Multiple degree of freedom optical pattern recognition

NASA Technical Reports Server (NTRS)

Casasent, D.

1987-01-01

Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

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

De novo PHIP-predicted deleterious variants are associated with developmental delay, intellectual disability, obesity, and dysmorphic features.

PubMed

Webster, Emily; Cho, Megan T; Alexander, Nora; Desai, Sonal; Naidu, Sakkubai; Bekheirnia, Mir Reza; Lewis, Andrea; Retterer, Kyle; Juusola, Jane; Chung, Wendy K

2016-11-01

Using whole-exome sequencing, we have identified novel de novo heterozygous pleckstrin homology domain-interacting protein ( PHIP ) variants that are predicted to be deleterious, including a frameshift deletion, in two unrelated patients with common clinical features of developmental delay, intellectual disability, anxiety, hypotonia, poor balance, obesity, and dysmorphic features. A nonsense mutation in PHIP has previously been associated with similar clinical features. Patients with microdeletions of 6q14.1, including PHIP , have a similar phenotype of developmental delay, intellectual disability, hypotonia, and obesity, suggesting that the phenotype of our patients is a result of loss-of-function mutations. PHIP produces multiple protein products, such as PHIP1 (also known as DCAF14), PHIP, and NDRP. PHIP1 is one of the multiple substrate receptors of the proteolytic CUL4-DDB1 ubiquitin ligase complex. CUL4B deficiency has been associated with intellectual disability, central obesity, muscle wasting, and dysmorphic features. The overlapping phenotype associated with CUL4B deficiency suggests that PHIP mutations cause disease through disruption of the ubiquitin ligase pathway.

Breast cancer - one term, many entities?

PubMed

Bertos, Nicholas R; Park, Morag

2011-10-01

Breast cancer, rather than constituting a monolithic entity, comprises heterogeneous tumors with different clinical characteristics, disease courses, and responses to specific treatments. Tumor-intrinsic features, including classical histological and immunopathological classifications as well as more recently described molecular subtypes, separate breast tumors into multiple groups. Tumor-extrinsic features, including microenvironmental configuration, also have prognostic significance and further expand the list of tumor-defining variables. A better understanding of the features underlying heterogeneity, as well as of the mechanisms and consequences of their interactions, is essential to improve targeting of existing therapies and to develop novel agents addressing specific combinations of features.

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.

Sensor feature fusion for detecting buried objects

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

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

1993-04-01

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

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.

LC-IMS-MS Feature Finder. Detecting Multidimensional Liquid Chromatography, Ion Mobility, and Mass Spectrometry Features in Complex Datasets

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

Crowell, Kevin L.; Slysz, Gordon W.; Baker, Erin Shammel

2013-09-05

We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time, and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension.

Feature extraction from multiple data sources using genetic programming

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Brumby, Steven P.; Pope, Paul A.; Eads, Damian R.; Esch-Mosher, Diana M.; Galassi, Mark C.; Harvey, Neal R.; McCulloch, Hersey D.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Bloch, Jeffrey J.; David, Nancy A.

2002-08-01

Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

A primitive study of voxel feature generation by multiple stacked denoising autoencoders for detecting cerebral aneurysms on MRA

NASA Astrophysics Data System (ADS)

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu; Ohtomo, Kuni

2016-03-01

The purpose of this study is to evaluate the feasibility of a novel feature generation, which is based on multiple deep neural networks (DNNs) with boosting, for computer-assisted detection (CADe). It is hard and time-consuming to optimize the hyperparameters for DNNs such as stacked denoising autoencoder (SdA). The proposed method allows using SdA based features without the burden of the hyperparameter setting. The proposed method was evaluated by an application for detecting cerebral aneurysms on magnetic resonance angiogram (MRA). A baseline CADe process included four components; scaling, candidate area limitation, candidate detection, and candidate classification. Proposed feature generation method was applied to extract the optimal features for candidate classification. Proposed method only required setting range of the hyperparameters for SdA. The optimal feature set was selected from a large quantity of SdA based features by multiple SdAs, each of which was trained using different hyperparameter set. The feature selection was operated through ada-boost ensemble learning method. Training of the baseline CADe process and proposed feature generation were operated with 200 MRA cases, and the evaluation was performed with 100 MRA cases. Proposed method successfully provided SdA based features just setting the range of some hyperparameters for SdA. The CADe process by using both previous voxel features and SdA based features had the best performance with 0.838 of an area under ROC curve and 0.312 of ANODE score. The results showed that proposed method was effective in the application for detecting cerebral aneurysms on MRA.

Multimodal optical imaging system for in vivo investigation of cerebral oxygen delivery and energy metabolism

PubMed Central

Yaseen, Mohammad A.; Srinivasan, Vivek J.; Gorczynska, Iwona; Fujimoto, James G.; Boas, David A.; Sakadžić, Sava

2015-01-01

Improving our understanding of brain function requires novel tools to observe multiple physiological parameters with high resolution in vivo. We have developed a multimodal imaging system for investigating multiple facets of cerebral blood flow and metabolism in small animals. The system was custom designed and features multiple optical imaging capabilities, including 2-photon and confocal lifetime microscopy, optical coherence tomography, laser speckle imaging, and optical intrinsic signal imaging. Here, we provide details of the system’s design and present in vivo observations of multiple metrics of cerebral oxygen delivery and energy metabolism, including oxygen partial pressure, microvascular blood flow, and NADH autofluorescence. PMID:26713212

Context-based automated defect classification system using multiple morphological masks

DOEpatents

Gleason, Shaun S.; Hunt, Martin A.; Sari-Sarraf, Hamed

2002-01-01

Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact. At the heart of the system is a knowledge database that stores and distributes historical semiconductor wafer and defect data to guide the feature extraction and classification processes. In summary, this invention takes as its input a set of images containing semiconductor defect information, and generates as its output a classification for the defect that describes not only the defect itself, but also the location of that defect with respect to the semiconductor process layers.

Control of Visually Guided Saccades in Multiple Sclerosis: Disruption to Higher-Order Processes

ERIC Educational Resources Information Center

Fielding, Joanne; Kilpatrick, Trevor; Millist, Lynette; White, Owen

2009-01-01

Ocular motor abnormalities are a common feature of multiple sclerosis (MS), with more salient deficits reflecting tissue damage within brainstem and cerebellar circuits. However, MS may also result in disruption to higher level or cognitive control processes governing eye movement, including attentional processes that enhance the neural processing…

Conflict Resolution and Peace Education: Transformations across Disciplines

ERIC Educational Resources Information Center

Carter, Candice C., Ed.

2012-01-01

Peace education includes lessons about conflict sources, transformation and resolution. While featuring field-based examples in multiple disciplines, including political science, anthropology, communication, psychology, sociology, counseling, law and teacher training, this book presents real cases of conflict work. Explained are concepts…

The use of mobile applications to support self-management for people with asthma: a systematic review of controlled studies to identify features associated with clinical effectiveness and adherence.

PubMed

Hui, Chi Yan; Walton, Robert; McKinstry, Brian; Jackson, Tracy; Parker, Richard; Pinnock, Hilary

2017-05-01

Telehealth is promoted as a strategy to support self-management of long-term conditions. The aim of this systematic review is to identify which information and communication technology features implemented in mobile apps to support asthma self-management are associated with adoption, adherence to usage, and clinical effectiveness. We systematically searched 9 databases, scanned reference lists, and undertook manual searches (January 2000 to April 2016). We include randomized controlled trials (RCTs) and quasiexperimental studies with adults. All eligible papers were assessed for quality, and we extracted data on the features included, health-related outcomes (asthma control, exacerbation rate), process/intermediate outcomes (adherence to monitoring or treatment, self-efficacy), and level of adoption of and adherence to use of technology. Meta-analysis and narrative synthesis were used. We included 12 RCTs employing a range of technologies. A meta-analysis (n = 3) showed improved asthma control (mean difference -0.25 [95% CI, -0.37 to -0.12]). Included studies incorporated 10 features grouped into 7 categories (education, monitoring/electronic diary, action plans, medication reminders/prompts, facilitating professional support, raising patient awareness of asthma control, and decision support for professionals). The most successful interventions included multiple features, but effects on health-related outcomes were inconsistent. No studies explicitly reported adoption of and adherence to the technology system. Meta-analysis of data from 3 trials showed improved asthma control, though overall the clinical effectiveness of apps, typically incorporating multiple features, varied. Further studies are needed to identify the features that are associated with adoption of and adherence to use of the mobile app and those that improve health outcomes. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Time dependent emission line profiles in the radially streaming particle model of Seyfert galaxy nuclei and quasi-stellar objects

NASA Technical Reports Server (NTRS)

Hubbard, R.

1974-01-01

The radially-streaming particle model for broad quasar and Seyfert galaxy emission features is modified to include sources of time dependence. The results are suggestive of reported observations of multiple components, variability, and transient features in the wings of Seyfert and quasi-stellar emission lines.

Multiple Paths to Mathematics Practice in Al-Kashi's Key to Arithmetic

NASA Astrophysics Data System (ADS)

Taani, Osama

2014-01-01

In this paper, I discuss one of the most distinguishing features of Jamshid al-Kashi's pedagogy from his Key to Arithmetic, a well-known Arabic mathematics textbook from the fifteenth century. This feature is the multiple paths that he includes to find a desired result. In the first section light is shed on al-Kashi's life and his contributions to mathematics and astronomy. Section 2 starts with a brief discussion of the contents and pedagogy of the Key to Arithmetic. Al-Kashi's multiple approaches are discussed through four different examples of his versatility in presenting a topic from multiple perspectives. These examples are multiple definitions, multiple algorithms, multiple formulas, and multiple methods for solving word problems. Section 3 is devoted to some benefits that can be gained by implementing al-Kashi's multiple paths approach in modern curricula. For this discussion, examples from two teaching modules taken from the Key to Arithmetic and implemented in Pre-Calculus and mathematics courses for preservice teachers are discussed. Also, the conclusions are supported by some aspects of these modules. This paper is an attempt to help mathematics educators explore more benefits from reading from original sources.

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

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

2002-08-01

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

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.

Improved classification accuracy by feature extraction using genetic algorithms

NASA Astrophysics Data System (ADS)

Patriarche, Julia; Manduca, Armando; Erickson, Bradley J.

2003-05-01

A feature extraction algorithm has been developed for the purposes of improving classification accuracy. The algorithm uses a genetic algorithm / hill-climber hybrid to generate a set of linearly recombined features, which may be of reduced dimensionality compared with the original set. The genetic algorithm performs the global exploration, and a hill climber explores local neighborhoods. Hybridizing the genetic algorithm with a hill climber improves both the rate of convergence, and the final overall cost function value; it also reduces the sensitivity of the genetic algorithm to parameter selection. The genetic algorithm includes the operators: crossover, mutation, and deletion / reactivation - the last of these effects dimensionality reduction. The feature extractor is supervised, and is capable of deriving a separate feature space for each tissue (which are reintegrated during classification). A non-anatomical digital phantom was developed as a gold standard for testing purposes. In tests with the phantom, and with images of multiple sclerosis patients, classification with feature extractor derived features yielded lower error rates than using standard pulse sequences, and with features derived using principal components analysis. Using the multiple sclerosis patient data, the algorithm resulted in a mean 31% reduction in classification error of pure tissues.

Characterizing facial features in individuals with craniofacial microsomia: A systematic approach for clinical research.

PubMed

Heike, Carrie L; Wallace, Erin; Speltz, Matthew L; Siebold, Babette; Werler, Martha M; Hing, Anne V; Birgfeld, Craig B; Collett, Brent R; Leroux, Brian G; Luquetti, Daniela V

2016-11-01

Craniofacial microsomia (CFM) is a congenital condition with wide phenotypic variability, including hypoplasia of the mandible and external ear. We assembled a cohort of children with facial features within the CFM spectrum and children without known craniofacial anomalies. We sought to develop a standardized approach to assess and describe the facial characteristics of the study cohort, using multiple sources of information gathered over the course of this longitudinal study and to create case subgroups with shared phenotypic features. Participants were enrolled between 1996 and 2002. We classified the facial phenotype from photographs, ratings using a modified version of the Orbital, Ear, Mandible, Nerve, Soft tissue (OMENS) pictorial system, data from medical record abstraction, and health history questionnaires. The participant sample included 142 cases and 290 controls. The average age was 13.5 years (standard deviation, 1.3 years; range, 11.1-17.1 years). Sixty-one percent of cases were male, 74% were white non-Hispanic. Among cases, the most common features were microtia (66%) and mandibular hypoplasia (50%). Case subgroups with meaningful group definitions included: (1) microtia without other CFM-related features (n = 24), (2) microtia with mandibular hypoplasia (n = 46), (3) other combinations of CFM- related facial features (n = 51), and (4) atypical features (n = 21). We developed a standardized approach for integrating multiple data sources to phenotype individuals with CFM, and created subgroups based on clinically-meaningful, shared characteristics. We hope that this system can be used to explore associations between phenotype and clinical outcomes of children with CFM and to identify the etiology of CFM. Birth Defects Research (Part A) 106:915-926, 2016.© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Quantifying site-specific physical heterogeneity within an estuarine seascape

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

Additivity of Feature-Based and Symmetry-Based Grouping Effects in Multiple Object Tracking

PubMed Central

Wang, Chundi; Zhang, Xuemin; Li, Yongna; Lyu, Chuang

2016-01-01

Multiple object tracking (MOT) is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the “laws of perceptual organization” proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape) among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. “Additive effect” refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The “where” and “what” pathways might have played an important role in the additive grouping effect. PMID:27199875

Life Span as the Measure of Performance and Learning in a Business Gaming Simulation

ERIC Educational Resources Information Center

Thavikulwat, Precha

2012-01-01

This study applies the learning curve method of measuring learning to participants of a computer-assisted business gaming simulation that includes a multiple-life-cycle feature. The study involved 249 participants. It verified the workability of the feature and estimated the participants' rate of learning at 17.4% for every doubling of experience.…

Chondrodysplasia with multiple dislocations: comprehensive study of a series of 30 cases.

