cao, Yuan; Chen, Sheng; Desai, Sachi; Hohil, Myron E.

2008-03-01

This paper proposes a novel adaptive learning method for data mining in support of decision-making systems. Due to the inherent characteristics of information ambiguity/uncertainty, high dimensionality and noisy in many homeland security and defense applications, such as surveillances, monitoring, net-centric battlefield, and others, it is critical to develop autonomous learning methods to efficiently learn useful information from raw data to help the decision making process. The proposed method is based on a dynamic learning principle in the feature spaces. Generally speaking, conventional approaches of learning from high dimensional data sets include various feature extraction (principal component analysis, wavelet transform, and others) and feature selection (embedded approach, wrapper approach, filter approach, and others) methods. However, very limited understandings of adaptive learning from different feature spaces have been achieved. We propose an integrative approach that takes advantages of feature selection and hypothesis ensemble techniques to achieve our goal. Based on the training data distributions, a feature score function is used to provide a measurement of the importance of different features for learning purpose. Then multiple hypotheses are iteratively developed in different feature spaces according to their learning capabilities. Unlike the pre-set iteration steps in many of the existing ensemble learning approaches, such as adaptive boosting (AdaBoost) method, the iterative learning process will automatically stop when the intelligent system can not provide a better understanding than a random guess in that particular subset of feature spaces. Finally, a voting algorithm is used to combine all the decisions from different hypotheses to provide the final prediction results. Simulation analyses of the proposed method on classification of different US military aircraft databases show the effectiveness of this method.

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.

Influence of Solid Noise Barriers on Near-Road and On-Road Air Quality

EPA Science Inventory

Public health concerns regarding adverse health effects for populations spending significant amounts of time near high traffic roadways has increased substantially in recent years. Roadside features, including solid noise barriers, have been investigated as potential methods to ...

A Course for Engineering and Science Students

ERIC Educational Resources Information Center

Companion, A.; Schug, K.

1973-01-01

Discusses the features of a course which emphasizes training of scientists and engineers with broad interdisciplinary knowledge in addition to those with a highly specialized professional preparation. Included is a list of books relating to applications of materials science concepts in general chemistry. (CC)

NASA Tech Briefs, April 1989. Volume 13, No. 4

NASA Technical Reports Server (NTRS)

1989-01-01

A special feature of this issue is an article about the evolution of high technology in Texas. Topics include: Electronic Components & and Circuits. Electronic Systems, Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Fabrication Technology, Mathematics and Information Sciences, and Life Sciences.

On the Origin of the Bolivian High and Related Circulation Features of the South American Climate.

NASA Astrophysics Data System (ADS)

Lenters, J. D.; Cook, K. H.

1997-03-01

The climatological structure in the upper-tropospheric summertime circulation over South America is diagnosed using a GCM (with and without South American topography), a linear model, and observational data. Emphasis is placed on understanding the origin of observed features such as the Bolivian high and the accompanying `Nordeste low' to the east. Results from the linear model indicate that these two features are generated in response to precipitation over the Amazon basin, central Andes, and South Atlantic convergence zone, with African precipitation also playing a crucial role in the formation of the Nordeste low. The direct mechanical and sensible heating effects of the Andes are minimal, acting only to induce a weak lee trough in midlatitudes and a shallow monsoonal circulation over the central Andes. In the GCM, the effects of the Andes include a strengthening of the Bolivian high and northward shift of the Nordeste low, primarily through changes in the precipitation field. The position of the Bolivian high is primarily determined by Amazonian precipitation and is little affected by the removal of the Andes. Strong subsidence to the west of the high is found to be important for the maintenance of the high's warm core, while large-scale convective overshooting to the east is responsible for a layer of cold air above the high.

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.

The predictive value of magnetic resonance imaging of retinoblastoma for the likelihood of high-risk pathologic features.

PubMed

Hiasat, Jamila G; Saleh, Alaa; Al-Hussaini, Maysa; Al Nawaiseh, Ibrahim; Mehyar, Mustafa; Qandeel, Monther; Mohammad, Mona; Deebajah, Rasha; Sultan, Iyad; Jaradat, Imad; Mansour, Asem; Yousef, Yacoub A

2018-06-01

To evaluate the predictive value of magnetic resonance imaging in retinoblastoma for the likelihood of high-risk pathologic features. A retrospective study of 64 eyes enucleated from 60 retinoblastoma patients. Contrast-enhanced magnetic resonance imaging was performed before enucleation. Main outcome measures included demographics, laterality, accuracy, sensitivity, and specificity of magnetic resonance imaging in detecting high-risk pathologic features. Optic nerve invasion and choroidal invasion were seen microscopically in 34 (53%) and 28 (44%) eyes, respectively, while they were detected in magnetic resonance imaging in 22 (34%) and 15 (23%) eyes, respectively. The accuracy of magnetic resonance imaging in detecting prelaminar invasion was 77% (sensitivity 89%, specificity 98%), 56% for laminar invasion (sensitivity 27%, specificity 94%), 84% for postlaminar invasion (sensitivity 42%, specificity 98%), and 100% for optic cut edge invasion (sensitivity100%, specificity 100%). The accuracy of magnetic resonance imaging in detecting focal choroidal invasion was 48% (sensitivity 33%, specificity 97%), and 84% for massive choroidal invasion (sensitivity 53%, specificity 98%), and the accuracy in detecting extrascleral extension was 96% (sensitivity 67%, specificity 98%). Magnetic resonance imaging should not be the only method to stratify patients at high risk from those who are not, eventhough it can predict with high accuracy extensive postlaminar optic nerve invasion, massive choroidal invasion, and extrascleral tumor extension.

Exploring high dimensional data with Butterfly: a novel classification algorithm based on discrete dynamical systems.

PubMed

Geraci, Joseph; Dharsee, Moyez; Nuin, Paulo; Haslehurst, Alexandria; Koti, Madhuri; Feilotter, Harriet E; Evans, Ken

2014-03-01

We introduce a novel method for visualizing high dimensional data via a discrete dynamical system. This method provides a 2D representation of the relationship between subjects according to a set of variables without geometric projections, transformed axes or principal components. The algorithm exploits a memory-type mechanism inherent in a certain class of discrete dynamical systems collectively referred to as the chaos game that are closely related to iterative function systems. The goal of the algorithm was to create a human readable representation of high dimensional patient data that was capable of detecting unrevealed subclusters of patients from within anticipated classifications. This provides a mechanism to further pursue a more personalized exploration of pathology when used with medical data. For clustering and classification protocols, the dynamical system portion of the algorithm is designed to come after some feature selection filter and before some model evaluation (e.g. clustering accuracy) protocol. In the version given here, a univariate features selection step is performed (in practice more complex feature selection methods are used), a discrete dynamical system is driven by this reduced set of variables (which results in a set of 2D cluster models), these models are evaluated for their accuracy (according to a user-defined binary classification) and finally a visual representation of the top classification models are returned. Thus, in addition to the visualization component, this methodology can be used for both supervised and unsupervised machine learning as the top performing models are returned in the protocol we describe here. Butterfly, the algorithm we introduce and provide working code for, uses a discrete dynamical system to classify high dimensional data and provide a 2D representation of the relationship between subjects. We report results on three datasets (two in the article; one in the appendix) including a public lung cancer dataset that comes along with the included Butterfly R package. In the included R script, a univariate feature selection method is used for the dimension reduction step, but in the future we wish to use a more powerful multivariate feature reduction method based on neural networks (Kriesel, 2007). A script written in R (designed to run on R studio) accompanies this article that implements this algorithm and is available at http://butterflygeraci.codeplex.com/. For details on the R package or for help installing the software refer to the accompanying document, Supporting Material and Appendix.

categoryCompare, an analytical tool based on feature annotations

PubMed Central

Flight, Robert M.; Harrison, Benjamin J.; Mohammad, Fahim; Bunge, Mary B.; Moon, Lawrence D. F.; Petruska, Jeffrey C.; Rouchka, Eric C.

2014-01-01

Assessment of high-throughput—omics data initially focuses on relative or raw levels of a particular feature, such as an expression value for a transcript, protein, or metabolite. At a second level, analyses of annotations including known or predicted functions and associations of each individual feature, attempt to distill biological context. Most currently available comparative- and meta-analyses methods are dependent on the availability of identical features across data sets, and concentrate on determining features that are differentially expressed across experiments, some of which may be considered “biomarkers.” The heterogeneity of measurement platforms and inherent variability of biological systems confounds the search for robust biomarkers indicative of a particular condition. In many instances, however, multiple data sets show involvement of common biological processes or signaling pathways, even though individual features are not commonly measured or differentially expressed between them. We developed a methodology, categoryCompare, for cross-platform and cross-sample comparison of high-throughput data at the annotation level. We assessed the utility of the approach using hypothetical data, as well as determining similarities and differences in the set of processes in two instances: (1) denervated skin vs. denervated muscle, and (2) colon from Crohn's disease vs. colon from ulcerative colitis (UC). The hypothetical data showed that in many cases comparing annotations gave superior results to comparing only at the gene level. Improved analytical results depended as well on the number of genes included in the annotation term, the amount of noise in relation to the number of genes expressing in unenriched annotation categories, and the specific method in which samples are combined. In the skin vs. muscle denervation comparison, the tissues demonstrated markedly different responses. The Crohn's vs. UC comparison showed gross similarities in inflammatory response in the two diseases, with particular processes specific to each disease. PMID:24808906

18F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

PubMed

Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

2017-11-01

The aims of our study were to find the textural features on 18 F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18 F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18 F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. 18 F-FDG PET textural features might reflect the differences in histological architecture between cervical cancer subtypes. PET radiomics approaches reveal the association between PET features and will be useful for finding a single feature or a combination of features leading to precise diagnoses, potential prognostic models, and effective therapeutic strategies.

OpenMM 7: Rapid development of high performance algorithms for molecular dynamics

PubMed Central

Swails, Jason; Zhao, Yutong; Beauchamp, Kyle A.; Wang, Lee-Ping; Stern, Chaya D.; Brooks, Bernard R.; Pande, Vijay S.

2017-01-01

OpenMM is a molecular dynamics simulation toolkit with a unique focus on extensibility. It allows users to easily add new features, including forces with novel functional forms, new integration algorithms, and new simulation protocols. Those features automatically work on all supported hardware types (including both CPUs and GPUs) and perform well on all of them. In many cases they require minimal coding, just a mathematical description of the desired function. They also require no modification to OpenMM itself and can be distributed independently of OpenMM. This makes it an ideal tool for researchers developing new simulation methods, and also allows those new methods to be immediately available to the larger community. PMID:28746339

Multiscale Simulations of ALD in Cross Flow Reactors

DOE PAGES

Yanguas-Gil, Angel; Libera, Joseph A.; Elam, Jeffrey W.

2014-08-13

In this study, we have developed a multiscale simulation code that allows us to study the impact of surface chemistry on the coating of large area substrates with high surface area/high aspect-ratio features. Our code, based on open-source libraries, takes advantage of the ALD surface chemistry to achieve an extremely efficient two-way coupling between reactor and feature length scales, and it can provide simulated quartz crystal microbalance and mass spectrometry data at any point of the reactor. By combining experimental surface characterization with simple analysis of growth profiles in a tubular cross flow reactor, we are able to extract amore » minimal set of reactions to effectively model the surface chemistry, including the presence of spurious CVD, to evaluate the impact of surface chemistry on the coating of large, high surface area substrates.« less

Turbine component casting core with high resolution region

DOEpatents

Kamel, Ahmed; Merrill, Gary B.

2014-08-26

A hollow turbine engine component with complex internal features can include a first region and a second, high resolution region. The first region can be defined by a first ceramic core piece formed by any conventional process, such as by injection molding or transfer molding. The second region can be defined by a second ceramic core piece formed separately by a method effective to produce high resolution features, such as tomo lithographic molding. The first core piece and the second core piece can be joined by interlocking engagement that once subjected to an intermediate thermal heat treatment process thermally deform to form a three dimensional interlocking joint between the first and second core pieces by allowing thermal creep to irreversibly interlock the first and second core pieces together such that the joint becomes physically locked together providing joint stability through thermal processing.

Advanced energy system program

NASA Astrophysics Data System (ADS)

Trester, K.

1987-06-01

The ogjectives are to design, develop, and demonstrate a natural-gas-fueled, highly recuperated, 50 kw Brayton-cycle cogeneration system for commercial, institutional, and multifamily residential applications. Recent marketing studies have shown that the Advanced Energy System (AES), with its many cost-effective features, has the potential to offer significant reductions in annual electrical and thermal energy costs to the consumer. Specific advantates of the system that result in low cost ownership are high electrical efficiency (34 percent, LHV), low maintenance, high reliability and long life (20 years). Significant technical features include: an integral turbogenerator with shaft-speed permanent magnet generator; a rotating assembly supported by compliant foil air bearings; a formed-tubesheet plate/fin recuperator with 91 percent effectiveness; and a bi-directional power conditioner to ultilize the generator for system startup. The planned introduction of catalytic combustion will further enhance the economic and ecological attractiveness.

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

Butler, T.; Curtis, O.; Stephenson, R.

As part of the NAHB Research Center Industry Partnership, Southface partnered with TaC Studios, an Atlanta-based architecture firm specializing in residential and light commercial design, on the construction of a new test home in Atlanta, GA, in the mixed humid climate. This home serves as a residence and home office for the firm's owners, as well as a demonstration of their design approach to potential and current clients. Southface believes the home demonstrates current best practices for the mixed-humid climate, including a building envelope featuring advanced air sealing details and low density spray foam insulation, glazing that exceeds ENERGY STARmore » requirements, and a high performance heating and cooling system. Construction quality and execution was a high priority for TaC Studios and was ensured by a third party review process. Post-construction testing showed that the project met stated goals for envelope performance, an air infiltration rate of 2.15 ACH50. The homeowners wished to further validate whole house energy savings through the project's involvement with Building America and this long-term monitoring effort. As a Building America test home, this home was evaluated to detail whole house energy use, end use loads, and the efficiency and operation of the ground source heat pump and associated systems. Given that the home includes many non-typical end use loads including a home office, pool, landscape water feature, and other luxury features not accounted for in Building America modeling tools, these end uses were separately monitored to determine their impact on overall energy consumption.« less

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

Butler, T.; Curtis, O.; Stephenson, R.

As part of the NAHB Research Center Industry Partnership, Southface partnered with TaC Studios, an Atlanta-based architecture firm specializing in residential and light commercial design, on the construction of a new test home in Atlanta, GA in the mixed humid climate. This home serves as a residence and home office for the firm's owners, as well as a demonstration of their design approach topotential and current clients. Southface believes the home demonstrates current best practices for the mixed-humid climate, including a building envelope featuring advanced air sealing details and low density spray foam insulation, glazing that exceeds ENERGY STAR requirements,more » and a high performance heating and cooling system. Construction quality and execution was a high priority for TaCStudios and was ensured by a third party review process. Post-construction testing showed that the project met stated goals for envelope performance, an air infiltration rate of 2.15 ACH50. The homeowners wished to further validate whole house energy savings through the project's involvement with Building America and this long-term monitoring effort. As a Building America test home, this homewas evaluated to detail whole house energy use, end use loads, and the efficiency and operation of the ground source heat pump and associated systems. Given that the home includes many non-typical end use loads including a home office, pool, landscape water feature, and other luxury features not accounted for in Building America modeling tools, these end uses were separately monitored todetermine their impact on overall energy consumption.« less

Assessing the Pathogenicity of Insertion and Deletion Variants with the Variant Effect Scoring Tool (VEST‐Indel)

PubMed Central

Douville, Christopher; Masica, David L.; Stenson, Peter D.; Cooper, David N.; Gygax, Derek M.; Kim, Rick; Ryan, Michael

2015-01-01

ABSTRACT Insertion/deletion variants (indels) alter protein sequence and length, yet are highly prevalent in healthy populations, presenting a challenge to bioinformatics classifiers. Commonly used features—DNA and protein sequence conservation, indel length, and occurrence in repeat regions—are useful for inference of protein damage. However, these features can cause false positives when predicting the impact of indels on disease. Existing methods for indel classification suffer from low specificities, severely limiting clinical utility. Here, we further develop our variant effect scoring tool (VEST) to include the classification of in‐frame and frameshift indels (VEST‐indel) as pathogenic or benign. We apply 24 features, including a new “PubMed” feature, to estimate a gene's importance in human disease. When compared with four existing indel classifiers, our method achieves a drastically reduced false‐positive rate, improving specificity by as much as 90%. This approach of estimating gene importance might be generally applicable to missense and other bioinformatics pathogenicity predictors, which often fail to achieve high specificity. Finally, we tested all possible meta‐predictors that can be obtained from combining the four different indel classifiers using Boolean conjunctions and disjunctions, and derived a meta‐predictor with improved performance over any individual method. PMID:26442818

Spectra of late type dwarf stars of known abundance for stellar population models

NASA Technical Reports Server (NTRS)

Oconnell, R. W.

1990-01-01

The project consisted of two parts. The first was to obtain new low-dispersion, long-wavelength, high S/N IUE spectra of F-G-K dwarf stars with previously determined abundances, temperatures, and gravities. To insure high quality, the spectra are either trailed, or multiple exposures are taken within the large aperture. Second, the spectra are assembled into a library which combines the new data with existing IUE Archive data to yield mean spectral energy distributions for each important type of star. My principal responsibility is the construction and maintenance of this UV spectral library. It covers the spectral range 1200-3200A and is maintained in two parts: a version including complete wavelength coverage at the full spectral resolution of the Low Resolution cameras; and a selected bandpass version, consisting of the mean flux in pre-selected 20A bands. These bands are centered on spectral features or continuum regions of special utility - e.g. the C IV lambda 1550 or Mg II lambda 2800 feature. In the middle-UV region, special emphasis is given to those features (including continuum 'breaks') which are most useful in the study of F-G-K star spectra in the integrated light of old stellar populations.

The role of learning environment on high school chemistry students' motivation and self-regulatory processes

NASA Astrophysics Data System (ADS)

Judd, Jeffrey S.

Changes to the global workforce and technological advancements require graduating high school students to be more autonomous, self-directed, and critical in their thinking. To reflect societal changes, current educational reform has focused on developing more problem-based, collaborative, and student-centered classrooms to promote effective self-regulatory learning strategies, with the goal of helping students adapt to future learning situations and become life-long learners. This study identifies key features that may characterize these "powerful learning environments", which I term "high self-regulating learning environments" for ease of discussion, and examine the environment's role on students' motivation and self-regulatory processes. Using direct observation, surveys, and formal and informal interviews, I identified perceptions, motivations, and self-regulatory strategies of 67 students in my high school chemistry classes as they completed academic tasks in both high and low self-regulating learning environments. With social cognitive theory as a theoretical framework, I then examined how students' beliefs and processes changed after they moved from low to a high self-regulating learning environment. Analyses revealed that key features such as task meaning, utility, complexity, and control appeared to play a role in promoting positive changes in students' motivation and self-regulation. As embedded cases, I also included four students identified as high self-regulating, and four students identified as low self-regulating to examine whether the key features of high and low self-regulating learning environments played a similar role in both groups. Analysis of findings indicates that key features did play a significant role in promoting positive changes in both groups, with high self-regulating students' motivation and self-regulatory strategies generally remaining higher than the low self-regulating students; this was the case in both environments. Findings suggest that classroom learning environments and instruction can be modified using variations of these key features to promote specific or various levels of motivation and self-regulatory skill. In this way, educators may tailor their lessons or design their classrooms to better match and develop students' current level of motivation and self-regulation in order to maximize engagement in an academic task.

Feature Selection Methods for Zero-Shot Learning of Neural Activity

PubMed Central

Caceres, Carlos A.; Roos, Matthew J.; Rupp, Kyle M.; Milsap, Griffin; Crone, Nathan E.; Wolmetz, Michael E.; Ratto, Christopher R.

2017-01-01

Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy. PMID:28690513

Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.

NASA Astrophysics Data System (ADS)

Campo, D.; Quintero, O. L.; Bastidas, M.

2016-04-01

We propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.

Detecting bursts in the EEG of very and extremely premature infants using a multi-feature approach.

PubMed

O'Toole, John M; Boylan, Geraldine B; Lloyd, Rhodri O; Goulding, Robert M; Vanhatalo, Sampsa; Stevenson, Nathan J

2017-07-01

To develop a method that segments preterm EEG into bursts and inter-bursts by extracting and combining multiple EEG features. Two EEG experts annotated bursts in individual EEG channels for 36 preterm infants with gestational age < 30 weeks. The feature set included spectral, amplitude, and frequency-weighted energy features. Using a consensus annotation, feature selection removed redundant features and a support vector machine combined features. Area under the receiver operator characteristic (AUC) and Cohen's kappa (κ) evaluated performance within a cross-validation procedure. The proposed channel-independent method improves AUC by 4-5% over existing methods (p < 0.001, n=36), with median (95% confidence interval) AUC of 0.989 (0.973-0.997) and sensitivity-specificity of 95.8-94.4%. Agreement rates between the detector and experts' annotations, κ=0.72 (0.36-0.83) and κ=0.65 (0.32-0.81), are comparable to inter-rater agreement, κ=0.60 (0.21-0.74). Automating the visual identification of bursts in preterm EEG is achievable with a high level of accuracy. Multiple features, combined using a data-driven approach, improves on existing single-feature methods. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Investigating Aquatic Dead Zones

ERIC Educational Resources Information Center

Testa, Jeremy; Gurbisz, Cassie; Murray, Laura; Gray, William; Bosch, Jennifer; Burrell, Chris; Kemp, Michael

2010-01-01

This article features two engaging high school activities that include current scientific information, data, and authentic case studies. The activities address the physical, biological, and chemical processes that are associated with oxygen-depleted areas, or "dead zones," in aquatic systems. Students can explore these dead zones through both…

A Periglacial Analog for Landforms in Gale Crater, Mars

NASA Technical Reports Server (NTRS)

Oehler, Dorothy Z.

2013-01-01

Several features in a high thermal inertia (TI) unit at Gale crater can be interpreted within a periglacial framework. These features include polygonally fractured terrain (cf. ice-wedge polygons), circumferential patterns of polygonal fractures (cf. relict pingos with ice-wedge polygons on their surfaces), irregularly-shaped and clustered depressions (cf. remnants of collapsed pingos and ephemeral lakes), and a general hummocky topography (cf. thermokarst). This interpretation would imply a major history of water and ice in Gale crater, involving permafrost, freeze-thaw cycles, and perhaps ponded surface water.

An Application Development Platform for Neuromorphic Computing

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

Dean, Mark; Chan, Jason; Daffron, Christopher

2016-01-01

Dynamic Adaptive Neural Network Arrays (DANNAs) are neuromorphic computing systems developed as a hardware based approach to the implementation of neural networks. They feature highly adaptive and programmable structural elements, which model arti cial neural networks with spiking behavior. We design them to solve problems using evolutionary optimization. In this paper, we highlight the current hardware and software implementations of DANNA, including their features, functionalities and performance. We then describe the development of an Application Development Platform (ADP) to support efficient application implementation and testing of DANNA based solutions. We conclude with future directions.

Intestinal microbiome-gut-brain axis and irritable bowel syndrome.

PubMed

Moser, Gabriele; Fournier, Camille; Peter, Johannes

2018-03-01

Psychological comorbidity is highly present in irritable bowel syndrome (IBS). Recent research points to a role of intestinal microbiota in visceral hypersensitivity, anxiety, and depression. Increased disease reactivity to psychological stress has been described too. A few clinical studies have attempted to identify features of dysbiosis in IBS. While animal studies revealed strong associations between stress and gut microbiota, studies in humans are rare. This review covers the most important studies on intestinal microbial correlates of psychological and clinical features in IBS, including stress, anxiety, and depression.

On Laboratory Work

NASA Astrophysics Data System (ADS)

Olney, Dave

1997-11-01

This paper offers some suggestions on making lab work for high school chemistry students more productive, with students taking an active role. They include (1) rewriting labs from manuals to better suit one's purpose, (2) the questionable use of canned data tables, (3) designing microscale labs that utilize its unique features, such as safety and ease of repetition, (4) having students actually carry out experimental design on occasion, using a model from PRACTICE IN THINKING, and (5) using comuters/calculators in the lab in meaningful ways. Many examples feature discovery-type labs the author has developed over the years.

MerCat: a versatile k-mer counter and diversity estimator for database-independent property analysis obtained from metagenomic and/or metatranscriptomic sequencing data

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

White, Richard A.; Panyala, Ajay R.; Glass, Kevin A.

MerCat is a parallel, highly scalable and modular property software package for robust analysis of features in next-generation sequencing data. MerCat inputs include assembled contigs and raw sequence reads from any platform resulting in feature abundance counts tables. MerCat allows for direct analysis of data properties without reference sequence database dependency commonly used by search tools such as BLAST and/or DIAMOND for compositional analysis of whole community shotgun sequencing (e.g. metagenomes and metatranscriptomes).

First hundred cases of variant Creutzfeldt-Jakob disease: retrospective case note review of early psychiatric and neurological features

PubMed Central

Spencer, Michael D; Knight, Richard S G; Will, Robert G

2002-01-01

Objective To describe the early psychiatric and neurological features of variant Creutzfeldt-Jakob disease. Design Cohort study. Setting National surveillance system for Creutzfeldt-Jakob disease in the United Kingdom. Participants The first 100 cases of variant Creutzfeldt-Jakob disease identified in the United Kingdom. Main outcome measures The timing and nature of early psychiatric and neurological symptoms in variant Creutzfeldt-Jakob disease. Results The early stages of variant Creutzfeldt-Jakob disease are dominated by psychiatric symptoms, but neurological symptoms precede psychiatric symptoms in 15% of cases and are present in combination with psychiatric symptoms in 22% of cases from the onset of disease. Common early psychiatric features include dysphoria, withdrawal, anxiety, insomnia, and loss of interest. No common early neurological features exist, but a significant proportion of patients do exhibit neurological symptoms within 4 months of clinical onset, including poor memory, pain, sensory symptoms, unsteadiness of gait, and dysarthria. Conclusions Although the diagnosis of variant Creutzfeldt-Jakob disease may be impossible in the early stages of the illness, particular combinations of psychiatric and neurological features may allow early diagnosis in an appreciable proportion of patients. What is already known on this topicThe early stages of variant Creutzfeldt-Jakob disease are dominated by psychiatric symptomatologySome patients have early neurological features that might suggest the presence of an underlying neurological disorderWhat this study addsThis study provides a comprehensive description of the evolution of psychiatric and neurological features in variant Creutzfeldt-Jakob diseaseAn appreciable proportion of patients have early neurological symptomsA high proportion of patients have a combination of psychiatric and neurological features within four months of clinical onset that suggest the diagnosis of variant Creutzfeldt-Jakob disease PMID:12077031

Insights into multimodal imaging classification of ADHD

PubMed Central

Colby, John B.; Rudie, Jeffrey D.; Brown, Jesse A.; Douglas, Pamela K.; Cohen, Mark S.; Shehzad, Zarrar

2012-01-01

Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by clinicians via subjective ADHD-specific behavioral instruments and by reports from the parents and teachers. Considering its high prevalence and large economic and societal costs, a quantitative tool that aids in diagnosis by characterizing underlying neurobiology would be extremely valuable. This provided motivation for the ADHD-200 machine learning (ML) competition, a multisite collaborative effort to investigate imaging classifiers for ADHD. Here we present our ML approach, which used structural and functional magnetic resonance imaging data, combined with demographic information, to predict diagnostic status of individuals with ADHD from typically developing (TD) children across eight different research sites. Structural features included quantitative metrics from 113 cortical and non-cortical regions. Functional features included Pearson correlation functional connectivity matrices, nodal and global graph theoretical measures, nodal power spectra, voxelwise global connectivity, and voxelwise regional homogeneity. We performed feature ranking for each site and modality using the multiple support vector machine recursive feature elimination (SVM-RFE) algorithm, and feature subset selection by optimizing the expected generalization performance of a radial basis function kernel SVM (RBF-SVM) trained across a range of the top features. Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set. A voting approach was used to combine these multiple predictions and assign final class labels. With this methodology we were able to predict diagnosis of ADHD with 55% accuracy (versus a 39% chance level in this sample), 33% sensitivity, and 80% specificity. This approach also allowed us to evaluate predictive structural and functional features giving insight into abnormal brain circuitry in ADHD. PMID:22912605

Evaluation of features to support safety and quality in general practice clinical software

PubMed Central

2011-01-01

Background Electronic prescribing is now the norm in many countries. We wished to find out if clinical software systems used by general practitioners in Australia include features (functional capabilities and other characteristics) that facilitate improved patient safety and care, with a focus on quality use of medicines. Methods Seven clinical software systems used in general practice were evaluated. Fifty software features that were previously rated as likely to have a high impact on safety and/or quality of care in general practice were tested and are reported here. Results The range of results for the implementation of 50 features across the 7 clinical software systems was as follows: 17-31 features (34-62%) were fully implemented, 9-13 (18-26%) partially implemented, and 9-20 (18-40%) not implemented. Key findings included: Access to evidence based drug and therapeutic information was limited. Decision support for prescribing was available but varied markedly between systems. During prescribing there was potential for medicine mis-selection in some systems, and linking a medicine with its indication was optional. The definition of 'current medicines' versus 'past medicines' was not always clear. There were limited resources for patients, and some medicines lists for patients were suboptimal. Results were provided to the software vendors, who were keen to improve their systems. Conclusions The clinical systems tested lack some of the features expected to support patient safety and quality of care. Standards and certification for clinical software would ensure that safety features are present and that there is a minimum level of clinical functionality that clinicians could expect to find in any system.

Relationships between self-reported childhood traumatic experiences, attachment style, neuroticism and features of borderline personality disorders in patients with mood disorders.

PubMed

Baryshnikov, Ilya; Joffe, Grigori; Koivisto, Maaria; Melartin, Tarja; Aaltonen, Kari; Suominen, Kirsi; Rosenström, Tom; Näätänen, Petri; Karpov, Boris; Heikkinen, Martti; Isometsä, Erkki

2017-03-01

Co-occurring borderline personality disorder (BPD) features have a marked impact on treatment of patients with mood disorders. Overall, high neuroticism, childhood traumatic experiences (TEs) and insecure attachment are plausible aetiological factors for BPD. However, their relationship with BPD features specifically among patients with mood disorders remains unclear. We investigated these relationships among unipolar and bipolar mood disorder patients. As part of the Helsinki University Psychiatric Consortium study, the McLean Screening Instrument (MSI), the Experiences in Close Relationships-Revised (ECR-R), the Short Five (S5) and the Trauma and Distress Scale (TADS) were filled in by patients with mood disorders (n=282) in psychiatric care. Correlation coefficients between total scores of scales and their dimensions were estimated, and multivariate regression (MRA) and mediation analyses were conducted. Spearman's correlations were strong (rho=0.58; p<0.001) between total scores of MSI and S5 Neuroticism and moderate (rho=0.42; p<0.001) between MSI and TADS as well as between MSI and ECR-R Attachment Anxiety. In MRA, young age, S5 Neuroticism and TADS predicted scores of MSI (p<0.001). ECR-R Attachment Anxiety mediated 33% (CI=17-53%) of the relationships between TADS and MSI. Cross-sectional questionnaire study. We found moderately strong correlations between self-reported BPD features and concurrent high neuroticism, reported childhood traumatic experiences and Attachment Anxiety also among patients with mood disorders. Independent predictors for BPD features include young age, frequency of childhood traumatic experiences and high neuroticism. Insecure attachment may partially mediate the relationship between childhood traumatic experiences and borderline features among mood disorder patients. Copyright © 2016 Elsevier B.V. All rights reserved.

State estimation and prediction using clustered particle filters.

PubMed

Lee, Yoonsang; Majda, Andrew J

2016-12-20

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

Pluto's Surface in Detail

NASA Image and Video Library

2017-07-14

On July 14, 2015, NASA's New Horizons spacecraft made its historic flight through the Pluto system. This detailed, high-quality global mosaic of Pluto was assembled from nearly all of the highest-resolution images obtained by the Long-Range Reconnaissance Imager (LORRI) and the Multispectral Visible Imaging Camera (MVIC) on New Horizons. The mosaic is the most detailed and comprehensive global view yet of Pluto's surface using New Horizons data. It includes topography data of the hemisphere visible to New Horizons during the spacecraft's closest approach. The topography is derived from digital stereo-image mapping tools that measure the parallax -- or the difference in the apparent relative positions -- of features on the surface obtained at different viewing angles during the encounter. Scientists use these parallax displacements of high and low terrain to estimate landform heights. The global mosaic has been overlain with transparent, colorized topography data wherever on the surface stereo data is available. Terrain south of about 30°S was in darkness leading up to and during the flyby, so is shown in black. Examples of large-scale topographic features on Pluto include the vast expanse of very flat, low-elevation nitrogen ice plains of Sputnik Planitia ("P") -- note that all feature names in the Pluto system are informal -- and, on the eastern edge of the encounter hemisphere, the aligned, high-elevation ridges of Tartarus Dorsa ("T") that host the enigmatic bladed terrain, mountains, possible cryovolcanos, canyons, craters and more. https://photojournal.jpl.nasa.gov/catalog/PIA21861

State estimation and prediction using clustered particle filters

PubMed Central

Lee, Yoonsang; Majda, Andrew J.

2016-01-01

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

Biomimetic membranes and methods of making biomimetic membranes

DOEpatents

Rempe, Susan; Brinker, Jeffrey C.; Rogers, David Michael; Jiang, Ying-Bing; Yang, Shaorong

2016-11-08

The present disclosure is directed to biomimetic membranes and methods of manufacturing such membranes that include structural features that mimic the structures of cellular membrane channels and produce membrane designs capable of high selectivity and high permeability or adsorptivity. The membrane structure, material and chemistry can be selected to perform liquid separations, gas separation and capture, ion transport and adsorption for a variety of applications.

Affective Functioning among Early Adolescents at High and Low Familial Risk for Depression and Their Mothers: A Focus on Individual and Transactional Processes across Contexts

ERIC Educational Resources Information Center

McMakin, Dana L.; Burkhouse, Katie L.; Olino, Thomas M.; Siegle, Greg J.; Dahl, Ronald E.; Silk, Jennifer S.

2011-01-01

This study aimed to characterize affective functioning in families of youth at high familial risk for depression, with particular attention to features of affective functioning that appear to be critical to adaptive functioning but have been underrepresented in prior research including: positive "and" negative affect across multiple contexts,…

A Science Summer Camp as an Effective Way to Recruit High School Students to Major in the Physical Sciences and Science Education

ERIC Educational Resources Information Center

Bischoff, Paul J.; Castendyk, Devin; Gallagher, Hugh; Schaumloffel, John; Labroo, Sunil

2008-01-01

Now in its fifth year, PR[superscript 2]EPS is a National Science Foundation funded initiative designed to recruit high school students to attend college majoring in the physical sciences, including engineering and secondary science education, and to help ensure their retention within these programs until graduation. A central feature of the…

High temperature arc-track resistant aerospace insulation

NASA Technical Reports Server (NTRS)

Dorogy, William

1994-01-01

The topics are presented in viewgraph form and include the following: high temperature aerospace insulation; Foster-Miller approach to develop a 300 C rated, arc-track resistant aerospace insulation; advantages and disadvantages of key structural features; summary goals and achievements of the phase 1 program; performance goals for selected materials; materials under evaluation; molecular structures of candidate polymers; candidate polymer properties; film properties; and a detailed program plan.

The Europa Imaging System (EIS): High-Resolution, 3-D Insight into Europa's Geology, Ice Shell, and Potential for Current Activity

NASA Astrophysics Data System (ADS)

Turtle, E. P.; McEwen, A. S.; Collins, G. C.; Fletcher, L. N.; Hansen, C. J.; Hayes, A.; Hurford, T., Jr.; Kirk, R. L.; Barr, A.; Nimmo, F.; Patterson, G.; Quick, L. C.; Soderblom, J. M.; Thomas, N.

2015-12-01

The Europa Imaging System will transform our understanding of Europa through global decameter-scale coverage, three-dimensional maps, and unprecedented meter-scale imaging. EIS combines narrow-angle and wide-angle cameras (NAC and WAC) designed to address high-priority Europa science and reconnaissance goals. It will: (A) Characterize the ice shell by constraining its thickness and correlating surface features with subsurface structures detected by ice penetrating radar; (B) Constrain formation processes of surface features and the potential for current activity by characterizing endogenic structures, surface units, global cross-cutting relationships, and relationships to Europa's subsurface structure, and by searching for evidence of recent activity, including potential plumes; and (C) Characterize scientifically compelling landing sites and hazards by determining the nature of the surface at scales relevant to a potential lander. The NAC provides very high-resolution, stereo reconnaissance, generating 2-km-wide swaths at 0.5-m pixel scale from 50-km altitude, and uses a gimbal to enable independent targeting. NAC observations also include: near-global (>95%) mapping of Europa at ≤50-m pixel scale (to date, only ~14% of Europa has been imaged at ≤500 m/pixel, with best pixel scale 6 m); regional and high-resolution stereo imaging at <1-m/pixel; and high-phase-angle observations for plume searches. The WAC is designed to acquire pushbroom stereo swaths along flyby ground-tracks, generating digital topographic models with 32-m spatial scale and 4-m vertical precision from 50-km altitude. These data support characterization of cross-track clutter for radar sounding. The WAC also performs pushbroom color imaging with 6 broadband filters (350-1050 nm) to map surface units and correlations with geologic features and topography. EIS will provide comprehensive data sets essential to fulfilling the goal of exploring Europa to investigate its habitability and perform collaborative science with other investigations, including cartographic and geologic maps, regional and high-resolution digital topography, GIS products, color and photometric data products, a geodetic control network tied to radar altimetry, and a database of plume-search observations.

Three-dimensional velocity models of the Mount St. Helens magmatic system using the iMUSH active-source data set

NASA Astrophysics Data System (ADS)

Kiser, E.; Levander, A.; Zelt, C. A.; Palomeras, I.; Creager, K.; Ulberg, C. W.; Schmandt, B.; Hansen, S. M.; Harder, S. H.; Abers, G. A.; Crosbie, K.

2017-12-01

Building upon previously published 2D results, this presentation will show the first 3D velocity models down to the Moho using the iMUSH (imaging Magma Under St. Helens) active-source seismic data set. Direct P and S wave travel times from 23 borehole shots recorded at approximately 6000 seismograph locations are used to model Vp, Vs, and Vp/Vs over an area extending approximately 75 km from the edifice of Mount St. Helens and down to approximately 15 km depth. At shallow depths, results show several high and low velocity anomalies that correspond well with known geological features. These include the Chehalis Basin northwest of Mount St. Helens, and the Silver Star Mountain, Spirit Lake, and Spud Mountain plutons. Starting at 4 km depth, low velocities and high Vp/Vs values are observed near Mount St. Helens, which may be associated with shallow magmatic fluids. High Vp/Vs values are also observed beneath the Indian Heaven Volcanic Field southeast of Mount St. Helens. At the regional scale, high amplitude north/south trending low and high velocity features extend from the western margin of the resolved models to approximately 30 km west of Mount St. Helens. In general these high and low velocity features also correspond to high and low Vp/Vs anomalies, respectively. These results are in agreement with previous studies that conclude that the accreted terrane Siletzia is composed of multiple igneous bodies interspersed with sedimentary units in this region. Another regional feature of interest is a broad low Vp/Vs area between Mount St. Helens, Mount Adams, and Mount Rainier that spatially correlates with the Southern Washington Cascades Conductor, indicating a non-magmatic origin to this body at shallow and mid-crustal depths. In addition to these shallow results, preliminary 3D velocity models of the entire crust will be presented that utilize both direct and reflected seismic phases from the Moho and other mid-crustal discontinuities. These models will constrain the lateral extents of lower-crustal high and low velocity features observed in previous 2D results. This information will be critical for understanding the distribution of cumulate bodies, magma reservoirs, and accreted terranes in the lower crust, and how these features have affected recent volcanic activity in this region.

Contact-free heart rate measurement using multiple video data

NASA Astrophysics Data System (ADS)

Hung, Pang-Chan; Lee, Kual-Zheng; Tsai, Luo-Wei

2013-10-01

In this paper, we propose a contact-free heart rate measurement method by analyzing sequential images of multiple video data. In the proposed method, skin-like pixels are firstly detected from multiple video data for extracting the color features. These color features are synchronized and analyzed by independent component analysis. A representative component is finally selected among these independent component candidates to measure the HR, which achieves under 2% deviation on average compared with a pulse oximeter in the controllable environment. The advantages of the proposed method include: 1) it uses low cost and high accessibility camera device; 2) it eases users' discomfort by utilizing contact-free measurement; and 3) it achieves the low error rate and the high stability by integrating multiple video data.

Fast 3D Surface Extraction 2 pages (including abstract)

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

Sewell, Christopher Meyer; Patchett, John M.; Ahrens, James P.

Ocean scientists searching for isosurfaces and/or thresholds of interest in high resolution 3D datasets required a tedious and time-consuming interactive exploration experience. PISTON research and development activities are enabling ocean scientists to rapidly and interactively explore isosurfaces and thresholds in their large data sets using a simple slider with real time calculation and visualization of these features. Ocean Scientists can now visualize more features in less time, helping them gain a better understanding of the high resolution data sets they work with on a daily basis. Isosurface timings (512{sup 3} grid): VTK 7.7 s, Parallel VTK (48-core) 1.3 s, PISTONmore » OpenMP (48-core) 0.2 s, PISTON CUDA (Quadro 6000) 0.1 s.« less

Hand ultrasound: a high-fidelity simulation of lung sliding.

PubMed

Shokoohi, Hamid; Boniface, Keith

2012-09-01

Simulation training has been effectively used to integrate didactic knowledge and technical skills in emergency and critical care medicine. In this article, we introduce a novel model of simulating lung ultrasound and the features of lung sliding and pneumothorax by performing a hand ultrasound. The simulation model involves scanning the palmar aspect of the hand to create normal lung sliding in varying modes of scanning and to mimic ultrasound features of pneumothorax, including "stratosphere/barcode sign" and "lung point." The simple, reproducible, and readily available simulation model we describe demonstrates a high-fidelity simulation surrogate that can be used to rapidly illustrate the signs of normal and abnormal lung sliding at the bedside. © 2012 by the Society for Academic Emergency Medicine.

Shift-invariant discrete wavelet transform analysis for retinal image classification.

PubMed

Khademi, April; Krishnan, Sridhar

2007-12-01

This work involves retinal image classification and a novel analysis system was developed. From the compressed domain, the proposed scheme extracts textural features from wavelet coefficients, which describe the relative homogeneity of localized areas of the retinal images. Since the discrete wavelet transform (DWT) is shift-variant, a shift-invariant DWT was explored to ensure that a robust feature set was extracted. To combat the small database size, linear discriminant analysis classification was used with the leave one out method. 38 normal and 48 abnormal (exudates, large drusens, fine drusens, choroidal neovascularization, central vein and artery occlusion, histoplasmosis, arteriosclerotic retinopathy, hemi-central retinal vein occlusion and more) were used and a specificity of 79% and sensitivity of 85.4% were achieved (the average classification rate is 82.2%). The success of the system can be accounted to the highly robust feature set which included translation, scale and semi-rotational, features. Additionally, this technique is database independent since the features were specifically tuned to the pathologies of the human eye.

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

PubMed

Li, Yangming; Olson, Edwin B

2010-01-01

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

A General Purpose Feature Extractor for Light Detection and Ranging Data

PubMed Central

Li, Yangming; Olson, Edwin B.

2010-01-01

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

Recursive feature elimination for biomarker discovery in resting-state functional connectivity.

PubMed

Ravishankar, Hariharan; Madhavan, Radhika; Mullick, Rakesh; Shetty, Teena; Marinelli, Luca; Joel, Suresh E

2016-08-01

Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensionality of images, inter-subject and intra-subject variability and small numbers of subjects compared to the number of derived features. Traditional univariate analysis suffers from the problem of multiple comparisons. Here, we adopt an alternative data-driven method for identifying population differences in functional connectivity. We propose a machine-learning approach to down-select functional connectivity features associated with symptom severity in mild traumatic brain injury (mTBI). Using this approach, we identified functional regions with altered connectivity in mTBI. including the executive control, visual and precuneus networks. We compared functional connections at multiple resolutions to determine which scale would be more sensitive to changes related to patient recovery. These modular network-level features can be used as diagnostic tools for predicting disease severity and recovery profiles.

deepNF: Deep network fusion for protein function prediction.

PubMed

Gligorijevic, Vladimir; Barot, Meet; Bonneau, Richard

2018-06-01

The prevalence of high-throughput experimental methods has resulted in an abundance of large-scale molecular and functional interaction networks. The connectivity of these networks provides a rich source of information for inferring functional annotations for genes and proteins. An important challenge has been to develop methods for combining these heterogeneous networks to extract useful protein feature representations for function prediction. Most of the existing approaches for network integration use shallow models that encounter difficulty in capturing complex and highly-nonlinear network structures. Thus, we propose deepNF, a network fusion method based on Multimodal Deep Autoencoders to extract high-level features of proteins from multiple heterogeneous interaction networks. We apply this method to combine STRING networks to construct a common low-dimensional representation containing high-level protein features. We use separate layers for different network types in the early stages of the multimodal autoencoder, later connecting all the layers into a single bottleneck layer from which we extract features to predict protein function. We compare the cross-validation and temporal holdout predictive performance of our method with state-of-the-art methods, including the recently proposed method Mashup. Our results show that our method outperforms previous methods for both human and yeast STRING networks. We also show substantial improvement in the performance of our method in predicting GO terms of varying type and specificity. deepNF is freely available at: https://github.com/VGligorijevic/deepNF. vgligorijevic@flatironinstitute.org, rb133@nyu.edu. Supplementary data are available at Bioinformatics online.

Comparison of Surface Flow Features from Lidar-Derived Digital Elevation Models with Historical Elevation and Hydrography Data for Minnehaha County, South Dakota

USGS Publications Warehouse

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

2009-01-01

The U.S. Geological Survey (USGS) has taken the lead in the creation of a valuable remote sensing product by incorporating digital elevation models (DEMs) derived from Light Detection and Ranging (lidar) into the National Elevation Dataset (NED), the elevation layer of 'The National Map'. High-resolution lidar-derived DEMs provide the accuracy needed to systematically quantify and fully integrate surface flow including flow direction, flow accumulation, sinks, slope, and a dense drainage network. In 2008, 1-meter resolution lidar data were acquired in Minnehaha County, South Dakota. The acquisition was a collaborative effort between Minnehaha County, the city of Sioux Falls, and the USGS Earth Resources Observation and Science (EROS) Center. With the newly acquired lidar data, USGS scientists generated high-resolution DEMs and surface flow features. This report compares lidar-derived surface flow features in Minnehaha County to 30- and 10-meter elevation data previously incorporated in the NED and ancillary hydrography datasets. Surface flow features generated from lidar-derived DEMs are consistently integrated with elevation and are important in understanding surface-water movement to better detect surface-water runoff, flood inundation, and erosion. Many topographic and hydrologic applications will benefit from the increased availability of accurate, high-quality, and high-resolution surface-water data. The remotely sensed data provide topographic information and data integration capabilities needed for meeting current and future human and environmental needs.

High dynamic range vision sensor for automotive applications

NASA Astrophysics Data System (ADS)

Grenet, Eric; Gyger, Steve; Heim, Pascal; Heitger, Friedrich; Kaess, Francois; Nussbaum, Pascal; Ruedi, Pierre-Francois

2005-02-01

A 128 x 128 pixels, 120 dB vision sensor extracting at the pixel level the contrast magnitude and direction of local image features is used to implement a lane tracking system. The contrast representation (relative change of illumination) delivered by the sensor is independent of the illumination level. Together with the high dynamic range of the sensor, it ensures a very stable image feature representation even with high spatial and temporal inhomogeneities of the illumination. Dispatching off chip image feature is done according to the contrast magnitude, prioritizing features with high contrast magnitude. This allows to reduce drastically the amount of data transmitted out of the chip, hence the processing power required for subsequent processing stages. To compensate for the low fill factor (9%) of the sensor, micro-lenses have been deposited which increase the sensitivity by a factor of 5, corresponding to an equivalent of 2000 ASA. An algorithm exploiting the contrast representation output by the vision sensor has been developed to estimate the position of a vehicle relative to the road markings. The algorithm first detects the road markings based on the contrast direction map. Then, it performs quadratic fits on selected kernel of 3 by 3 pixels to achieve sub-pixel accuracy on the estimation of the lane marking positions. The resulting precision on the estimation of the vehicle lateral position is 1 cm. The algorithm performs efficiently under a wide variety of environmental conditions, including night and rainy conditions.

High Velocity Horizontal Motions at the Edge of Sunspot Penumbrae

NASA Astrophysics Data System (ADS)

Hagenaar-Daggett, Hermance J.; Shine, R.

2010-05-01

The outer edges of sunspot penumbrae have long been noted as a region of interesting dynamics including formation of MMFs, extensions and retractions of the penumbral tips, fast moving (2-3 km/s) bright features dubbed"streakers", and localized regions of high speed downflows interpreted as Evershed "sinks". Using 30s cadence movies of high spatial resolution G band and Ca II H images taken by the Hinode SOT/FPP instrument from 5-7 Jan 2007, we have been investigating the penumbra around a sunspot in AR 10933. In addition to the expected phenomena, we also see occasional small dark crescent-shaped features with high horizontal velocities (6.5 km/s) in G band movies. These appear to be emitted from penumbral tips. They travel about 1.5 Mm developing a bright wake that evolves into a slower moving (1-2 km/s) bright feature. In some cases, there may be an earlier outward propagating disturbance within the penumbra. We have also analyzed available Fe 6302 Stokes V images to obtain information on the magnetic field. Although only lower resolution 6302 images made with a slower cadence are available for these particular data sets, we can establish that the features have the opposite magnetic polarity of the sunspot. This observation may be in agreement with simulations showing that a horizontal flux tube develops crests that move outward with a velocity as large as 10 km/s. This work was supported by NASA contract NNM07AA01C.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

PubMed

Guo, Hao; Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

PubMed Central

Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%. PMID:29387141

Shock metamorphism and impact melting in small impact craters on Earth: Evidence from Kamil crater, Egypt

NASA Astrophysics Data System (ADS)

Fazio, Agnese; Folco, Luigi; D'Orazio, Massimo; Frezzotti, Maria Luce; Cordier, Carole

2014-12-01

Kamil is a 45 m diameter impact crater identified in 2008 in southern Egypt. It was generated by the hypervelocity impact of the Gebel Kamil iron meteorite on a sedimentary target, namely layered sandstones with subhorizontal bedding. We have carried out a petrographic study of samples from the crater wall and ejecta deposits collected during our first geophysical campaign (February 2010) in order to investigate shock effects recorded in these rocks. Ejecta samples reveal a wide range of shock features common in quartz-rich target rocks. They have been divided into two categories, as a function of their abundance at thin section scale: (1) pervasive shock features (the most abundant), including fracturing, planar deformation features, and impact melt lapilli and bombs, and (2) localized shock features (the least abundant) including high-pressure phases and localized impact melting in the form of intergranular melt, melt veins, and melt films in shatter cones. In particular, Kamil crater is the smallest impact crater where shatter cones, coesite, stishovite, diamond, and melt veins have been reported. Based on experimental calibrations reported in the literature, pervasive shock features suggest that the maximum shock pressure was between 30 and 60 GPa. Using the planar impact approximation, we calculate a vertical component of the impact velocity of at least 3.5 km s-1. The wide range of shock features and their freshness make Kamil a natural laboratory for studying impact cratering and shock deformation processes in small impact structures.

Large-scale Topographical Screen for Investigation of Physical Neural-Guidance Cues

NASA Astrophysics Data System (ADS)

Li, Wei; Tang, Qing Yuan; Jadhav, Amol D.; Narang, Ankit; Qian, Wei Xian; Shi, Peng; Pang, Stella W.

2015-03-01

A combinatorial approach was used to present primary neurons with a large library of topographical features in the form of micropatterned substrate for high-throughput screening of physical neural-guidance cues that can effectively promote different aspects of neuronal development, including axon and dendritic outgrowth. Notably, the neuronal-guidance capability of specific features was automatically identified using a customized image processing software, thus significantly increasing the screening throughput with minimal subjective bias. Our results indicate that the anisotropic topographies promote axonal and in some cases dendritic extension relative to the isotropic topographies, while dendritic branching showed preference to plain substrates over the microscale features. The results from this work can be readily applied towards engineering novel biomaterials with precise surface topography that can serve as guidance conduits for neuro-regenerative applications. This novel topographical screening strategy combined with the automated processing capability can also be used for high-throughput screening of chemical or genetic regulatory factors in primary neurons.

2-DE combined with two-layer feature selection accurately establishes the origin of oolong tea.

PubMed

Chien, Han-Ju; Chu, Yen-Wei; Chen, Chi-Wei; Juang, Yu-Min; Chien, Min-Wei; Liu, Chih-Wei; Wu, Chia-Chang; Tzen, Jason T C; Lai, Chien-Chen

2016-11-15

Taiwan is known for its high quality oolong tea. Because of high consumer demand, some tea manufactures mix lower quality leaves with genuine Taiwan oolong tea in order to increase profits. Robust scientific methods are, therefore, needed to verify the origin and quality of tea leaves. In this study, we investigated whether two-dimensional gel electrophoresis (2-DE) and nanoscale liquid chromatography/tandem mass spectroscopy (nano-LC/MS/MS) coupled with a two-layer feature selection mechanism comprising information gain attribute evaluation (IGAE) and support vector machine feature selection (SVM-FS) are useful in identifying characteristic proteins that can be used as markers of the original source of oolong tea. Samples in this study included oolong tea leaves from 23 different sources. We found that our method had an accuracy of 95.5% in correctly identifying the origin of the leaves. Overall, our method is a novel approach for determining the origin of oolong tea leaves. Copyright © 2016 Elsevier Ltd. All rights reserved.

Redox flow cell energy storage systems

NASA Technical Reports Server (NTRS)

Thaller, L. H.

1979-01-01

NASA-Redox systems are electrochemical storage devices that use two fully soluble Redox couples, anode and cathode fluids, as active electrode materials separated by a highly selective ion exchange membrane. The reactants are contained in large storage tanks and pumped through a stack of Redox flow cells where the electrochemical reactions (reduction and oxidation) take place at porous carbon felt electrodes. A string or stack of these power producing cells is connected in series in a bipolar manner. Redox energy storage systems promise to be inexpensive and possess many features that provide for flexible design, long life, high reliability and minimal operation and maintenance costs. These features include independent sizing of power and storage capacity requirements and inclusion within the cell stack of a cell that monitors the state of charge of the system as a whole, and a rebalance cell which permits continuous correction to be made for minor side reactions that would tend to result in the anode fluid and cathode fluids becoming electrochemically out of balance. These system features are described and discussed.

hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

PubMed

Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

SU-F-R-14: PET Based Radiomics to Predict Outcomes in Patients with Hodgkin Lymphoma

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

Lee, J; Aristophanous, M; Akhtari, M

Purpose: To identify PET-based radiomics features associated with high refractory/relapsed disease risk for Hodgkin lymphoma patients. Methods: A total of 251 Hodgkin lymphoma patients including 19 primary refractory and 9 relapsed patients were investigated. All patients underwent an initial pre-treatment diagnostic FDG PET/CT scan. All cancerous lymph node regions (ROIs) were delineated by an experienced physician based on thresholding each volume of disease in the anatomical regions to SUV>2.5. We extracted 122 image features and evaluated the effect of ROI selection (the largest ROI, the ROI with highest mean SUV, merged ROI, and a single anatomic region [e.g. mediastinum]) onmore » classification accuracy. Random forest was used as a classifier and ROC analysis was used to assess the relationship between selected features and patient’s outcome status. Results: Each patient had between 1 and 9 separate ROIs, with much intra-patient variability in PET features. The best model, which used features from a single anatomic region (the mediastinal ROI, only volumes>5cc: 169 patients with 12 primary refractory) had a classification accuracy of 80.5% for primary refractory disease. The top five features, based on Gini index, consist of shape features (max 3D-diameter and volume) and texture features (correlation and information measure of correlation1&2). In the ROC analysis, sensitivity and specificity of the best model were 0.92 and 0.80, respectively. The area under the ROC (AUC) and the accuracy were 0.86 and 0.86, respectively. The classification accuracy was less than 60% for other ROI models or when ROIs less than 5cc were included. Conclusion: This study showed that PET-based radiomics features from the mediastinal lymph region are associated with primary refractory disease and therefore may play an important role in predicting outcomes in Hodgkin lymphoma patients. These features could be additive beyond baseline tumor and clinical characteristics, and may warrant more aggressive treatment.« less

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis.

PubMed

Bühnemann, Claudia; Li, Simon; Yu, Haiyue; Branford White, Harriet; Schäfer, Karl L; Llombart-Bosch, Antonio; Machado, Isidro; Picci, Piero; Hogendoorn, Pancras C W; Athanasou, Nicholas A; Noble, J Alison; Hassan, A Bassim

2014-01-01

Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK) localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases). Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%). The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36) was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. Such an automated and integrated methodology has potential application in the identification of prognostic classifiers based on tumour cell heterogeneity.

Automatic seizure detection in SEEG using high frequency activities in wavelet domain.