PubMed

Ranza, E; Huber, C; Levin, N; Baujat, G; Bole-Feysot, C; Nitschke, P; Masson, C; Alanay, Y; Al-Gazali, L; Bitoun, P; Boute, O; Campeau, P; Coubes, C; McEntagart, M; Elcioglu, N; Faivre, L; Gezdirici, A; Johnson, D; Mihci, E; Nur, B G; Perrin, L; Quelin, C; Terhal, P; Tuysuz, B; Cormier-Daire, V

2017-06-01

The group of chondrodysplasia with multiple dislocations includes several entities, characterized by short stature, dislocation of large joints, hand and/or vertebral anomalies. Other features, such as epiphyseal or metaphyseal changes, cleft palate, intellectual disability are also often part of the phenotype. In addition, several conditions with overlapping features are related to this group and broaden the spectrum. The majority of these disorders have been linked to pathogenic variants in genes encoding proteins implicated in the synthesis or sulfation of proteoglycans (PG). In a series of 30 patients with multiple dislocations, we have performed exome sequencing and subsequent targeted analysis of 15 genes, implicated in chondrodysplasia with multiple dislocations, and related conditions. We have identified causative pathogenic variants in 60% of patients (18/30); when a clinical diagnosis was suspected, this was molecularly confirmed in 53% of cases. Forty percent of patients remain without molecular etiology. Pathogenic variants in genes implicated in PG synthesis are of major importance in chondrodysplasia with multiple dislocations and related conditions. The combination of hand features, growth failure severity, radiological aspects of long bones and of vertebrae allowed discrimination among the different conditions. We propose key diagnostic clues to the clinician. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Jet engine nozzle exit configurations and associated systems and methods

NASA Technical Reports Server (NTRS)

Mengle, Vinod G. (Inventor)

2011-01-01

Nozzle exit configurations and associated systems and methods are disclosed. An aircraft system in accordance with one embodiment includes a jet engine exhaust nozzle having an internal flow surface and an exit aperture, with the exit aperture having a perimeter that includes multiple projections extending in an aft direction. Aft portions of individual neighboring projections are spaced apart from each other by a gap, and a geometric feature of the multiple can change in a monotonic manner along at least a portion of the perimeter.

Jet Engine Nozzle Exit Configurations and Associated Systems and Methods

NASA Technical Reports Server (NTRS)

Mengle, Vinod G. (Inventor)

2013-01-01

Nozzle exit configurations and associated systems and methods are disclosed. An aircraft system in accordance with one embodiment includes a jet engine exhaust nozzle having an internal flow surface and an exit aperture, with the exit aperture having a perimeter that includes multiple projections extending in an aft direction. Aft portions of individual neighboring projections are spaced apart from each other by a gap, and a geometric feature of the multiple can change in a monotonic manner along at least a portion of the perimeter.

Registration and Fusion of Multiple Source Remotely Sensed Image Data

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline

2004-01-01

Earth and Space Science often involve the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, global coverage of an area at multiple resolutions, map updating or validation of new instruments, as well as integration of data provided by multiple instruments carried on multiple platforms, e.g. in spacecraft constellations or fleets of planetary rovers. Our focus is on developing methods to perform fast, accurate and automatic image registration and fusion. General methods for automatic image registration are being reviewed and evaluated. Various choices for feature extraction, feature matching and similarity measurements are being compared, including wavelet-based algorithms, mutual information and statistically robust techniques. Our work also involves studies related to image fusion and investigates dimension reduction and co-kriging for application-dependent fusion. All methods are being tested using several multi-sensor datasets, acquired at EOS Core Sites, and including multiple sensors such as IKONOS, Landsat-7/ETM+, EO1/ALI and Hyperion, MODIS, and SeaWIFS instruments. Issues related to the coregistration of data from the same platform (i.e., AIRS and MODIS from Aqua) or from several platforms of the A-train (i.e., MLS, HIRDLS, OMI from Aura with AIRS and MODIS from Terra and Aqua) will also be considered.

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.

Multiple-channel, total-reflection optic with controllable divergence

DOEpatents

Gibson, David M.; Downing, Robert G.

1997-01-01

An apparatus and method for providing focused x-ray, gamma-ray, charged particle and neutral particle, including neutron, radiation beams with a controllable amount of divergence are disclosed. The apparatus features a novel use of a radiation blocking structure, which, when combined with multiple-channel total reflection optics, increases the versatility of the optics by providing user-controlled output-beam divergence.

Multiple-channel, total-reflection optic with controllable divergence

DOEpatents

Gibson, D.M.; Downing, R.G.

1997-02-18

An apparatus and method for providing focused x-ray, gamma-ray, charged particle and neutral particle, including neutron, radiation beams with a controllable amount of divergence are disclosed. The apparatus features a novel use of a radiation blocking structure, which, when combined with multiple-channel total reflection optics, increases the versatility of the optics by providing user-controlled output-beam divergence. 11 figs.

Childhood Trauma and Multiple Personality Disorder: The Case of a 9-Year-Old Girl.

ERIC Educational Resources Information Center

LaPorta, Lauren D.

1992-01-01

This paper reports the case of a nine-year-old female victim of sexual abuse, evaluated and diagnosed with multiple personality disorder over a six-month period. Included is a description of the child's presentation with historical and developmental data. A discussion of the dynamic and predisposing features of the case follows, along with…

XML Content Finally Arrives on the Web!

ERIC Educational Resources Information Center

Funke, Susan

1998-01-01

Explains extensible markup language (XML) and how it differs from hypertext markup language (HTML) and standard generalized markup language (SGML). Highlights include features of XML, including better formatting of documents, better searching capabilities, multiple uses for hyperlinking, and an increase in Web applications; Web browsers; and what…

Recurrent knee pain in an athletic adult: multiple schwannomas secondary to schwannomatosis: a case report.

PubMed

Maceroli, Michael; Uglialoro, Anthony D; Beebe, Kathleen S; Benevenia, Joseph

2010-11-01

Schwannomatosis has been used to describe patients with multiple nonvestibular schwannomas with no associated features of neurofibromatosis type 2. In our case, a 28-year-old athletic man underwent a right knee excisional biopsy for multifocal, benign schwannomatosis. After being asymptomatic for 4 years postresection, he returned to our musculoskeletal oncology service. Imaging studies revealed local recurrence identical to his initial presentation. Excisional biopsy of discrete masses was performed and histologic examination revealed recurrent benign schwannomatosis. To our knowledge, this is the second reported case of recurrent benign schwannomatosis. We review schwannomatosis, including its etiology, radiographic features, and relationship to neurofibromatosis.

Shuttle ku-band communications/radar technical concepts

NASA Technical Reports Server (NTRS)

Griffin, J. W.; Kelley, J. S.; Steiner, A. W.; Vang, H. A.; Zrubek, W. E.; Huth, G. K.

1985-01-01

Technical data on the Shuttle Orbiter K sub u-band communications/radar system are presented. The more challenging aspects of the system design and development are emphasized. The technical problems encountered and the advancements made in solving them are discussed. The radar functions are presented first. Requirements and design/implementation approaches are discussed. Advanced features are explained, including Doppler measurement, frequency diversity, multiple pulse repetition frequencies and pulse widths, and multiple modes. The communications functions that are presented include advances made because of the requirements for multiple communications modes. Spread spectrum, quadrature phase shift keying (QPSK), variable bit rates, and other advanced techniques are discussed. Performance results and conclusions reached are outlined.

The role of optics in secure credentials

NASA Astrophysics Data System (ADS)

Lichtenstein, Terri L.

2006-02-01

The global need for secure ID credentials has grown rapidly over the last few years. This is evident both in government and commercial sectors. Governmental programs include national ID card programs, permanent resident cards for noncitizens, biometric visas or border crossing cards, foreign worker ID programs and secure vehicle registration programs. The commercial need for secure credentials includes secure banking and financial services, security and access control systems and digital healthcare record cards. All of these programs necessitate the use of multiple tamper and counterfeit resistant features for credential authentication and cardholder verification. It is generally accepted that a secure credential should include a combination of overt, covert and forensic security features. The LaserCard optical memory card is a proven example of a secure credential that uses a variety of optical features to enhance its counterfeit resistance and reliability. This paper will review those features and how they interact to create a better credential.

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

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

System, Apparatus, and Method for Active Debris Removal

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

Action recognition via cumulative histogram of multiple features

NASA Astrophysics Data System (ADS)

Yan, Xunshi; Luo, Yupin

2011-01-01

Spatial-temporal interest points (STIPs) are popular in human action recognition. However, they suffer from difficulties in determining size of codebook and losing much information during forming histograms. In this paper, spatial-temporal interest regions (STIRs) are proposed, which are based on STIPs and are capable of marking the locations of the most ``shining'' human body parts. In order to represent human actions, the proposed approach takes great advantages of multiple features, including STIRs, pyramid histogram of oriented gradients and pyramid histogram of oriented optical flows. To achieve this, cumulative histogram is used to integrate dynamic information in sequences and to form feature vectors. Furthermore, the widely used nearest neighbor and AdaBoost methods are employed as classification algorithms. Experiments on public datasets KTH, Weizmann and UCF sports show that the proposed approach achieves effective and robust results.

Cutaneous involvement in multiple myeloma (MM): A case series with clinicopathologic correlation.

PubMed

Malysz, Jozef; Talamo, Giampaolo; Zhu, Junjia; Clarke, Loren E; Bayerl, Michael G; Ali, Liaqat; Helm, Klaus F; Chung, Catherine G

2016-05-01

Disease-specific skin lesions are rare in patients with multiple myeloma (MM). We sought to further characterize the clinical and pathologic features of patients with cutaneous involvement with MM. We identified 13 patients with cutaneous lesions of MM. Cutaneous lesions consisted of pink, red, and violaceous papules, nodules, and/or plaques that varied in size. Histopathology revealed atypical plasma cells with occasional plasmablastic features. MM had aggressive biologic features and was at an advanced stage in the majority of patients. Despite aggressive management, including chemotherapy and stem-cell transplantation, most patients died of progressive disease within a few months after the development of cutaneous lesions. The study group was relatively small. Cutaneous involvement with MM is associated with aggressive biologic behavior and short survival. Copyright © 2015 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Selective attention to temporal features on nested time scales.

PubMed

Henry, Molly J; Herrmann, Björn; Obleser, Jonas

2015-02-01

Meaningful auditory stimuli such as speech and music often vary simultaneously along multiple time scales. Thus, listeners must selectively attend to, and selectively ignore, separate but intertwined temporal features. The current study aimed to identify and characterize the neural network specifically involved in this feature-selective attention to time. We used a novel paradigm where listeners judged either the duration or modulation rate of auditory stimuli, and in which the stimulation, working memory demands, response requirements, and task difficulty were held constant. A first analysis identified all brain regions where individual brain activation patterns were correlated with individual behavioral performance patterns, which thus supported temporal judgments generically. A second analysis then isolated those brain regions that specifically regulated selective attention to temporal features: Neural responses in a bilateral fronto-parietal network including insular cortex and basal ganglia decreased with degree of change of the attended temporal feature. Critically, response patterns in these regions were inverted when the task required selectively ignoring this feature. The results demonstrate how the neural analysis of complex acoustic stimuli with multiple temporal features depends on a fronto-parietal network that simultaneously regulates the selective gain for attended and ignored temporal features. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Individual Morphological Brain Network Construction Based on Multivariate Euclidean Distances Between Brain Regions.

PubMed

Yu, Kaixin; Wang, Xuetong; Li, Qiongling; Zhang, Xiaohui; Li, Xinwei; Li, Shuyu

2018-01-01

Morphological brain network plays a key role in investigating abnormalities in neurological diseases such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, most of the morphological brain network construction methods only considered a single morphological feature. Each type of morphological feature has specific neurological and genetic underpinnings. A combination of morphological features has been proven to have better diagnostic performance compared with a single feature, which suggests that an individual morphological brain network based on multiple morphological features would be beneficial in disease diagnosis. Here, we proposed a novel method to construct individual morphological brain networks for two datasets by calculating the exponential function of multivariate Euclidean distance as the evaluation of similarity between two regions. The first dataset included 24 healthy subjects who were scanned twice within a 3-month period. The topological properties of these brain networks were analyzed and compared with previous studies that used different methods and modalities. Small world property was observed in all of the subjects, and the high reproducibility indicated the robustness of our method. The second dataset included 170 patients with MCI (86 stable MCI and 84 progressive MCI cases) and 169 normal controls (NC). The edge features extracted from the individual morphological brain networks were used to distinguish MCI from NC and separate MCI subgroups (progressive vs. stable) through the support vector machine in order to validate our method. The results showed that our method achieved an accuracy of 79.65% (MCI vs. NC) and 70.59% (stable MCI vs. progressive MCI) in a one-dimension situation. In a multiple-dimension situation, our method improved the classification performance with an accuracy of 80.53% (MCI vs. NC) and 77.06% (stable MCI vs. progressive MCI) compared with the method using a single feature. The results indicated that our method could effectively construct an individual morphological brain network based on multiple morphological features and could accurately discriminate MCI from NC and stable MCI from progressive MCI, and may provide a valuable tool for the investigation of individual morphological brain networks.

Tachycardia detection in ICDs by Boston Scientific : Algorithms, pearls, and pitfalls.

PubMed

Zanker, Norbert; Schuster, Diane; Gilkerson, James; Stein, Kenneth

2016-09-01

The aim of this study was to summarize how implantable cardioverter defibrillators (ICDs) by Boston Scientific sense, detect, discriminate rhythms, and classify episodes. Modern devices include multiple programming selections, diagnostic features, therapy options, memory functions, and device-related history features. Device operation includes logical steps from sensing, detection, discrimination, therapy delivery to history recording. The program is designed to facilitate the application of the device algorithms to the individual patient's clinical needs. Features and functions described in this article represent a selective excerpt by the authors from Boston Scientific publicly available product resources. Programming of ICDs may affect patient outcomes. Patient-adapted and optimized programming requires understanding of device operation and concepts.

Gorlin-Goltz syndrome.

PubMed

Kohli, Munish; Kohli, Monica; Sharma, Naresh; Siddiqui, Saif Rauf; Tulsi, S P S

2010-01-01

Gorlin-Goltz syndrome is an inherited autosomal dominant disorder with complete penetrance and extreme variable expressivity. The authors present a case of an 11-year-old girl with typical features of Gorlin-Goltz syndrome with special respect to medical and dental problems which include multiple bony cage deformities like spina bifida with scoliosis having convexity to the left side, presence of an infantile uterus and multiple odonogenic keratocysts in the maxillofacial region.

Identification of appropriate patients for cardiometabolic risk management.

PubMed

Peters, Anne L

2007-01-01

Patients at increased risk for cardiovascular disease have a wide array of clinical features that should alert practitioners to the need for risk reduction. Some, but not all, of these features relate to insulin resistance. Multiple approaches exist for diagnosing and defining this risk, including the traditional Framingham risk assessment, various definitions of the metabolic syndrome, and assessment of risk factors not commonly included in the standard criteria. This article reviews the many clinical findings that should alert healthcare providers to the need for aggressive cardiovascular risk reduction.