PubMed

Ayoubian, L; Lacoma, H; Gotman, J

2013-03-01

Existing automatic detection techniques show high sensitivity and moderate specificity, and detect seizures a relatively long time after onset. High frequency (80-500 Hz) activity has recently been shown to be prominent in the intracranial EEG of epileptic patients but has not been used in seizure detection. The purpose of this study is to investigate if these frequencies can contribute to seizure detection. The system was designed using 30 h of intracranial EEG, including 15 seizures in 15 patients. Wavelet decomposition, feature extraction, adaptive thresholding and artifact removal were employed in training data. An EMG removal algorithm was developed based on two features: Lack of correlation between frequency bands and energy-spread in frequency. Results based on the analysis of testing data (36 h of intracranial EEG, including 18 seizures) show a sensitivity of 72%, a false detection of 0.7/h and a median delay of 5.7 s. Missed seizures originated mainly from seizures with subtle or absent high frequencies or from EMG removal procedures. False detections were mainly due to weak EMG or interictal high frequency activities. The system performed sufficiently well to be considered for clinical use, despite the exclusive use of frequencies not usually considered in clinical interpretation. High frequencies have the potential to contribute significantly to the detection of epileptic seizures. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

Automatic seizure detection in SEEG using high frequency activities in wavelet domain

PubMed Central

Ayoubian, L.; Lacoma, H.; Gotman, J.

2015-01-01

Existing automatic detection techniques show high sensitivity and moderate specificity, and detect seizures a relatively long time after onset. High frequency (80–500 Hz) activity has recently been shown to be prominent in the intracranial EEG of epileptic patients but has not been used in seizure detection. The purpose of this study is to investigate if these frequencies can contribute to seizure detection. The system was designed using 30 h of intracranial EEG, including 15 seizures in 15 patients. Wavelet decomposition, feature extraction, adaptive thresholding and artifact removal were employed in training data. An EMG removal algorithm was developed based on two features: Lack of correlation between frequency bands and energy-spread in frequency. Results based on the analysis of testing data (36 h of intracranial EEG, including 18 seizures) show a sensitivity of 72%, a false detection of 0.7/h and a median delay of 5.7 s. Missed seizures originated mainly from seizures with subtle or absent high frequencies or from EMG removal procedures. False detections were mainly due to weak EMG or interictal high frequency activities. The system performed sufficiently well to be considered for clinical use, despite the exclusive use of frequencies not usually considered in clinical interpretation. High frequencies have the potential to contribute significantly to the detection of epileptic seizures. PMID:22647836

K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

NASA Astrophysics Data System (ADS)

Wang, Dong

2016-03-01

Gears are the most commonly used components in mechanical transmission systems. Their failures may cause transmission system breakdown and result in economic loss. Identification of different gear crack levels is important to prevent any unexpected gear failure because gear cracks lead to gear tooth breakage. Signal processing based methods mainly require expertize to explain gear fault signatures which is usually not easy to be achieved by ordinary users. In order to automatically identify different gear crack levels, intelligent gear crack identification methods should be developed. The previous case studies experimentally proved that K-nearest neighbors based methods exhibit high prediction accuracies for identification of 3 different gear crack levels under different motor speeds and loads. In this short communication, to further enhance prediction accuracies of existing K-nearest neighbors based methods and extend identification of 3 different gear crack levels to identification of 5 different gear crack levels, redundant statistical features are constructed by using Daubechies 44 (db44) binary wavelet packet transform at different wavelet decomposition levels, prior to the use of a K-nearest neighbors method. The dimensionality of redundant statistical features is 620, which provides richer gear fault signatures. Since many of these statistical features are redundant and highly correlated with each other, dimensionality reduction of redundant statistical features is conducted to obtain new significant statistical features. At last, the K-nearest neighbors method is used to identify 5 different gear crack levels under different motor speeds and loads. A case study including 3 experiments is investigated to demonstrate that the developed method provides higher prediction accuracies than the existing K-nearest neighbors based methods for recognizing different gear crack levels under different motor speeds and loads. Based on the new significant statistical features, some other popular statistical models including linear discriminant analysis, quadratic discriminant analysis, classification and regression tree and naive Bayes classifier, are compared with the developed method. The results show that the developed method has the highest prediction accuracies among these statistical models. Additionally, selection of the number of new significant features and parameter selection of K-nearest neighbors are thoroughly investigated.

Uniform competency-based local feature extraction for remote sensing images

NASA Astrophysics Data System (ADS)

Sedaghat, Amin; Mohammadi, Nazila

2018-01-01

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

Melancholic features and hostility are associated with suicidality risk in Asian patients with major depressive disorder.

PubMed

Jeon, Hong Jin; Peng, Daihui; Chua, Hong Choon; Srisurapanont, Manit; Fava, Maurizio; Bae, Jae-Nam; Man Chang, Sung; Hong, Jin Pyo

2013-06-01

Suicide rates are higher in East-Asians than other populations, and especially high in Koreans. However, little is known about suicidality risk and melancholic features in Asian patients with major depressive disorder (MDD). Drug-free MDD outpatients were included from 13 centers across five ethnicities consisting of Chinese (n=290), Korean (n=101), Thai (n=102), Indian (n=27), and Malay (n=27). All were interviewed using the Mini-International Neuropsychiatric Interview (M.I.N.I.), the Montgomery-Åsberg Depression Rating Scale (MADRS), and the Symptoms Checklist 90-Revised (SCL-90-R). Of 547 subjects, 177 MDD patients showed melancholic features (32.4%). These melancholic MDD patients revealed significantly higher suicidality risk (p<0.0001), hostility (p=0.037), and severity of depression (p<0.0001) than those MDD patients without melancholic features. Suicidality risk was significantly higher in MDD with melancholic features than those without in subjects with lower hostility, whereas it showed no difference in higher hostility. Adjusted odds ratios of melancholic features and hostility for moderate to high suicidality risk were 1.79 (95% CI=1.15-2.79) and 2.45 (95% CI=1.37-4.38), after adjusting for age, sex, education years, and depression severity. Post-hoc analyses showed that suicidality risk was higher in Korean and Chinese than that of Thai, Indian and Malay in MDD subjects with melancholic features, although depression severity showed no significant differences among the ethnicities. Suicidality risk is associated with both melancholic features and hostility and it shows cross-ethnic differences in Asian MDD patients, independent of depression severity. Copyright © 2013 Elsevier B.V. All rights reserved.

Macropolygon morphology, development, and classification on North Panamint and Eureka playas, Death Valley National Park CA

USGS Publications Warehouse

Messina, P.; Stoffer, P.; Smith, W.C.

2005-01-01

Panamint and Eureka playas, both located within Death Valley National Park, exhibit a host of surficial features including fissures, pits, mounds, and plant-covered ridges, representing topographic highs and lows that vary up to 2 m of relief from the playa surface. Aerial photographs reveal that these linear strands often converge to form polygons, ranging in length from several meters to nearly a kilometer. These features stand out in generally dark contrast to the brighter intervening expanse of flat, plant-free, desiccated mud of the typical playa surface. Ground-truth mapping of playa features with differential GPS (Global Positioning System) was conducted in 1999 (North Panamint Valley) and 2002 (Eureka Valley). High-resolution digital maps reveal that both playas possess macropolygons of similar scale and geometry, and that fissures may be categorized into one of two genetic groups: (1) shore-parallel or playa-interior desiccation and shrinkage; and (2) tectonic-induced cracks. Early investigations of these features in Eureka Valley concluded that their origin may have been related to agricultural activity by paleo-Indian communities. Although human artifacts are abundant at each locale, there is no evidence to support the inference that surface features reported on Eureka Playa are anthropogenic in origin. Our assumptions into the genesis of polygons on playas is based on our fortuitous experience of witnessing a fissure in the process of formation on Panamint Playa after a flash flood (May 1999); our observations revealed a paradox that saturation of the upper playa crusts contributes to the establishment of some desiccation features. Follow-up visits to the same feature over 2 yrs' time are a foundation for insight into the evolution and possible longevity of these features. ?? 2005 Elsevier B.V. All rights reserved.

PCI-based WILDFIRE reconfigurable computing engines

NASA Astrophysics Data System (ADS)

Fross, Bradley K.; Donaldson, Robert L.; Palmer, Douglas J.

1996-10-01

WILDFORCE is the first PCI-based custom reconfigurable computer that is based on the Splash 2 technology transferred from the National Security Agency and the Institute for Defense Analyses, Supercomputing Research Center (SRC). The WILDFORCE architecture has many of the features of the WILDFIRE computer, such as field- programmable gate array (FPGA) based processing elements, linear array and crossbar interconnection, and high- performance memory and I/O subsystems. New features introduced in the PCI-based WILDFIRE systems include memory/processor options that can be added to any processing element. These options include static and dynamic memory, digital signal processors (DSPs), FPGAs, and microprocessors. In addition to memory/processor options, many different application specific connectors can be used to extend the I/O capabilities of the system, including systolic I/O, camera input and video display output. This paper also discusses how this new PCI-based reconfigurable computing engine is used for rapid-prototyping, real-time video processing and other DSP applications.

A passive solar residence using native and recycled materials, Bee Cave, Texas

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

Holder, L.M. III; King, L.H.

The Booth Residence at Bee Cave, Texas is a Passive Solar residence in a hot humid climate and a good example of both passive solar and renewable features. The design, operation, materials, and furnishings give the structure a regional and rustic character. Passive solar strategies employed include solar orientation, solar shading, natural ventilation, induced ventilation, night flushing, direct gain clearstory, high mass floors, daylighting, radiant barrier, and a double ventilated roof system. The project is in contrast to the existing compound which includes three identical buildings each rotated 120 degrees and intended to be energy efficient, but actual operation hasmore » pointed out some deficiencies in the design. Additional features include extensive use of natural, recycled, and materials reused from other buildings. The Boothe Residence is an example of building in harmony with the local climate, the use of locally available materials, craftsman, artists, manpower, and reuse of trim and furnishings.« less

Deep Learning in Label-free Cell Classification

PubMed Central

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-01-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells. PMID:26975219

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

PubMed Central

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain. PMID:27057543

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder.

PubMed

Zhao, Guangjun; Wang, Xuchu; Niu, Yanmin; Tan, Liwen; Zhang, Shao-Xiang

2016-01-01

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Deep Learning in Label-free Cell Classification

NASA Astrophysics Data System (ADS)

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

2016-03-01

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer

NASA Astrophysics Data System (ADS)

Zhang, Yucheng; Oikonomou, Anastasia; Wong, Alexander; Haider, Masoom A.; Khalvati, Farzad

2017-04-01

Radiomics characterizes tumor phenotypes by extracting large numbers of quantitative features from radiological images. Radiomic features have been shown to provide prognostic value in predicting clinical outcomes in several studies. However, several challenges including feature redundancy, unbalanced data, and small sample sizes have led to relatively low predictive accuracy. In this study, we explore different strategies for overcoming these challenges and improving predictive performance of radiomics-based prognosis for non-small cell lung cancer (NSCLC). CT images of 112 patients (mean age 75 years) with NSCLC who underwent stereotactic body radiotherapy were used to predict recurrence, death, and recurrence-free survival using a comprehensive radiomics analysis. Different feature selection and predictive modeling techniques were used to determine the optimal configuration of prognosis analysis. To address feature redundancy, comprehensive analysis indicated that Random Forest models and Principal Component Analysis were optimum predictive modeling and feature selection methods, respectively, for achieving high prognosis performance. To address unbalanced data, Synthetic Minority Over-sampling technique was found to significantly increase predictive accuracy. A full analysis of variance showed that data endpoints, feature selection techniques, and classifiers were significant factors in affecting predictive accuracy, suggesting that these factors must be investigated when building radiomics-based predictive models for cancer prognosis.

The Solar Flare 4: 10 keV X-ray Spectrum

NASA Technical Reports Server (NTRS)

Phillips, K. J. H.

2004-01-01

The 4-10 keV solar flare spectrum includes highly excited lines of stripped Ca, Fe, and Ni ions as well as a continuum steeply falling with energy. Groups of lines at approximately 7 keV and approximately 8 keV, observed during flares by the broad-band RHESSI spectrometer and called here the Fe-line and Fe/Ni-line features, are formed mostly of Fe lines but with Ni lines contributing to the approximately 8 keV feature. Possible temperature indicators of these line features are discussed - the peak or centroid energies of the Fe-line feature, the line ratio of the Fe-line to the Fe/Ni-line features, and the equivalent width of the Fe-line feature. The equivalent width is by far the most sensitive to temperature. However, results will be confused if, as is commonly believed, the abundance of Fe varies from flare to flare, even during the course of a single flare. With temperature determined from the thermal continuum, the Fe-line feature becomes a diagnostic of the Fe abundance in flare plasmas. These results are of interest for other hot plasmas in coronal ionization equilibrium such as stellar flare plasmas, hot gas in galaxies, and older supernova remnants.

High pressure flow-rate switch

NASA Technical Reports Server (NTRS)

Gale, G. P.

1970-01-01

Flow-rate switch adjusts easily over a wide switching range and operates uniformly over many cycles. It adapts easily to control of various fluids and has the possibility of introducing multi-point switching. Novel design features include the tapered spool, balanced porting, capillary-bypass lubrication, and capillary-restriction damping.

Reflecting Schmidt/Littrow Prism Imaging Spectrometer

NASA Technical Reports Server (NTRS)

Breckinridge, J. B.; Page, N. A.; Shack, R. V.; Shannon, R. R.

1985-01-01

High resolution achieved with wide field of view. Imaging Spectrometer features off-axis reflecting optics, including reflecting "slit" that also serves as field flattener. Only refracting element is prism. By scanning slit across object or scene and timing out signal, both spectral and spatial information in scene are obtained.

Group Therapy Techniques for Sexually Abused Preteen Girls.

ERIC Educational Resources Information Center

Berman, Pearl

1990-01-01

Describes an open-ended, structured, highly intensive therapy group for sexually abused preteen girls that was the primary mode of treatment for 11 girls from low-income, rural White families with numerous problems. Unique features of the group included simultaneous group and individualized goals. (Author/BB)

Some Common and Unique Features of Special Education in the Nordic Countries.

ERIC Educational Resources Information Center

Juul, Kristen D.

1989-01-01

Similarities in special education services in the five Scandinavian countries include their normalization philosophy and cooperative policy development. Among unique Scandinavian innovations are camp schools, folk high schools, toy libraries (lekoteks), therapeutic communities or collectives for young substance abuses, and measures to combat…

47 CFR 15.403 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Network. (r) Transmit Power Control (TPC). A feature that enables a U-NII device to dynamically switch... control level. Power must be summed across all antennas and antenna elements. The average must not include... modulation techniques and provide a wide array of high data rate mobile and fixed communications for...

47 CFR 15.403 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Network. (r) Transmit Power Control (TPC). A feature that enables a U-NII device to dynamically switch... control level. Power must be summed across all antennas and antenna elements. The average must not include... modulation techniques and provide a wide array of high data rate mobile and fixed communications for...

TU-D-207B-02: Delta-Radiomics: The Prognostic Value of Therapy-Induced Changes in Radiomics Features for Stage III Non-Small Cell Lung Cancer Patients

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

Fave, X; Court, L; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX

Purpose: To determine how radiomics features change during radiation therapy and whether those changes (delta-radiomics features) can improve prognostic models built with clinical factors. Methods: 62 radiomics features, including histogram, co-occurrence, run-length, gray-tone difference, and shape features, were calculated from pretreatment and weekly intra-treatment CTs for 107 stage III NSCLC patients (5–9 images per patient). Image preprocessing for each feature was determined using the set of pretreatment images: bit-depth resample and/or a smoothing filter were tested for their impact on volume-correlation and significance of each feature in univariate cox regression models to maximize their information content. Next, the optimized featuresmore » were calculated from the intratreatment images and tested in linear mixed-effects models to determine which features changed significantly with dose-fraction. The slopes in these significant features were defined as delta-radiomics features. To test their prognostic potential multivariate cox regression models were fitted, first using only clinical features and then clinical+delta-radiomics features for overall-survival, local-recurrence, and distant-metastases. Leave-one-out cross validation was used for model-fitting and patient predictions. Concordance indices(c-index) and p-values for the log-rank test with patients stratified at the median were calculated. Results: Approximately one-half of the 62 optimized features required no preprocessing, one-fourth required smoothing, and one-fourth required smoothing and resampling. From these, 54 changed significantly during treatment. For overall-survival, the c-index improved from 0.52 for clinical factors alone to 0.62 for clinical+delta-radiomics features. For distant-metastases, the c-index improved from 0.53 to 0.58, while for local-recurrence it did not improve. Patient stratification significantly improved (p-value<0.05) for overallsurvival and distant-metastases when delta-radiomics features were included. The delta-radiomics versions of autocorrelation, kurtosis, and compactness were selected most frequently in leave-one-out iterations. Conclusion: Weekly changes in radiomics features can potentially be used to evaluate treatment response and predict patient outcomes. High-risk patients could be recommended for dose escalation or consolidation chemotherapy. This project was funded in part by grants from the National Cancer Institute (NCI) and the Cancer Prevention Research Institute of Texas (CPRIT).« less

High-performance large-area AMLCD avionic display module

NASA Astrophysics Data System (ADS)

Syroid, Daniel D.; Hansen, Glenn A.

1995-06-01

There is a need for a reliable source of high performance large area sunlight readable active matrix liquid crystal displays (AMLCDs) for avionic and military land vehicle applications. Image Quest has developed an avionic display module (ADM) to demonstrate the capability to produce high performance avionic displays to satisfy this need. The ADM is a large area (6.24 X 8.32 inch) display with VGA compatible interface, 640 X 480 color pixels and 64 gray shades per primary color. The display features excellent color discrimination in full sunlight due to a saturated color gamut, very low specular reflectance (< 1%) and high output white luminance (200 fL). The ADM is designed from the glass up to fully meet the avionic and military application and environment. Control over all the display performance parameters including contrast, transmission, chroma, resolution, active size and packaging configuration is ensured because Image Quest produces all of the critical elements of the display. These elements include the a-Si TFT AMLCD glass, RGB color filter matrix, bonding of folded back driver TABs, anti-reflective cover glass, LC heater and integration of high luminance hot cathode backlight with thermal controls. The display features rugged compact packaging, 2000:1 luminance dimming range and wide operating temperature range (-40 to +71 $DRGC). In the immediate future Image Quest plans to expand the development efforts to other similar custom high resolution and high performance avionic display module configurations including 4 X 4 inch delta triad, 6.7 X 6.7 inch delta triad and 16.5 inch diagonal with 1280 X 1024 pixels. Image Quest can deliver up to 10,000 displays per year on a timely basis at a reasonable cost.

Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE.

PubMed

Jamieson, Andrew R; Giger, Maryellen L; Drukker, Karen; Li, Hui; Yuan, Yading; Bhooshan, Neha

2010-01-01

In this preliminary study, recently developed unsupervised nonlinear dimension reduction (DR) and data representation techniques were applied to computer-extracted breast lesion feature spaces across three separate imaging modalities: Ultrasound (U.S.) with 1126 cases, dynamic contrast enhanced magnetic resonance imaging with 356 cases, and full-field digital mammography with 245 cases. Two methods for nonlinear DR were explored: Laplacian eigenmaps [M. Belkin and P. Niyogi, "Laplacian eigenmaps for dimensionality reduction and data representation," Neural Comput. 15, 1373-1396 (2003)] and t-distributed stochastic neighbor embedding (t-SNE) [L. van der Maaten and G. Hinton, "Visualizing data using t-SNE," J. Mach. Learn. Res. 9, 2579-2605 (2008)]. These methods attempt to map originally high dimensional feature spaces to more human interpretable lower dimensional spaces while preserving both local and global information. The properties of these methods as applied to breast computer-aided diagnosis (CADx) were evaluated in the context of malignancy classification performance as well as in the visual inspection of the sparseness within the two-dimensional and three-dimensional mappings. Classification performance was estimated by using the reduced dimension mapped feature output as input into both linear and nonlinear classifiers: Markov chain Monte Carlo based Bayesian artificial neural network (MCMC-BANN) and linear discriminant analysis. The new techniques were compared to previously developed breast CADx methodologies, including automatic relevance determination and linear stepwise (LSW) feature selection, as well as a linear DR method based on principal component analysis. Using ROC analysis and 0.632+bootstrap validation, 95% empirical confidence intervals were computed for the each classifier's AUC performance. In the large U.S. data set, sample high performance results include, AUC0.632+ = 0.88 with 95% empirical bootstrap interval [0.787;0.895] for 13 ARD selected features and AUC0.632+ = 0.87 with interval [0.817;0.906] for four LSW selected features compared to 4D t-SNE mapping (from the original 81D feature space) giving AUC0.632+ = 0.90 with interval [0.847;0.919], all using the MCMC-BANN. Preliminary results appear to indicate capability for the new methods to match or exceed classification performance of current advanced breast lesion CADx algorithms. While not appropriate as a complete replacement of feature selection in CADx problems, DR techniques offer a complementary approach, which can aid elucidation of additional properties associated with the data. Specifically, the new techniques were shown to possess the added benefit of delivering sparse lower dimensional representations for visual interpretation, revealing intricate data structure of the feature space.

Diffuse alveolar hemorrhage in patients with systemic lupus erythematosus. Clinical manifestations, treatment, and prognosis.

PubMed

Martínez-Martínez, Marco Ulises; Abud-Mendoza, Carlos

2014-01-01

Diffuse alveolar hemorrhage (DAH) in patients with systemic lupus erythematosus is a rare but potentially fatal condition. Although the pathogenesis of this condition is unknown, high disease activity is the main characteristic; moreover, histopathology in some studies showed alveolar immune complex deposits and capillaritis. Clinical features of DAH include dyspnea, a drop in hemoglobin, and diffuse radiographic alveolar images, with or without hemoptysis. Factors associated with mortality include mechanical ventilation, renal failure, and infections. Bacterial infections have been reported frequently in patients with DAH, but also invasive fungal infections including aspergillosis. DAH treatment is based on high dose methylprednisolone; other accepted therapies include cyclophosphamide (controversial), plasmapheresis, immunoglobulin and rituximab. Copyright © 2013 Elsevier España, S.L. All rights reserved.

High-Torque, Lightweight, Pneumatically Driven Wrench For Small Spaces

NASA Technical Reports Server (NTRS)

Miller, Thomas W.

1995-01-01

Pneumatically driven wrench provides torque up to 3,000 lb. per ft. in small space. Designed to reach into 2.6 x 2.75 x 6 in. pocket. Weighs approximately 25 lbs. Includes reversible pneumatic motor (electric motor could be used instead) and slip clutch. Also includes device indicating total angle through which wrench turned bolt or nut. This feature used for turn-of-the-nut tightening method.

PR[superscript 2]EPS: Preparation, Recruitment, Retention and Excellence in the Physical Sciences, Including Engineering. A Report on the 2004, 2005 and 2006 Science Summer Camps

ERIC Educational Resources Information Center

Bachman, Nancy J.; Bischoff, Paul J.; Gallagher, Hugh; Labroo, Sunil; Schaumloffel, John C.

2008-01-01

Now in its fourth year, PR[superscript 2]EPS is a National Science Foundation funded initiative designed to recruit high school students to attend college majoring in the physical sciences, including engineering and secondary science education, and to help ensure their retention within the program until graduation. A central feature of the…

Visual perception as retrospective Bayesian decoding from high- to low-level features.

PubMed

Ding, Stephanie; Cueva, Christopher J; Tsodyks, Misha; Qian, Ning

2017-10-24

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. Published under the PNAS license.

Development of low-cost high-performance multispectral camera system at Banpil

NASA Astrophysics Data System (ADS)

Oduor, Patrick; Mizuno, Genki; Olah, Robert; Dutta, Achyut K.

2014-05-01

Banpil Photonics (Banpil) has developed a low-cost high-performance multispectral camera system for Visible to Short- Wave Infrared (VIS-SWIR) imaging for the most demanding high-sensitivity and high-speed military, commercial and industrial applications. The 640x512 pixel InGaAs uncooled camera system is designed to provide a compact, smallform factor to within a cubic inch, high sensitivity needing less than 100 electrons, high dynamic range exceeding 190 dB, high-frame rates greater than 1000 frames per second (FPS) at full resolution, and low power consumption below 1W. This is practically all the feature benefits highly desirable in military imaging applications to expand deployment to every warfighter, while also maintaining a low-cost structure demanded for scaling into commercial markets. This paper describes Banpil's development of the camera system including the features of the image sensor with an innovation integrating advanced digital electronics functionality, which has made the confluence of high-performance capabilities on the same imaging platform practical at low cost. It discusses the strategies employed including innovations of the key components (e.g. focal plane array (FPA) and Read-Out Integrated Circuitry (ROIC)) within our control while maintaining a fabless model, and strategic collaboration with partners to attain additional cost reductions on optics, electronics, and packaging. We highlight the challenges and potential opportunities for further cost reductions to achieve a goal of a sub-$1000 uncooled high-performance camera system. Finally, a brief overview of emerging military, commercial and industrial applications that will benefit from this high performance imaging system and their forecast cost structure is presented.

The NGC 4013 tale: a pseudo-bulged, late-type spiral shaped by a major merger

NASA Astrophysics Data System (ADS)

Wang, Jianling; Hammer, Francois; Puech, Mathieu; Yang, Yanbin; Flores, Hector

2015-10-01

Many spiral galaxy haloes show stellar streams with various morphologies when observed with deep images. The origin of these tidal features is discussed, either coming from a satellite infall or caused by residuals of an ancient, gas-rich major merger. By modelling the formation of the peculiar features observed in the NGC 4013 halo, we investigate their origin. By using GADGET-2 with implemented gas cooling, star formation, and feedback, we have modelled the overall NGC 4013 galaxy and its associated halo features. A gas-rich major merger occurring 2.7-4.6 Gyr ago succeeds in reproducing the NGC 4013 galaxy properties, including all the faint stellar features, strong gas warp, boxy-shaped halo and vertical 3.6 μm luminosity distribution. High gas fractions in the progenitors are sufficient to reproduce the observed thin and thick discs, with a small bulge fraction, as observed. A major merger is able to reproduce the overall NGC 4013 system, including the warp strength, the red colour and the high stellar mass density of the loop, while a minor merger model cannot. Because the gas-rich model suffices to create a pseudo-bulge with a small fraction of the light, NGC 4013 is perhaps the archetype of a late-type galaxy formed by a relatively recent merger. Then late type, pseudo-bulge spirals are not mandatorily made through secular evolution, and the NGC 4013 properties also illustrate that strong warps in isolated galaxies may well occur at a late phase of a gas-rich major merger.

Dynamic Encoding of Speech Sequence Probability in Human Temporal Cortex

PubMed Central

Leonard, Matthew K.; Bouchard, Kristofer E.; Tang, Claire

2015-01-01

Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. PMID:25948269

Quality control in urodynamics and the role of software support in the QC procedure.

PubMed

Hogan, S; Jarvis, P; Gammie, A; Abrams, P

2011-11-01

This article aims to identify quality control (QC) best practice, to review published QC audits in order to identify how closely good practice is followed, and to carry out a market survey of the software features that support QC offered by urodynamics machines available in the UK. All UK distributors of urodynamic systems were contacted and asked to provide information on the software features relating to data quality of the products they supply. The results of the market survey show that the features offered by manufacturers differ greatly. Automated features, which can be turned off in most cases, include: cough recognition, detrusor contraction detection, and high pressure alerts. There are currently no systems that assess data quality based on published guidelines. A literature review of current QC guidelines for urodynamics was carried out; QC audits were included in the literature review to see how closely guidelines were being followed. This review highlights the fact that basic QC is not being carried out effectively by urodynamicists. Based on the software features currently available and the results of the literature review there is both the need and capacity for a greater degree of automation in relation to urodynamic data quality and accuracy assessment. Some progress has been made in this area and certain manufacturers have already developed automated cough detection. Copyright © 2011 Wiley Periodicals, Inc.

Defining Features of Unhealthy Exercise Associated with Disordered Eating and Eating Disorder Diagnoses

PubMed Central

Holland, Lauren A.; Brown, Tiffany A.; Keel, Pamela K.

2013-01-01

Objectives The current study sought to compare different features of unhealthy exercise on associations with disordered eating and their ability to identify individuals with eating disorders. A secondary aim of the study was to compare prevalence and overlap of different aspects of unhealthy exercise and potential differences in their gender distribution. Design Cross-sectional epidemiological study. Methods A community-based sample of men (n=592) and women (n=1468) completed surveys of health and eating patterns, including questions regarding exercise habits and eating disorder symptoms. Results Compulsive and compensatory features of exercise were the best predictors of disordered eating and eating disorder diagnoses compared to exercise that was excessive in quantity. Further, compulsive and compensatory aspects of unhealthy exercise represented overlapping, yet distinct qualities in both men and women. Conclusions Including the compulsive quality among the defining features of unhealthy exercise may improve identification of eating disorders, particularly in men. Results suggest that the compensatory aspect of unhealthy exercise is not adequately captured by the compulsive aspect of unhealthy exercise. Thus, interventions that target unhealthy exercise behaviors among high-risk individuals, such as athletes, may benefit from addressing both the compulsive and compensatory aspects of unhealthy exercise. Future prospective longitudinal studies will aid in determining the direction of the association between these features of unhealthy exercise and the onset of eating pathology. PMID:24391457

Automatic parameter selection for feature-based multi-sensor image registration

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Tom, Victor; Webb, Helen; Chao, Alan

2006-05-01

Accurate image registration is critical for applications such as precision targeting, geo-location, change-detection, surveillance, and remote sensing. However, the increasing volume of image data is exceeding the current capacity of human analysts to perform manual registration. This image data glut necessitates the development of automated approaches to image registration, including algorithm parameter value selection. Proper parameter value selection is crucial to the success of registration techniques. The appropriate algorithm parameters can be highly scene and sensor dependent. Therefore, robust algorithm parameter value selection approaches are a critical component of an end-to-end image registration algorithm. In previous work, we developed a general framework for multisensor image registration which includes feature-based registration approaches. In this work we examine the problem of automated parameter selection. We apply the automated parameter selection approach of Yitzhaky and Peli to select parameters for feature-based registration of multisensor image data. The approach consists of generating multiple feature-detected images by sweeping over parameter combinations and using these images to generate estimated ground truth. The feature-detected images are compared to the estimated ground truth images to generate ROC points associated with each parameter combination. We develop a strategy for selecting the optimal parameter set by choosing the parameter combination corresponding to the optimal ROC point. We present numerical results showing the effectiveness of the approach using registration of collected SAR data to reference EO data.

Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.

PubMed

Nikfarjam, Azadeh; Sarker, Abeed; O'Connor, Karen; Ginn, Rachel; Gonzalez, Graciela

2015-05-01

Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural language processing (NLP) techniques. However, the language in social media is highly informal, and user-expressed medical concepts are often nontechnical, descriptive, and challenging to extract. There has been limited progress in addressing these challenges, and thus far, advanced machine learning-based NLP techniques have been underutilized. Our objective is to design a machine learning-based approach to extract mentions of adverse drug reactions (ADRs) from highly informal text in social media. We introduce ADRMine, a machine learning-based concept extraction system that uses conditional random fields (CRFs). ADRMine utilizes a variety of features, including a novel feature for modeling words' semantic similarities. The similarities are modeled by clustering words based on unsupervised, pretrained word representation vectors (embeddings) generated from unlabeled user posts in social media using a deep learning technique. ADRMine outperforms several strong baseline systems in the ADR extraction task by achieving an F-measure of 0.82. Feature analysis demonstrates that the proposed word cluster features significantly improve extraction performance. It is possible to extract complex medical concepts, with relatively high performance, from informal, user-generated content. Our approach is particularly scalable, suitable for social media mining, as it relies on large volumes of unlabeled data, thus diminishing the need for large, annotated training data sets. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Optimizing defect inspection strategy through the use of design-aware database control layers

NASA Astrophysics Data System (ADS)

Stoler, Dvori; Ruch, Wayne; Ma, Weimin; Chakravarty, Swapnajit; Liu, Steven; Morgan, Ray; Valadez, John; Moore, Bill; Burns, John

2007-10-01

Resolution limitations in the mask making process can cause differences between the features that appear in a database and those printed to a reticle. These differences may result from intentional or unintentional features in the database exceeding the resolution limit of the mask making process such as small gaps or lines in the data, line end shortening on small sub-resolution assist features etc creating challenges to both mask writing and mask inspection. Areas with high variance from design to mask, often referred to as high MEEF areas (mask error enhancement factor), become highly problematic and can directly impact mask and device yield, mask manufacturing cycle time and ultimately mask costs. Specific to mask inspection it may be desirable to inspect certain non-critical or non-relevant features at reduced sensitivity so as not to detect real, but less significant process defects. In contrast there may also be times where increased sensitivity is required for critical mask features or areas. Until recently, this process was extremely manual, creating added time and cost to the mask inspection cycle. Shifting to more intelligent and automated inspection flows is the key focus of this paper. A novel approach to importing design data directly into the mask inspection to include both MDP generated MRC errors files and LRC generated MEEF files. The results of recently developed inspection and review capability based upon controlling defect inspection using design aware data base control layers on a pixel basis are discussed. Typical mask shop applications and implementations will be shown.

Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy Using Spatial-Temporal {sup 18}F-FDG PET Features, Clinical Parameters, and Demographics

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

Zhang, Hao; Tan, Shan; Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan

2014-01-01

Purpose: To construct predictive models using comprehensive tumor features for the evaluation of tumor response to neoadjuvant chemoradiation therapy (CRT) in patients with esophageal cancer. Methods and Materials: This study included 20 patients who underwent trimodality therapy (CRT + surgery) and underwent {sup 18}F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) both before and after CRT. Four groups of tumor features were examined: (1) conventional PET/CT response measures (eg, standardized uptake value [SUV]{sub max}, tumor diameter); (2) clinical parameters (eg, TNM stage, histology) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associated changesmore » resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, cross-validations being used to avoid model overfitting. Prediction accuracy was assessed by area under the receiver operating characteristic curve (AUC), and precision was evaluated by confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). With the use of spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications)—results that were significantly better than when conventional PET/CT measures or clinical parameters and demographics alone were used. For groups with many tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than did the LR model. Conclusions: The SVM model that used all features including spatial-temporal PET features accurately and precisely predicted pathologic tumor response to CRT in esophageal cancer.« less

Global MHD Modeling of Auroral Conjugacy for Different IMF Conditions

NASA Astrophysics Data System (ADS)

Hesse, M.; Kuznetsova, M. M.; Liu, Y. H.; Birn, J.; Rastaetter, L.

2016-12-01

The question whether auroral features are conjugate or not, and the search for the underlying scientific causes is of high interest in magnetospheric and ionospheric physics. Consequently, this topic has attracted considerable attention in space-based observations of auroral features, and it has inspired a number of theoretical ideas and related modeling activities. Potential contributing factors to the presence or absence of auroral conjugacy include precipitation asymmetries in case of the diffuse aurora, inter-hemispherical conductivity differences, magnetospheric asymmetries brought about by, e.g., dipole tilt, corotation, or IMF By, and, finally, asymmetries in field-aligned current generation primarily in the nightside magnetosphere. In this presentation, we will analyze high-resolution, global MHD simulations of magnetospheric dynamics, with emphasis on auroral conjugacy. For the purpose of this study, we define controlled conditions by selecting solstice times with steady solar wind input, the latter of which includes an IMF rotation from purely southward to east-westward. Conductivity models will include both auroral precipaition proxies as well as the effects of the aysmmetric daylight. We will analyze these simulations with respect to conjugacies or the lack thereof, and study the role of the effects above in determing the former.

Simulations & Measurements of Airframe Noise: A BANC Workshops Perspective

NASA Technical Reports Server (NTRS)

Choudhari, Meelan; Lockard, David

2016-01-01

Airframe noise corresponds to the acoustic radiation due to turbulent flow in the vicinity of airframe components such as high-lift devices and landing gears. Since 2010, the American Institute of Aeronautics and Astronautics has organized an ongoing series of workshops devoted to Benchmark Problems for Airframe Noise Computations (BANC). The BANC workshops are aimed at enabling a systematic progress in the understanding and high-fidelity predictions of airframe noise via collaborative investigations that integrate computational fluid dynamics, computational aeroacoustics, and in depth measurements targeting a selected set of canonical yet realistic configurations that advance the current state-of-the-art in multiple respects. Unique features of the BANC Workshops include: intrinsically multi-disciplinary focus involving both fluid dynamics and aeroacoustics, holistic rather than predictive emphasis, concurrent, long term evolution of experiments and simulations with a powerful interplay between the two, and strongly integrative nature by virtue of multi-team, multi-facility, multiple-entry measurements. This paper illustrates these features in the context of the BANC problem categories and outlines some of the challenges involved and how they were addressed. A brief summary of the BANC effort, including its technical objectives, strategy, and selective outcomes thus far is also included.

Development of the Brican TD100 Small Uas and Payload Trials

NASA Astrophysics Data System (ADS)

Eggleston, B.; McLuckie, B.; Koski, W. R.; Bird, D.; Patterson, C.; Bohdanov, D.; Liu, H.; Mathews, T.; Gamage, G.

2015-08-01

The Brican TD100 is a high performance, small UAS designed and made in Brampton Ontario Canada. The concept was defined in late 2009 and it is designed for a maximum weight of 25 kg which is now the accepted cut-off defining small civil UASs. A very clean tractor propeller layout is used with a lightweight composite structure and a high aspect ratio wing to obtain good range and endurance. The design features and performance of the initial electrically powered version are discussed and progress with developing a multifuel engine version is described. The system includes features enabling operation beyond line of sight (BLOS) and the proving missions are described. The vehicle has been used for aerial photography and low cost mapping using a professional grade Nikon DSLR camera. For forest fire research a FLIR A65 IR camera was used, while for georeferenced mapping a new Applanix AP20 system was calibrated with the Nikon camera. The sorties to be described include forest fire research, wildlife photography of bowhead whales in the Arctic and surveys of endangered caribou in a remote area of Labrador, with all these applications including the DSLR camera.

Gutzwiller charge phase diagram of cuprates, including electron–phonon coupling effects

DOE PAGES

Markiewicz, R. S.; Seibold, G.; Lorenzana, J.; ...

2015-02-01

Besides significant electronic correlations, high-temperature superconductors also show a strong coupling of electrons to a number of lattice modes. Combined with the experimental detection of electronic inhomogeneities and ordering phenomena in many high-T c compounds, these features raise the question as to what extent phonons are involved in the associated instabilities. Here we address this problem based on the Hubbard model including a coupling to phonons in order to capture several salient features of the phase diagram of hole-doped cuprates. Charge degrees of freedom, which are suppressed by the large Hubbard U near half-filling, are found to become active atmore » a fairly low doping level. We find that possible charge order is mainly driven by Fermi surface nesting, with competition between a near-(π, π) order at low doping and antinodal nesting at higher doping, very similar to the momentum structure of magnetic fluctuations. The resulting nesting vectors are generally consistent with photoemission and tunneling observations, evidence for charge density wave order in YBa₂Cu₃O 7-δ including Kohn anomalies, and suggestions of competition between one- and two-q-vector nesting.« less

Autonomous Science Analysis with the New Millennium Program-Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Doggett, T.; Davies, A. G.; Castano, R. A.; Baker, V. R.; Dohm, J. M.; Greeley, R.; Williams, K. K.; Chien, S.; Sherwood, R.

2002-12-01

The NASA New Millennium Program (NMP) is a testbed for new, high-risk technologies, including new software and hardware. The Autonomous Sciencecraft Experiment (ASE) will fly on the Air Force Research Laboratory TechSat-21 mission in 2006 is such a NMP mission, and is managed by the Jet Propulsion Laboratory, California Institute of Technology. TechSat-21 consists of three satellites, each equipped with X-band Synthetic Aperture Radar (SAR) that will occupy a 13-day repeat track Earth orbit. The main science objectives of ASE are to demonstrate that process-related change detection and feature identification can be conducted autonomously during space flight, leading to autonomous onboard retargeting of the spacecraft. This mission will observe transient geological and environmental processes using SAR. Examples of geologic processes that may be observed and investigated include active volcanism, the movement of sand dunes and transient features in desert environments, water flooding, and the formation and break-up of lake ice. Science software onboard the spacecraft will allow autonomous processing and formation of SAR images and extraction of scientific information. The subsequent analyses, performed on images formed onboard from the SAR data, will include feature identification using scalable feature "templates" for each target, change detection through comparison of current and archived images, and science discovery, a search for other features of interest in each image. This approach results in obtaining the same science return for a reduced amount of resource use (such as downlink) when compared to that from a mission operating without ASE technology. Redundant data is discarded. The science-driven goals of ASE will evolve during the ASE mission through onboard replanning software that can re-task satellite operations. If necessary, as a result of a discovery made autonomously by onboard science processing, existing observation sequences will be pre-empted to obtain data of potential high scientific content. Flight validation of this software will enable radically different missions with significant onboard decision-making and novel science concepts (onboard decision making and selective data return). This work has been carried out at the Jet Propulsion Laboratory-California Institute of Technology, under contract to NASA.

Article and process for producing an article

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

Lacy, Benjamin Paul; Jacala, Ariel Caesar Prepena; Kottilingam, Srikanth Chandrudu

An article and a process of producing an article are provided. The article includes a base material, a cooling feature arrangement positioned on the base material, the cooling feature arrangement including an additive-structured material, and a cover material. The cooling feature arrangement is between the base material and the cover material. The process of producing the article includes manufacturing a cooling feature arrangement by an additive manufacturing technique, and then positioning the cooling feature arrangement between a base material and a cover material.

Device and method for imaging of non-linear and linear properties of formations surrounding a borehole

DOEpatents

Johnson, Paul A; Tencate, James A; Le Bas, Pierre-Yves; Guyer, Robert; Vu, Cung Khac; Skelt, Christopher

2013-11-05

In some aspects of the disclosure, a method and an apparatus is disclosed for investigating material surrounding the borehole. The method includes generating a first low frequency acoustic wave within the borehole, wherein the first low frequency acoustic wave induces a linear and a nonlinear response in one or more features in the material that are substantially perpendicular to a radius of the borehole; directing a first sequence of high frequency pulses in a direction perpendicularly with respect to the longitudinal axis of the borehole into the material contemporaneously with the first acoustic wave; and receiving one or more second high frequency pulses at one or more receivers positionable in the borehole produced by an interaction between the first sequence of high frequency pulses and the one or more features undergoing linear and nonlinear elastic distortion due to the first low frequency acoustic wave to investigate the material surrounding the borehole.

Transcriptomic features associated with energy production in the muscles of Pacific bluefin tuna and Pacific cod.

PubMed

Shibata, Mami; Mekuchi, Miyuki; Mori, Kazuki; Muta, Shigeru; Chowdhury, Vishwajit Sur; Nakamura, Yoji; Ojima, Nobuhiko; Saitoh, Kenji; Kobayashi, Takanori; Wada, Tokio; Inouye, Kiyoshi; Kuhara, Satoru; Tashiro, Kosuke

2016-06-01

Bluefin tuna are high-performance swimmers and top predators in the open ocean. Their swimming is grounded by unique features including an exceptional glycolytic potential in white muscle, which is supported by high enzymatic activities. Here we performed high-throughput RNA sequencing (RNA-Seq) in muscles of the Pacific bluefin tuna (Thunnus orientalis) and Pacific cod (Gadus macrocephalus) and conducted a comparative transcriptomic analysis of genes related to energy production. We found that the total expression of glycolytic genes was much higher in the white muscle of tuna than in the other muscles, and that the expression of only six genes for glycolytic enzymes accounted for 83.4% of the total. These expression patterns were in good agreement with the patterns of enzyme activity previously reported. The findings suggest that the mRNA expression of glycolytic genes may contribute directly to the enzymatic activities in the muscles of tuna.

Cell classification using big data analytics plus time stretch imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Jalali, Bahram; Chen, Claire L.; Mahjoubfar, Ata

2016-09-01

We show that blood cells can be classified with high accuracy and high throughput by combining machine learning with time stretch quantitative phase imaging. Our diagnostic system captures quantitative phase images in a flow microscope at millions of frames per second and extracts multiple biophysical features from individual cells including morphological characteristics, light absorption and scattering parameters, and protein concentration. These parameters form a hyperdimensional feature space in which supervised learning and cell classification is performed. We show binary classification of T-cells against colon cancer cells, as well classification of algae cell strains with high and low lipid content. The label-free screening averts the negative impact of staining reagents on cellular viability or cell signaling. The combination of time stretch machine vision and learning offers unprecedented cell analysis capabilities for cancer diagnostics, drug development and liquid biopsy for personalized genomics.

Hypnosis and belief: A review of hypnotic delusions.

PubMed

Connors, Michael H

2015-11-01

Hypnosis can create temporary, but highly compelling alterations in belief. As such, it can be used to model many aspects of clinical delusions in the laboratory. This approach allows researchers to recreate features of delusions on demand and examine underlying processes with a high level of experimental control. This paper reviews studies that have used hypnosis to model delusions in this way. First, the paper reviews studies that have focused on reproducing the surface features of delusions, such as their high levels of subjective conviction and strong resistance to counter-evidence. Second, the paper reviews studies that have focused on modelling underlying processes of delusions, including anomalous experiences or cognitive deficits that underpin specific delusional beliefs. Finally, the paper evaluates this body of research as a whole. The paper discusses advantages and limitations of using hypnotic models to study delusions and suggests some directions for future research. Copyright © 2015 Elsevier Inc. All rights reserved.

Recent advances in flexible low power cholesteric LCDs

NASA Astrophysics Data System (ADS)

Khan, Asad; Shiyanovskaya, Irina; Montbach, Erica; Schneider, Tod; Nicholson, Forrest; Miller, Nick; Marhefka, Duane; Ernst, Todd; Doane, J. W.

2006-05-01

Bistable reflective cholesteric displays are a liquid crystal display technology developed to fill a market need for very low power displays. Their unique look, high reflectivity, bistability, and simple structure make them an ideal flat panel display choice for handheld or other portable devices where small lightweight batteries with long lifetimes are important. Applications ranging from low resolution large signs to ultra high resolution electronic books can utilize cholesteric displays to not only benefit from the numerous features, but also create enabling features that other flat panel display technologies cannot. Flexible displays are the focus of attention of numerous research groups and corporations worldwide. Cholesteric displays have been demonstrated to be highly amenable to flexible substrates. This paper will review recent advances in flexible cholesteric displays including both phase separation and emulsification approaches to encapsulation. Both approaches provide unique benefits to various aspects of manufacturability, processes, flexibility, and conformability.

Landsat real-time processing

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

Davis, E.L.

A novel method for performing real-time acquisition and processing Landsat/EROS data covers all aspects including radiometric and geometric corrections of multispectral scanner or return-beam vidicon inputs, image enhancement, statistical analysis, feature extraction, and classification. Radiometric transformations include bias/gain adjustment, noise suppression, calibration, scan angle compensation, and illumination compensation, including topography and atmospheric effects. Correction or compensation for geometric distortion includes sensor-related distortions, such as centering, skew, size, scan nonlinearity, radial symmetry, and tangential symmetry. Also included are object image-related distortions such as aspect angle (altitude), scale distortion (altitude), terrain relief, and earth curvature. Ephemeral corrections are also applied to compensatemore » for satellite forward movement, earth rotation, altitude variations, satellite vibration, and mirror scan velocity. Image enhancement includes high-pass, low-pass, and Laplacian mask filtering and data restoration for intermittent losses. Resource classification is provided by statistical analysis including histograms, correlational analysis, matrix manipulations, and determination of spectral responses. Feature extraction includes spatial frequency analysis, which is used in parallel discriminant functions in each array processor for rapid determination. The technique uses integrated parallel array processors that decimate the tasks concurrently under supervision of a control processor. The operator-machine interface is optimized for programming ease and graphics image windowing.« less

Simulator study of the effectiveness of an automatic control system designed to improve the high-angle-of-attack characteristics of a fighter airplane

NASA Technical Reports Server (NTRS)

Gilbert, W. P.; Nguyen, L. T.; Vangunst, R. W.

1976-01-01

A piloted, fixed-base simulation was conducted to study the effectiveness of some automatic control system features designed to improve the stability and control characteristics of fighter airplanes at high angles of attack. These features include an angle-of-attack limiter, a normal-acceleration limiter, an aileron-rudder interconnect, and a stability-axis yaw damper. The study was based on a current lightweight fighter prototype. The aerodynamic data used in the simulation were measured on a 0.15-scale model at low Reynolds number and low subsonic Mach number. The simulation was conducted on the Langley differential maneuvering simulator, and the evaluation involved representative combat maneuvering. Results of the investigation show the fully augmented airplane to be quite stable and maneuverable throughout the operational angle-of-attack range. The angle-of-attack/normal-acceleration limiting feature of the pitch control system is found to be a necessity to avoid angle-of-attack excursions at high angles of attack. The aileron-rudder interconnect system is shown to be very effective in making the airplane departure resistant while the stability-axis yaw damper provided improved high-angle-of-attack roll performance with a minimum of sideslip excursions.

DETECTING RELATIVISTIC X-RAY JETS IN HIGH-REDSHIFT QUASARS

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

McKeough, Kathryn; Siemiginowska, Aneta; Kashyap, Vinay L.

We analyze Chandra X-ray images of a sample of 11 quasars that are known to contain kiloparsec scale radio jets. The sample consists of five high-redshift ( z  ≥ 3.6) flat-spectrum radio quasars, and six intermediate redshift (2.1 <  z  < 2.9) quasars. The data set includes four sources with integrated steep radio spectra and seven with flat radio spectra. A total of 25 radio jet features are present in this sample. We apply a Bayesian multi-scale image reconstruction method to detect and measure the X-ray emission from the jets. We compute deviations from a baseline model that does not include the jet,more » and compare observed X-ray images with those computed with simulated images where no jet features exist. This allows us to compute p -value upper bounds on the significance that an X-ray jet is detected in a pre-determined region of interest. We detected 12 of the features unambiguously, and an additional six marginally. We also find residual emission in the cores of three quasars and in the background of one quasar that suggest the existence of unresolved X-ray jets. The dependence of the X-ray to radio luminosity ratio on redshift is a potential diagnostic of the emission mechanism, since the inverse Compton scattering of cosmic microwave background photons (IC/CMB) is thought to be redshift dependent, whereas in synchrotron models no clear redshift dependence is expected. We find that the high-redshift jets have X-ray to radio flux ratios that are marginally inconsistent with those from lower redshifts, suggesting that either the X-ray emissions are due to the IC/CMB rather than the synchrotron process, or that high-redshift jets are qualitatively different.« less

Industry-relevant magnetron sputtering and cathodic arc ultra-high vacuum deposition system for in situ x-ray diffraction studies of thin film growth using high energy synchrotron radiation.

PubMed

Schroeder, J L; Thomson, W; Howard, B; Schell, N; Näslund, L-Å; Rogström, L; Johansson-Jõesaar, M P; Ghafoor, N; Odén, M; Nothnagel, E; Shepard, A; Greer, J; Birch, J

2015-09-01

We present an industry-relevant, large-scale, ultra-high vacuum (UHV) magnetron sputtering and cathodic arc deposition system purposefully designed for time-resolved in situ thin film deposition/annealing studies using high-energy (>50 keV), high photon flux (>10(12) ph/s) synchrotron radiation. The high photon flux, combined with a fast-acquisition-time (<1 s) two-dimensional (2D) detector, permits time-resolved in situ structural analysis of thin film formation processes. The high-energy synchrotron-radiation based x-rays result in small scattering angles (<11°), allowing large areas of reciprocal space to be imaged with a 2D detector. The system has been designed for use on the 1-tonne, ultra-high load, high-resolution hexapod at the P07 High Energy Materials Science beamline at PETRA III at the Deutsches Elektronen-Synchrotron in Hamburg, Germany. The deposition system includes standard features of a typical UHV deposition system plus a range of special features suited for synchrotron radiation studies and industry-relevant processes. We openly encourage the materials research community to contact us for collaborative opportunities using this unique and versatile scientific instrument.

Large space deployable antenna systems

NASA Technical Reports Server (NTRS)

1978-01-01

The design technology is described for manufacturing a 20 m or larger space erectable antenna with high thermal stability, high dynamic stiffness, and minimum stowed size. The selected approach includes a wrap rib design with a cantilever beam basic element and graphite-epoxy composite lenticular cross section ribs. The rib configuration and powered type operated deploying mechanism are described and illustrated. Other features of the parabolic reflector discussed include weight and stowed diameter characteristics, structural dynamics characteristics, orbit thermal aperture limitations, and equivalent element and secondary (on axis) patterns. A block diagram of the multiple beam pattern is also presented.

Is Tridymite at Gale Crater Evidence for Silicic Volcanism on Mars?

NASA Technical Reports Server (NTRS)

Morris, Richard V.; Vaniman, David T.; Ming, Douglas W.; Graff, Trevor G.; Downs, Robert T.; Fendrich, Kim; Mertzman, Stanley A.

2016-01-01

The X-ray diffraction (XRD) instrument (CheMin) onboard the MSL rover Curiosity detected 17 wt% of the SiO2 polymorph tridymite (relative to bulk sample) for the Buckskin drill sample (73 wt% SiO2) obtained from sedimentary rock in the Murray formation at Gale Crater, Mars. Other detected crystalline materials are plagioclase, sanidine, cristobalite, cation-deficient magnetite, and anhydrite. XRD amorphous material constitutes approx. 60 wt% of bulk sample, and the position of its broad diffraction peak near approx. 26 deg. 2-theta is consistent with opal-A. Tridymite is a lowpressure, high-temperature mineral (approx. 870 to 1670 deg. C) whose XRD-identified occurrence on the Earth is usually associated with silicic (e.g., rhyolitic) volcanism. High SiO2 deposits have been detected at Gale crater by remote sensing from martian orbit and interpreted as opal-A on the basis H2O and Si-OH spectral features. Proposed opal-A formation pathways include precipitation of silica from lake waters and high-SiO2 residues of acid-sulfate leaching. Tridymite is nominally anhydrous and would not exhibit these spectral features. We have chemically and spectrally analyzed rhyolitic samples from New Mexico and Iwodake volcano (Japan). The glassy (by XRD) NM samples have H2O spectral features similar to opal-A. The Iwodake sample, which has been subjected to high-temperature acid sulfate leaching, also has H2O spectral features similar to opal-A. The Iwodake sample has approx. 98 wt% SiO2 and 1% wt% TiO2 (by XRF), tridymite (>80 wt.% of crystalline material without detectable quartz by XRD), and H2O and Si-OH spectral features. These results open the working hypothesis that the opal-A-like high-SiO2 deposits at Gale crater detected from martian orbit are products of alteration associated with silicic volcanism. The presence or absence of tridymite will depend on lava crystallization temperatures (NM) and post crystallization alteration temperatures (Iwodake).

Low progression of intraductal papillary mucinous neoplasms with worrisome features and high-risk stigmata undergoing non-operative management: a mid-term follow-up analysis.

PubMed

Crippa, Stefano; Bassi, Claudio; Salvia, Roberto; Malleo, Giuseppe; Marchegiani, Giovanni; Rebours, Vinciane; Levy, Philippe; Partelli, Stefano; Suleiman, Shadeah L; Banks, Peter A; Ahmed, Nazir; Chari, Suresh T; Fernández-Del Castillo, Carlos; Falconi, Massimo

2017-03-01

To evaluate mid-term outcomes and predictors of survival in non-operated patients with pancreatic intraductal papillary mucinous neoplasms (IPMNs) with worrisome features or high-risk stigmata as defined by International Consensus Guidelines for IPMN. Reasons for non-surgical options were physicians' recommendation, patient personal choice or comorbidities precluding surgery. In this retrospective, multicentre analysis, IPMNs were classified as branch duct (BD) and main duct (MD), the latter including mixed IPMNs. Univariate and multivariate analysis for overall survival (OS) and disease-specific survival (DSS) were obtained. Of 281 patients identified, 159 (57%) had BD-IPMNs and 122 (43%) had MD-IPMNs; 50 (18%) had high-risk stigmata and 231 (82%) had worrisome features. Median follow-up was 51 months. The 5-year OS and DSS for the entire cohort were 81% and 89.9%. An invasive pancreatic malignancy developed in 34 patients (12%); 31 had invasive IPMNs (11%) and 3 had IPMN-distinct pancreatic ductal adenocarcinoma (1%). Independent predictors of poor DSS in the entire cohort were age >70 years, atypical/malignant cyst fluid cytology, jaundice and MD >15 mm. Compared with MD-IPMNs, BD-IPMNs had significantly better 5-year OS (86% vs 74.1%, p=0.002) and DSS (97% vs 81.2%, p<0.0001). Patients with worrisome features had better 5-year DSS compared with those with high-risk stigmata (96.2% vs 60.2%, p<0.0001). In elderly patients with IPMNs that have worrisome features, the 5-year DSS is 96%, suggesting that conservative management is appropriate. By contrast, presence of high-risk stigmata is associated with a 40% risk of IPMN-related death, reinforcing that surgical resection should be offered to fit patients. 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/.

Relational Information Management Data-Base System

NASA Technical Reports Server (NTRS)

Storaasli, O. O.; Erickson, W. J.; Gray, F. P.; Comfort, D. L.; Wahlstrom, S. O.; Von Limbach, G.

1985-01-01

DBMS with several features particularly useful to scientists and engineers. RIM5 interfaced with any application program written in language capable of Calling FORTRAN routines. Applications include data management for Space Shuttle Columbia tiles, aircraft flight tests, high-pressure piping, atmospheric chemistry, census, university registration, CAD/CAM Geometry, and civil-engineering dam construction.

Adventure Racing for the Rest of Us

ERIC Educational Resources Information Center

Moorman, Marta K.; English, Kathleen A.

2015-01-01

Adventure racing got started in the 1990s. The Eco-Challenge and Primal Quest races were multi-day events that included challenging physical activities and extreme conditions. Today, highly publicized adventure races like the Eco-Challenge and Amazing Race usually feature elite athletes or celebrities completing exotic tasks or globe-hopping to…

Invasibility of mature and 15-year-old deciduous forests by exotic plants

Treesearch

Cynthia D. Huebner; Patrick C. Tobin

2006-01-01

High species richness, resource availability and disturbance are community characteristics associated with forest invasibility. We categorized commonly measured community variables, including species composition, topography, and landscape features, within both mature and 15-year-old clearcuts in West Virginia, USA. We evaluated the importance of each variable for...