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

Diagnostic Features of Common Oral Ulcerative Lesions: An Updated Decision Tree

PubMed Central

Safi, Yaser

2016-01-01

Diagnosis of oral ulcerative lesions might be quite challenging. This narrative review article aims to introduce an updated decision tree for diagnosing oral ulcerative lesions on the basis of their diagnostic features. Various general search engines and specialized databases including PubMed, PubMed Central, Medline Plus, EBSCO, Science Direct, Scopus, Embase, and authenticated textbooks were used to find relevant topics by means of MeSH keywords such as “oral ulcer,” “stomatitis,” and “mouth diseases.” Thereafter, English-language articles published since 1983 to 2015 in both medical and dental journals including reviews, meta-analyses, original papers, and case reports were appraised. Upon compilation of the relevant data, oral ulcerative lesions were categorized into three major groups: acute, chronic, and recurrent ulcers and into five subgroups: solitary acute, multiple acute, solitary chronic, multiple chronic, and solitary/multiple recurrent, based on the number and duration of lesions. In total, 29 entities were organized in the form of a decision tree in order to help clinicians establish a logical diagnosis by stepwise progression. PMID:27781066

A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

PubMed

Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

2014-11-01

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method.

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

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

PubMed

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

2017-05-01

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

CD-ROM and Metering--An Overview.

ERIC Educational Resources Information Center

Shear, Victor

1992-01-01

Discusses the need for security and metering features for CD-ROM products. Topics covered include user productivity issues, pricing problems, integrated information resources, advantages of CD-ROM distribution systems, unauthorized use, content encryption, and multiple simultaneous meters. (MES)

Multiplicity

DTIC Science & Technology

1991-04-01

that it has not adopted that test. 1 3 5 The Court did, however, recognize that the double Jeopardy protection includes a collateral estoppel feature... estoppel feature. 1 4 1 The Court articulated this new test in the following terms: The Double Jeopardy Clause bars any subsequent prosecution in which...126 Ashe v. Swenson, 397 U.S. at 452 (Brennan, J., concurring). 127 "We defined collateral estoppel as providing that ’when an issue of ultimate

Neural basis for dynamic updating of object representation in visual working memory.

PubMed

Takahama, Sachiko; Miyauchi, Satoru; Saiki, Jun

2010-02-15

In real world, objects have multiple features and change dynamically. Thus, object representations must satisfy dynamic updating and feature binding. Previous studies have investigated the neural activity of dynamic updating or feature binding alone, but not both simultaneously. We investigated the neural basis of feature-bound object representation in a dynamically updating situation by conducting a multiple object permanence tracking task, which required observers to simultaneously process both the maintenance and dynamic updating of feature-bound objects. Using an event-related design, we separated activities during memory maintenance and change detection. In the search for regions showing selective activation in dynamic updating of feature-bound objects, we identified a network during memory maintenance that was comprised of the inferior precentral sulcus, superior parietal lobule, and middle frontal gyrus. In the change detection period, various prefrontal regions, including the anterior prefrontal cortex, were activated. In updating object representation of dynamically moving objects, the inferior precentral sulcus closely cooperates with a so-called "frontoparietal network", and subregions of the frontoparietal network can be decomposed into those sensitive to spatial updating and feature binding. The anterior prefrontal cortex identifies changes in object representation by comparing memory and perceptual representations rather than maintaining object representations per se, as previously suggested. Copyright 2009 Elsevier Inc. All rights reserved.

CoMet: a workflow using contig coverage and composition for binning a metagenomic sample with high precision.

PubMed

Herath, Damayanthi; Tang, Sen-Lin; Tandon, Kshitij; Ackland, David; Halgamuge, Saman Kumara

2017-12-28

In metagenomics, the separation of nucleotide sequences belonging to an individual or closely matched populations is termed binning. Binning helps the evaluation of underlying microbial population structure as well as the recovery of individual genomes from a sample of uncultivable microbial organisms. Both supervised and unsupervised learning methods have been employed in binning; however, characterizing a metagenomic sample containing multiple strains remains a significant challenge. In this study, we designed and implemented a new workflow, Coverage and composition based binning of Metagenomes (CoMet), for binning contigs in a single metagenomic sample. CoMet utilizes coverage values and the compositional features of metagenomic contigs. The binning strategy in CoMet includes the initial grouping of contigs in guanine-cytosine (GC) content-coverage space and refinement of bins in tetranucleotide frequencies space in a purely unsupervised manner. With CoMet, the clustering algorithm DBSCAN is employed for binning contigs. The performances of CoMet were compared against four existing approaches for binning a single metagenomic sample, including MaxBin, Metawatt, MyCC (default) and MyCC (coverage) using multiple datasets including a sample comprised of multiple strains. Binning methods based on both compositional features and coverages of contigs had higher performances than the method which is based only on compositional features of contigs. CoMet yielded higher or comparable precision in comparison to the existing binning methods on benchmark datasets of varying complexities. MyCC (coverage) had the highest ranking score in F1-score. However, the performances of CoMet were higher than MyCC (coverage) on the dataset containing multiple strains. Furthermore, CoMet recovered contigs of more species and was 18 - 39% higher in precision than the compared existing methods in discriminating species from the sample of multiple strains. CoMet resulted in higher precision than MyCC (default) and MyCC (coverage) on a real metagenome. The approach proposed with CoMet for binning contigs, improves the precision of binning while characterizing more species in a single metagenomic sample and in a sample containing multiple strains. The F1-scores obtained from different binning strategies vary with different datasets; however, CoMet yields the highest F1-score with a sample comprised of multiple strains.

Mof-Tree: A Spatial Access Method To Manipulate Multiple Overlapping Features.

ERIC Educational Resources Information Center

Manolopoulos, Yannis; Nardelli, Enrico; Papadopoulos, Apostolos; Proietti, Guido

1997-01-01

Investigates the manipulation of large sets of two-dimensional data representing multiple overlapping features, and presents a new access method, the MOF-tree. Analyzes storage requirements and time with respect to window query operations involving multiple features. Examines both the pointer-based and pointerless MOF-tree representations.…

Gorlin-Goltz syndrome

PubMed Central

Kohli, Munish; Kohli, Monica; Sharma, Naresh; Siddiqui, Saif Rauf; Tulsi, S.P.S.

2010-01-01

Gorlin-Goltz syndrome is an inherited autosomal dominant disorder with complete penetrance and extreme variable expressivity. The authors present a case of an 11-year-old girl with typical features of Gorlin-Goltz syndrome with special respect to medical and dental problems which include multiple bony cage deformities like spina bifida with scoliosis having convexity to the left side, presence of an infantile uterus and multiple odonogenic keratocysts in the maxillofacial region. PMID:22442551

Video to Text (V2T) in Wide Area Motion Imagery

DTIC Science & Technology

2015-09-01

microtext) or a document (e.g., using Sphinx or Apache NLP ) as an automated approach [102]. Previous work in natural language full-text searching...language processing ( NLP ) based module. The heart of the structured text processing module includes the following seven key word banks...Features Tracker MHT Multiple Hypothesis Tracking MIL Multiple Instance Learning NLP Natural Language Processing OAB Online AdaBoost OF Optic Flow

Information Commons for Rice (IC4R)

PubMed Central

2016-01-01

Rice is the most important staple food for a large part of the world's human population and also a key model organism for plant research. Here, we present Information Commons for Rice (IC4R; http://ic4r.org), a rice knowledgebase featuring adoption of an extensible and sustainable architecture that integrates multiple omics data through community-contributed modules. Each module is developed and maintained by different committed groups, deals with data collection, processing and visualization, and delivers data on-demand via web services. In the current version, IC4R incorporates a variety of rice data through multiple committed modules, including genome-wide expression profiles derived entirely from RNA-Seq data, resequencing-based genomic variations obtained from re-sequencing data of thousands of rice varieties, plant homologous genes covering multiple diverse plant species, post-translational modifications, rice-related literatures and gene annotations contributed by the rice research community. Unlike extant related databases, IC4R is designed for scalability and sustainability and thus also features collaborative integration of rice data and low costs for database update and maintenance. Future directions of IC4R include incorporation of other omics data and association of multiple omics data with agronomically important traits, dedicating to build IC4R into a valuable knowledgebase for both basic and translational researches in rice. PMID:26519466

Hierarchical content-based image retrieval by dynamic indexing and guided search

NASA Astrophysics Data System (ADS)

You, Jane; Cheung, King H.; Liu, James; Guo, Linong

2003-12-01

This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

Jet engine nozzle exit configurations, including projections oriented relative to pylons, and associated systems and methods

NASA Technical Reports Server (NTRS)

Mengle, Vinod G. (Inventor); Thomas, Russell H. (Inventor)

2012-01-01

Nozzle exit configurations and associated systems and methods are disclosed. An aircraft system in accordance with one embodiment includes a jet engine exhaust nozzle having an internal flow surface and an exit aperture, with the exit aperture having a perimeter that includes multiple projections extending in an aft direction. Aft portions of individual neighboring projections are spaced apart from each other by a gap, and a geometric feature of the multiple can change in a monotonic manner along at least a portion of the perimeter. Projections near a support pylon and/or associated heat shield can have particular configurations, including greater flow immersion than other projections.

Computer Based Behavioral Biometric Authentication via Multi-Modal Fusion

DTIC Science & Technology

2013-03-01

the decisions made by each individual modality. Fusion of features is the simple concatenation of feature vectors from multiple modalities to be...of Features BayesNet MDL 330 LibSVM PCA 80 J48 Wrapper Evaluator 11 3.5.3 Ensemble Based Decision Level Fusion. In ensemble learning multiple ...The high fusion percentages validate our hypothesis that by combining features from multiple modalities, classification accuracy can be improved. As

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

Multiple parton interactions and production of charged particles up to the intermediate-pT range in high-multiplicity p p events at the LHC

NASA Astrophysics Data System (ADS)

Kar, Somnath; Choudhury, Subikash; Muhuri, Sanjib; Ghosh, Premomoy

2017-01-01

Satisfactory description of data by hydrodynamics-motivated models, as has been reported recently by experimental collaborations at the LHC, confirm "collectivity" in high-multiplicity proton-proton (p p ) collisions. Notwithstanding this, a detailed study of high-multiplicity p p data in other approaches or models is essential for better understanding of the specific phenomenon. In this study, the focus is on a pQCD-inspired multiparton interaction (MPI) model, including a color reconnection (CR) scheme as implemented in the Monte Carlo code, PYTHIA8 tune 4C. The MPI with the color reconnection reproduces the dependence of the mean transverse momentum ⟨pT⟩ on the charged particle multiplicity Nch in p p collisions at the LHC, providing an alternate explanation to the signature of "hydrodynamic collectivity" in p p data. It is, therefore, worth exploring how this model responds to other related features of high-multiplicity p p events. This comparative study with recent experimental results demonstrates the limitations of the model in explaining some of the prominent features of the final-state charged particles up to the intermediate-pT (pT<2.0 GeV /c ) range in high-multiplicity p p events.

MicrobeWorld Radio and Communications Initiative

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

Barbara Hyde

2006-11-22

MicrobeWorld is a 90-second feature broadcast daily on more than 90 public radio stations and available from several sources as a podcast, including www.microbeworld.org. The feature has a strong focus on the use and adapatbility of microbes as alternative sources of energy, in bioremediation, their role in climate, and especially the many benefits and scientific advances that have resulting from decoding microbial genomes. These audio features are permanantly archived on an educational outreach site, microbeworld.org, where they are linked to the National Science Education Standards. They are also being used by instructors at all levels to introduce students to themore » multiple roles and potential of microbes, including a pilot curriculum program for middle-school students in New York.« less

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.

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

PubMed

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

2013-11-01

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

A phantom design for assessment of detectability in PET imaging

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

Wollenweber, Scott D., E-mail: scott.wollenweber@g

2016-09-15

Purpose: The primary clinical role of positron emission tomography (PET) imaging is the detection of anomalous regions of {sup 18}F-FDG uptake, which are often indicative of malignant lesions. The goal of this work was to create a task-configurable fillable phantom for realistic measurements of detectability in PET imaging. Design goals included simplicity, adjustable feature size, realistic size and contrast levels, and inclusion of a lumpy (i.e., heterogeneous) background. Methods: The detection targets were hollow 3D-printed dodecahedral nylon features. The exostructure sphere-like features created voids in a background of small, solid non-porous plastic (acrylic) spheres inside a fillable tank. The featuresmore » filled at full concentration while the background concentration was reduced due to filling only between the solid spheres. Results: Multiple iterations of feature size and phantom construction were used to determine a configuration at the limit of detectability for a PET/CT system. A full-scale design used a 20 cm uniform cylinder (head-size) filled with a fixed pattern of features at a contrast of approximately 3:1. Known signal-present and signal-absent PET sub-images were extracted from multiple scans of the same phantom and with detectability in a challenging (i.e., useful) range. These images enabled calculation and comparison of the quantitative observer detectability metrics between scanner designs and image reconstruction methods. The phantom design has several advantages including filling simplicity, wall-less contrast features, the control of the detectability range via feature size, and a clinically realistic lumpy background. Conclusions: This phantom provides a practical method for testing and comparison of lesion detectability as a function of imaging system, acquisition parameters, and image reconstruction methods and parameters.« less

Effects of human disturbance on waterbird nesting and reproductive success at restoration pond SF2, south San Francisco Bay, California

USGS Publications Warehouse

Ackerman, Joshua T.; Herzog, Mark P.; Hartman, Christopher A.

2014-01-01

To determine the effects that human disturbance may have on waterbirds nesting on these newly constructed islands in Pond SF2, we assessed the potential effects of human disturbance features (specifically, access trails, viewing platforms, internal pond berms, exterior levees, and highways) on breeding waterbirds in 2011 and 2012. We found no clear pattern of potential disturbance features on a group of reproductive factors, including nest survival, nest initiation date, and clutch size. Because all the islands were constructed greater than 90 meters from the nearest disturbance feature, Pond SF2 alone did not provide adequate variation in the distance of disturbance features to detect potential detrimental effects for islands closer to disturbance features in other areas of the SBSP Restoration Project. If there is a need for SBSP Restoration Project Management Team to understand how close islands can be built to disturbance features in the future, we suggest a more comprehensive study that includes multiple ponds, other than SF2, with islands at varying distances to disturbance features.

Region 9 Tribal Lands

EPA Pesticide Factsheets

Dataset of all Indian Reservations in US EPA Region 9 (California, Arizona and Nevada) with some reservation border areas of adjacent states included (adjacent areas of Colorado, New Mexico and Utah). Reservation boundaries are compiled from multiple sources and are derived from several different source scales. Information such as reservation type, primary tribe name are included with the feature dataset. Public Domain Allotments are not included in this data set.