Building America's Industrial Revolution: The Boott Cotton Mills of Lowell, Massachusetts. Teaching with Historic Places.

ERIC Educational Resources Information Center

Stowell, Stephen

1995-01-01

Presents a high school unit about the U.S. Industrial Revolution featuring the Boott Cotton Mills of Lowell, Massachusetts. Includes student objectives, step-by-step instructional procedures, and discussion questions. Provides two maps, five illustrations, one photograph, and three student readings. (ACM)

Brevard Top Scholars

NASA Image and Video Library

2017-05-05

About 40 Brevard County high school seniors attended Brevard Top Scholars Day at Kennedy Space Center on May 5. Kennedy's Office of Education coordinated the event that featured a special behind-the-scenes tour of Kennedy, including prototype shops, cryogenic labs and facilities such as the Vehicle Assembly Building and the Launch Control Center firing rooms.

Brevard Top Scholars

NASA Image and Video Library

2017-05-05

About 40 Brevard County high school seniors take in the enormity of the Vehicle Assembly Building during Brevard Top Scholars Day on May 5. Kennedy's Office of Education coordinated the event that featured a special behind-the-scenes tour of Kennedy, including prototype shops, cryogenic labs and the Launch Control Center firing rooms.

Attachment Theory and Primary Caregiving

ERIC Educational Resources Information Center

Colmer, Kaye; Rutherford, Lynne; Murphy, Pam

2011-01-01

Offering intensive parent support programs within an early childhood setting recognises that early childhood educators are uniquely placed to form highly supportive and ongoing relationships with children and their families as part of their everyday work. This feature of early childhood programs can be utilised to include educators as partners in…

As the Crow Flies. A Social Studies/Newspaper Guide. A Newspaper in Education Service.

ERIC Educational Resources Information Center

Richardson, Lynn J.

Appropriate for intermediate grades through high school, this social studies newspaper guide suggests learning activities using newspapers. The areas covered are history, geography, current events, the working class, sociology, the political scene, cultures, government, and travel. Suggested assignments include writing a feature or news interview…

The Open Learning Initiative: New Directions for Higher Education.

ERIC Educational Resources Information Center

King, Bruce

This paper describes the Australian Open Learning Initiative (OLI), a program to facilitate access to postsecondary education. The program will provide off-campus or distance education courses for which there is evident high demand. Program features include an independent brokering agency, coordination by a university or group of universities,…

1977 Pacemakers: The New Simplicity and a New Notion of What's News

ERIC Educational Resources Information Center

Brasler, Wayne

1978-01-01

Presents an overview of distinctive features of the ten high school and college winners of the 1977 Pacemaker Newspaper Awards; then reproduces a front page from each of the publications and presents additional information about each. Includes judges' comments on each of the winning publications. (GW)

Land and Freedom--Economic Studies.

ERIC Educational Resources Information Center

Ehrman, Ted; Rubenstein, Stan

This series of 20 self-contained lessons in the study of economics, features activities that can be used with any high school economics instruction. The lessons included are: (1) Opportunity Costs; (2) Factors of Production; (3) Economic Systems; (4) Self Interest; (5) Class Struggle; (6) Economic Institutions; (7) Supply and Demand; (8) Markets…

Electric System Flexibility and Storage | Energy Analysis | NREL

Science.gov Websites

. Featured Studies India Renewable Integration Study Grid Flexibility and Storage Required To Achieve Very demand-in Texas. Key findings from this study include: A highly flexible system with must-run baseload . Publications Renewable Electricity Futures Study. Volume 2: Renewable Electricity Generation and Storage

High-resolution spectrometrometry/interferometer

NASA Technical Reports Server (NTRS)

Breckinridge, J. B.; Norton, R. H.; Schindler, R. A.

1980-01-01

Modified double-pass interferometer has several features that maximize its resolution. Proposed for rocket-borne probes of upper atmosphere, it includes cat's-eye retroreflectors in both arms, wedge-shaped beam splitter, and wedged optical-path compensator. Advantages are full tilt compensation, minimal spectrum "channeling," easy tunability, maximum fringe contrast, and even two-sided interferograms.

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework

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

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Design of the HELICS High-Performance Transmission-Distribution-Communication-Market Co-Simulation Framework: Preprint

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

Palmintier, Bryan S; Krishnamurthy, Dheepak; Top, Philip

This paper describes the design rationale for a new cyber-physical-energy co-simulation framework for electric power systems. This new framework will support very large-scale (100,000+ federates) co-simulations with off-the-shelf power-systems, communication, and end-use models. Other key features include cross-platform operating system support, integration of both event-driven (e.g. packetized communication) and time-series (e.g. power flow) simulation, and the ability to co-iterate among federates to ensure model convergence at each time step. After describing requirements, we begin by evaluating existing co-simulation frameworks, including HLA and FMI, and conclude that none provide the required features. Then we describe the design for the new layeredmore » co-simulation architecture.« less

Modeling formalisms in Systems Biology

PubMed Central

2011-01-01

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future. PMID:22141422

High Fidelity Simulations of Plume Impingement to the International Space Station

NASA Technical Reports Server (NTRS)

Lumpkin, Forrest E., III; Marichalar, Jeremiah; Stewart, Benedicte D.

2012-01-01

With the retirement of the Space Shuttle, the United States now depends on recently developed commercial spacecraft to supply the International Space Station (ISS) with cargo. These new vehicles supplement ones from international partners including the Russian Progress, the European Autonomous Transfer Vehicle (ATV), and the Japanese H-II Transfer Vehicle (HTV). Furthermore, to carry crew to the ISS and supplement the capability currently provided exclusively by the Russian Soyuz, new designs and a refinement to a cargo vehicle design are in work. Many of these designs include features such as nozzle scarfing or simultaneous firing of multiple thrusters resulting in complex plumes. This results in a wide variety of complex plumes impinging upon the ISS. Therefore, to ensure safe "proximity operations" near the ISS, the need for accurate and efficient high fidelity simulation of plume impingement to the ISS is as high as ever. A capability combining computational fluid dynamics (CFD) and the Direct Simulation Monte Carlo (DSMC) techniques has been developed to properly model the large density variations encountered as the plume expands from the high pressure in the combustion chamber to the near vacuum conditions at the orbiting altitude of the ISS. Details of the computational tools employed by this method, including recent software enhancements and the best practices needed to achieve accurate simulations, are discussed. Several recent examples of the application of this high fidelity capability are presented. These examples highlight many of the real world, complex features of plume impingement that occur when "visiting vehicles" operate in the vicinity of the ISS.

Hydrothermal and tectonic activity in northern Yellowstone Lake, Wyoming

USGS Publications Warehouse

Johnson, S.Y.; Stephenson, W.J.; Morgan, L.A.; Shanks, Wayne C.; Pierce, K.L.

2003-01-01

Yellowstone National Park is the site of one of the world's largest calderas. The abundance of geothermal and tectonic activity in and around the caldera, including historic uplift and subsidence, makes it necessary to understand active geologic processes and their associated hazards. To that end, we here use an extensive grid of high-resolution seismic reflection profiles (???450 km) to document hydrothermal and tectonic features and deposits in northern Yellowstone Lake. Sublacustrine geothermal features in northern Yellowstone Lake include two of the largest known hydrothermal explosion craters, Mary Bay and Elliott's. Mary Bay explosion breccia is distributed uniformly around the crater, whereas Elliott's crater breccia has an asymmetric distribution and forms a distinctive, ???2-km-long, hummocky lobe on the lake floor. Hydrothermal vents and low-relief domes are abundant on the lake floor; their greatest abundance is in and near explosion craters and along linear fissures. Domed areas on the lake floor that are relatively unbreached (by vents) are considered the most likely sites of future large hydrothermal explosions. Four submerged shoreline terraces along the margins of northern Yellowstone Lake add to the Holocene record or postglacial lake-level fluctuations attributed to "heavy breathing" of the Yellowstone magma reservoir and associated geothermal system. The Lake Hotel fault cuts through northwestern Yellowstone Lake and represents part of a 25-km-long distributed extensional deformation zone. Three postglacial ruptures indicate a slip rate of ???0.27 to 0.34 mm/yr. The largest (3.0 m slip) and most recent event occurred in the past ???2100 yr. Although high heat flow in the crust limits the rupture area of this fault zone, future earthquakes of magnitude ???5.3 to 6.5 are possible. Earthquakes and hydrothermal explosions have probably triggered landslides, common features around the lake margins. Few high-resolution seismic reflection surveys have been conducted in lakes in active volcanic areas. Our data reveal active geothermal features with unprecedented resolution and provide important analogues for recognition of comparable features and potential hazards in other subaqueous geothermal environments.

Research on the high-precision non-contact optical detection technology for banknotes

NASA Astrophysics Data System (ADS)

Jin, Xiaofeng; Liang, Tiancai; Luo, Pengfeng; Sun, Jianfeng

2015-09-01

The technology of high-precision laser interferometry was introduced for optical measurement of the banknotes in this paper. Taking advantage of laser short wavelength and high sensitivity, information of adhesive tape and cavity about the banknotes could be checked efficiently. Compared with current measurement devices, including mechanical wheel measurement device, Infrared measurement device, ultrasonic measurement device, the laser interferometry measurement has higher precision and reliability. This will improve the ability of banknotes feature information in financial electronic equipment.

Distributed acoustic cues for caller identity in macaque vocalization.

PubMed

Fukushima, Makoto; Doyle, Alex M; Mullarkey, Matthew P; Mishkin, Mortimer; Averbeck, Bruno B

2015-12-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured 'coo' call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral-temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call's fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized.

Distributed acoustic cues for caller identity in macaque vocalization

PubMed Central

Doyle, Alex M.; Mullarkey, Matthew P.; Mishkin, Mortimer; Averbeck, Bruno B.

2015-01-01

Individual primates can be identified by the sound of their voice. Macaques have demonstrated an ability to discern conspecific identity from a harmonically structured ‘coo’ call. Voice recognition presumably requires the integrated perception of multiple acoustic features. However, it is unclear how this is achieved, given considerable variability across utterances. Specifically, the extent to which information about caller identity is distributed across multiple features remains elusive. We examined these issues by recording and analysing a large sample of calls from eight macaques. Single acoustic features, including fundamental frequency, duration and Weiner entropy, were informative but unreliable for the statistical classification of caller identity. A combination of multiple features, however, allowed for highly accurate caller identification. A regularized classifier that learned to identify callers from the modulation power spectrum of calls found that specific regions of spectral–temporal modulation were informative for caller identification. These ranges are related to acoustic features such as the call’s fundamental frequency and FM sweep direction. We further found that the low-frequency spectrotemporal modulation component contained an indexical cue of the caller body size. Thus, cues for caller identity are distributed across identifiable spectrotemporal components corresponding to laryngeal and supralaryngeal components of vocalizations, and the integration of those cues can enable highly reliable caller identification. Our results demonstrate a clear acoustic basis by which individual macaque vocalizations can be recognized. PMID:27019727

Recognizing emotions from EEG subbands using wavelet analysis.

PubMed

Candra, Henry; Yuwono, Mitchell; Handojoseno, Ardi; Chai, Rifai; Su, Steven; Nguyen, Hung T

2015-01-01

Objectively recognizing emotions is a particularly important task to ensure that patients with emotional symptoms are given the appropriate treatments. The aim of this study was to develop an emotion recognition system using Electroencephalogram (EEG) signals to identify four emotions including happy, sad, angry, and relaxed. We approached this objective by firstly investigating the relevant EEG frequency band followed by deciding the appropriate feature extraction method. Two features were considered namely: 1. Wavelet Energy, and 2. Wavelet Entropy. EEG Channels reduction was then implemented to reduce the complexity of the features. The ground truth emotional states of each subject were inferred using Russel's circumplex model of emotion, that is, by mapping the subjectively reported degrees of valence (pleasure) and arousal to the appropriate emotions - for example, an emotion with high valence and high arousal is equivalent to a `happy' emotional state, while low valence and low arousal is equivalent to a `sad' emotional state. The Support Vector Machine (SVM) classifier was then used for mapping each feature vector into corresponding discrete emotions. The results presented in this study indicated thatWavelet features extracted from alpha, beta and gamma bands seem to provide the necessary information for describing the aforementioned emotions. Using the DEAP (Dataset for Emotion Analysis using electroencephalogram, Physiological and Video Signals), our proposed method achieved an average sensitivity and specificity of 77.4% ± 14.1% and 69.1% ± 12.8%, respectively.

Image Quality Assessment of High-Resolution Satellite Images with Mtf-Based Fuzzy Comprehensive Evaluation Method

NASA Astrophysics Data System (ADS)

Wu, Z.; Luo, Z.; Zhang, Y.; Guo, F.; He, L.

2018-04-01

A Modulation Transfer Function (MTF)-based fuzzy comprehensive evaluation method was proposed in this paper for the purpose of evaluating high-resolution satellite image quality. To establish the factor set, two MTF features and seven radiant features were extracted from the knife-edge region of image patch, which included Nyquist, MTF0.5, entropy, peak signal to noise ratio (PSNR), average difference, edge intensity, average gradient, contrast and ground spatial distance (GSD). After analyzing the statistical distribution of above features, a fuzzy evaluation threshold table and fuzzy evaluation membership functions was established. The experiments for comprehensive quality assessment of different natural and artificial objects was done with GF2 image patches. The results showed that the calibration field image has the highest quality scores. The water image has closest image quality to the calibration field, quality of building image is a little poor than water image, but much higher than farmland image. In order to test the influence of different features on quality evaluation, the experiment with different weights were tested on GF2 and SPOT7 images. The results showed that different weights correspond different evaluating effectiveness. In the case of setting up the weights of edge features and GSD, the image quality of GF2 is better than SPOT7. However, when setting MTF and PSNR as main factor, the image quality of SPOT7 is better than GF2.

Granulomatous responses in larval taeniid infections.

PubMed

Díaz, Á; Sagasti, C; Casaravilla, C

2018-05-01

Granulomas are responses to persistent nonliving bodies or pathogens, centrally featuring specialized macrophage forms called epithelioid and multinucleated giant cells. The larval stages of the cestode parasites of the Taeniidae family (Taenia, Echinococcus) develop for years in fixed tissue sites in mammals. In consequence, they are targets of granulomatous responses. The information on tissue responses to larval taeniids is fragmented among host and parasite species and scattered over many decades. We attempt to draw an integrated picture of these responses in solid tissues. The intensity of inflammation around live parasites spans a spectrum from minimal to high, parasite vitality correlating with low inflammation. The low end of the inflammatory spectrum features collagen capsules proximal to the parasites and moderate distal infiltration. The middle of the spectrum is dominated by classical granulomatous responses, whereas the high end features massive eosinophil invasions. Across the range of parasite species, much observational evidence suggests that eosinophils are highly effective at killing larval taeniids in solid tissues, before and during chronic granulomatous responses. The evidence available also suggests that these parasites are adapted to inhibit host granulomatous responses, in part through the exacerbation of host regulatory mechanisms including regulatory T cells and TGF-β. © 2018 John Wiley & Sons Ltd.

Novel drift structures for silicon and compound semiconductor X-ray and gamma-ray detectors

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

Patt, B.E.; Iwanczyk, J.S.

Recently developed silicon- and compound-semiconductor-based drift detector structures have produced excellent performance for charged particles, X-rays, and gamma rays and for low-signal visible light detection. The silicon drift detector (SDD) structures that the authors discuss relate to direct X-ray detectors and scintillation photon detectors coupled with scintillators for gamma rays. Recent designs include several novel features that ensure very low dark current and hence low noise. In addition, application of thin window technology ensures a very high quantum efficiency entrance window on the drift photodetector. The main features of the silicon drift structures for X rays and light detection aremore » very small anode capacitance independent of the overall detector size, low noise, and high throughput. To take advantage of the small detector capacitance, the first stage of the electronics needs to be integrated into the detector anode. In the gamma-ray application, factors other than electronic noise dominate, and there is no need to integrate the electronics into the anode. Thus, a different drift structure is needed in conjunction with a high-Z material. The main features in this case are large active detector volume and electron-only induced signal.« less

SU-D-BRA-07: A Phantom Study to Assess the Variability in Radiomics Features Extracted From Cone-Beam CT Images

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

Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX

2015-06-15

Purpose: Several studies have demonstrated the prognostic potential for texture features extracted from CT images of non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine if these features could be extracted with high reproducibility from cone-beam CT (CBCT) images in order for features to be easily tracked throughout a patient’s treatment. Methods: Two materials in a radiomics phantom, designed to approximate NSCLC tumor texture, were used to assess the reproducibility of 26 features. This phantom was imaged on 9 CBCT scanners, including Elekta and Varian machines. Thoracic and head imaging protocols were acquired on eachmore » machine. CBCT images from 27 NSCLC patients imaged using the thoracic protocol on Varian machines were obtained for comparison. The variance for each texture measured from these patients was compared to the variance in phantom values for different manufacturer/protocol subsets. Levene’s test was used to identify features which had a significantly smaller variance in the phantom scans versus the patient data. Results: Approximately half of the features (13/26 for material1 and 15/26 for material2) had a significantly smaller variance (p<0.05) between Varian thoracic scans of the phantom compared to patient scans. Many of these same features remained significant for the head scans on Varian (12/26 and 8/26). However, when thoracic scans from Elekta and Varian were combined, only a few features were still significant (4/26 and 5/26). Three features (skewness, coarsely filtered mean and standard deviation) were significant in almost all manufacturer/protocol subsets. Conclusion: Texture features extracted from CBCT images of a radiomics phantom are reproducible and show significantly less variation than the same features measured from patient images when images from the same manufacturer or with similar parameters are used. Reproducibility between CBCT scanners may be high enough to allow the extraction of meaningful texture values for patients. This project was funded in part by the Cancer Prevention Research Institute of Texas (CPRIT). Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« less

Diamond X-ray Photodiode for White and Monochromatic SR beams

PubMed Central

Keister, Jeffrey W.; Smedley, John; Muller, Erik M.; Bohon, Jen; Héroux, Annie

2011-01-01

High purity, single crystal CVD diamond plates are screened for quality and instrumented into a sensor assembly for quantitative characterization of flux and position sensitivity. Initial investigations have yielded encouraging results and have led to further development. Several limiting complications are observed and discussed, as well as mitigations thereof. For example, diamond quality requirements for x-ray diodes include low nitrogen impurity and crystallographic defectivity. Thin electrode windows and electronic readout performance are ultimately also critical to device performance. Promising features observed so far from prototype devices include calculable responsivity, flux linearity, position sensitivity and timing performance. Recent results from testing in high flux and high speed applications are described. PMID:21822344

Energy efficient engine high-pressure turbine supersonic cascade technology report

NASA Technical Reports Server (NTRS)

Kopper, F. C.; Milano, R.; Davis, R. L.; Dring, R. P.; Stoeffler, R. C.

1981-01-01

The performance of two vane endwall geometries and three blade sections for the high-pressure turbine was evaluated in terms of the efficiency requirements of the Energy Efficient Engine high-pressure turbine component. The van endwall designs featured a straight wall and S-wall configuration. The blade designs included a base blade, straightback blade, and overcambered blade. Test results indicated that the S-wall vane configuration and the base blade configuration offered the most promising performance characteristics for the Energy Efficient Engine high-pressure turbine component.

Integrating High-Reliability Principles to Transform Access and Throughput by Creating a Centralized Operations Center.

PubMed

Davenport, Paul B; Carter, Kimberly F; Echternach, Jeffrey M; Tuck, Christopher R

2018-02-01

High-reliability organizations (HROs) demonstrate unique and consistent characteristics, including operational sensitivity and control, situational awareness, hyperacute use of technology and data, and actionable process transformation. System complexity and reliance on information-based processes challenge healthcare organizations to replicate HRO processes. This article describes a healthcare organization's 3-year journey to achieve key HRO features to deliver high-quality, patient-centric care via an operations center powered by the principles of high-reliability data and software to impact patient throughput and flow.

Photovoltaic module and interlocked stack of photovoltaic modules

DOEpatents

Wares, Brian S.

2012-09-04

One embodiment relates to an arrangement of photovoltaic modules configured for transportation. The arrangement includes a plurality of photovoltaic modules, each photovoltaic module including a frame having at least a top member and a bottom member. A plurality of alignment features are included on the top member of each frame, and a plurality of alignment features are included on the bottom member of each frame. Adjacent photovoltaic modules are interlocked by the alignment features on the top member of a lower module fitting together with the alignment features on the bottom member of an upper module. Other embodiments, features and aspects are also disclosed.

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

PubMed

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

2018-01-01

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

A systematic literature review of diabetes self-management education features to improve diabetes education in women of Black African/Caribbean and Hispanic/Latin American ethnicity.

PubMed

Gucciardi, Enza; Chan, Vivian Wing-Sheung; Manuel, Lisa; Sidani, Souraya

2013-08-01

This systematic literature review aims to identify diabetes self-management education (DSME) features to improve diabetes education for Black African/Caribbean and Hispanic/Latin American women with Type 2 diabetes mellitus. We conducted a literature search in six health databases for randomized controlled trials and comparative studies. Success rates of intervention features were calculated based on effectiveness in improving glycosolated hemoglobin (HbA1c), anthropometrics, physical activity, or diet outcomes. Calculations of rate differences assessed whether an intervention feature positively or negatively affected an outcome. From 13 studies included in our analysis, we identified 38 intervention features in relation to their success with an outcome. Five intervention features had positive rate differences across at least three outcomes: hospital-based interventions, group interventions, the use of situational problem-solving, frequent sessions, and incorporating dietitians as interventionists. Six intervention features had high positive rate differences (i.e. ≥50%) on specific outcomes. Different DSME intervention features may influence broad and specific self-management outcomes for women of African/Caribbean and Hispanic/Latin ethnicity. With the emphasis on patient-centered care, patients and care providers can consider options based on DSME intervention features for its broad and specific impact on outcomes to potentially make programming more effective. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

NCBI GEO: archive for high-throughput functional genomic data.

PubMed

Barrett, Tanya; Troup, Dennis B; Wilhite, Stephen E; Ledoux, Pierre; Rudnev, Dmitry; Evangelista, Carlos; Kim, Irene F; Soboleva, Alexandra; Tomashevsky, Maxim; Marshall, Kimberly A; Phillippy, Katherine H; Sherman, Patti M; Muertter, Rolf N; Edgar, Ron

2009-01-01

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as 'Minimum Information About a Microarray Experiment' (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Adiposity and Fat Metabolism in Lactating and Fasting Northern Elephant Seals12

PubMed Central

Crocker, Daniel E.; Champagne, Cory D.; Fowler, Melinda A.; Houser, Dorian S.

2014-01-01

Several taxa of animals fast completely from food and water during energy-intensive periods such as lactation, breeding, and development. In elephant seals, these behaviors are sustained by high adiposity, high rates of fat mobilization, and reduced oxidation of carbohydrates and proteins. Adiposity and the regulation of lipolysis directly affect lactation energetics, milk composition, and mating success. Long-term fasting induces changes in regulation of lipolysis and lipid metabolism that influence fatty acid (FA) availability and the onset of insulin resistance. Hypoinsulinemia and elevated circulating FAs are also associated with several unique features of carbohydrate metabolism, including elevated plasma glucose, gluconeogenesis, and Cori cycle activity as well as high rates of pyruvate and tricarboxylic acid cycling. Glucose-lactate pools and triacylglycerol-FA cycles may be linked via glyceroneogenesis and this may be an important pathway influencing both fat and carbohydrate metabolism. Together, these features allow a sustained, high intensity, fat-based metabolism without substantial accumulation of ketoacids. PMID:24425723

Logic computation in phase change materials by threshold and memory switching.

PubMed

Cassinerio, M; Ciocchini, N; Ielmini, D

2013-11-06

Memristors, namely hysteretic devices capable of changing their resistance in response to applied electrical stimuli, may provide new opportunities for future memory and computation, thanks to their scalable size, low switching energy and nonvolatile nature. We have developed a functionally complete set of logic functions including NOR, NAND and NOT gates, each utilizing a single phase-change memristor (PCM) where resistance switching is due to the phase transformation of an active chalcogenide material. The logic operations are enabled by the high functionality of nanoscale phase change, featuring voltage comparison, additive crystallization and pulse-induced amorphization. The nonvolatile nature of memristive states provides the basis for developing reconfigurable hybrid logic/memory circuits featuring low-power and high-speed switching. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection of breast cancer in automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Mus, Roel; Karssemeijer, Nico

2012-03-01

Automated 3D breast ultrasound (ABUS) is a novel imaging modality, in which motorized scans of the breasts are made with a wide transducer through a membrane under modest compression. The technology has gained high interest and may become widely used in screening of dense breasts, where sensitivity of mammography is poor. ABUS has a high sensitivity for detecting solid breast lesions. However, reading ABUS images is time consuming, and subtle abnormalities may be missed. Therefore, we are developing a computer aided detection (CAD) system to help reduce reading time and errors. In the multi-stage system we propose, segmentations of the breast and nipple are performed, providing landmarks for the detection algorithm. Subsequently, voxel features characterizing coronal spiculation patterns, blobness, contrast, and locations with respect to landmarks are extracted. Using an ensemble of classifiers, a likelihood map indicating potential malignancies is computed. Local maxima in the likelihood map are determined using a local maxima detector and form a set of candidate lesions in each view. These candidates are further processed in a second detection stage, which includes region segmentation, feature extraction and a final classification. Region segmentation is performed using a 3D spiral-scanning dynamic programming method. Region features include descriptors of shape, acoustic behavior and texture. Performance was determined using a 78-patient dataset with 93 images, including 50 malignant lesions. We used 10-fold cross-validation. Using FROC analysis we found that the system obtains a lesion sensitivity of 60% and 70% at 2 and 4 false positives per image respectively.

Building America Case Study: Ground Source Heat Pump Research, TaC Studios Residence, Atlanta, Georigia (Fact Sheet)

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

Not Available

2014-09-01

As part of the NAHB Research Center Industry Partnership, Southface partnered with TaC Studios, an Atlanta based architecture firm specializing in residential and light commercial design, on the construction of a new test home in Atlanta, GA in the mixed-humid climate. This home serves as a residence and home office for the firm's owners, as well as a demonstration of their design approach to potential and current clients. Southface believes the home demonstrates current best practices for the mixed-humid climate, including a building envelope featuring advanced air sealing details and low density spray foam insulation, glazing that exceeds ENERGY STARmore » requirements, and a high performance heating and cooling system. Construction quality and execution was a high priority for TaC Studios and was ensured by a third party review process. Post construction testing showed that the project met stated goals for envelope performance, an air infiltration rate of 2.15 ACH50. The homeowner's wished to further validate whole house energy savings through the project's involvement with Building America and this long-term monitoring effort. As a Building America test home, this home was evaluated to detail whole house energy use, end use loads, and the efficiency and operation of the ground source heat pump and associated systems. Given that the home includes many non-typical end use loads including a home office, pool, landscape water feature, and other luxury features not accounted for in Building America modeling tools, these end uses were separately monitored to determine their impact on overall energy consumption.« less

Radiomic texture-curvature (RTC) features for precision medicine of patients with rheumatoid arthritis-associated interstitial lung disease

NASA Astrophysics Data System (ADS)

Watari, Chinatsu; Matsuhiro, Mikio; Näppi, Janne J.; Nasirudin, Radin A.; Hironaka, Toru; Kawata, Yoshiki; Niki, Noboru; Yoshida, Hiroyuki

2018-03-01

We investigated the effect of radiomic texture-curvature (RTC) features of lung CT images in the prediction of the overall survival of patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD). We retrospectively collected 70 RA-ILD patients who underwent thin-section lung CT and serial pulmonary function tests. After the extraction of the lung region, we computed hyper-curvature features that included the principal curvatures, curvedness, bright/dark sheets, cylinders, blobs, and curvature scales for the bronchi and the aerated lungs. We also computed gray-level co-occurrence matrix (GLCM) texture features on the segmented lungs. An elastic-net penalty method was used to select and combine these features with a Cox proportional hazards model for predicting the survival of the patient. Evaluation was performed by use of concordance index (C-index) as a measure of prediction performance. The C-index values of the texture features, hyper-curvature features, and the combination thereof (RTC features) in predicting patient survival was estimated by use of bootstrapping with 2,000 replications, and they were compared with an established clinical prognostic biomarker known as the gender, age, and physiology (GAP) index by means of two-sided t-test. Bootstrap evaluation yielded the following C-index values for the clinical and radiomic features: (a) GAP index: 78.3%; (b) GLCM texture features: 79.6%; (c) hypercurvature features: 80.8%; and (d) RTC features: 86.8%. The RTC features significantly outperformed any of the other predictors (P < 0.001). The Kaplan-Meier survival curves of patients stratified to low- and high-risk groups based on the RTC features showed statistically significant (P < 0.0001) difference. Thus, the RTC features can provide an effective imaging biomarker for predicting the overall survival of patients with RA-ILD.

Using High Resolution Commercial Satellite Imagery to Quantify Spatial Features of Urban Areas and their Relationship to Quality of Life Indicators in Accra, Ghana

NASA Astrophysics Data System (ADS)

Sandborn, A.; Engstrom, R.; Yu, Q.

2014-12-01

Mapping urban areas via satellite imagery is an important task for detecting and anticipating land cover and land use change at multiple scales. As developing countries experience substantial urban growth and expansion, remotely sensed based estimates of population and quality of life indicators can provide timely and spatially explicit information to researchers and planners working to determine how cities are changing. In this study, we use commercial high spatial resolution satellite imagery in combination with fine resolution census data to determine the ability of using remotely sensed data to reveal the spatial patterns of quality of life in Accra, Ghana. Traditionally, spectral characteristics are used on a per-pixel basis to determine land cover; however, in this study, we test a new methodology that quantifies spatial characteristics using a variety of spatial features observed in the imagery to determine the properties of an urban area. The spatial characteristics used in this study include histograms of oriented gradients, PanTex, Fourier transform, and line support regions. These spatial features focus on extracting structural and textural patterns of built-up areas, such as homogeneous building orientations and straight line indices. Information derived from aggregating the descriptive statistics of the spatial features at both the fine-resolution census unit and the larger neighborhood level are then compared to census derived quality of life indicators including information about housing, education, and population estimates. Preliminary results indicate that there are correlations between straight line indices and census data including available electricity and literacy rates. Results from this study will be used to determine if this methodology provides a new and improved way to measure a city structure in developing cities and differentiate between residential and commercial land use zones, as well as formal versus informal housing areas.

Unification of gauge and Yukawa couplings

NASA Astrophysics Data System (ADS)

Abdalgabar, Ammar; Khojali, Mohammed Omer; Cornell, Alan S.; Cacciapaglia, Giacomo; Deandrea, Aldo

2018-01-01

The unification of gauge and top Yukawa couplings is an attractive feature of gauge-Higgs unification models in extra-dimensions. This feature is usually considered difficult to obtain based on simple group theory analyses. We reconsider a minimal toy model including the renormalisation group running at one loop. Our results show that the gauge couplings unify asymptotically at high energies, and that this may result from the presence of an UV fixed point. The Yukawa coupling in our toy model is enhanced at low energies, showing that a genuine unification of gauge and Yukawa couplings may be achieved.

A satellite-based personal communication system for the 21st century

NASA Technical Reports Server (NTRS)

Sue, Miles K.; Dessouky, Khaled; Levitt, Barry; Rafferty, William

1990-01-01

Interest in personal communications (PCOMM) has been stimulated by recent developments in satellite and terrestrial mobile communications. A personal access satellite system (PASS) concept was developed at the Jet Propulsion Laboratory (JPL) which has many attractive user features, including service diversity and a handheld terminal. Significant technical challenges addressed in formulating the PASS space and ground segments are discussed. PASS system concept and basic design features, high risk enabling technologies, an optimized multiple access scheme, alternative antenna coverage concepts, the use of non-geostationary orbits, user terminal radiation constraints, and user terminal frequency reference are covered.

Field defects in progression to gastrointestinal tract cancers

PubMed Central

Bernstein, Carol; Bernstein, Harris; Payne, Claire M.; Dvorak, Katerina; Garewal, Harinder

2009-01-01

A field of defective tissue may represent a pre-malignant stage in progression to many cancers. However, field defects are often overlooked in studies of cancer progression through assuming tissue at some distance from the cancer is normal. We indicate, however, the generality of field defects in gastrointestinal cancers, including cancers of the oropharynx, esophagus, stomach, bile duct, pancreas, small intestine and colon/rectum. Common features of these field defects are reduced apoptosis competence, aberrant proliferation and genomic instability. These features are often associated with high bile acid exposure and may explain the association of dietary-related factors with cancer progression. PMID:18164807

Computer-assisted diagnosis of melanoma.

PubMed

Fuller, Collin; Cellura, A Paul; Hibler, Brian P; Burris, Katy

2016-03-01

The computer-assisted diagnosis of melanoma is an exciting area of research where imaging techniques are combined with diagnostic algorithms in an attempt to improve detection and outcomes for patients with skin lesions suspicious for malignancy. Once an image has been acquired, it undergoes a processing pathway which includes preprocessing, enhancement, segmentation, feature extraction, feature selection, change detection, and ultimately classification. Practicality for everyday clinical use remains a vital question. A successful model must obtain results that are on par or outperform experienced dermatologists, keep costs at a minimum, be user-friendly, and be time efficient with high sensitivity and specificity. ©2015 Frontline Medical Communications.

Some Aspects of an Air-Core Single-Coil Magnetic Suspension System

NASA Technical Reports Server (NTRS)

Hamlet, Irvin L.; Kilgore, Robert A.

1966-01-01

This paper presents some of the technical aspects in the development at the Langley Research Center of an air-cove, dual-wound, single-coil, magnetic-suspension system with one-dimensional control. Overall electrical system design features and techniques are discussed in addition to the problems of control and stability. Special treatment is given to the operation of a dual-wound, high-current support coil which provides the bias fields and superimposed modulated field. Other designs features include a six-phase, solid-state power stage for modulation of the relatively large magnitude control current, and an associated six-phase trigger circuit.

Circulating D-dimer level correlates with disease characteristics in hepatoblastoma patients

PubMed Central

Zhang, BinBin; Liu, GongBao; Liu, XiangQi; Zheng, Shan; Dong, Kuiran; Dong, Rui

2017-01-01

Abstract Objectives: Hepatoblastoma (HB) is the most common pediatric liver malignancy, typically affecting children within the first 4 years of life. However, only a few validated blood biomarkers are used in clinical evaluation. The current study explored the clinical application and significance of D-dimer levels in patients with HB. Method: Forty-four patients with HB were included in this retrospective study. D-dimer and plasma fibrinogen levels were examined, and their correlation with other clinical features was analyzed. D-dimer and plasma fibrinogen levels were examined between HB and other benign hepatic tumors. Results: D-dimer levels were significantly associated with high-risk HB features, such as advanced stage and high α-fetoprotein (AFP) levels. Higher D-dimer levels were observed in stage 4 patients compared with stage 1/2/3 patients (P = .028). Higher D-dimer levels were also observed in patients with higher AFP levels before chemotherapy compared with patients with lower AFP levels after chemotherapy (P< 0.001). In addition, higher D-dimer levels were observed in HB compared with other benign hepatic tumors such as hepatic hemangioma and hepatocellular adenoma (P = .012). No significant difference in D-dimer levels was found between sex (P = .503) and age (≥12 vs <12 months, P = .424). There was no significant difference in plasma fibrinogen levels between sex or age and high-risk HB features, such as advanced stage and high AFP levels. Conclusions: Elevated D-dimer levels could be a useful determinant biomarker for high-risk features in patients with HB. This finding also supports the clinical application of D-dimer in HB. PMID:29381980

Neuroleptic malignant syndrome as a presenting feature of subacute sclerosing panencephalitis.

PubMed

Garg, Divyani; Reddy, Varun; Singh, Rajesh Kumar; Dash, Deepa; Bhatia, Rohit; Tripathi, Manjari

2018-02-01

Subacute sclerosing panencephalitis (SSPE) is a slowly progressive degenerative disorder caused by measles virus. It is characterised by typical clinical and electrophysiological features in the form of slow myoclonic jerks, with progressive cognitive impairment, visual symptoms, and periodic complexes on EEG, with raised titres of anti-measles antibodies in CSF and serum. Atypical presentations of SSPE have been reported including brainstem involvement, ADEM-like presentation, acute encephalitis, and cerebellar ataxia. Presentation with predominant extrapyramidal features is uncommon. We describe a case of SSPE presenting with extensive rigidity with highly elevated CPK values, mimicking neuroleptic malignant syndrome (NMS) which was most probably due to central dopaminergic blockade induced by the disease process. To our knowledge, this is the first case of SSPE presenting with a NMS-like syndrome.

Predicting Future Morphological Changes of Lesions from Radiotracer Uptake in 18F-FDG-PET Images

PubMed Central

Bagci, Ulas; Yao, Jianhua; Miller-Jaster, Kirsten; Chen, Xinjian; Mollura, Daniel J.

2013-01-01

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on 18F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 18F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUVmax (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUVmax. We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16). PMID:23431398

An initial trial of a prototype telepathology system featuring static imaging with discrete control of the remote microscope.

PubMed

Winokur, T S; McClellan, S; Siegal, G P; Reddy, V; Listinsky, C M; Conner, D; Goldman, J; Grimes, G; Vaughn, G; McDonald, J M

1998-07-01

Routine diagnosis of pathology images transmitted over telecommunications lines remains an elusive goal. Part of the resistance stems from the difficulty of enabling image selection by the remote pathologist. To address this problem, a telepathology microscope system (TelePath, TeleMedicine Solutions, Birmingham, Ala) that has features associated with static and dynamic imaging systems was constructed. Features of the system include near real time image transmission, provision of a tiled overview image, free choice of any fields at any desired optical magnification, and automated tracking of the pathologist's image selection. All commands and images are discrete, avoiding many inherent problems of full motion video and continuous remote control. A set of 64 slides was reviewed by 3 pathologists in a simulated frozen section environment. Each pathologist provided diagnoses for all 64 slides, as well as qualitative information about the system. Thirty-one of 192 diagnoses disagreed with the reference diagnosis that had been reached before the trial began. Qf the 31, 13 were deferrals and 12 were diagnoses of cases that had a deferral as the reference diagnosis. In 6 cases, the diagnosis disagreed with the reference diagnosis yielding an overall accuracy of 96.9%. Confidence levels in the diagnoses were high. This trial suggests that this system provides high-quality anatomic pathology services, including intraoperative diagnoses, over telecommunications lines.

Sidescan-Sonar Imagery and Surficial Geologic Interpretations of the Sea Floor in Western Rhode Island Sound

USGS Publications Warehouse

McMullen, K.Y.; Poppe, L.J.; Haupt, T.A.; Crocker, J.M.

2009-01-01

The U.S. Geological Survey (USGS) and National Oceanic and Atmospheric Administration (NOAA) have been working together to interpret sea-floor geology along the northeastern coast of the United States. In 2004, the NOAA Ship RUDE completed survey H11322, a sidescan-sonar and bathymetric survey that covers about 60 square kilometers of the sea floor in western Rhode Island Sound. This report interprets sidescan-sonar and bathymetric data from NOAA survey H11322 to delineate sea-floor features and sedimentary environments in the study area. Paleozoic bedrock and Cretaceous Coastal Plain sediments in Rhode Island Sound underlie Pleistocene glacial drift that affects the distribution of surficial Holocene marine and transgressional sediments. The study area has three bathymetric highs separated by a channel system. Features and patterns in the sidescan-sonar imagery include low, moderate, and high backscatter; sand waves; scarps; erosional outliers; boulders; trawl marks; and dredge spoils. Four sedimentary environments in the study area, based on backscatter and bathymetric features, include those characterized by erosion or nondeposition, coarse-grained bedload transport, sorting and reworking, and deposition. Environments characterized by erosion or nondeposition and coarse-grained bedload transport are located in shallower areas and environments characterized by deposition are located in deeper areas; environments characterized by sorting and reworking processes are generally located at moderate depths.

The first Korean patient with Potocki-Shaffer syndrome: a rare cause of multiple exostoses.

PubMed

Sohn, Young Bae; Yim, Shin-Young; Cho, Eun-Hae; Kim, Ok-Hwa

2015-02-01

Potocki-Shaffer syndrome (PSS, OMIM #601224) is a rare contiguous gene deletion syndrome caused by haploinsufficiency of genes located on the 11p11.2p12. Affected individuals have a number of characteristic features including multiple exostoses, biparietal foramina, abnormalities of genitourinary system, hypotonia, developmental delay, and intellectual disability. We report here on the first Korean case of an 8-yr-old boy with PSS diagnosed by high resolution microarray. Initial evaluation was done at age 6 months because of a history of developmental delay, hypotonia, and dysmorphic face. Coronal craniosynostosis and enlarged parietal foramina were found on skull radiographs. At age 6 yr, he had severe global developmental delay. Multiple exostoses of long bones were detected during a radiological check-up. Based on the clinical and radiological features, PSS was highly suspected. Subsequently, chromosomal microarray analysis identified an 8.6 Mb deletion at 11p11.2 [arr 11p12p11.2 (Chr11:39,204,770-47,791,278)×1]. The patient continued rehabilitation therapy for profound developmental delay. The progression of multiple exostosis has being monitored. This case confirms and extends data on the genetic basis of PSS. In clinical and radiologic aspect, a patient with multiple exostoses accompanying with syndromic features, including craniofacial abnormalities and mental retardation, the diagnosis of PSS should be considered.

Clustering Suicide Attempters: Impulsive-Ambivalent, Well-Planned, or Frequent.

PubMed

Lopez-Castroman, Jorge; Nogue, Erika; Guillaume, Sebastien; Picot, Marie Christine; Courtet, Philippe

2016-06-01

Attempts to predict suicidal behavior within high-risk populations have so far shown insufficient accuracy. Although several psychosocial and clinical features have been consistently associated with suicide attempts, investigations of latent structure in well-characterized populations of suicide attempters are lacking. We analyzed a sample of 1,009 hospitalized suicide attempters that were recruited between 1999 and 2012. Eleven clinically relevant items related to the characteristics of suicidal behavior were submitted to a Hierarchical Ascendant Classification. Phenotypic profiles were compared between the resulting clusters. A decisional tree was constructed to facilitate the differentiation of individuals classified within the first 2 clusters. Most individuals were included in a cluster characterized by less lethal means and planning ("impulse-ambivalent"). A second cluster featured more carefully planned attempts ("well-planned"), more alcohol or drug use before the attempt, and more precautions to avoid interruptions. Finally, a small, third cluster included individuals reporting more attempts ("frequent"), more often serious or violent attempts, and an earlier age at first attempt. Differences across clusters by demographic and clinical characteristics were also found, particularly with the third cluster whose participants had experienced high levels of childhood abuse. Cluster analysis consistently supported 3 distinct clusters of individuals with specific features in their suicidal behaviors and phenotypic profiles that could help clinicians to better focus prevention strategies. © Copyright 2016 Physicians Postgraduate Press, Inc.

Comparative study of bacteremias caused by Enterococcus spp. with and without high-level resistance to gentamicin. The Grupo Andaluz para el estudio de las Enfermedades Infecciosas.

PubMed

Caballero-Granado, F J; Cisneros, J M; Luque, R; Torres-Tortosa, M; Gamboa, F; Díez, F; Villanueva, J L; Pérez-Cano, R; Pasquau, J; Merino, D; Menchero, A; Mora, D; López-Ruz, M A; Vergara, A

1998-02-01

A prospective, multicenter study was carried out over a period of 10 months. All patients with clinically significant bacteremia caused by Enterococcus spp. were included. The epidemiological, microbiological, clinical, and prognostic features and the relationship of these features to the presence of high-level resistance to gentamicin (HLRG) were studied. Ninety-three patients with enterococcal bacteremia were included, and 31 of these cases were caused by HLRG (33%). The multivariate analysis selected chronic renal failure, intensive care unit stay, previous use of antimicrobial agents, and Enterococcus faecalis species as the independent risk factors that influenced the development of HLRG. The strains with HLRG showed lower levels of susceptibility to penicillin and ciprofloxacin. Clinical features (except for chronic renal failure) were similar in both groups of patients. HLRG did not influence the prognosis for patients with enterococcal bacteremia in terms of either the crude mortality rate (29% for patients with bacteremia caused by enterococci with HLRG and 28% for patients not infected with strains with HLRG) or the hospital stay after the acquisition of enterococcal bacteremia. Hemodynamic compromise, inappropriate antimicrobial therapy, and mechanical ventilation were revealed in the multivariate analysis to be the independent risk factors for mortality. Prolonged hospitalization was associated with the nosocomial acquisition of bacteremia and polymicrobial infections.

Photovoltaic module and interlocked stack of photovoltaic modules

DOEpatents

Wares, Brian S.

2014-09-02

One embodiment relates to an arrangement of photovoltaic modules configured for transportation. The arrangement includes a plurality of photovoltaic modules, each photovoltaic module including a frame. A plurality of individual male alignment features and a plurality of individual female alignment features are included on each frame. Adjacent photovoltaic modules are interlocked by multiple individual male alignment features on a first module of the adjacent photovoltaic modules fitting into and being surrounded by corresponding individual female alignment features on a second module of the adjacent photovoltaic modules. Other embodiments, features and aspects are also disclosed.

Titan solar occultation observations reveal transit spectra of a hazy world.

PubMed

Robinson, Tyler D; Maltagliati, Luca; Marley, Mark S; Fortney, Jonathan J

2014-06-24

High-altitude clouds and hazes are integral to understanding exoplanet observations, and are proposed to explain observed featureless transit spectra. However, it is difficult to make inferences from these data because of the need to disentangle effects of gas absorption from haze extinction. Here, we turn to the quintessential hazy world, Titan, to clarify how high-altitude hazes influence transit spectra. We use solar occultation observations of Titan's atmosphere from the Visual and Infrared Mapping Spectrometer aboard National Aeronautics and Space Administration's (NASA) Cassini spacecraft to generate transit spectra. Data span 0.88-5 μm at a resolution of 12-18 nm, with uncertainties typically smaller than 1%. Our approach exploits symmetry between occultations and transits, producing transit radius spectra that inherently include the effects of haze multiple scattering, refraction, and gas absorption. We use a simple model of haze extinction to explore how Titan's haze affects its transit spectrum. Our spectra show strong methane-absorption features, and weaker features due to other gases. Most importantly, the data demonstrate that high-altitude hazes can severely limit the atmospheric depths probed by transit spectra, bounding observations to pressures smaller than 0.1-10 mbar, depending on wavelength. Unlike the usual assumption made when modeling and interpreting transit observations of potentially hazy worlds, the slope set by haze in our spectra is not flat, and creates a variation in transit height whose magnitude is comparable to those from the strongest gaseous-absorption features. These findings have important consequences for interpreting future exoplanet observations, including those from NASA's James Webb Space Telescope.

Overlapping features of polymyositis and inclusion body myositis in HIV-infected patients

PubMed Central

Lloyd, Thomas E.; Pinal-Fernandez, Iago; Michelle, E. Harlan; Christopher-Stine, Lisa; Pak, Katherine; Sacktor, Ned

2017-01-01

Objective: To characterize patients with myositis with HIV infection. Methods: All HIV-positive patients with myositis seen at the Johns Hopkins Myositis Center from 2003 to 2013 were included in this case series. Muscle biopsy features, weakness pattern, serum creatine kinase (CK) level, and anti–nucleotidase 1A (NT5C1A) status of HIV-positive patients with myositis were assessed. Results: Eleven of 1,562 (0.7%) patients with myositis were HIV-positive. Myositis was the presenting feature of HIV infection in 3 patients. Eight of 11 patients had weakness onset at age 45 years or less. The mean time from the onset of weakness to the diagnosis of myositis was 3.6 years (SD 3.2 years). The mean of the highest measured CK levels was 2,796 IU/L (SD 1,592 IU/L). On muscle biopsy, 9 of 10 (90%) had endomysial inflammation, 7 of 10 (70%) had rimmed vacuoles, and none had perifascicular atrophy. Seven of 11 (64%) patients were anti-NT5C1A-positive. Upon presentation, all had proximal and distal weakness. Five of 6 (83%) patients followed 1 year or longer on immunosuppressive therapy had improved proximal muscle strength. However, each eventually developed weakness primarily affecting wrist flexors, finger flexors, knee extensors, or ankle dorsiflexors. Conclusions: HIV-positive patients with myositis may present with some characteristic polymyositis features including young age at onset, very high CK levels, or proximal weakness that improves with treatment. However, all HIV-positive patients with myositis eventually develop features most consistent with inclusion body myositis, including finger and wrist flexor weakness, rimmed vacuoles on biopsy, or anti-NT5C1A autoantibodies. PMID:28283597

Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment.

PubMed

Torres-Valencia, Cristian A; Álvarez, Mauricio A; Orozco-Gutiérrez, Alvaro A

2014-01-01

Human emotion recognition (HER) allows the assessment of an affective state of a subject. Until recently, such emotional states were described in terms of discrete emotions, like happiness or contempt. In order to cover a high range of emotions, researchers in the field have introduced different dimensional spaces for emotion description that allow the characterization of affective states in terms of several variables or dimensions that measure distinct aspects of the emotion. One of the most common of such dimensional spaces is the bidimensional Arousal/Valence space. To the best of our knowledge, all HER systems so far have modelled independently, the dimensions in these dimensional spaces. In this paper, we study the effect of modelling the output dimensions simultaneously and show experimentally the advantages in modeling them in this way. We consider a multimodal approach by including features from the Electroencephalogram and a few physiological signals. For modelling the multiple outputs, we employ a multiple output regressor based on support vector machines. We also include an stage of feature selection that is developed within an embedded approach known as Recursive Feature Elimination (RFE), proposed initially for SVM. The results show that several features can be eliminated using the multiple output support vector regressor with RFE without affecting the performance of the regressor. From the analysis of the features selected in smaller subsets via RFE, it can be observed that the signals that are more informative into the arousal and valence space discrimination are the EEG, Electrooculogram/Electromiogram (EOG/EMG) and the Galvanic Skin Response (GSR).

Individual classification of ADHD patients by integrating multiscale neuroimaging markers and advanced pattern recognition techniques

PubMed Central

Cheng, Wei; Ji, Xiaoxi; Zhang, Jie; Feng, Jianfeng

2012-01-01

Accurate classification or prediction of the brain state across individual subject, i.e., healthy, or with brain disorders, is generally a more difficult task than merely finding group differences. The former must be approached with highly informative and sensitive biomarkers as well as effective pattern classification/feature selection approaches. In this paper, we propose a systematic methodology to discriminate attention deficit hyperactivity disorder (ADHD) patients from healthy controls on the individual level. Multiple neuroimaging markers that are proved to be sensitive features are identified, which include multiscale characteristics extracted from blood oxygenation level dependent (BOLD) signals, such as regional homogeneity (ReHo) and amplitude of low-frequency fluctuations. Functional connectivity derived from Pearson, partial, and spatial correlation is also utilized to reflect the abnormal patterns of functional integration, or, dysconnectivity syndromes in the brain. These neuroimaging markers are calculated on either voxel or regional level. Advanced feature selection approach is then designed, including a brain-wise association study (BWAS). Using identified features and proper feature integration, a support vector machine (SVM) classifier can achieve a cross-validated classification accuracy of 76.15% across individuals from a large dataset consisting of 141 healthy controls and 98 ADHD patients, with the sensitivity being 63.27% and the specificity being 85.11%. Our results show that the most discriminative features for classification are primarily associated with the frontal and cerebellar regions. The proposed methodology is expected to improve clinical diagnosis and evaluation of treatment for ADHD patient, and to have wider applications in diagnosis of general neuropsychiatric disorders. PMID:22888314

Temporal assessment of radiomic features on clinical mammography in a high-risk population

NASA Astrophysics Data System (ADS)

Mendel, Kayla R.; Li, Hui; Lan, Li; Chan, Chun-Wai; King, Lauren M.; Tayob, Nabihah; Whitman, Gary; El-Zein, Randa; Bedrosian, Isabelle; Giger, Maryellen L.

2018-02-01

Extraction of high-dimensional quantitative data from medical images has become necessary in disease risk assessment, diagnostics and prognostics. Radiomic workflows for mammography typically involve a single medical image for each patient although medical images may exist for multiple imaging exams, especially in screening protocols. Our study takes advantage of the availability of mammograms acquired over multiple years for the prediction of cancer onset. This study included 841 images from 328 patients who developed subsequent mammographic abnormalities, which were confirmed as either cancer (n=173) or non-cancer (n=155) through diagnostic core needle biopsy. Quantitative radiomic analysis was conducted on antecedent FFDMs acquired a year or more prior to diagnostic biopsy. Analysis was limited to the breast contralateral to that in which the abnormality arose. Novel metrics were used to identify robust radiomic features. The most robust features were evaluated in the task of predicting future malignancies on a subset of 72 subjects (23 cancer cases and 49 non-cancer controls) with mammograms over multiple years. Using linear discriminant analysis, the robust radiomic features were merged into predictive signatures by: (i) using features from only the most recent contralateral mammogram, (ii) change in feature values between mammograms, and (iii) ratio of feature values over time, yielding AUCs of 0.57 (SE=0.07), 0.63 (SE=0.06), and 0.66 (SE=0.06), respectively. The AUCs for temporal radiomics (ratio) statistically differed from chance, suggesting that changes in radiomics over time may be critical for risk assessment. Overall, we found that our two-stage process of robustness assessment followed by performance evaluation served well in our investigation on the role of temporal radiomics in risk assessment.

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

Segmentation of retinal blood vessels using artificial neural networks for early detection of diabetic retinopathy

NASA Astrophysics Data System (ADS)

Mann, Kulwinder S.; Kaur, Sukhpreet

2017-06-01

There are various eye diseases in the patients suffering from the diabetes which includes Diabetic Retinopathy, Glaucoma, Hypertension etc. These all are the most common sight threatening eye diseases due to the changes in the blood vessel structure. The proposed method using supervised methods concluded that the segmentation of the retinal blood vessels can be performed accurately using neural networks training. It uses features which include Gray level features; Moment Invariant based features, Gabor filtering, Intensity feature, Vesselness feature for feature vector computation. Then the feature vector is calculated using only the prominent features.

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.

The role of histopathology in establishing the diagnosis of tuberculous pericardial effusions in the presence of HIV.

PubMed

Reuter, H; Burgess, L J; Schneider, J; Van Vuuren, W; Doubell, A F

2006-02-01

To establish the influence of human immunodeficiency virus (HIV) infection on the histopathological features of patients presenting with tuberculous pericarditis. A prospective study was carried out at Tygerberg Academic Hospital, South Africa; 36 patients with large pericardial effusions had open pericardial biopsies under general anaesthesia and were included in the study. Patients underwent pericardiocentesis, followed by daily intermittent catheter drainage; a comprehensive diagnostic work-up (including histopathology of the pericardial tissue) was also performed. Histological tuberculous pericarditis was diagnosed according to predetermined criteria. Tuberculous pericarditis was identified in 25 patients, five of whom were HIV+. The presence of granulomatous inflammation (with or without necrosis) and/or Ziehl-Neelsen positivity yielded the best test results (sensitivity 64%, specificity 100% and diagnostic efficiency 75%). Co-infection with HIV impacts on the histopathological features of pericardial tuberculosis and leads to a decrease in the sensitivity of the test. In areas which have a high prevalence of tuberculosis, the combination of a sensitive test such as adenosine deaminase, chest X-ray and clinical features has a higher diagnostic efficiency than pericardial biopsy in diagnosing tuberculous pericarditis.

mHealth applications for diabetes: User preference and implications for app development.

PubMed

Conway, Nicholas; Campbell, Iona; Forbes, Paula; Cunningham, Scott; Wake, Deborah

2016-12-01

Increasing diabetes prevalence has led to the need for more sustainable and person-centred services. The diabetes self-care mHealth marketplace is growing, but most effective/valued features are unknown. This study gauges diabetes app user opinion to inform development work. An analysis of diabetes mHealth apps informed design of a questionnaire sent to a random sample of 400 patients stratified by diabetes type and age. Responses were analysed by sub-group, and preferences were compared with current diabetes apps. App features included data storage/graphics, exercise tracking, health/diet, reminders/alarms, education. Questionnaire response rate was 59 per cent (234/400); 144/233 (62%) owned smartphones. Smartphone users expressed preference towards mHealth (101/142 (71%)), although diabetes use was low (12/163 (7%)). Respondents favoured many potential features, with similar preferences between diabetes types. This study demonstrates that while mHealth acceptance is high, current engagement is low. Engagement and functionality could be improved by including stakeholders in future development, driven by clinical/user need. © The Author(s) 2015.

IgG4-related tumour-forming mastitis with histological appearances of granulomatous lobular mastitis: comparison with other types of tumour-forming mastitis.

PubMed

Ogura, Kanako; Matsumoto, Toshiharu; Aoki, Yuji; Kitabatake, Toshiaki; Fujisawa, Minoru; Kojima, Kuniaki

2010-07-01

Sometimes, mastitis needs to be differentiated from carcinoma because of its association with induration and with ultrasound findings (such as low-echo lesions) that resemble those in carcinoma. The aim was to define this type of mastitis and to examine 18 cases to clarify its clinicopathological features. All cases were categorized into three types: non-specific mastitis with neutrophilic infiltration (n = 7); non-specific mastitis with lymphoplasmacytic infiltration (n = 9); and granulomatous lobular mastitis (n = 2). The three types of mastitis presented similar ultrasound findings and shared certain histological features including fibrosis and diffuse or lobulocentric inflammation. Granulomatous lobular mastitis showed specific clinicopathological features including lobulocentric inflammation with giant cells, diffuse IgG4+ plasma cells, and also a high level of serum IgG4. Granulomatous lobular mastitis could be categorized into IgG4-related and non-IgG4-related granulomatous lobular mastitis. IgG4 immunohistochemistry serum IgG4 might be useful for diagnosis of IgG4-related granulomatous lobular mastitis and could help to avoid overtreatment such as wide excision.