Spectral-spatial hyperspectral image classification using super-pixel-based spatial pyramid representation

NASA Astrophysics Data System (ADS)

Fan, Jiayuan; Tan, Hui Li; Toomik, Maria; Lu, Shijian

2016-10-01

Spatial pyramid matching has demonstrated its power for image recognition task by pooling features from spatially increasingly fine sub-regions. Motivated by the concept of feature pooling at multiple pyramid levels, we propose a novel spectral-spatial hyperspectral image classification approach using superpixel-based spatial pyramid representation. This technique first generates multiple superpixel maps by decreasing the superpixel number gradually along with the increased spatial regions for labelled samples. By using every superpixel map, sparse representation of pixels within every spatial region is then computed through local max pooling. Finally, features learned from training samples are aggregated and trained by a support vector machine (SVM) classifier. The proposed spectral-spatial hyperspectral image classification technique has been evaluated on two public hyperspectral datasets, including the Indian Pines image containing 16 different agricultural scene categories with a 20m resolution acquired by AVIRIS and the University of Pavia image containing 9 land-use categories with a 1.3m spatial resolution acquired by the ROSIS-03 sensor. Experimental results show significantly improved performance compared with the state-of-the-art works. The major contributions of this proposed technique include (1) a new spectral-spatial classification approach to generate feature representation for hyperspectral image, (2) a complementary yet effective feature pooling approach, i.e. the superpixel-based spatial pyramid representation that is used for the spatial correlation study, (3) evaluation on two public hyperspectral image datasets with superior image classification performance.

Spectrum of PORCN mutations in Focal Dermal Hypoplasia

USDA-ARS?s Scientific Manuscript database

Focal Dermal Hypoplasia (FDH), also known as Goltz syndrome (OMIM 305600), is a genetic disorder that affects multiple organ systems early in development. Features of FDH include skin abnormalities, (hypoplasia, atrophy, linear pigmentation, and herniation of fat through dermal defects); papillomas...

Extramedullary (EMP) relapse in unusual locations in multiple myeloma: Is there an association with precedent thalidomide administration and a correlation of special biological features with treatment and outcome?

PubMed

Katodritou, E; Gastari, V; Verrou, E; Hadjiaggelidou, C; Varthaliti, M; Georgiadou, S; Laschos, K; Xirou, P; Yiannaki, E; Constantinou, N; Markala, D; Zervas, K

2009-08-01

Extramedullary relapse constitutes an uncommon manifestation of multiple myeloma (MM), characterized by highly malignant histology, special biological features, resistance to treatment and poor outcome. Its incidence has been increased during the last years, probably due to the introduction of novel strategies in the management of MM, including intensified treatment and immunomodulatory drugs. Here we report nine cases of extramedullary relapse of MM, presented in unusual locations, seven of which had previously been treated with thalidomide-containing regimens (TCR). Our aim was to explore the morphological, immunophenotypical, molecular and laboratory characteristics accompanying EMP-relapse and seek possible correlations with treatment and clinical outcome.

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

[A complexity analysis of Chinese herbal property theory: the multiple formations of herbal property].

PubMed

Jin, Rui; Zhang, Bing

2012-11-01

Chinese herbal property theory (CHPT) is the fundamental characteristic of Chinese materia medica different from modern medicines. It reflects the herbal properties associated with efficacy and formed the early framework of four properties and five flavors in Shennong's Classic of Materia Medica. After the supplement and improvement of CHPT in the past thousands of years, it has developed a theory system including four properties, five flavors, meridian entry, direction of medicinal actions (ascending, descending, floating and sinking) and toxicity. However, because of the influence of philosophy about yin-yang theory and five-phase theory and the difference of cognitive approach and historical background at different times, CHPT became complex. One of the complexity features was the multiple methods for determining herbal property, which might include the inference from herbal efficacy, the thought of Chinese Taoist School and witchcraft, the classification thinking according to manifestations, etc. Another complexity feature was the multiselection associations between herbal property and efficacy, which indicated that the same property could be inferred from different kinds of efficacy. This paper analyzed these complexity features and provided the importance of cognitive approaches and efficacy attributes corresponding to certain herbal property in the study of CHPT.

Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

PubMed Central

2013-01-01

Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539

Dementia in the Oldest Old

PubMed Central

Bullain, Szófia S.; Corrada, María M.

2013-01-01

Purpose of Review: This article discusses some of the unique features of dementia in the oldest old, including some of the most common diagnostic challenges, and potential strategies to overcome them. Recent Findings: Advances include new insight into the role of common risk factors and the effects of multiple underlying neuropathologic features for dementia in the oldest old. In addition, this article contains the latest age-specific normative data for commonly used neuropsychological tests for the oldest old. Summary: The oldest old—people aged 90 years and older—are the fastest-growing segment of society and have the highest rates of dementia in the population. The risk factors, diagnostic challenges, and underlying neuropathologic features of dementia are strikingly different in the 90-years-and-older population compared to younger elderly. Special consideration of these unique features of dementia is necessary when evaluating oldest-old subjects with cognitive impairment. PMID:23558489

DHS Summary Report -- Robert Weldon

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

Weldon, Robert A.

This summer I worked on benchmarking the Lawrence Livermore National Laboratory fission multiplicity capability used in the Monte Carlo particle transport code MCNPX. This work involved running simulations and then comparing the simulation results with experimental experiments. Outlined in this paper is a brief description of the work completed this summer, skills and knowledge gained, and how the internship has impacted my planning for the future. Neutron multiplicity counting is a neutron detection technique that leverages the multiplicity emissions of neutrons from fission to identify various actinides in a lump of material. The identification of individual actinides in lumps ofmore » material crossing our boarders, especially U-235 and Pu-239, is a key component for maintaining the safety of the country from nuclear threats. Several multiplicity emission options from spontaneous and induced fission already existed in MCNPX 2.4.0. These options can be accessed through use of the 6th entry on the PHYS:N card. Lawrence Livermore National Laboratory (LLNL) developed a physics model for the simulation of neutron and gamma ray emission from fission and photofission that was included in MCNPX 2.7.B as an undocumented feature and then was documented in MCNPX 2.7.C. The LLNL multiplicity capability provided a different means for MCNPX to simulate neutron and gamma-ray distributions for neutron induced, spontaneous and photonuclear fission reactions. The original testing on the model for implementation into MCNPX was conducted by Gregg McKinney and John Hendricks. The model is an encapsulation of measured data of neutron multiplicity distributions from Gwin, Spencer, and Ingle, along with the data from Zucker and Holden. One of the founding principles of MCNPX was that it would have several redundant capabilities, providing the means of testing and including various physics packages. Though several multiplicity sampling methodologies already existed within MCNPX, the LLNL fission multiplicity was included to provide a separate capability for computing multiplicity as well as including several new features not already included in MCNPX. These new features include: (1) prompt gamma emission/multiplicity from neutron-induced fission; (2) neutron multiplicity and gamma emission/multiplicity from photofission; and (3) an option to enforce energy correlation for gamma neutron multiplicity emission. These new capabilities allow correlated signal detection for identifying presence of special nuclear material (SNM). Therefore, these new capabilities help meet the missions of the Domestic Nuclear Detection Office (DNDO), which is tasked with developing nuclear detection strategies for identifying potential radiological and nuclear threats, by providing new simulation capability for detection strategies that leverage the new available physics in the LLNL multiplicity capability. Two types of tests were accomplished this summer to test the default LLNL neutron multiplicity capability: neutron-induced fission tests and spontaneous fission tests. Both cases set the 6th entry on the PHYS:N card to 5 (i.e. use LLNL multiplicity). The neutron-induced fission tests utilized a simple 0.001 cm radius sphere where 0.0253 eV neutrons were released at the sphere center. Neutrons were forced to immediately collide in the sphere and release all progeny from the sphere, without further collision, using the LCA card, LCA 7j -2 (therefore density and size of the sphere were irrelevant). Enough particles were run to ensure that the average error of any specific multiplicity did not exceed 0.36%. Neutron-induced fission multiplicities were computed for U-233, U-235, Pu-239, and Pu-241. The spontaneous fission tests also used the same spherical geometry, except: (1) the LCA card was removed; (2) the density of the sphere was set to 0.001 g/cm3; and (3) instead of emitting a thermal neutron, the PAR keyword was set to PAR=SF. The purpose of the small density was to ensure that the spontaneous fission neutrons would not further interact and induce fissions (i.e. the mean free path greatly exceeded the size of the sphere). Enough particles were run to ensure that the average error of any specific spontaneous multiplicity did not exceed 0.23%. Spontaneous fission multiplicities were computed for U-238, Pu-238, Pu-240, Pu-242, Cm-242, and Cm-244. All of the computed results were compared against experimental results compiled by Holden at Brookhaven National Laboratory.« less

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.

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

PubMed

Liu, Tsung-Jung; Liu, Kuan-Hsien

2018-03-01

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

Annual Research Review: The neurobehavioral development of multiple memory systems: implications for childhood and adolescent psychiatric disorders

PubMed Central

Goodman, Jarid; Marsh, Rachel; Peterson, Bradley S.; Packard, Mark G.

2014-01-01

Extensive evidence indicates that mammalian memory is organized into multiple brains systems, including a “cognitive” memory system that depends upon the hippocampus and a stimulus-response “habit” memory system that depends upon the dorsolateral striatum. Dorsal striatal-dependent habit memory may in part influence the development and expression of some human psychopathologies, particularly those characterized by strong habit-like behavioral features. The present review considers this hypothesis as it pertains to psychopathologies that typically emerge during childhood and adolescence. These disorders include Tourette syndrome, attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, eating disorders, and autism spectrum disorders. Human and nonhuman animal research shows that the typical development of memory systems comprises the early maturation of striatal-dependent habit memory and the relatively late maturation of hippocampal-dependent cognitive memory. We speculate that the differing rates of development of these memory systems may in part contribute to the early emergence of habit-like symptoms in childhood and adolescence. In addition, abnormalities in hippocampal and striatal brain regions have been observed consistently in youth with these disorders, suggesting that the aberrant development of memory systems may also contribute to the emergence of habit-like symptoms as core pathological features of these illnesses. Considering these disorders within the context of multiple memory systems may help elucidate the pathogenesis of habit-like symptoms in childhood and adolescence, and lead to novel treatments that lessen the habit-like behavioral features of these disorders. PMID:24286520

Bi-level Multi-Source Learning for Heterogeneous Block-wise Missing Data

PubMed Central

Xiang, Shuo; Yuan, Lei; Fan, Wei; Wang, Yalin; Thompson, Paul M.; Ye, Jieping

2013-01-01

Bio-imaging technologies allow scientists to collect large amounts of high-dimensional data from multiple heterogeneous sources for many biomedical applications. In the study of Alzheimer's Disease (AD), neuroimaging data, gene/protein expression data, etc., are often analyzed together to improve predictive power. Joint learning from multiple complementary data sources is advantageous, but feature-pruning and data source selection are critical to learn interpretable models from high-dimensional data. Often, the data collected has block-wise missing entries. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), most subjects have MRI and genetic information, but only half have cerebrospinal fluid (CSF) measures, a different half has FDG-PET; only some have proteomic data. Here we propose how to effectively integrate information from multiple heterogeneous data sources when data is block-wise missing. We present a unified “bi-level” learning model for complete multi-source data, and extend it to incomplete data. Our major contributions are: (1) our proposed models unify feature-level and source-level analysis, including several existing feature learning approaches as special cases; (2) the model for incomplete data avoids imputing missing data and offers superior performance; it generalizes to other applications with block-wise missing data sources; (3) we present efficient optimization algorithms for modeling complete and incomplete data. We comprehensively evaluate the proposed models including all ADNI subjects with at least one of four data types at baseline: MRI, FDG-PET, CSF and proteomics. Our proposed models compare favorably with existing approaches. PMID:23988272

Bi-level multi-source learning for heterogeneous block-wise missing data.

PubMed

Xiang, Shuo; Yuan, Lei; Fan, Wei; Wang, Yalin; Thompson, Paul M; Ye, Jieping

2014-11-15

Bio-imaging technologies allow scientists to collect large amounts of high-dimensional data from multiple heterogeneous sources for many biomedical applications. In the study of Alzheimer's Disease (AD), neuroimaging data, gene/protein expression data, etc., are often analyzed together to improve predictive power. Joint learning from multiple complementary data sources is advantageous, but feature-pruning and data source selection are critical to learn interpretable models from high-dimensional data. Often, the data collected has block-wise missing entries. In the Alzheimer's Disease Neuroimaging Initiative (ADNI), most subjects have MRI and genetic information, but only half have cerebrospinal fluid (CSF) measures, a different half has FDG-PET; only some have proteomic data. Here we propose how to effectively integrate information from multiple heterogeneous data sources when data is block-wise missing. We present a unified "bi-level" learning model for complete multi-source data, and extend it to incomplete data. Our major contributions are: (1) our proposed models unify feature-level and source-level analysis, including several existing feature learning approaches as special cases; (2) the model for incomplete data avoids imputing missing data and offers superior performance; it generalizes to other applications with block-wise missing data sources; (3) we present efficient optimization algorithms for modeling complete and incomplete data. We comprehensively evaluate the proposed models including all ADNI subjects with at least one of four data types at baseline: MRI, FDG-PET, CSF and proteomics. Our proposed models compare favorably with existing approaches. © 2013 Elsevier Inc. All rights reserved.

EVALUATION AND DIAGNOSIS OF THE DYSMORPHIC INFANT

PubMed Central

Jones, Kelly L.; Adam, Margaret P.

2015-01-01

SYNOPSIS Neonatologists often have the unique opportunity to be the first to identify abnormalities in the neonate. In this review, multiple anomalies and physical features are discussed along with the potential associated genetic syndromes. The anomalies and physical features that are discussed include birth parameters, aplasia cutis congenita, holoprosencephaly, asymmetric crying facies, preauricular ear tags and pits, cleft lip with or without cleft palate, esophageal atresia/tracheoesophageal fistula, congenital heart defects, ventral wall defects, and polydactyly. PMID:26042903

Quantitative Imaging In Pathology (QUIP) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

This site hosts web accessible applications, tools and data designed to support analysis, management, and exploration of whole slide tissue images for cancer research. The following tools are included: caMicroscope: A digital pathology data management and visualization plaform that enables interactive viewing of whole slide tissue images and segmentation results. caMicroscope can be also used independently of QUIP. FeatureExplorer: An interactive tool to allow patient-level feature exploration across multiple dimensions.

Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-04-29

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm(-1)) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice. Copyright © 2011 Elsevier B.V. All rights reserved.

POLO2: a user's guide to multiple Probit Or LOgit analysis

Treesearch

Robert M. Russell; N. E. Savin; Jacqueline L. Robertson

1981-01-01

This guide provides instructions for the use of POLO2, a computer program for multivariate probit or logic analysis of quantal response data. As many as 3000 test subjects may be included in a single analysis. Including the constant term, up to nine explanatory variables may be used. Examples illustrating input, output, and uses of the program's special features...

Reduced multiple empirical kernel learning machine.

PubMed

Wang, Zhe; Lu, MingZhe; Gao, Daqi

2015-02-01

Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3) this paper adopts the Gauss Elimination, one of the on-the-shelf techniques, to generate a basis of the original feature space, which is stable and efficient.

Contextualizing School Psychology Practice: Introducing Featured Research Commentaries

ERIC Educational Resources Information Center

Burns, Matthew K.