Lymphocytic esophagitis: Report of three cases and review of the literature

PubMed Central

Jideh, Bilel; Keegan, Andrew; Weltman, Martin

2016-01-01

Lymphocytic esophagitis (LyE) is a rare condition characterised histologically by high numbers of esophageal intraepithelial lymphocytes without significant granulocytes infiltration, in addition to intercellular edema (“spongiosis”). The clinical significance and natural history of LyE is poorly defined although dysphagia is reportedly the most common symptom. Endoscopic features range from normal appearing esophageal mucosa to features similar to those seen in eosinophilic esophagitis, including esophageal rings, linear furrows, whitish exudates, and esophageal strictures/stenosis. Symptomatic gastroesophageal reflux disease is an inconsistent association. LyE has been associated in paediatric Crohn’s disease, and recently in primary esophageal dysmotility disorder in adults. There are no studies assessing effective treatment strategies for LyE; empirical therapies have included use of proton pump inhibitor and corticosteroids. Esophageal dilatation have been used to manage esophageal strictures. LyE has been reported to run a benign course; however there has been a case of esophageal perforation associated with LyE. Here, we describe the clinical, endoscopic and histopathological features of three patients with lymphocytic esophagitis along with a review of the current literature. PMID:28035315

Do Arabic weight-loss apps adhere to evidence-informed practices?

PubMed

Alnasser, Aroub A; Amalraj, Raja E; Sathiaseelan, Arjuna; Al-Khalifa, Abdulrahman S; Marais, Debbi

2016-09-01

Mobile technology has been used successfully for promoting health and weight loss and for treating obesity. There is a high prevalence of smartphone and tablet users among the Saudi population. This study aimed to identify whether current Arabic weight-loss apps had features that adhered to evidence-informed practices. The six most relevant app stores were systematically searched using the Arabic words for weight and diet (n = 298). All apps that met the inclusion criteria (n = 65) were downloaded and examined for adherence to 13 evidence-informed practices. Latent class analysis identified two subgroups of apps: self-monitoring (15 % of apps) and advice-giving apps (85 %). The median number of evidence-informed practices was 1 (1, 2), with no apps having more than six and only nine apps including four to six. Meal planning was the most common feature (38 % of apps). These findings identify serious weaknesses in the currently available Arabic weight-loss apps. Thus, existing and future apps should include more features based on the best available evidence in the context of Arab culture.

The contraction/expansion history of Charon with implications for its planetary-scale tectonic belt

NASA Astrophysics Data System (ADS)

Malamud, Uri; Perets, Hagai B.; Schubert, Gerald

2017-06-01

The New Horizons mission to the Kuiper belt has recently revealed intriguing features on the surface of Charon, including a network of chasmata, cutting across or around a series of high topography features, conjoining to form a belt. It is proposed that this tectonic belt is a consequence of contraction/expansion episodes in the moon's evolution associated particularly with compaction, differentiation and geochemical reactions of the interior. The proposed scenario involves no need for solidification of a vast subsurface ocean and/or a warm initial state. This scenario is based on a new, detailed thermo-physical evolution model of Charon that includes multiple processes. According to the model, Charon experiences two contraction/expansion episodes in its history that may provide the proper environment for the formation of the tectonic belt. This outcome remains qualitatively the same, for several different initial conditions and parameter variations. The precise orientation of Charon's tectonic belt, and the cryovolcanic features observed south of the tectonic belt may have involved a planetary-scale impact, that occurred only after the belt had already formed.

Dedifferentiated chondrosarcoma with telangiectatic osteosarcoma-like features.

PubMed

Okada, K; Hasegawa, T; Tateishi, U; Endo, M; Itoi, E

2006-11-01

A 35-year-old Japanese man was admitted to the National Cancer Center, Tokyo, Japan, in December 2000, with a 2-month history of pain around the left thigh. Radiographs showed a poorly demarcated osteolytic lesion with focal mineralisation and endosteal scalloping in the left proximal femur. Biopsy showed a proliferation of highly anaplastic cells without any cartilaginous component. A wide excision of the left proximal femur with a replacement by endoprosthesis was carried out in February 2001 after treatment with methotrexate and 20 Gy radiation therapy. Pathological examination of the surgical specimen showed a focus of low-grade chondrosarcoma and the coexistence of telangiectatic osteosarcoma-like features. The patient was diagnosed with dedifferentiated chondrosarcoma with telangiectatic osteosarcoma-like features. Lung metastasis appeared in July 2001 despite an adjuvant chemotherapy including methotrexate, cis-platinum and doxorubicin. The latest follow-up study in June 2004 showed multiple lung metastases. Establishing a definitive diagnosis of dedifferentiated chondrosarcoma may be difficult with limited small biopsy specimens. Dedifferentiated chondrosarcoma should be included in the differential diagnosis of osteolytic tumours with focal calcification and endosteal scalloping even if an extraosseous tumour component is not identified.

Amino acid analogs for tumor imaging

DOEpatents

Goodman, M.M.; Shoup, T.

1998-09-15

The invention provides novel amino acid compounds of use in detecting and evaluating brain and body tumors. These compounds combine the advantageous properties of 1-amino-cycloalkyl-1-carboxylic acids, namely, their rapid uptake and prolonged retention in tumors with the properties of halogen substituents, including certain useful halogen isotopes including fluorine-18, iodine-123, iodine-125, iodine-131, bromine-75, bromine-76, bromine-77 and bromine-82. In one aspect, the invention features amino acid compounds that have a high specificity for target sites when administered to a subject in vivo. Preferred amino acid compounds show a target to non-target ratio of at least 5:1, are stable in vivo and substantially localized to target within 1 hour after administration. An especially preferred amino acid compound is [{sup 18}F]-1-amino-3-fluorocyclobutane-1-carboxylic acid (FACBC). In another aspect, the invention features pharmaceutical compositions comprised of an {alpha}-amino acid moiety attached to either a four, five, or a six member carbon-chain ring. In addition, the invention features analogs of {alpha}-aminoisobutyric acid.

Amino acid analogs for tumor imaging

DOEpatents

Goodman, M.M.; Shoup, T.

1998-10-06

The invention provides novel amino acid compounds of use in detecting and evaluating brain and body tumors. These compounds combine the advantageous properties of 1-amino-cycloalkyl-1-carboxylic acids, namely, their rapid uptake and prolonged retention in tumors with the properties of halogen substituents, including certain useful halogen isotopes including fluorine-18, iodine-123, iodine-125, iodine-131, bromine-75, bromine-76, bromine-77 and bromine-82. In one aspect, the invention features amino acid compounds that have a high specificity for target sites when administered to a subject in vivo. Preferred amino acid compounds show a target to non-target ratio of at least 5:1, are stable in vivo and substantially localized to target within 1 hour after administration. An especially preferred amino acid compound is [{sup 18}F]-1-amino-3-fluorocyclobutane-1-carboxylic acid (FACBC). In another aspect, the invention features pharmaceutical compositions comprised of an {alpha}-amino acid moiety attached to either a four, five, or a six member carbon-chain ring. In addition, the invention features analogs of {alpha}-aminoisobutyric acid.

Amino acid analogs for tumor imaging

DOEpatents

Goodman, Mark M.; Shoup, Timothy

1998-09-15

The invention provides novel amino acid compounds of use in detecting and evaluating brain and body tumors. These compounds combine the advantageous properties of 1-amino-cycloalkyl-1-carboxylic acids, namely, their rapid uptake and prolonged retention in tumors with the properties of halogen substituents, including certain useful halogen isotopes including fluorine-18, iodine-123, iodine-125, iodine-131, bromine-75, bromine-76, bromine-77 and bromine-82. In one aspect, the invention features amino acid compounds that have a high specificity for target sites when administered to a subject in vivo. Preferred amino acid compounds show a target to non-target ratio of at least 5:1, are stable in vivo and substantially localized to target within 1 hour after administration. An especially preferred amino acid compound is ›.sup.18 F!-1-amino-3-fluorocyclobutane-1-carboxylic acid (FACBC). In another aspect, the invention features pharmaceutical compositions comprised of an .alpha.-amino acid moiety attached to either a four, five, or a six member carbon-chain ring. In addition, the invention features analogs of .alpha.-aminoisobutyric acid.

Amino acid analogs for tumor imaging

DOEpatents

Goodman, Mark M.; Shoup, Timothy

1998-10-06

The invention provides novel amino acid compounds of use in detecting and evaluating brain and body tumors. These compounds combine the advantageous properties of 1-amino-cycloalkyl-1-carboxylic acids, namely, their rapid uptake and prolonged retention in tumors with the properties of halogen substituents, including certain useful halogen isotopes including fluorine-18, iodine-123, iodine-125, iodine-131, bromine-75, bromine-76, bromine-77 and bromine-82. In one aspect, the invention features amino acid compounds that have a high specificity for target sites when administered to a subject in vivo. Preferred amino acid compounds show a target to non-target ratio of at least 5:1, are stable in vivo and substantially localized to target within 1 hour after administration. An especially preferred amino acid compound is ›.sup.18 F!-1-amino-3-fluorocyclobutane-1-carboxylic acid (FACBC). In another aspect, the invention features pharmaceutical compositions comprised of an .alpha.-amino acid moiety attached to either a four, five, or a six member carbon-chain ring. In addition, the invention features analogs of .alpha.-aminoisobutyric acid.

Image segmentation using joint spatial-intensity-shape features: application to CT lung nodule segmentation

NASA Astrophysics Data System (ADS)

Ye, Xujiong; Siddique, Musib; Douiri, Abdel; Beddoe, Gareth; Slabaugh, Greg

2009-02-01

Automatic segmentation of medical images is a challenging problem due to the complexity and variability of human anatomy, poor contrast of the object being segmented, and noise resulting from the image acquisition process. This paper presents a novel feature-guided method for the segmentation of 3D medical lesions. The proposed algorithm combines 1) a volumetric shape feature (shape index) based on high-order partial derivatives; 2) mean shift clustering in a joint spatial-intensity-shape (JSIS) feature space; and 3) a modified expectation-maximization (MEM) algorithm on the mean shift mode map to merge the neighboring regions (modes). In such a scenario, the volumetric shape feature is integrated into the process of the segmentation algorithm. The joint spatial-intensity-shape features provide rich information for the segmentation of the anatomic structures or lesions (tumors). The proposed method has been evaluated on a clinical dataset of thoracic CT scans that contains 68 nodules. A volume overlap ratio between each segmented nodule and the ground truth annotation is calculated. Using the proposed method, the mean overlap ratio over all the nodules is 0.80. On visual inspection and using a quantitative evaluation, the experimental results demonstrate the potential of the proposed method. It can properly segment a variety of nodules including juxta-vascular and juxta-pleural nodules, which are challenging for conventional methods due to the high similarity of intensities between the nodules and their adjacent tissues. This approach could also be applied to lesion segmentation in other anatomies, such as polyps in the colon.

Imaging genetics approach to predict progression of Parkinson's diseases.

PubMed

Mansu Kim; Seong-Jin Son; Hyunjin Park

2017-07-01

Imaging genetics is a tool to extract genetic variants associated with both clinical phenotypes and imaging information. The approach can extract additional genetic variants compared to conventional approaches to better investigate various diseased conditions. Here, we applied imaging genetics to study Parkinson's disease (PD). We aimed to extract significant features derived from imaging genetics and neuroimaging. We built a regression model based on extracted significant features combining genetics and neuroimaging to better predict clinical scores of PD progression (i.e. MDS-UPDRS). Our model yielded high correlation (r = 0.697, p <; 0.001) and low root mean squared error (8.36) between predicted and actual MDS-UPDRS scores. Neuroimaging (from 123 I-Ioflupane SPECT) predictors of regression model were computed from independent component analysis approach. Genetic features were computed using image genetics approach based on identified neuroimaging features as intermediate phenotypes. Joint modeling of neuroimaging and genetics could provide complementary information and thus have the potential to provide further insight into the pathophysiology of PD. Our model included newly found neuroimaging features and genetic variants which need further investigation.

Discrimination of artificial categories structured by family resemblances: a comparative study in people (Homo sapiens) and pigeons (Columba livia).

PubMed

Makino, Hiroshi; Jitsumori, Masako

2007-02-01

Adult humans (Homo sapiens) and pigeons (Columba livia) were trained to discriminate artificial categories that the authors created by mimicking 2 properties of natural categories. One was a family resemblance relationship: The highly variable exemplars, including those that did not have features in common, were structured by a similarity network with the features correlating to one another in each category. The other was a polymorphous rule: No single feature was essential for distinguishing the categories, and all the features overlapped between the categories. Pigeons learned the categories with ease and then showed a prototype effect in accord with the degrees of family resemblance for novel stimuli. Some evidence was also observed for interactive effects of learning of individual exemplars and feature frequencies. Humans had difficulty in learning the categories. The participants who learned the categories generally responded to novel stimuli in an all-or-none fashion on the basis of their acquired classification decision rules. The processes that underlie the classification performances of the 2 species are discussed.

Principles for the formation of an effective concept of multifunctional high-rise construction investment projects

NASA Astrophysics Data System (ADS)

Beliakov, Sergei

2018-03-01

Investment projects of high-rise construction have a number of features that determine specific risks and additional opportunities that require analysis and accounting in the formation of an effective project concept. The most significant features of high-rise construction include long construction time, complexity of technical and technological solutions, complexity of decisions on the organization of construction and operation, high cost of construction and operation, complexity in determining the ratio of areas designed to accommodate different functional areas, when organizing and coordinating the operation of the facility, with internal zoning. Taking into account the specificity of high-rise construction, among the factors determining the effectiveness of projects, it is advisable to consider as key factors: organizational, technological and investment factors. Within the framework of the article, the author singled out key particular functions for each group of factors under consideration, and also developed a system of principles for the formation of an effective concept of multifunctional high-rise construction investment projects, including the principle of logistic efficiency, the principle of optimal functional zoning, the principle of efficiency of equipment use, the principle of optimizing technological processes, the principle maximization of income, the principle of fund management, the principle of risk management . The model of formation of an effective concept of investment projects of multifunctional high-rise construction developed by the author can contribute to the development of methodological tools in the field of managing the implementation of high-rise construction projects, taking into account their specificity in the current economic conditions.

Magnetization-prepared rapid acquisition with gradient echo magnetic resonance imaging signal and texture features for the prediction of mild cognitive impairment to Alzheimer's disease progression.

PubMed

Martinez-Torteya, Antonio; Rodriguez-Rojas, Juan; Celaya-Padilla, José M; Galván-Tejada, Jorge I; Treviño, Victor; Tamez-Peña, Jose

2014-10-01

Early diagnoses of Alzheimer's disease (AD) would confer many benefits. Several biomarkers have been proposed to achieve such a task, where features extracted from magnetic resonance imaging (MRI) have played an important role. However, studies have focused exclusively on morphological characteristics. This study aims to determine whether features relating to the signal and texture of the image could predict mild cognitive impairment (MCI) to AD progression. Clinical, biological, and positron emission tomography information and MRI images of 62 subjects from the AD neuroimaging initiative were used in this study, extracting 4150 features from each MRI. Within this multimodal database, a feature selection algorithm was used to obtain an accurate and small logistic regression model, generated by a methodology that yielded a mean blind test accuracy of 0.79. This model included six features, five of them obtained from the MRI images, and one obtained from genotyping. A risk analysis divided the subjects into low-risk and high-risk groups according to a prognostic index. The groups were statistically different ([Formula: see text]). These results demonstrated that MRI features related to both signal and texture add MCI to AD predictive power, and supported the ongoing notion that multimodal biomarkers outperform single-modality ones.

Extending the McDonald Observatory Serendipitous Survey of UV/Blue Asteroid Spectra

NASA Technical Reports Server (NTRS)

Vilas, Faith; Cochran, A. L.

1999-01-01

Moderate resolution asteroid spectra in the 350 - 650 nm spectral range acquired randomly over many years (Cochran and Vilas, Icarus v 127, 121, 1997) identified absorption features in spectra of some of the asteroids. A feature centered at 430 nm was identified in the spectra of some low-albedo asteroids (C class and subclass), similar to the feature identified by Vilas et al. (Icarus, v. 102, 225,1993) in other low-albedo asteroid spectra and attributed to a ferric iron spin-forbidden transition in iron alteration minerals such as jarosite. Features at 505 nm and 430 nm were identified in the spectrum of 4 Vesta. The 505-nm feature is highly diagnostic of the amount and form of calcium in pyroxenes. This suggested further research on the sharpness and spectral placement of this feature in the spectra of Vesta and Vestoids (e.g., Cochran and Vilas, Icarus v. 134, 207, 1998). In 1997 and 1998, additional UV/blue spectra were obtained at the 2.7-m Harlan J. Smith telescope with a facility cassegrain spectrograph. These included spectra of low-albedo asteroids, the R-class asteroid 349 Dembowska, and the M-class asteroid 135 Hertha. These spectra will be presented and identified features will be discussed.

Imagine...Opportunities and Resources for Academically Talented Youth.

ERIC Educational Resources Information Center

Hartman, Melissa E., Ed.

2000-01-01

These five issues of a magazine designed for highly gifted and talented secondary students address marine science, anthropology and archaeology, making the most of summer, medicine and health sciences, and the World Wide Web. Featured articles include: (1) "The Ocean's Call: How My Love for the Ocean Grew into a Career" (Jessica Schulman Farrar);…

Service Learning: High School Social Studies Students "Building Bridges" to the Community

ERIC Educational Resources Information Center

Cranford, Sara L.

2011-01-01

This case study examined the relationships between the programmatic features of service learning and student willingness to participate in and development during a service learning opportunity in the secondary, Social Studies classroom. The sample included two sections of Advanced Placement Psychology which consisted of 58 junior and senior…

Mistaking Identities: Challenging Representations of Language, Gender, and Race in High Tech Television Programs.

ERIC Educational Resources Information Center

Voithofer, R. J.

Television programs are increasingly featuring information technologies like computers as significant narrative devices, including the use of computer-based technologies as virtual worlds or environments in which characters interact, the use of computers as tools in problem solving and confronting conflict, and characters that are part human, part…

OCEANIDS: Autonomous Data Acquisition, Management and Distribution System

NASA Technical Reports Server (NTRS)

Bingham, Andrew; Rigor, Eric; Cervantes, Alex; Armstrong, Edward

2004-01-01

OCEANIDS is a clearinghouse for mission essential and near-real-time satellite data streams. This viewgraph presentation describes this mission, and includes the following topics: 1) OCEANIDS Motivation; 2) High-Level Architecture; 3) OCEANIDS Features; 4) OCEANIDS GUI: Nodes; 5) OCEANIDS GUI: Cluster; 6) Data Streams; 7) Statistics; and 8) GHRSST-PP.

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

none,

The home that won a Production Builder award in the 2014 Housing Innovation Awards serves as a model for this builder, showcasing high-tech features including an electric car charging station; a compressed natural gas (CNG) car fueling station; a greywater recycling system that filters shower, sink, and clothes washer water for yard irrigation; smart appliances; and an electronic energy management system.

Interventions for Toddlers with Autism Spectrum Disorders: An Evaluation of Research Evidence

ERIC Educational Resources Information Center

Schertz, Hannah H.; Reichow, Brian; Tan, Paulo; Vaiouli, Potheini; Yildirim, Emine

2012-01-01

Recently emerging intervention studies for toddlers with autism spectrum disorders (ASD) were reviewed through a systematic assessment of intervention outcomes, research rigor, and intervention features. The review includes published peer-reviewed experimental studies of toddlers with high risk for or diagnosis of ASD in which the majority of…

[Abdominal gunshot wounds. Ballistic data and practical management].

PubMed

Vicq, P; Jourdan, P; Chapuis, O; Baranger, B

1996-01-01

The mortality from abdominal gunshot wounds remains high, either in civilian or military cases. The severity factors of these wounds include bullet calibre and energy transfer of the missile. This paper studies some of the ballistics features of abdominal gunshot wounds. Practical guidelines are inferred concerning diagnosis and treatment of these wounds.

Expectancies and Motivations to Attend an Informal Science Lecture Series

ERIC Educational Resources Information Center

AbiGhannam, Niveen; Kahlor, LeeAnn; Dudo, Anthony; Liang, Ming-Ching; Rosenthal, Sonny; Banner, Jay L.

2016-01-01

This study explored the expectancies and motivations that prompt audiences to attend a university science lecture series. The series features talks by science experts from the host campus and around the USA. Each lecture typically attracts between 300 and 600 attendees, including middle and high school student groups, university students, and…

Fabrication of a novel transparent SERS substrate comprised of Ag-nanoparticle arrays and its application in rapid detection of ractopamine on meat

USDA-ARS?s Scientific Manuscript database

Surface-enhanced Raman spectroscopy (SERS) is an emerging analytical tool that boasts the feature of high detection sensitivity and molecular fingerprint specificity attracting increased attention and showing promise in applications including detecting residues of veterinary drugs. In practice, spec...

Interactional Competence in a Paired Speaking Test: Features Salient to Raters

ERIC Educational Resources Information Center

May, Lyn

2011-01-01

Paired speaking tests are now commonly used in both high-stakes testing and classroom assessment contexts. The co-construction of discourse by candidates is regarded as a strength of paired speaking tests, as candidates have the opportunity to display a wider range of interactional competencies, including turn taking, initiating topics, and…

Social Justice and Provision for Children with Additional Support Needs in Scotland

ERIC Educational Resources Information Center

Riddell, Sheila; Weedon, Elisabet

2017-01-01

Since the re-establishment of the Scottish Parliament in 1999, successive administrations have reaffirmed their commitment to social justice. However, despite high-level equality policies, social-class inequality is a major feature of Scottish society, affecting all social policy domains, including education. In this article, we provide a brief…

An Optical Disk-Based Information Retrieval System.

ERIC Educational Resources Information Center

Bender, Avi

1988-01-01

Discusses a pilot project by the Nuclear Regulatory Commission to apply optical disk technology to the storage and retrieval of documents related to its high level waste management program. Components and features of the microcomputer-based system which provides full-text and image access to documents are described. A sample search is included.…

Intelligent trend analysis for a solar thermal energy collector field

NASA Astrophysics Data System (ADS)

Juuso, E. K.

2018-03-01

Solar thermal power plants collect available solar energy in a usable form at a temperature range which is adapted to the irradiation levels and seasonal variations. Solar energy can be collected only when the irradiation is high enough to produce the required temperatures. During the operation, a trade-off of the temperature and the flow is needed to achieve a good level for the collected power. The scaling approach brings temporal analysis to all measurements and features: trend indices are calculated by comparing the averages in the long and short time windows, a weighted sum of the trend index and its derivative detects the trend episodes and severity of the trend is estimated by including also the variable level in the sum. The trend index, trend episodes and especially, the deviation index reveal early evolving changes in the operating conditions, including cloudiness and load disturbances. The solution is highly compact: all variables, features and indices are transformed to the range [-2, 2] and represented in natural language which is important in integrating data-driven solutions with domain expertise. The special situations detected during the test campaigns are explained well.

2006 Compilation of Alaska Gravity Data and Historical Reports

USGS Publications Warehouse

Saltus, Richard W.; Brown, Philip J.; Morin, Robert L.; Hill, Patricia L.

2008-01-01

Gravity anomalies provide fundamental geophysical information about Earth structure and dynamics. To increase geologic and geodynamic understanding of Alaska, the U.S. Geological Survey (USGS) has collected and processed Alaska gravity data for the past 50 years. This report introduces and describes an integrated, State-wide gravity database and provides accompanying gravity calculation tools to assist in its application. Additional information includes gravity base station descriptions and digital scans of historical USGS reports. The gravity calculation tools enable the user to reduce new gravity data in a consistent manner for combination with the existing database. This database has sufficient resolution to define the regional gravity anomalies of Alaska. Interpretation of regional gravity anomalies in parts of the State are hampered by the lack of local isostatic compensation in both southern and northern Alaska. However, when filtered appropriately, the Alaska gravity data show regional features having geologic significance. These features include gravity lows caused by low-density rocks of Cenozoic basins, flysch belts, and felsic intrusions, as well as many gravity highs associated with high-density mafic and ultramafic complexes.

Phase behaviour of disordered proteins underlying low density and high permeability of liquid organelles

NASA Astrophysics Data System (ADS)

Wei, Ming-Tzo; Elbaum-Garfinkle, Shana; Holehouse, Alex S.; Chen, Carlos Chih-Hsiung; Feric, Marina; Arnold, Craig B.; Priestley, Rodney D.; Pappu, Rohit V.; Brangwynne, Clifford P.

2017-11-01

Many intracellular membraneless organelles form via phase separation of intrinsically disordered proteins (IDPs) or regions (IDRs). These include the Caenorhabditis elegans protein LAF-1, which forms P granule-like droplets in vitro. However, the role of protein disorder in phase separation and the macromolecular organization within droplets remain elusive. Here, we utilize a novel technique, ultrafast-scanning fluorescence correlation spectroscopy, to measure the molecular interactions and full coexistence curves (binodals), which quantify the protein concentration within LAF-1 droplets. The binodals of LAF-1 and its IDR display a number of unusual features, including 'high concentration' binodal arms that correspond to remarkably dilute droplets. We find that LAF-1 and other in vitro and intracellular droplets are characterized by an effective mesh size of ∼3-8 nm, which determines the size scale at which droplet properties impact molecular diffusion and permeability. These findings reveal how specific IDPs can phase separate to form permeable, low-density (semi-dilute) liquids, whose structural features are likely to strongly impact biological function.

High-speed civil transport flight- and propulsion-control technological issues

NASA Technical Reports Server (NTRS)

Ray, J. K.; Carlin, C. M.; Lambregts, A. A.

1992-01-01

Technology advances required in the flight and propulsion control system disciplines to develop a high speed civil transport (HSCT) are identified. The mission and requirements of the transport and major flight and propulsion control technology issues are discussed. Each issue is ranked and, for each issue, a plan for technology readiness is given. Certain features are unique and dominate control system design. These features include the high temperature environment, large flexible aircraft, control-configured empennage, minimizing control margins, and high availability and excellent maintainability. The failure to resolve most high-priority issues can prevent the transport from achieving its goals. The flow-time for hardware may require stimulus, since market forces may be insufficient to ensure timely production. Flight and propulsion control technology will contribute to takeoff gross weight reduction. Similar technology advances are necessary also to ensure flight safety for the transport. The certification basis of the HSCT must be negotiated between airplane manufacturers and government regulators. Efficient, quality design of the transport will require an integrated set of design tools that support the entire engineering design team.

Quantitative evaluation of the underground Geoheritage in karst areas: The Picos de Europa National Park, North Spain

NASA Astrophysics Data System (ADS)

Ballesteros, Daniel; Jiménez-Sánchez, Montserrat; José Domínguez-Cuestra, María; García-Sansegundo, Joaquín; Meléndez-Asensio, Mónica

2014-05-01

Karst areas show a lot of kilometers of cave conduits with a hidden Geoheritage poorly investigated in previous works that concerning with their cultural, scientific and education values. The evaluation of cave Geoheritage is complex due to methodological constrains. One of the most important karst areas in the World is the Picos de Europa National Park (North Spain) that was declared as a Global Geosite in 2007 and includes 14 % of the World's Deepest Caves. The GEOCAVE research project is being developed in several caves from the Picos de Europa National Park since 2012 in order to characterize geomorphology and geochronology of the cavities, proposing and validating new methodologies adapted to these environments. The aim of this work is to evaluate the Geoheritage of the Picos de Europa caves based on the studies made in nine selected caves. The methodology includes: 1) elaboration of geomorphological maps of the nine selected caves, projecting geomorphological, geological, hydrogeological, paleontological and cultural forms on the caves surveys; and 2) definition and calculation of three indexes useful to evaluate the Geoheritage of the caves. The indexes are: a) Cave Geoheritage Extension Index (CGhEI), defined as the percentage of the area occupied by the entire features divided by the cave area (excluding the forms that represent the conduits themselves), b) Feature Extension Index (FEI), defined as the area occupied by each group of form divided by the cave area, and c) Cave Geodiversity Index (CGdI), defined as the number of forms divided by the cave area. The nine cave geomorphological maps cover 178,639 m2 of caves and include a whole of 14.9 km of karst conduits, representing these caves the 4.1 % of the conduits of the Picos de Europa. The values of the Cave Geoheritage Extension Index range from 22 to 82 %, while the values of the Feature Extension Indexes for each group of features reach the following values: Geomorphological FEI take values of 20-80 % (speleothems FEI is 15-60 %, fluviokarst FEI is 5-25 %, gravity FEI is 10-40 %); Geological FEI is 4-5 %; Hydrogeological FEI is 0-3 %; Paleontological FEI is 0-0.1% and cultural FEI is 0-4 %. the On the other hand, 84 features are recognized into the caves and the Cave Geodiversity Index ranges from 0.3 to 1.1 features/cm2. These results evidence that 22 to 82 % of the cave conduits are occupy with Geoheritage features, being most of them geomorphological forms (speleothems, fluviokarst and gravity forms). The Geodiversity of the karst caves is high, recognizing a whole of 84 features into the caves and showing a high density of forms. Consequently, underground Geoheritage from karst areas can be estimated combining geomorphological maps few selected caves and three indexes based on number and extensions of the features. These indexes allow us to assign a preliminary weight of the geomorphological, geological, hydrogeological, paleontological and cultural features in a karst area.