2013-01-01

Bronfenbrenner (1977) defined ecological-systems theory (EST) as the study of the multiple interconnected environmental systems that influence individual development. To understand the child, psychologists must fully examine the environment in which the child lives including the home, school, community, and culture (Bronfenbrenner, 1986). There…

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

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

PubMed

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

2012-09-01

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

Management of an affiliated Physics Residency Program using a commercial software tool.

PubMed

Zacarias, Albert S; Mills, Michael D

2010-06-01

A review of commercially available allied health educational management software tools was performed to evaluate their capacity to manage program data associated with a CAMPEP-accredited Therapy Physics Residency Program. Features of these software tools include: a) didactic course reporting and organization, b) competency reporting by topic, category and didactic course, c) student time management and accounting, and d) student patient case reporting by topic, category and course. The software package includes features for recording school administrative information; setting up lists of courses, faculty, clinical sites, categories, competencies, and time logs; and the inclusion of standardized external documents. There are provisions for developing evaluation and survey instruments. The mentors and program may be evaluated by residents, and residents may be evaluated by faculty members using this feature. Competency documentation includes the time spent on the problem or with the patient, time spent with the mentor, date of the competency, and approval by the mentor and program director. Course documentation includes course and lecture title, lecturer, topic information, date of lecture and approval by the Program Director. These software tools have the facility to include multiple clinical sites, with local subadministrators having the ability to approve competencies and attendance at clinical conferences. In total, these software tools have the capability of managing all components of a CAMPEP-accredited residency program. The application database lends the software to the support of multiple affiliated clinical sites within a single residency program. Such tools are a critical and necessary component if the medical physics profession is to meet the projected needs for qualified medical physicists in future years.

The medial habenula and interpeduncular nucleus circuitry is critical in addiction, anxiety, and mood regulation.

PubMed

McLaughlin, Ian; Dani, John A; De Biasi, Mariella

2017-08-01

Abstinence from chronic use of addictive drugs triggers an aversive withdrawal syndrome that compels relapse and deters abstinence. Many features of this syndrome are common across multiple drugs, involving both affective and physical symptoms. Some of the network signaling underlying withdrawal symptoms overlaps with activity that is associated with aversive mood states, including anxiety and depression. Given these shared features, it is not surprising that a particular circuit, the dorsal diencephalic conduction system, and the medial habenula (MHb) and interpeduncular nucleus (IPN), in particular, have been identified as critical to the emergence of aversive states that arise both as a result and, independently, of drug addiction. As the features of this circuit continue to be characterized, the MHb-IPN axis is emerging as a viable target for therapeutics to aid in the treatment of addiction to multiple drugs of abuse as well as mood-associated disorders. This is an article for the special issue XVth International Symposium on Cholinergic Mechanisms. © 2017 International Society for Neurochemistry.

Double trisomy 48,XXX,+18 with multiple dysmorphic features.

PubMed

Jiang, Zi-Yan; Wu, Xiao-Hui; Zou, Chao-Chun

2015-02-01

Chromosomal abnormality is a common cause of congenital anomalies, psychiatric disorders, and mental retardation. However, the double trisomy 48,XXX,+18 is a rare chromosome abnormality. Case report and literature review. A 7-hour-old girl presented to our unit because of poor response after birth. She presented with multiple dysmorphic features, including small for gestational age infant, flat nasal bridge, widely-spaced eyes, the left thumb deformities, flat facial profile, raised sternum, ventricular septal defect, the third lateral brain ventricle enlargement, and small liver. This case expands the spectrum of malformations reported in association with the double trisomy 48,XXX,+18. The literature on 16 fetuses or infants with the 48,XXX,+18 were also reviewed. These data suggested that in patients with clinical features similar to trisomy 18, especially with anomalies of the ears and/or reproductive malformations, double trisomy (48,XXX,+18) should be considered and karyotyping should be performed although it is a rare disease.

A Fine-Scale Functional Logic to Convergence from Retina to Thalamus.

PubMed

Liang, Liang; Fratzl, Alex; Goldey, Glenn; Ramesh, Rohan N; Sugden, Arthur U; Morgan, Josh L; Chen, Chinfei; Andermann, Mark L

2018-05-31

Numerous well-defined classes of retinal ganglion cells innervate the thalamus to guide image-forming vision, yet the rules governing their convergence and divergence remain unknown. Using two-photon calcium imaging in awake mouse thalamus, we observed a functional arrangement of retinal ganglion cell axonal boutons in which coarse-scale retinotopic ordering gives way to fine-scale organization based on shared preferences for other visual features. Specifically, at the ∼6 μm scale, clusters of boutons from different axons often showed similar preferences for either one or multiple features, including axis and direction of motion, spatial frequency, and changes in luminance. Conversely, individual axons could "de-multiplex" information channels by participating in multiple, functionally distinct bouton clusters. Finally, ultrastructural analyses demonstrated that retinal axonal boutons in a local cluster often target the same dendritic domain. These data suggest that functionally specific convergence and divergence of retinal axons may impart diverse, robust, and often novel feature selectivity to visual thalamus. Copyright © 2018 Elsevier Inc. All rights reserved.

[Phenotypic and genetic analysis of a patient presented with Tietz/Waardenburg type II a syndrome].

PubMed

Wang, Huanhuan; Tang, Lifang; Zhang, Jingmin; Hu, Qin; Chen, Yingwei; Xiao, Bing

2015-08-01

To determine the genetic cause for a patient featuring decreased pigmentation of the skin and iris, hearing loss and multiple congenital anomalies. Routine chromosomal banding was performed to analyze the karyotype of the patient and his parents. Single nucleotide polymorphism array (SNP array) was employed to identify cryptic chromosome aberrations, and quantitative real-time PCR was used to confirm the results. Karyotype analysis has revealed no obvious anomaly for the patient and his parents. SNP array analysis of the patient has demonstrated a 3.9 Mb deletion encompassing 3p13p14.1, which caused loss of entire MITF gene. The deletion was confirmed by quantitative real-time PCR. Clinical features of the patient have included severe bilateral hearing loss, decreased pigmentation of the skin and iris and multiple congenital anomalies. The patient, carrying a 3p13p14.1 deletion, has features of Tietz syndrome/Waardenburg syndrome type IIa. This case may provide additional data for the study of genotype-phenotype correlation of this disease.

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

PubMed

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

1991-11-01

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

Nuclear hormone receptors in parasitic helminths

PubMed Central

Wu, Wenjie; LoVerde, Philip T

2010-01-01

Nuclear receptors (NRs) belong to a large protein superfamily that are important transcriptional modulators in metazoans. Parasitic helminths include parasitic worms from the Lophotrochozoa (Platyhelminths) and Ecdysozoa (Nematoda). NRs in parasitic helminths diverged into two different evolutionary lineages. NRs in parasitic Platyhelminths have orthologues in Deuterostomes, in arthropods or both with a feature of extensive gene loss and gene duplication within different gene groups. NRs in parasitic Nematoda follow the nematode evolutionary lineage with a feature of multiple duplication of SupNRs and gene loss. PMID:20600585

The MedDRA paradox.

PubMed

Merrill, Gary H

2008-11-06

MedDRA (the Medical Dictionary for Regulatory Activities Terminology) is a controlled vocabulary widely used as a medical coding scheme. However, MedDRA's characterization of its structural hierarchy exhibits some confusing and paradoxical features. The goal of this paper is to examine these features, determine whether there is a coherent view of the MedDRA hierarchy that emerges, and explore what lessons are to be learned from this for using MedDRA and similar terminologies in a broad medical informatics context that includes relations among multiple disparate terminologies, thesauri, and ontologies.

Soft Somatosensitive Actuators via Embedded 3D Printing.

PubMed

Truby, Ryan L; Wehner, Michael; Grosskopf, Abigail K; Vogt, Daniel M; Uzel, Sebastien G M; Wood, Robert J; Lewis, Jennifer A

2018-04-01

Humans possess manual dexterity, motor skills, and other physical abilities that rely on feedback provided by the somatosensory system. Herein, a method is reported for creating soft somatosensitive actuators (SSAs) via embedded 3D printing, which are innervated with multiple conductive features that simultaneously enable haptic, proprioceptive, and thermoceptive sensing. This novel manufacturing approach enables the seamless integration of multiple ionically conductive and fluidic features within elastomeric matrices to produce SSAs with the desired bioinspired sensing and actuation capabilities. Each printed sensor is composed of an ionically conductive gel that exhibits both long-term stability and hysteresis-free performance. As an exemplar, multiple SSAs are combined into a soft robotic gripper that provides proprioceptive and haptic feedback via embedded curvature, inflation, and contact sensors, including deep and fine touch contact sensors. The multimaterial manufacturing platform enables complex sensing motifs to be easily integrated into soft actuating systems, which is a necessary step toward closed-loop feedback control of soft robots, machines, and haptic devices. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A visualization tool to support decision making in environmental and biological planning

USGS Publications Warehouse

Romañach, Stephanie S.; McKelvy, James M.; Conzelmann, Craig; Suir, Kevin J.

2014-01-01

Large-scale ecosystem management involves consideration of many factors for informed decision making. The EverVIEW Data Viewer is a cross-platform desktop decision support tool to help decision makers compare simulation model outputs from competing plans for restoring Florida's Greater Everglades. The integration of NetCDF metadata conventions into EverVIEW allows end-users from multiple institutions within and beyond the Everglades restoration community to share information and tools. Our development process incorporates continuous interaction with targeted end-users for increased likelihood of adoption. One of EverVIEW's signature features is side-by-side map panels, which can be used to simultaneously compare species or habitat impacts from alternative restoration plans. Other features include examination of potential restoration plan impacts across multiple geographic or tabular displays, and animation through time. As a result of an iterative, standards-driven approach, EverVIEW is relevant to large-scale planning beyond Florida, and is used in multiple biological planning efforts in the United States.

Multiple Schwannomas of the Spine: Review of the Schwannomatosis or Congenital Neurilemmomatosis: A Case Report.

PubMed

Lee, Sang-Hoon; Kim, Se-Hoon; Kim, Bum-Joon; Lim, Dong-Jun

2015-06-01

Schwannomas are the most common benign nerve sheath tumors originating in Schwann cells. With special conditions like neurofibromatosis type 2 or entity called schwannomatosis, patients develop multiple schwannomas. But in clinical setting, distinguishing schwannomatosis from neurofibromatosis type 2 is challengeable. We describe 58-year-old male who presented with severe neuropathic pain, from schwannomatosis featuring multiple schwannomas of spine and trunk, and underwent surgical treatment. We demonstrate his radiologic and clinical findings, and discuss about important clinical features of this condition. To confirm schwannomatosis, we performed brain magnetic resonance imaging, and took his familial history. Staged surgery was done for pathological confirmation and relief of the pain. Schwannomatosis and neurofibromatosis type 2 are similar but different disease. There are diagnostic hallmarks of these conditions, including familial history, pathology, and brain imaging. Because of different prognosis, the two diseases must be distinguished, so diagnostic tests that are mentioned above should be performed in caution.

Multiple Schwannomas of the Spine: Review of the Schwannomatosis or Congenital Neurilemmomatosis: A Case Report

PubMed Central

Lee, Sang-Hoon; Kim, Bum-Joon; Lim, Dong-Jun

2015-01-01

Schwannomas are the most common benign nerve sheath tumors originating in Schwann cells. With special conditions like neurofibromatosis type 2 or entity called schwannomatosis, patients develop multiple schwannomas. But in clinical setting, distinguishing schwannomatosis from neurofibromatosis type 2 is challengeable. We describe 58-year-old male who presented with severe neuropathic pain, from schwannomatosis featuring multiple schwannomas of spine and trunk, and underwent surgical treatment. We demonstrate his radiologic and clinical findings, and discuss about important clinical features of this condition. To confirm schwannomatosis, we performed brain magnetic resonance imaging, and took his familial history. Staged surgery was done for pathological confirmation and relief of the pain. Schwannomatosis and neurofibromatosis type 2 are similar but different disease. There are diagnostic hallmarks of these conditions, including familial history, pathology, and brain imaging. Because of different prognosis, the two diseases must be distinguished, so diagnostic tests that are mentioned above should be performed in caution. PMID:26217390

JOVIAL/Ada Microprocessor Study.

DTIC Science & Technology

1982-04-01

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

Inherited genetic variants associated with occurrence of multiple primary melanoma.

PubMed

Gibbs, David C; Orlow, Irene; Kanetsky, Peter A; Luo, Li; Kricker, Anne; Armstrong, Bruce K; Anton-Culver, Hoda; Gruber, Stephen B; Marrett, Loraine D; Gallagher, Richard P; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J; Cust, Anne E; Ollila, David W; Begg, Colin B; Berwick, Marianne; Thomas, Nancy E

2015-06-01

Recent studies, including genome-wide association studies, have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 SNPs from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% confidence intervals were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma, while NCOA6 rs4911442 approached significance (P = 0.06). The GEM Study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. ©2015 American Association for Cancer Research.

Inherited genetic variants associated with occurrence of multiple primary melanoma

PubMed Central

Gibbs, David C.; Orlow, Irene; Kanetsky, Peter A.; Luo, Li; Kricker, Anne; Armstrong, Bruce K.; Anton-Culver, Hoda; Gruber, Stephen B.; Marrett, Loraine D.; Gallagher, Richard P.; Zanetti, Roberto; Rosso, Stefano; Dwyer, Terence; Sharma, Ajay; La Pilla, Emily; From, Lynn; Busam, Klaus J.; Cust, Anne E.; Ollila, David W.; Begg, Colin B.; Berwick, Marianne; Thomas, Nancy E.

2015-01-01

Recent studies including genome-wide association studies have identified several putative low-penetrance susceptibility loci for melanoma. We sought to determine their generalizability to genetic predisposition for multiple primary melanoma in the international population-based Genes, Environment, and Melanoma (GEM) Study. GEM is a case-control study of 1,206 incident cases of multiple primary melanoma and 2,469 incident first primary melanoma participants as the control group. We investigated the odds of developing multiple primary melanoma for 47 single nucleotide polymorphisms (SNP) from 21 distinct genetic regions previously reported to be associated with melanoma. ORs and 95% CIs were determined using logistic regression models adjusted for baseline features (age, sex, age by sex interaction, and study center). We investigated univariable models and built multivariable models to assess independent effects of SNPs. Eleven SNPs in 6 gene neighborhoods (TERT/CLPTM1L, TYRP1, MTAP, TYR, NCOA6, and MX2) and a PARP1 haplotype were associated with multiple primary melanoma. In a multivariable model that included only the most statistically significant findings from univariable modeling and adjusted for pigmentary phenotype, back nevi, and baseline features, we found TERT/CLPTM1L rs401681 (P = 0.004), TYRP1 rs2733832 (P = 0.006), MTAP rs1335510 (P = 0.0005), TYR rs10830253 (P = 0.003), and MX2 rs45430 (P = 0.008) to be significantly associated with multiple primary melanoma while NCOA6 rs4911442 approached significance (P = 0.06). The GEM study provides additional evidence for the relevance of these genetic regions to melanoma risk and estimates the magnitude of the observed genetic effect on development of subsequent primary melanoma. PMID:25837821

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation.

PubMed

Mourad, Raphaël; Cuvier, Olivier

2016-05-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1.

Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation

PubMed Central

Mourad, Raphaël; Cuvier, Olivier

2016-01-01

Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1. PMID:27203237

Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

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

Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.

A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expectedmore » clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.« less

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

PubMed

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

2016-01-13

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

Estimation of lung tumor position from multiple anatomical features on 4D-CT using multiple regression analysis.

PubMed

Ono, Tomohiro; Nakamura, Mitsuhiro; Hirose, Yoshinori; Kitsuda, Kenji; Ono, Yuka; Ishigaki, Takashi; Hiraoka, Masahiro

2017-09-01

To estimate the lung tumor position from multiple anatomical features on four-dimensional computed tomography (4D-CT) data sets using single regression analysis (SRA) and multiple regression analysis (MRA) approach and evaluate an impact of the approach on internal target volume (ITV) for stereotactic body radiotherapy (SBRT) of the lung. Eleven consecutive lung cancer patients (12 cases) underwent 4D-CT scanning. The three-dimensional (3D) lung tumor motion exceeded 5 mm. The 3D tumor position and anatomical features, including lung volume, diaphragm, abdominal wall, and chest wall positions, were measured on 4D-CT images. The tumor position was estimated by SRA using each anatomical feature and MRA using all anatomical features. The difference between the actual and estimated tumor positions was defined as the root-mean-square error (RMSE). A standard partial regression coefficient for the MRA was evaluated. The 3D lung tumor position showed a high correlation with the lung volume (R = 0.92 ± 0.10). Additionally, ITVs derived from SRA and MRA approaches were compared with ITV derived from contouring gross tumor volumes on all 10 phases of the 4D-CT (conventional ITV). The RMSE of the SRA was within 3.7 mm in all directions. Also, the RMSE of the MRA was within 1.6 mm in all directions. The standard partial regression coefficient for the lung volume was the largest and had the most influence on the estimated tumor position. Compared with conventional ITV, average percentage decrease of ITV were 31.9% and 38.3% using SRA and MRA approaches, respectively. The estimation accuracy of lung tumor position was improved by the MRA approach, which provided smaller ITV than conventional ITV. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Exploring the cognitive features in children with autism spectrum disorder, their co-twins, and typically developing children within a population-based sample.

PubMed

Brunsdon, Victoria E A; Colvert, Emma; Ames, Catherine; Garnett, Tracy; Gillan, Nicola; Hallett, Victoria; Lietz, Stephanie; Woodhouse, Emma; Bolton, Patrick; Happé, Francesca

2015-08-01

The behavioural symptoms of autism spectrum disorder (ASD) are thought to reflect underlying cognitive deficits/differences. The findings in the literature are somewhat mixed regarding the cognitive features of ASD. This study attempted to address this issue by investigating a range of cognitive deficits and the prevalence of multiple cognitive atypicalities in a large population-based sample comprising children with ASD, their unaffected co-twins, and typically developing comparison children. Participants included families from the Twins Early Development Study (TEDS) where one or both children met diagnostic criteria for ASD. Overall, 181 adolescents with a diagnosis of ASD and 73 unaffected co-twins were included, plus an additional 160 comparison control participants. An extensive cognitive battery was administered to measure IQ, central coherence, executive function, and theory of mind ability. Differences between groups (ASD, co-twin, control) are reported on tasks assessing theory of mind, executive function, and central coherence. The ASD group performed atypically in significantly more cognitive tasks than the unaffected co-twin and control groups. Nearly a third of the ASD group presented with multiple cognitive atypicalities. Multiple cognitive atypicalities appear to be a characteristic, but not universal feature, of ASD. Further work is needed to investigate whether specific cognitive atypicalities, either alone or together, are related to specific behaviours characteristic of ASD. © 2014 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

Limb/pelvis hypoplasia/aplasia with skull defect (Schinzel phocomelia): distinctive features and prenatal detection.

PubMed

Olney, R S; Hoyme, H E; Roche, F; Ferguson, K; Hintz, S; Madan, A

2001-11-01

Schinzel phocomelia syndrome is characterized by limb/pelvis hypoplasia/aplasia: specifically, intercalary limb deficiencies and absent or hypoplastic pelvic bones. The phenotype is similar to that described in a related multiple malformation syndrome known as Al-Awadi/Raas-Rothschild syndrome. The additional important feature of large parietooccipital skull defects without meningocele, encephalocele, or other brain malformation has thus far been reported only in children with Schinzel phocomelia syndrome. We recently evaluated a boy affected with Schinzel phocomelia born to nonconsanguineous healthy parents of Mexican origin. A third-trimester fetal ultrasound scan showed severe limb deficiencies and an absent pelvis. The infant died shortly after birth. Dysmorphology examination, radiographs, and autopsy revealed quadrilateral intercalary limb deficiencies with preaxial toe polydactyly; an absent pelvis and a 7 x 3-cm skull defect; and extraskeletal anomalies including microtia, telecanthus, micropenis with cryptorchidism, renal cysts, stenosis of the colon, and a cleft alveolar ridge. A normal 46,XY karyotype was demonstrated, and autosomal recessive inheritance was presumed on the basis of previously reported families. This case report emphasizes the importance of recognizing severe pelvic and skull deficiencies (either post- or prenatally) in differentiating infants with Schinzel phocomelia from other multiple malformation syndromes that feature intercalary limb defects, including thalidomide embryopathy and Roberts-SC phocomelia. Copyright 2001 Wiley-Liss, Inc.

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

Changes in channel morphology over human time scales [Chapter 32

Treesearch

John M. Buffington

2012-01-01

Rivers are exposed to changing environmental conditions over multiple spatial and temporal scales, with the imposed environmental conditions and response potential of the river modulated to varying degrees by human activity and our exploitation of natural resources. Watershed features that control river morphology include topography (valley slope and channel...

Opening Mathematics Texts: Resisting the Seduction

ERIC Educational Resources Information Center

Wagner, David

2012-01-01

This analysis of the writing in a grade 7 mathematics textbook distinguishes between closed texts and open texts, which acknowledge multiple possibilities. I use tools that have recently been applied in mathematics contexts, focussing on grammatical features that include personal pronouns, modality, and types of imperatives, as well as on…

OASIS: Prototyping Graphical Interfaces to Networked Information.

ERIC Educational Resources Information Center

Buckland, Michael K.; And Others

1993-01-01

Describes the latest modifications being made to OASIS, a front-end enhancement to the University of California's MELVYL online union catalog. Highlights include the X Windows interface; multiple database searching to act as an information network; Lisp implementation for flexible data representation; and OASIS commands and features to help…

Rainbows of Intelligence. Exploring How Students Learn.

ERIC Educational Resources Information Center

Teele, Sue

This book offers practical applications for exploring multiple intelligences in the classroom to help each student express his or her own personal learning rainbow. Special features of the book include seven complete lesson plans ready to be adapted to any grade level; objectives, activities, and applications that meet U.S. and California…

Feature Assignment in Perception of Auditory Figure

ERIC Educational Resources Information Center

Gregg, Melissa K.; Samuel, Arthur G.

2012-01-01

Because the environment often includes multiple sounds that overlap in time, listeners must segregate a sound of interest (the auditory figure) from other co-occurring sounds (the unattended auditory ground). We conducted a series of experiments to clarify the principles governing the extraction of auditory figures. We distinguish between auditory…

14 CFR Appendix A to Part 33 - Instructions for Continued Airworthiness

Code of Federal Regulations, 2012 CFR

2012-01-01

... features and data to the extent necessary for maintenance or preventive maintenance. (2) A detailed... limits, maximum continuous power or thrust, bleed air, and power extraction required for a relevant... Airworthiness consist of multiple documents, the section required under this paragraph must be included in the...

14 CFR Appendix A to Part 33 - Instructions for Continued Airworthiness

Code of Federal Regulations, 2011 CFR

2011-01-01

... features and data to the extent necessary for maintenance or preventive maintenance. (2) A detailed... limits, maximum continuous power or thrust, bleed air, and power extraction required for a relevant... Airworthiness consist of multiple documents, the section required under this paragraph must be included in the...

Using dBASE II for Bibliographic Files.

ERIC Educational Resources Information Center

Sullivan, Jeanette

1985-01-01

Describes use of a database management system (dBASE II, produced by Ashton-Tate), noting best features and disadvantages. Highlights include data entry, multiple access points available, training requirements, use of dBASE for a bibliographic application, auxiliary software, and dBASE updates. Sample searches, auxiliary programs, and requirements…

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

NASA Astrophysics Data System (ADS)

Hargitai, Henrik

2016-10-01

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

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.

PubMed

Dimitriadis, S I; Liparas, Dimitris; Tsolaki, Magda N

2018-05-15

In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI. Based on preprocessed MRI images from the organizers of a neuroimaging challenge, 3 we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme. In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition. The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature. Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD. Copyright © 2017 Elsevier B.V. All rights reserved.

Visual Analytics for Heterogeneous Geoscience Data

NASA Astrophysics Data System (ADS)

Pan, Y.; Yu, L.; Zhu, F.; Rilee, M. L.; Kuo, K. S.; Jiang, H.; Yu, H.

2017-12-01

Geoscience data obtained from diverse sources have been routinely leveraged by scientists to study various phenomena. The principal data sources include observations and model simulation outputs. These data are characterized by spatiotemporal heterogeneity originated from different instrument design specifications and/or computational model requirements used in data generation processes. Such inherent heterogeneity poses several challenges in exploring and analyzing geoscience data. First, scientists often wish to identify features or patterns co-located among multiple data sources to derive and validate certain hypotheses. Heterogeneous data make it a tedious task to search such features in dissimilar datasets. Second, features of geoscience data are typically multivariate. It is challenging to tackle the high dimensionality of geoscience data and explore the relations among multiple variables in a scalable fashion. Third, there is a lack of transparency in traditional automated approaches, such as feature detection or clustering, in that scientists cannot intuitively interact with their analysis processes and interpret results. To address these issues, we present a new scalable approach that can assist scientists in analyzing voluminous and diverse geoscience data. We expose a high-level query interface that allows users to easily express their customized queries to search features of interest across multiple heterogeneous datasets. For identified features, we develop a visualization interface that enables interactive exploration and analytics in a linked-view manner. Specific visualization techniques such as scatter plots to parallel coordinates are employed in each view to allow users to explore various aspects of features. Different views are linked and refreshed according to user interactions in any individual view. In such a manner, a user can interactively and iteratively gain understanding into the data through a variety of visual analytics operations. We demonstrate with use cases how scientists can combine the query and visualization interfaces to enable a customized workflow facilitating studies using heterogeneous geoscience datasets.

Feature-aided multiple target tracking in the image plane

NASA Astrophysics Data System (ADS)

Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

2006-05-01

Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

Features of Coping with Disease in Iranian Multiple Sclerosis Patients: a Qualitative Study.

PubMed

Dehghani, Ali; Dehghan Nayeri, Nahid; Ebadi, Abbas

2018-03-01

Introduction: Coping with disease is of the main components improving the quality of life in multiple sclerosis patients. Identifying the characteristics of this concept is based on the experiences of patients. Using qualitative research is essential to improve the quality of life. This study was conducted to explore the features of coping with the disease in patients with multiple sclerosis. Method: In this conventional content analysis study, eleven multiple sclerosis patients from Iran MS Society in Tehran (Iran) participated. Purposive sampling was used to select participants. Data were gathered using semi structured interviews. To analyze data, a conventional content analysis approach was used to identify meaning units and to make codes and categories. Results: Results showed that features of coping with disease in multiple sclerosis patients consists of (a) accepting the current situation, (b) maintenance and development of human interactions, (c) self-regulation and (d) self-efficacy. Each of these categories is composed of sub-categories and codes that showed the perception and experience of patients about the coping with disease. Conclusion: Accordingly, a unique set of features regarding features of coping with the disease were identified among the patients with multiple sclerosis. Therefore, working to ensure the emergence of, and subsequent reinforcement of these features in MS patients can be an important step in improving the adjustment and quality of their lives.

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.

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.

Nursing Reference Center: a point-of-care resource.

PubMed

Vardell, Emily; Paulaitis, Gediminas Geddy

2012-01-01

Nursing Reference Center is a point-of-care resource designed for the practicing nurse, as well as nursing administrators, nursing faculty, and librarians. Users can search across multiple resources, including topical Quick Lessons, evidence-based care sheets, patient education materials, practice guidelines, and more. Additional features include continuing education modules, e-books, and a new iPhone application. A sample search and comparison with similar databases were conducted.

Disease and Stem Cell-Based Analysis of the 2014 ASNTR Meeting

PubMed Central

Eve, David J.

2015-01-01

A wide variety of subjects are presented at the annual American Society of Neural Therapy and Repair meeting every year, as typified by this summary of the 2014 meeting. Parkinson’s disease-related presentations were again the most popular topic, with traumatic brain injury, spinal cord injury, and stroke being close behind. Other disorders included Huntington’s disease, brain cancer, and bipolar disorders. Several studies were related to multiple diseases, and many studies attempted to reveal more about the disease process. The use of scaffolds, drugs, and gene therapy as disease models and/or potential therapies were also featured. An increasing proportion of presentations related to stem cells, with the study of multiple stem cell types being the most common. Induced pluripotent stem cells were increasingly popular, including two presentations each on a muscle-derived dedifferentiated cell type and cells derived from bipolar patients. Other stem cells, including neural stem cells, mesenchymal stem cells, umbilical cord blood cells, and embryonic stem cells, were featured. More than 55% of the stem cell studies involved transplantation, with human-derived cells being the most frequently transplanted, while rats were the most common recipient. Two human autologous studies for spinal cord injury and hypoxia-derived encephalopathy, while a further three allogenic studies for stroke and spinal cord injury, were also featured. This year’s meeting highlights the increasing promise of stem cells and other therapies for the treatment of neurodegenerative disorders. PMID:26858901

Site Features

EPA Pesticide Factsheets

This dataset consists of various site features from multiple Superfund sites in U.S. EPA Region 8. These data were acquired from multiple sources at different times and were combined into one region-wide layer.

Secure image retrieval with multiple keys

NASA Astrophysics Data System (ADS)

Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

2018-03-01

This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

Clinical diagnostic exome evaluation for an infant with a lethal disorder: genetic diagnosis of TARP syndrome and expansion of the phenotype in a patient with a newly reported RBM10 alteration.