A hierarchy for modeling high speed propulsion systems

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Deabreu, Alex

1991-01-01

General research efforts on reduced order propulsion models for control systems design are overviewed. Methods for modeling high speed propulsion systems are discussed including internal flow propulsion systems that do not contain rotating machinery such as inlets, ramjets, and scramjets. The discussion is separated into four sections: (1) computational fluid dynamics model for the entire nonlinear system or high order nonlinear models; (2) high order linearized model derived from fundamental physics; (3) low order linear models obtained from other high order models; and (4) low order nonlinear models. Included are special considerations on any relevant control system designs. The methods discussed are for the quasi-one dimensional Euler equations of gasdynamic flow. The essential nonlinear features represented are large amplitude nonlinear waves, moving normal shocks, hammershocks, subsonic combustion via heat addition, temperature dependent gases, detonation, and thermal choking.

Euclidean Distances as measures of speaker similarity including identical twin pairs: A forensic investigation using source and filter voice characteristics.

PubMed

San Segundo, Eugenia; Tsanas, Athanasios; Gómez-Vilda, Pedro

2017-01-01

There is a growing consensus that hybrid approaches are necessary for successful speaker characterization in Forensic Speaker Comparison (FSC); hence this study explores the forensic potential of voice features combining source and filter characteristics. The former relate to the action of the vocal folds while the latter reflect the geometry of the speaker's vocal tract. This set of features have been extracted from pause fillers, which are long enough for robust feature estimation while spontaneous enough to be extracted from voice samples in real forensic casework. Speaker similarity was measured using standardized Euclidean Distances (ED) between pairs of speakers: 54 different-speaker (DS) comparisons, 54 same-speaker (SS) comparisons and 12 comparisons between monozygotic twins (MZ). Results revealed that the differences between DS and SS comparisons were significant in both high quality and telephone-filtered recordings, with no false rejections and limited false acceptances; this finding suggests that this set of voice features is highly speaker-dependent and therefore forensically useful. Mean ED for MZ pairs lies between the average ED for SS comparisons and DS comparisons, as expected according to the literature on twin voices. Specific cases of MZ speakers with very high ED (i.e. strong dissimilarity) are discussed in the context of sociophonetic and twin studies. A preliminary simplification of the Vocal Profile Analysis (VPA) Scheme is proposed, which enables the quantification of voice quality features in the perceptual assessment of speaker similarity, and allows for the calculation of perceptual-acoustic correlations. The adequacy of z-score normalization for this study is also discussed, as well as the relevance of heat maps for detecting the so-called phantoms in recent approaches to the biometric menagerie. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Deep Learning in Label-free Cell Classification

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

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Deep Learning in Label-free Cell Classification

DOE PAGES

Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; ...

2016-03-15

Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individualmore » cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. In conclusion, this system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.« less

Fault Diagnosis for Rolling Bearings under Variable Conditions Based on Visual Cognition

PubMed Central

Cheng, Yujie; Zhou, Bo; Lu, Chen; Yang, Chao

2017-01-01

Fault diagnosis for rolling bearings has attracted increasing attention in recent years. However, few studies have focused on fault diagnosis for rolling bearings under variable conditions. This paper introduces a fault diagnosis method for rolling bearings under variable conditions based on visual cognition. The proposed method includes the following steps. First, the vibration signal data are transformed into a recurrence plot (RP), which is a two-dimensional image. Then, inspired by the visual invariance characteristic of the human visual system (HVS), we utilize speed up robust feature to extract fault features from the two-dimensional RP and generate a 64-dimensional feature vector, which is invariant to image translation, rotation, scaling variation, etc. Third, based on the manifold perception characteristic of HVS, isometric mapping, a manifold learning method that can reflect the intrinsic manifold embedded in the high-dimensional space, is employed to obtain a low-dimensional feature vector. Finally, a classical classification method, support vector machine, is utilized to realize fault diagnosis. Verification data were collected from Case Western Reserve University Bearing Data Center, and the experimental result indicates that the proposed fault diagnosis method based on visual cognition is highly effective for rolling bearings under variable conditions, thus providing a promising approach from the cognitive computing field. PMID:28772943

Ion Mobility-Mass Spectrometry Analysis of Serum N-linked Glycans from Esophageal Adenocarcinoma Phenotypes

PubMed Central

Gaye, M. M.; Valentine, S. J.; Hu, Y.; Mirjankar, N.; Hammoud, Z. T.; Mechref, Y.; Lavine, B. K.; Clemmer, D. E.

2012-01-01

Three disease phenotypes, Barrett’s esophagus (BE), high-grade dysplasia (HGD), esophageal adenocarcinoma (EAC), and a set of normal control (NC) serum samples are examined using a combination of ion mobility spectrometry (IMS), mass spectrometry (MS) and principal component analysis (PCA) techniques. Samples from a total of 136 individuals were examined, including: 7 characterized as BE, 12 as HGD, 56 as EAC and 61 as NC. In typical datasets it was possible to assign ~20 to 30 glycan ions based on MS measurements. Ion mobility distributions for these ions show multiple features. In some cases, such as the [S1H5N4+3Na]3+ and [S1F1H5N4+3Na]3+ glycan ions, the ratio of intensities of high-mobility features to low-mobility features vary significantly for different groups. The degree to which such variations in mobility profiles can be used to distinguish phenotypes is evaluated for eleven N-linked glycan ions. An outlier analysis on each sample class followed by an unsupervised PCA using a genetic algorithm for pattern recognition reveals that EAC samples are separated from NC samples based on 46 features originating from the 11-glycan composite IMS distribution. PMID:23126309

Prediction of human disease-associated phosphorylation sites with combined feature selection approach and support vector machine.

PubMed

Xu, Xiaoyi; Li, Ao; Wang, Minghui

2015-08-01

Phosphorylation is a crucial post-translational modification, which regulates almost all cellular processes in life. It has long been recognised that protein phosphorylation has close relationship with diseases, and therefore many researches are undertaken to predict phosphorylation sites for disease treatment and drug design. However, despite the success achieved by these approaches, no method focuses on disease-associated phosphorylation sites prediction. Herein, for the first time the authors propose a novel approach that is specially designed to identify associations between phosphorylation sites and human diseases. To take full advantage of local sequence information, a combined feature selection method-based support vector machine (CFS-SVM) that incorporates minimum-redundancy-maximum-relevance filtering process and forward feature selection process is developed. Performance evaluation shows that CFS-SVM is significantly better than the widely used classifiers including Bayesian decision theory, k nearest neighbour and random forest. With the extremely high specificity of 99%, CFS-SVM can still achieve a high sensitivity. Besides, tests on extra data confirm the effectiveness and general applicability of CFS-SVM approach on a variety of diseases. Finally, the analysis of selected features and corresponding kinases also help the understanding of the potential mechanism of disease-phosphorylation relationships and guide further experimental validations.

Assessing sufficiency of thermal riverscapes for resilient ...

EPA Pesticide Factsheets

Resilient salmon populations require river networks that provide water temperature regimes sufficient to support a diversity of salmonid life histories across space and time. Efforts to protect, enhance and restore watershed thermal regimes for salmon may target specific locations and features within stream networks hypothesized to provide disproportionately high-value functional resilience to salmon populations. These include relatively small-scale features such as thermal refuges, and larger-scale features such as entire watersheds or aquifers that support thermal regimes buffered from local climatic conditions. Quantifying the value of both small and large scale thermal features to salmon populations has been challenged by both the difficulty of mapping thermal regimes at sufficient spatial and temporal resolutions, and integrating thermal regimes into population models. We attempt to address these challenges by using newly-available datasets and modeling approaches to link thermal regimes to salmon populations across scales. We will describe an individual-based modeling approach for assessing sufficiency of thermal refuges for migrating salmon and steelhead in large rivers, as well as a population modeling approach for assessing large-scale climate refugia for salmon in the Pacific Northwest. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

Dental management of patient with Williams Syndrome - A case report.

PubMed

Wong, Daniel; Ramachandra, Srinivas Sulugodu; Singh, Ashish Kumar

2015-01-01

Williams syndrome is a multisystemic rare genetic disorder caused by deletion of 26-28 genes in the long arm of chromosome 7. It is characterized by developmental and physical abnormalities including congenital cardiovascular abnormalities, mental retardation, neurological features, growth deficiency, genitourinary manifestations, gastrointestinal problems, musculoskeletal problems, unique behavioral characteristics, and dental problems. Dental abnormalities include malocclusion, hypodontia, malformed teeth, taurodontism, pulp stones, increased space between teeth, enamel hypoplasia, and high prevalence of dental caries. Authors report a 17-year-old female patient with underlying Williams syndrome. Oral features and problems seen in the patient are listed. Malocclusion and screwdriver shaped teeth were noticed. Generalized widening of the periodontal ligament space with vital teeth was seen. This finding has not been reported in cases of Williams syndrome earlier. Precautions taken during dental treatment in patients with Williams syndrome are also discussed.

The evolution of heart gene delivery vectors.

PubMed

Wasala, Nalinda B; Shin, Jin-Hong; Duan, Dongsheng

2011-10-01

Gene therapy holds promise for treating numerous heart diseases. A key premise for the success of cardiac gene therapy is the development of powerful gene transfer vehicles that can achieve highly efficient and persistent gene transfer specifically in the heart. Other features of an ideal vector include negligible toxicity, minimal immunogenicity and easy manufacturing. Rapid progress in the fields of molecular biology and virology has offered great opportunities to engineer various genetic materials for heart gene delivery. Several nonviral vectors (e.g. naked plasmids, plasmid lipid/polymer complexes and oligonucleotides) have been tested. Commonly used viral vectors include lentivirus, adenovirus and adeno-associated virus. Among these, adeno-associated virus has shown many attractive features for pre-clinical experimentation in animal models of heart diseases. We review the history and evolution of these vectors for heart gene transfer. Copyright © 2011 John Wiley & Sons, Ltd.

The evolution of heart gene delivery vectors

PubMed Central

Wasala, Nalinda B.; Shin, Jin-Hong; Duan, Dongsheng

2012-01-01

Gene therapy holds promise for treating numerous heart diseases. A key premise for the success of cardiac gene therapy is the development of powerful gene transfer vehicles that can achieve highly efficient and persistent gene transfer specifically in the heart. Other features of an ideal vector include negligible toxicity, minimal immunogenicity and easy manufacturing. Rapid progress in the fields of molecular biology and virology has offered great opportunities to engineer various genetic materials for heart gene delivery. Several nonviral vectors (e.g. naked plasmids, plasmid lipid/polymer complexes and oligonucleotides) have been tested. Commonly used viral vectors include lentivirus, adenovirus and adeno-associated virus. Among these, adeno-associated virus has shown many attractive features for pre-clinical experimentation in animal models of heart diseases. We review the history and evolution of these vectors for heart gene transfer. PMID:21837689

Region 9 NPL Sites (Superfund Sites 2013)

EPA Pesticide Factsheets

NPL site POINT locations for the US EPA Region 9. NPL (National Priorities List) sites are hazardous waste sites that are eligible for extensive long-term cleanup under the Superfund program. Eligibility is determined by a scoring method called Hazard Ranking System. Sites with high scores are listed on the NPL. The majority of the locations are derived from polygon centroids of digitized site boundaries. The remaining locations were generated from address geocoding and digitizing. Area covered by this data set include Arizona, California, Nevada, Hawaii, Guam, American Samoa, Northern Marianas and Trust Territories. Attributes include NPL status codes, NPL industry type codes and environmental indicators. Related table, NPL_Contaminants contains information about contaminated media types and chemicals. This is a one-to-many relate and can be related to the feature class using the relationship classes under the Feature Data Set ENVIRO_CONTAMINANT.

Patterns of Walkability, Transit, and Recreation Environment for Physical Activity.

PubMed

Adams, Marc A; Todd, Michael; Kurka, Jonathan; Conway, Terry L; Cain, Kelli L; Frank, Lawrence D; Sallis, James F

2015-12-01

Diverse combinations of built environment (BE) features for physical activity (PA) are understudied. This study explored whether patterns of GIS-derived BE features explained objective and self-reported PA, sedentary behavior, and BMI. Neighborhood Quality of Life Study participants (N=2,199, aged 20-65 years, 48.2% female, 26% ethnic minority) were sampled in 2001-2005 from Seattle / King County WA and Baltimore MD / Washington DC regions. Their addresses were geocoded to compute net residential density, land use mix, retail floor area ratio, intersection density, public transit, and public park and private recreation facility densities using a 1-km network buffer. Latent profile analyses (LPAs) were estimated from these variables. Multilevel regression models compared profiles on accelerometer-measured moderate to vigorous PA (MVPA) and self-reported PA, adjusting for covariates and clustering. Analyses were conducted in 2013-2014. Seattle region LPAs yielded four profiles, including low walkability/transit/recreation (L-L-L); mean walkability/transit/recreation (M-M-M); moderately high walkability/transit/recreation (MH-MH-MH); and high walkability/transit/recreation (H-HH). All measures were higher in the HHH than the LLL profile (difference of 17.1 minutes/day for MVPA, 146.5 minutes/week for walking for transportation, 58.2 minutes/week for leisure-time PA, and 2.2 BMI points; all p<0.05). Baltimore region LPAs yielded four profiles, including L-L-L; M-M-M; high land use mix, transit, and recreation (HLU-HT-HRA); and high intersection density, high retail floor area ratio (HID-HRFAR). HLU-HT-HRA and L-L-L differed by 12.3 MVPA minutes/day; HID-HRFAR and L-L-L differed by 157.4 minutes/week for walking for transportation (all p<0.05). Patterns of environmental features explain greater differences in adults' PA than the four-component walkability index. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

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.

Evaluation of Sexual Communication Message Strategies

PubMed Central

2011-01-01

Parent-child communication about sex is an important proximal reproductive health outcome. But while campaigns to promote it such as the Parents Speak Up National Campaign (PSUNC) have been effective, little is known about how messages influence parental cognitions and behavior. This study examines which message features explain responses to sexual communication messages. We content analyzed 4 PSUNC ads to identify specific, measurable message and advertising execution features. We then develop quantitative measures of those features, including message strategies, marketing strategies, and voice and other stylistic features, and merged the resulting data into a dataset drawn from a national media tracking survey of the campaign. Finally, we conducted multivariable logistic regression models to identify relationships between message content and ad reactions/receptivity, and between ad reactions/receptivity and parents' cognitions related to sexual communication included in the campaign's conceptual model. We found that overall parents were highly receptive to the PSUNC ads. We did not find significant associations between message content and ad reactions/receptivity. However, we found that reactions/receptivity to specific PSUNC ads were associated with increased norms, self-efficacy, short- and long-term expectations about parent-child sexual communication, as theorized in the conceptual model. This study extends previous research and methods to analyze message content and reactions/receptivity. The results confirm and extend previous PSUNC campaign evaluation and provide further evidence for the conceptual model. Future research should examine additional message content features and the effects of reactions/receptivity. PMID:21599875

White perovskite based lighting devices.

PubMed

Bidikoudi, M; Fresta, E; Costa, R D

2018-06-28

Hybrid organic-inorganic and all-inorganic metal halide perovskites have been one of the most intensively studied materials during the last few years. In particular, research focusing on understanding how to tune the photoluminescence features and to apply perovskites to optoelectronic applications has led to a myriad of new materials featuring high photoluminescence quantum yields covering the whole visible range, as well as devices with remarkable performances. Having already established their successful incorporation in highly efficient solar cells, the next step is to tackle the challenges in solid-state lighting (SSL) devices. Here, the most prominent is the preparation of white-emitting devices. Herein, we have provided a comprehensive view of the route towards perovskite white lighting devices, including thin film light-emitting diodes (PeLEDs) and hybrid LEDs (HLEDs), using perovskite based color down-converting coatings. While synthesis and photoluminescence features are briefly discussed, we focus on highlighting the major achievements and limitations in white devices. Overall, we expect that this review will provide the reader a general overview of the current state of perovskite white SSL, paving the way towards new breakthroughs in the near future.

Line identifications, line strengths, and continuum flux measurements in the ultraviolet spectrum of Arcturus

NASA Technical Reports Server (NTRS)

Carpenter, K. G.; Wing, R. F.; Stencel, R. E.

1985-01-01

The ultraviolet spectrum of Arcturus has been observed at high resolution with the IUE satellite. Line identifications, mean absolute 'continuum' flux measurements, integrated absolute emission-line fluxes, and measurements of selected absorption line strengths are presented for the 2250-2930 A region. In the 1150-2000 A region, identifications are given primarily on the basis of low-resolution spectra. Chromospheric emission lines have been identified with low-excitation species including H I, C I, C II, O I, Mg I, Mg II, Al II, Si I, Si II, S I, and Fe II; there is no evidence for lines of C IV, N V, or other species requiring high temperatures. A search for molecular absorption features in the 2500-2930 A interval has led to several tentative identifications, but only OH could be established as definitely present. Iron lines strongly dominate the identifications in the 2250-2930 A region, Fe II accounting for about 86 percent of the emission features and Fe I for 43 percent of the identified absorption features.

The external morphology of adult female Egrasilus labracis as shown using hexamethyldisilazane treated, uncoated specimens for scanning electron microscopy.

PubMed

Murray, Harry M; Hill, Stephen J; Ang, Keng P

2016-07-01

The description and application of a modified Scanning Electron Microscope preparation technique using hexamethyldisilazane for small parasitic copepods was demonstrated though a high resolution depiction of individuals of Ergasilus labracis sampled from three spined stickleback (Gasterosteus aculeatus) in Bay D'Espoir, Newfoundland during summer 2015 and from archival samples retrieved from Atlantic salmon par (Salmo salar) stored at the Atlantic reference centre, St. Andrews, New Brunswick. The specimens were very well preserved showing high quality detail of important features and verifying those previously described using light microscopy by Hogans. Additionally the technique allowed excellent in situ demonstrations of mouth parts, swimming legs, and unusual and previously undescribed features of the second antenna including prominent striations and pore-like structures found to define the claw. It is thought that this technique will become a quick and efficient tool for describing important taxonomic features of small parasitic copepods like E. labracis or other similar small aquatic organisms. Microsc. Res. Tech. 79:657-663, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Star formation and ISM morphology in tidally induced spiral structures

NASA Astrophysics Data System (ADS)

Pettitt, Alex R.; Tasker, Elizabeth J.; Wadsley, James W.; Keller, Ben W.; Benincasa, Samantha M.

2017-07-01

Tidal encounters are believed to be one of the key drivers of galactic spiral structure in the Universe. Such spirals are expected to produce different morphological and kinematic features compared to density wave and dynamic spiral arms. In this work, we present high-resolution simulations of a tidal encounter of a small mass companion with a disc galaxy. Included are the effects of gas cooling and heating, star formation and stellar feedback. The structure of the perturbed disc differs greatly from the isolated galaxy, showing clear spiral features that act as sites of new star formation, and displaying interarm spurs. The two arms of the galaxy, the bridge and tail, appear to behave differently; with different star formation histories and structure. Specific attention is focused on offsets between gas and stellar spiral features which can be directly compared to observations. We find that some offsets do exist between different media, with gaseous arms appearing mostly on the convex side of the stellar arms, though the exact locations appear highly time dependent. These results further highlight the differences between tidal spirals and other theories of arm structure.

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.

An Improved Image Matching Method Based on Surf Algorithm

NASA Astrophysics Data System (ADS)

Chen, S. J.; Zheng, S. Z.; Xu, Z. G.; Guo, C. C.; Ma, X. L.

2018-04-01

Many state-of-the-art image matching methods, based on the feature matching, have been widely studied in the remote sensing field. These methods of feature matching which get highly operating efficiency, have a disadvantage of low accuracy and robustness. This paper proposes an improved image matching method which based on the SURF algorithm. The proposed method introduces color invariant transformation, information entropy theory and a series of constraint conditions to increase feature points detection and matching accuracy. First, the model of color invariant transformation is introduced for two matching images aiming at obtaining more color information during the matching process and information entropy theory is used to obtain the most information of two matching images. Then SURF algorithm is applied to detect and describe points from the images. Finally, constraint conditions which including Delaunay triangulation construction, similarity function and projective invariant are employed to eliminate the mismatches so as to improve matching precision. The proposed method has been validated on the remote sensing images and the result benefits from its high precision and robustness.

Atmospheric form drag over Arctic sea ice derived from high-resolution IceBridge elevation data

NASA Astrophysics Data System (ADS)

Petty, A.; Tsamados, M.; Kurtz, N. T.

2016-02-01

Here we present a detailed analysis of atmospheric form drag over Arctic sea ice, using high resolution, three-dimensional surface elevation data from the NASA Operation IceBridge Airborne Topographic Mapper (ATM) laser altimeter. Surface features in the sea ice cover are detected using a novel feature-picking algorithm. We derive information regarding the height, spacing and orientation of unique surface features from 2009-2014 across both first-year and multiyear ice regimes. The topography results are used to explicitly calculate atmospheric form drag coefficients; utilizing existing form drag parameterizations. The atmospheric form drag coefficients show strong regional variability, mainly due to variability in ice type/age. The transition from a perennial to a seasonal ice cover therefore suggest a decrease in the atmospheric form drag coefficients over Arctic sea ice in recent decades. These results are also being used to calibrate a recent form drag parameterization scheme included in the sea ice model CICE, to improve the representation of form drag over Arctic sea ice in global climate models.

A virtual microscope for academic medical education: the pate project.

PubMed

Brochhausen, Christoph; Winther, Hinrich B; Hundt, Christian; Schmitt, Volker H; Schömer, Elmar; Kirkpatrick, C James

2015-05-11

Whole-slide imaging (WSI) has become more prominent and continues to gain in importance in student teaching. Applications with different scope have been developed. Many of these applications have either technical or design shortcomings. To design a survey to determine student expectations of WSI applications for teaching histological and pathological diagnosis. To develop a new WSI application based on the findings of the survey. A total of 216 students were questioned about their experiences and expectations of WSI applications, as well as favorable and undesired features. The survey included 14 multiple choice and two essay questions. Based on the survey, we developed a new WSI application called Pate utilizing open source technologies. The survey sample included 216 students-62.0% (134) women and 36.1% (78) men. Out of 216 students, 4 (1.9%) did not disclose their gender. The best-known preexisting WSI applications included Mainzer Histo Maps (199/216, 92.1%), Histoweb Tübingen (16/216, 7.4%), and Histonet Ulm (8/216, 3.7%). Desired features for the students were latitude in the slides (190/216, 88.0%), histological (191/216, 88.4%) and pathological (186/216, 86.1%) annotations, points of interest (181/216, 83.8%), background information (146/216, 67.6%), and auxiliary informational texts (113/216, 52.3%). By contrast, a discussion forum was far less important (9/216, 4.2%) for the students. The survey revealed that the students appreciate a rich feature set, including WSI functionality, points of interest, auxiliary informational texts, and annotations. The development of Pate was significantly influenced by the findings of the survey. Although Pate currently has some issues with the Zoomify file format, it could be shown that Web technologies are capable of providing a high-performance WSI experience, as well as a rich feature set.

A hierarchy for modeling high speed propulsion systems

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Deabreu, Alex

1991-01-01

General research efforts on reduced order propulsion models for control systems design are overviewed. Methods for modeling high speed propulsion systems are discussed including internal flow propulsion systems that do not contain rotating machinery, such as inlets, ramjets, and scramjets. The discussion is separated into four areas: (1) computational fluid dynamics models for the entire nonlinear system or high order nonlinear models; (2) high order linearized models derived from fundamental physics; (3) low order linear models obtained from the other high order models; and (4) low order nonlinear models (order here refers to the number of dynamic states). Included in the discussion are any special considerations based on the relevant control system designs. The methods discussed are for the quasi-one-dimensional Euler equations of gasdynamic flow. The essential nonlinear features represented are large amplitude nonlinear waves, including moving normal shocks, hammershocks, simple subsonic combustion via heat addition, temperature dependent gases, detonations, and thermal choking. The report also contains a comprehensive list of papers and theses generated by this grant.

EEG-based Affect and Workload Recognition in a Virtual Driving Environment for ASD Intervention

PubMed Central

Wade, Joshua W.; Key, Alexandra P.; Warren, Zachary E.; Sarkar, Nilanjan

2017-01-01

objective To build group-level classification models capable of recognizing affective states and mental workload of individuals with autism spectrum disorder (ASD) during driving skill training. Methods Twenty adolescents with ASD participated in a six-session virtual reality driving simulator based experiment, during which their electroencephalogram (EEG) data were recorded alongside driving events and a therapist’s rating of their affective states and mental workload. Five feature generation approaches including statistical features, fractal dimension features, higher order crossings (HOC)-based features, power features from frequency bands, and power features from bins (Δf = 2 Hz) were applied to extract relevant features. Individual differences were removed with a two-step feature calibration method. Finally, binary classification results based on the k-nearest neighbors algorithm and univariate feature selection method were evaluated by leave-one-subject-out nested cross-validation to compare feature types and identify discriminative features. Results The best classification results were achieved using power features from bins for engagement (0.95) and boredom (0.78), and HOC-based features for enjoyment (0.90), frustration (0.88), and workload (0.86). Conclusion Offline EEG-based group-level classification models are feasible for recognizing binary low and high intensity of affect and workload of individuals with ASD in the context of driving. However, while promising the applicability of the models in an online adaptive driving task requires further development. Significance The developed models provide a basis for an EEG-based passive brain computer interface system that has the potential to benefit individuals with ASD with an affect- and workload-based individualized driving skill training intervention. PMID:28422647

2-45 Micron Infrared Spectroscopy of Carbon-Rich Proto-Planetary Nebulae

NASA Technical Reports Server (NTRS)

Hrivnak, Bruce J.; Volk, Kevin; Kwok, Sun

2000-01-01

Infrared Space Observatory (ISO) 2-45 micron observations of seven proto-planetary nebulae (PPNs) and two other carbon-rich objects are presented. The unidentified emission features at 21 and 30 microns are detected in six sources, including four new detections of the 30 micron feature. This previously unresolved 30 micron feature is now resolved and found to consist of a broad feature peaking at 27.2 microns (the '30 micron' feature) and a narrower feature at 25.5 microns (the '26 micron' feature). This new 26 micron feature is detected in eight sources and is particularly strong in IRAS Z02229 + 6208 and 16594-4656. The unidentified infrared (UIR) emission features at 3.3, 6.2, 7.7, and 11.3 microns which are commonly observed in planetary nebulae and H II regions, are also seen in these PPNs. However, their strengths relative to the continuum plateaus at 8 and 12 microns are weaker than in planetary nebulae. The 6.9 micron feature, seen almost exclusively in PPNs, is strong. New millimeter CO and HCN observations were made; they support the carbon-rich nature of the objects and yield the expansion velocities of the gaseous envelopes. The spectral energy distributions of these PPNs were fitted with a radiative-transfer model, taking into account the emission features at 21, 26, and 30 microns. A significant fraction of the total energy output is emitted in these features: as high as 20% in the 30 micron feature and 8% in the 21 micron feature. The fact that so much energy is carried in these features suggests that the material responsible for these features must be made of abundant elements and most likely involves carbon. SiS, appears to be ruled out as the emitter of the 21 micron feature due to the absence of a predicted companion feature.

Virtual reality, augmented reality…I call it i-Reality.

PubMed

Grossmann, Rafael J

2015-01-01

The new term improved reality (i-Reality) is suggested to include virtual reality (VR) and augmented reality (AR). It refers to a real world that includes improved, enhanced and digitally created features that would offer an advantage on a particular occasion (i.e., a medical act). I-Reality may help us bridge the gap between the high demand for medical providers and the low supply of them by improving the interaction between providers and patients.

Current status and future prospects for enabling chemistry technology in the drug discovery process.

PubMed

Djuric, Stevan W; Hutchins, Charles W; Talaty, Nari N

2016-01-01

This review covers recent advances in the implementation of enabling chemistry technologies into the drug discovery process. Areas covered include parallel synthesis chemistry, high-throughput experimentation, automated synthesis and purification methods, flow chemistry methodology including photochemistry, electrochemistry, and the handling of "dangerous" reagents. Also featured are advances in the "computer-assisted drug design" area and the expanding application of novel mass spectrometry-based techniques to a wide range of drug discovery activities.