PubMed

Powis, Zöe; Hart, Alexa; Cherny, Sara; Petrik, Igor; Palmaer, Erika; Tang, Sha; Jones, Carolyn

2017-06-02

Diagnostic Exome Sequencing (DES) has been shown to be an effective tool for diagnosis individuals with suspected genetic conditions. We report a male infant born with multiple anomalies including bilateral dysplastic kidneys, cleft palate, bilateral talipes, and bilateral absence of thumbs and first toes. Prenatal testing including chromosome analysis and microarray did not identify a cause for the multiple congenital anomalies. Postnatal diagnostic exome studies (DES) were utilized to find a molecular diagnosis for the patient. Exome sequencing of the proband, mother, and father showed a previously unreported maternally inherited RNA binding motif protein 10 (RBM10) c.1352_1353delAG (p.E451Vfs*66) alteration. Mutations in RBM10 are associated with TARP syndrome, an X-linked recessive disorder originally described with cardinal features of talipes equinovarus, atrial septal defect, Robin sequence, and persistent left superior vena cava. DES established a molecular genetic diagnosis of TARP syndrome for a neonatal patient with a poor prognosis in whom traditional testing methods were uninformative and allowed for efficient diagnosis and future reproductive options for the parents. Other reported cases of TARP syndrome demonstrate significant variability in clinical phenotype. The reported features in this infant including multiple hemivertebrae, imperforate anus, aplasia of thumbs and first toes have not been reported in previous patients, thus expanding the clinical phenotype for this rare disorder.

Putative Indigenous Carbon-Bearing Alteration Features in Martian Meteorite Yamato 000593

PubMed Central

Gibson, Everett K.; Thomas-Keprta, Kathie L.; Clemett, Simon J.; McKay, David S.

2014-01-01

Abstract We report the first observation of indigenous carbonaceous matter in the martian meteorite Yamato 000593. The carbonaceous phases are heterogeneously distributed within secondary iddingsite alteration veins and present in a range of morphologies including areas composed of carbon-rich spheroidal assemblages encased in multiple layers of iddingsite. We also observed microtubular features emanating from iddingsite veins penetrating into the host olivine comparable in shape to those interpreted to have formed by bioerosion in terrestrial basalts. Key Words: Meteorite—Yamato 000593—Mars—Carbon. Astrobiology 14, 170–181. PMID:24552234

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.

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

Predictive Modeling of Implantation Outcome in an In Vitro Fertilization Setting: An Application of Machine Learning Methods.

PubMed

Uyar, Asli; Bener, Ayse; Ciray, H Nadir

2015-08-01

Multiple embryo transfers in in vitro fertilization (IVF) treatment increase the number of successful pregnancies while elevating the risk of multiple gestations. IVF-associated multiple pregnancies exhibit significant financial, social, and medical implications. Clinicians need to decide the number of embryos to be transferred considering the tradeoff between successful outcomes and multiple pregnancies. To predict implantation outcome of individual embryos in an IVF cycle with the aim of providing decision support on the number of embryos transferred. Retrospective cohort study. Electronic health records of one of the largest IVF clinics in Turkey. The study data set included 2453 embryos transferred at day 2 or day 3 after intracytoplasmic sperm injection (ICSI). Each embryo was represented with 18 clinical features and a class label, +1 or -1, indicating positive and negative implantation outcomes, respectively. For each classifier tested, a model was developed using two-thirds of the data set, and prediction performance was evaluated on the remaining one-third of the samples using receiver operating characteristic (ROC) analysis. The training-testing procedure was repeated 10 times on randomly split (two-thirds to one-third) data. The relative predictive values of clinical input characteristics were assessed using information gain feature weighting and forward feature selection methods. The naïve Bayes model provided 80.4% accuracy, 63.7% sensitivity, and 17.6% false alarm rate in embryo-based implantation prediction. Multiple embryo implantations were predicted at a 63.8% sensitivity level. Predictions using the proposed model resulted in higher accuracy compared with expert judgment alone (on average, 75.7% and 60.1%, respectively). A machine learning-based decision support system would be useful in improving the success rates of IVF treatment. © The Author(s) 2014.

Circuit Design Features of a Stable Two-Cell System.

PubMed

Zhou, Xu; Franklin, Ruth A; Adler, Miri; Jacox, Jeremy B; Bailis, Will; Shyer, Justin A; Flavell, Richard A; Mayo, Avi; Alon, Uri; Medzhitov, Ruslan

2018-02-08

Cell communication within tissues is mediated by multiple paracrine signals including growth factors, which control cell survival and proliferation. Cells and the growth factors they produce and receive constitute a circuit with specific properties that ensure homeostasis. Here, we used computational and experimental approaches to characterize the features of cell circuits based on growth factor exchange between macrophages and fibroblasts, two cell types found in most mammalian tissues. We found that the macrophage-fibroblast cell circuit is stable and robust to perturbations. Analytical screening of all possible two-cell circuit topologies revealed the circuit features sufficient for stability, including environmental constraint and negative-feedback regulation. Moreover, we found that cell-cell contact is essential for the stability of the macrophage-fibroblast circuit. These findings illustrate principles of cell circuit design and provide a quantitative perspective on cell interactions. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Feature diagnosticity and task context shape activity in human scene-selective cortex.

PubMed

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

HILTOP supplement: Heliocentric interplanetary low thrust trajectory optimization program, supplement 1

NASA Technical Reports Server (NTRS)

Mann, F. I.; Horsewood, J. L.

1974-01-01

Modifications and improvements are described that were made to the HILTOP electric propulsion trajectory optimization computer program during calendar years 1973 and 1974. New program features include the simulation of power degradation, housekeeping power, launch asymptote declination optimization, and powered and unpowered ballistic multiple swingby missions with an optional deep space burn.

Exploring the Artwork of Young Students' Multimodal Compositions

ERIC Educational Resources Information Center

Pantaleo, Sylvia

2017-01-01

The data featured in this article were collected during a classroom-based study with seven- and eight-year-old children in British Columbia, Canada. The multiple purposes of the research included exploring how the development of the students' understanding of elements of visual art and design would affect their subsequent application of these same…

A Joyful Classroom Learning System with Robot Learning Companion for Children to Learn Mathematics Multiplication

ERIC Educational Resources Information Center

Wei, Chun-Wang; Hung, I-Chun; Lee, Ling; Chen, Nian-Shing

2011-01-01

This research demonstrates the design of a Joyful Classroom Learning System (JCLS) with flexible, mobile and joyful features. The theoretical foundations of this research include the experiential learning theory, constructivist learning theory and joyful learning. The developed JCLS consists of the robot learning companion (RLC), sensing input…

A Multi-criterial Decision Support System for Forest Management

Treesearch

Donald Nute; Geneho Kim; Walter D. Potter; Mark J. Twery; H. Michael Rauscher; Scott Thomasma; Deborah Bennett; Peter Kollasch

1999-01-01

We describe a research project that has as its goal development of a full-featured decision support system for managing forested land to satisfy multiple criteria represented as timber, wildlife, water, ecological, and wildlife objectives. The decision process proposed for what was originally conceived of as a Northeast Decision Model (NED) includes data acquisition,...

Reporting Multiple Individual Injuries in Studies of Team Ball Sports: A Systematic Review of Current Practice.

PubMed

Fortington, Lauren V; van der Worp, Henk; van den Akker-Scheek, Inge; Finch, Caroline F

2017-06-01

To identify and prioritise targets for injury prevention efforts, injury incidence studies are widely reported. The accuracy and consistency in calculation and reporting of injury incidence is crucial. Many individuals experience more than one injury but multiple injuries are not consistently reported in sport injury incidence studies. The aim of this systematic review was to evaluate current practice of how multiple injuries within individuals have been defined and reported in prospective, long-term, injury studies in team ball sports. A systematic search of three online databases for articles published before 2016. Publications were included if (1) they collected prospective data on musculoskeletal injuries in individual participants; (2) the study duration was >1 consecutive calendar year/season; and (3) individuals were the unit of analysis. Key study features were summarised, including definitions of injury, how multiple individual injuries were reported and results relating to multiple injuries. Of the 71 publications included, half did not specifically indicate multiple individual injuries; those that did were largely limited to reporting recurrent injuries. Eight studies reported the number/proportion of athletes with more than one injury, and 11 studies presented the mean/number of injuries per athlete. Despite it being relatively common to collect data on individuals across more than one season, the reporting of multiple injuries within individuals is much more limited. Ultimately, better addressing of multiple injuries will improve the accuracy of injury incidence studies and enable more precise targeting and monitoring of the effectiveness of preventive interventions.

Machine Learning Classification Combining Multiple Features of A Hyper-Network of fMRI Data in Alzheimer's Disease

PubMed Central

Guo, Hao; Zhang, Fan; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

Exploring functional interactions among various brain regions is helpful for understanding the pathological underpinnings of neurological disorders. Brain networks provide an important representation of those functional interactions, and thus are widely applied in the diagnosis and classification of neurodegenerative diseases. Many mental disorders involve a sharp decline in cognitive ability as a major symptom, which can be caused by abnormal connectivity patterns among several brain regions. However, conventional functional connectivity networks are usually constructed based on pairwise correlations among different brain regions. This approach ignores higher-order relationships, and cannot effectively characterize the high-order interactions of many brain regions working together. Recent neuroscience research suggests that higher-order relationships between brain regions are important for brain network analysis. Hyper-networks have been proposed that can effectively represent the interactions among brain regions. However, this method extracts the local properties of brain regions as features, but ignores the global topology information, which affects the evaluation of network topology and reduces the performance of the classifier. This problem can be compensated by a subgraph feature-based method, but it is not sensitive to change in a single brain region. Considering that both of these feature extraction methods result in the loss of information, we propose a novel machine learning classification method that combines multiple features of a hyper-network based on functional magnetic resonance imaging in Alzheimer's disease. The method combines the brain region features and subgraph features, and then uses a multi-kernel SVM for classification. This retains not only the global topological information, but also the sensitivity to change in a single brain region. To certify the proposed method, 28 normal control subjects and 38 Alzheimer's disease patients were selected to participate in an experiment. The proposed method achieved satisfactory classification accuracy, with an average of 91.60%. The abnormal brain regions included the bilateral precuneus, right parahippocampal gyrus\\hippocampus, right posterior cingulate gyrus, and other regions that are known to be important in Alzheimer's disease. Machine learning classification combining multiple features of a hyper-network of functional magnetic resonance imaging data in Alzheimer's disease obtains better classification performance. PMID:29209156

Delayed diagnosis of Gorlin syndrome: Learning from mistakes!

PubMed

Ramanathan, Subramaniyan; Kumar, Devendra; Al Heidous, Mahmoud; Palaniappan, Yegu

2015-01-01

Gorlin syndrome (GS) is a rare inherited multisystem disorder with predisposition to basal cell carcinomas and various other neoplasms. Characteristic features include falx calcification, multiple odontogenic keratocysts (OKCs), early onset medulloblastoma, craniofacial and skeletal malformations, cardiac and ovarian fibroma. We present a case of GS in a 9-year-old girl with recurrent dental infections which was overlooked for 8 years. Diagnosis was finally suggested by the incidental detection of multiple OKCs and ovarian fibromas on follow-up magnetic resonance imaging performed for surveillance of previous operated brain tumor.

Analysis of dynamic multiplicity fluctuations at PHOBOS

NASA Astrophysics Data System (ADS)

Chai, Zhengwei; PHOBOS Collaboration; Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Budzanowski, A.; Busza, W.; Carroll, A.; Chai, Z.; Decowski, M. P.; García, E.; George, N.; Gulbrandsen, K.; Gushue, S.; Halliwell, C.; Hamblen, J.; Heintzelman, G. A.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Holynski, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Katzy, J.; Khan, N.; Kucewicz, W.; Kulinich, P.; Kuo, C. M.; Lin, W. T.; Manly, S.; McLeod, D.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Park, I. C.; Pernegger, H.; Reed, C.; Remsberg, L. P.; Reuter, M.; Roland, C.; Roland, G.; Rosenberg, L.; Sagerer, J.; Sarin, P.; Sawicki, P.; Skulski, W.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Tang, J. L.; Trzupek, A.; Vale, C.; van Nieuwenhuizen, G. J.; Verdier, R.; Wolfs, F. L. H.; Wosiek, B.; Wozniak, K.; Wuosmaa, A. H.; Wyslouch, B.

2005-01-01

This paper presents the analysis of the dynamic fluctuations in the inclusive charged particle multiplicity measured by PHOBOS for Au+Au collisions at surdsNN = 200GeV within the pseudo-rapidity range of -3 < η < 3. First the definition of the fluctuations observables used in this analysis is presented, together with the discussion of their physics meaning. Then the procedure for the extraction of dynamic fluctuations is described. Some preliminary results are included to illustrate the correlation features of the fluctuation observable. New dynamic fluctuations results will be available in a later publication.

Incorporation of coupled nonequilibrium chemistry into a two-dimensional nozzle code (SEAGULL)

NASA Technical Reports Server (NTRS)

Ratliff, A. W.

1979-01-01

A two-dimensional multiple shock nozzle code (SEAGULL) was extended to include the effects of finite rate chemistry. The basic code that treats multiple shocks and contact surfaces was fully coupled with a generalized finite rate chemistry and vibrational energy exchange package. The modified code retains all of the original SEAGULL features plus the capability to treat chemical and vibrational nonequilibrium reactions. Any chemical and/or vibrational energy exchange mechanism can be handled as long as thermodynamic data and rate constants are available for all participating species.

Protein disulfide isomerase a multifunctional protein with multiple physiological roles

NASA Astrophysics Data System (ADS)

Ali Khan, Hyder; Mutus, Bulent

2014-08-01

Protein disulfide isomerase (PDI), is a member of the thioredoxin superfamily of redox proteins. PDI has three catalytic activities including, thiol-disulfide oxireductase, disulfide isomerase and redox-dependent chaperone. Originally, PDI was identified in the lumen of the endoplasmic reticulum and subsequently detected at additional locations, such as cell surfaces and the cytosol. This review will provide an overview of the recent advances in relating the structural features of PDI to its multiple catalytic roles as well as its physiological and pathophysiological functions related to redox regulation and protein folding.

Radiological Features of Brain Metastases from Non-small Cell Lung Cancer Harboring EGFR Mutation.

PubMed

Takamori, Shinkichi; Toyokawa, Gouji; Shimokawa, Mototsugu; Kinoshita, Fumihiko; Kozuma, Yuka; Matsubara, Taichi; Haratake, Naoki; Akamine, Takaki; Mukae, Nobutaka; Hirai, Fumihiko; Tagawa, Tetsuzo; Oda, Yoshinao; Iwaki, Toru; Iihara, Koji; Honda, Hiroshi; Maehara, Yoshihiko

2018-06-01

To investigate the radiological features on computed tomography (CT) of brain metastasis (BM) from epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC). Thirty-four patients with NSCLC with BMs who underwent surgical resection of the BMs at the Department of Neurosurgery, Kyushu University from 2005 to 2016 were enrolled in the study. The EGFR statuses of the 34 BMs were investigated. Radiological features, including the number, size, and location of the tumor, were delineated by CT. Patients with EGFR-mutated BMs had significantly higher frequencies of multiple metastases than those with the non-EGFR-mutated type (p=0.042). BMs harboring mutations in EGFR were more frequently observed in the central area of the brain compared to those without mutations in EGFR (p=0.037). Careful follow-up of patients with EGFR-mutated NSCLC may be necessary given the high frequencies of multiple BMs and their location in the central area of the brain. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention

PubMed Central

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

2016-01-01

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

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.

Multiple Hypotheses Image Segmentation and Classification With Application to Dietary Assessment

PubMed Central

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J.; Delp, Edward J.

2016-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier’s confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback. PMID:25561457

Multiple hypotheses image segmentation and classification with application to dietary assessment.

PubMed

Zhu, Fengqing; Bosch, Marc; Khanna, Nitin; Boushey, Carol J; Delp, Edward J

2015-01-01

We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy of image segmentation. These ideas are implemented by generating multiple segmentations of an image to select stable segmentations based on the classifier's confidence score assigned to each segmented image region. Automatic segmented regions are classified using a multichannel feature classification system. For each segmented region, multiple feature spaces are formed. Feature vectors in each of the feature spaces are individually classified. The final decision is obtained by combining class decisions from individual feature spaces using decision rules. We show improved accuracy of segmenting food images with classifier feedback.

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

WPBMB Entrez: An interface to NCBI Entrez for Wordpress.

PubMed

Gohara, David W

2018-03-01

Research-oriented websites are an important means for the timely communication of information. These websites fall under a number of categories including: research laboratories, training grant and program projects, and online service portals. Invariably there is content on a site, such as publication listings, that require frequent updating. A number of content management systems exist to aid in the task of developing and managing a website, each with their strengths and weaknesses. One popular choice is Wordpress, a free, open source and actively developed application for the creation of web content. During a recent site redesign for our department, the need arose to ensure publications were up to date for each of the research labs and department as a whole. Several plugins for Wordpress offer this type of functionality, but in many cases the plugins are either no longer maintained, are missing features that would require the use of several, possibly incompatible, plugins or lack features for layout on a webpage. WPBMB Entrez was developed to address these needs. WPBMB Entrez utilizes a subset of NCBI Entrez and RCSB databases to maintain up to date records of publications, and publication related information on Wordpress-based websites. The core functionality uses the same search query syntax as on the NCBI Entrez site, including advanced query syntaxes. The plugin is extensible allowing for rapid development and addition of new data sources as the need arises. WPBMB Entrez was designed to be easy to use, yet flexible enough to address more complex usage scenarios. Features of the plugin include: an easy to use interface, design customization, multiple templates for displaying publication results, a caching mechanism to reduce page load times, supports multiple distinct queries and retrieval modes, and the ability to aggregate multiple queries into unified lists. Additionally, developer documentation is provided to aid in customization of the plugin. WPBMB Entrez is available at no cost, is open source and works with all recent versions of Wordpress. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of Self-Paced Encoding and Practice on Age-Related Deficits in Binding Three Features

ERIC Educational Resources Information Center

Kinjo, Hikari

2010-01-01

Although much literature suggests that the age-related decline in episodic memory could be due to difficulties in binding features of information, previous studies focused mainly on memory of paired associations rather than memory of multiple bound features. In reality, however, there are many situations that require binding multiple features…

Syndrome disintegration: Exome sequencing reveals that Fitzsimmons syndrome is a co-occurrence of multiple events.

PubMed

Armour, Christine M; Smith, Amanda; Hartley, Taila; Chardon, Jodi Warman; Sawyer, Sarah; Schwartzentruber, Jeremy; Hennekam, Raoul; Majewski, Jacek; Bulman, Dennis E; Suri, Mohnish; Boycott, Kym M

2016-07-01

In 1987 Fitzsimmons and Guilbert described identical male twins with progressive spastic paraplegia, brachydactyly with cone shaped epiphyses, short stature, dysarthria, and "low-normal" intelligence. In subsequent years, four other patients, including one set of female identical twins, a single female child, and a single male individual were described with the same features, and the eponym Fitzsimmons syndrome was adopted (OMIM #270710). We performed exome analysis of the patient described in 2009, and one of the original twins from 1987, the only patients available from the literature. No single genetic etiology exists that explains Fitzsimmons syndrome; however, multiple different genetic causes were identified. Specifically, the twins described by Fitzsimmons had heterozygous mutations in the SACS gene, the gene responsible for autosomal recessive spastic ataxia of Charlevoix Saguenay (ARSACS), as well as a heterozygous mutation in the TRPS1, the gene responsible in Trichorhinophalangeal syndrome type 1 (TRPS1 type 1) which includes brachydactyly as a feature. A TBL1XR1 mutation was identified in the patient described in 2009 as contributing to his cognitive impairment and autistic features with no genetic cause identified for his spasticity or brachydactyly. The findings show that these individuals have multiple different etiologies giving rise to a similar phenotype, and that "Fitzsimmons syndrome" is in fact not one single syndrome. Over time, we anticipate that continued careful phenotyping with concomitant genome-wide analysis will continue to identify the causes of many rare syndromes, but it will also highlight that previously delineated clinical entities are, in fact, not syndromes at all. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Ephus: Multipurpose Data Acquisition Software for Neuroscience Experiments

PubMed Central

Suter, Benjamin A.; O'Connor, Timothy; Iyer, Vijay; Petreanu, Leopoldo T.; Hooks, Bryan M.; Kiritani, Taro; Svoboda, Karel; Shepherd, Gordon M. G.

2010-01-01

Physiological measurements in neuroscience experiments often involve complex stimulus paradigms and multiple data channels. Ephus (http://www.ephus.org) is an open-source software package designed for general-purpose data acquisition and instrument control. Ephus operates as a collection of modular programs, including an ephys program for standard whole-cell recording with single or multiple electrodes in typical electrophysiological experiments, and a mapper program for synaptic circuit mapping experiments involving laser scanning photostimulation based on glutamate uncaging or channelrhodopsin-2 excitation. Custom user functions allow user-extensibility at multiple levels, including on-line analysis and closed-loop experiments, where experimental parameters can be changed based on recently acquired data, such as during in vivo behavioral experiments. Ephus is compatible with a variety of data acquisition and imaging hardware. This paper describes the main features and modules of Ephus and their use in representative experimental applications. PMID:21960959

A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

Treesearch

D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

1993-01-01

A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

Visual Prediction Error Spreads Across Object Features in Human Visual Cortex

PubMed Central

Summerfield, Christopher; Egner, Tobias

2016-01-01

Visual cognition is thought to rely heavily on contextual expectations. Accordingly, previous studies have revealed distinct neural signatures for expected versus unexpected stimuli in visual cortex. However, it is presently unknown how the brain combines multiple concurrent stimulus expectations such as those we have for different features of a familiar object. To understand how an unexpected object feature affects the simultaneous processing of other expected feature(s), we combined human fMRI with a task that independently manipulated expectations for color and motion features of moving-dot stimuli. Behavioral data and neural signals from visual cortex were then interrogated to adjudicate between three possible ways in which prediction error (surprise) in the processing of one feature might affect the concurrent processing of another, expected feature: (1) feature processing may be independent; (2) surprise might “spread” from the unexpected to the expected feature, rendering the entire object unexpected; or (3) pairing a surprising feature with an expected feature might promote the inference that the two features are not in fact part of the same object. To formalize these rival hypotheses, we implemented them in a simple computational model of multifeature expectations. Across a range of analyses, behavior and visual neural signals consistently supported a model that assumes a mixing of prediction error signals across features: surprise in one object feature spreads to its other feature(s), thus rendering the entire object unexpected. These results reveal neurocomputational principles of multifeature expectations and indicate that objects are the unit of selection for predictive vision. SIGNIFICANCE STATEMENT We address a key question in predictive visual cognition: how does the brain combine multiple concurrent expectations for different features of a single object such as its color and motion trajectory? By combining a behavioral protocol that independently varies expectation of (and attention to) multiple object features with computational modeling and fMRI, we demonstrate that behavior and fMRI activity patterns in visual cortex are best accounted for by a model in which prediction error in one object feature spreads to other object features. These results demonstrate how predictive vision forms object-level expectations out of multiple independent features. PMID:27810936

Land mine detection using multispectral image fusion

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

Clark, G.A.; Sengupta, S.K.; Aimonetti, W.D.

1995-03-29

Our system fuses information contained in registered images from multiple sensors to reduce the effects of clutter and improve the ability to detect surface and buried land mines. The sensor suite currently consists of a camera that acquires images in six bands (400nm, 500nm, 600nm, 700nm, 800nm and 900nm). Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a varietymore » of physical properties that are more separable in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, etc.) and some artifacts. We use a supervised learning pattern recognition approach to detecting the metal and plastic land mines. The overall process consists of four main parts: Preprocessing, feature extraction, feature selection, and classification. These parts are used in a two step process to classify a subimage. We extract features from the images, and use feature selection algorithms to select only the most important features according to their contribution to correct detections. This allows us to save computational complexity and determine which of the spectral bands add value to the detection system. The most important features from the various sensors are fused using a supervised learning pattern classifier (the probabilistic neural network). We present results of experiments to detect land mines from real data collected from an airborne platform, and evaluate the usefulness of fusing feature information from multiple spectral bands.« less

A gaze independent hybrid-BCI based on visual spatial attention

NASA Astrophysics Data System (ADS)

Egan, John M.; Loughnane, Gerard M.; Fletcher, Helen; Meade, Emma; Lalor, Edmund C.

2017-08-01

Objective. Brain-computer interfaces (BCI) use measures of brain activity to convey a user’s intent without the need for muscle movement. Hybrid designs, which use multiple measures of brain activity, have been shown to increase the accuracy of BCIs, including those based on EEG signals reflecting covert attention. Our study examined whether incorporating a measure of the P3 response improved the performance of a previously reported attention-based BCI design that incorporates measures of steady-state visual evoked potentials (SSVEP) and alpha band modulations. Approach. Subjects viewed stimuli consisting of two bi-laterally located flashing white boxes on a black background. Streams of letters were presented sequentially within the boxes, in random order. Subjects were cued to attend to one of the boxes without moving their eyes, and they were tasked with counting the number of target-letters that appeared within. P3 components evoked by target appearance, SSVEPs evoked by the flashing boxes, and power in the alpha band are modulated by covert attention, and the modulations can be used to classify trials as left-attended or right-attended. Main Results. We showed that classification accuracy was improved by including a P3 feature along with the SSVEP and alpha features (the inclusion of a P3 feature lead to a 9% increase in accuracy compared to the use of SSVEP and Alpha features alone). We also showed that the design improves the robustness of BCI performance to individual subject differences. Significance. These results demonstrate that incorporating multiple neurophysiological indices of covert attention can improve performance in a gaze-independent BCI.

A review of multimodel superensemble forecasting for weather, seasonal climate, and hurricanes

NASA Astrophysics Data System (ADS)

Krishnamurti, T. N.; Kumar, V.; Simon, A.; Bhardwaj, A.; Ghosh, T.; Ross, R.

2016-06-01

This review provides a summary of work in the area of ensemble forecasts for weather, climate, oceans, and hurricanes. This includes a combination of multiple forecast model results that does not dwell on the ensemble mean but uses a unique collective bias reduction procedure. A theoretical framework for this procedure is provided, utilizing a suite of models that is constructed from the well-known Lorenz low-order nonlinear system. A tutorial that includes a walk-through table and illustrates the inner workings of the multimodel superensemble's principle is provided. Systematic errors in a single deterministic model arise from a host of features that range from the model's initial state (data assimilation), resolution, representation of physics, dynamics, and ocean processes, local aspects of orography, water bodies, and details of the land surface. Models, in their diversity of representation of such features, end up leaving unique signatures of systematic errors. The multimodel superensemble utilizes as many as 10 million weights to take into account the bias errors arising from these diverse features of multimodels. The design of a single deterministic forecast models that utilizes multiple features from the use of the large volume of weights is provided here. This has led to a better understanding of the error growths and the collective bias reductions for several of the physical parameterizations within diverse models, such as cumulus convection, planetary boundary layer physics, and radiative transfer. A number of examples for weather, seasonal climate, hurricanes and sub surface oceanic forecast skills of member models, the ensemble mean, and the superensemble are provided.

Medical image retrieval system using multiple features from 3D ROIs

NASA Astrophysics Data System (ADS)

Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

2012-02-01

Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

Road and Roadside Feature Extraction Using Imagery and LIDAR Data for Transportation Operation

NASA Astrophysics Data System (ADS)

Ural, S.; Shan, J.; Romero, M. A.; Tarko, A.

2015-03-01

Transportation agencies require up-to-date, reliable, and feasibly acquired information on road geometry and features within proximity to the roads as input for evaluating and prioritizing new or improvement road projects. The information needed for a robust evaluation of road projects includes road centerline, width, and extent together with the average grade, cross-sections, and obstructions near the travelled way. Remote sensing is equipped with a large collection of data and well-established tools for acquiring the information and extracting aforementioned various road features at various levels and scopes. Even with many remote sensing data and methods available for road extraction, transportation operation requires more than the centerlines. Acquiring information that is spatially coherent at the operational level for the entire road system is challenging and needs multiple data sources to be integrated. In the presented study, we established a framework that used data from multiple sources, including one-foot resolution color infrared orthophotos, airborne LiDAR point clouds, and existing spatially non-accurate ancillary road networks. We were able to extract 90.25% of a total of 23.6 miles of road networks together with estimated road width, average grade along the road, and cross sections at specified intervals. Also, we have extracted buildings and vegetation within a predetermined proximity to the extracted road extent. 90.6% of 107 existing buildings were correctly identified with 31% false detection rate.

Severe developmental delay and multiple strawberry naevi: a new syndrome?

PubMed Central

Upton, C J; Young, I D

1993-01-01

An 18 month old girl with dysmorphic features, severe developmental delay, multiple strawberry naevi, and capillary naevi is described. No previous report of a similar association of features has been identified. Images PMID:8230170

A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.

MEN1, MEN4, and Carney Complex: Pathology and Molecular Genetics

PubMed Central

Schernthaner-Reiter, Marie Helene; Trivellin, Giampaolo; Stratakis, Constantine A.

2015-01-01

Pituitary adenomas are a common feature of a subset of endocrine neoplasia syndromes, which have otherwise highly variable disease manifestations. We provide here a review of the clinical features and human molecular genetics of multiple endocrine neoplasia type 1 and 4 (MEN1 and MEN4, respectively) and Carney complex (CNC). MEN1, MEN4 and CNC are hereditary autosomal dominant syndromes that can present with pituitary adenomas. MEN1 is caused by inactivating mutations in the MEN1 gene, whose product menin is involved in multiple intracellular pathways contributing to transcriptional control and cell proliferation. MEN1 clinical features include primary hyperparathyroidism, pancreatic neuroendocrine tumours and prolactinomas and other pituitary adenomas. A subset of patients with pituitary adenomas and other MEN1 features have mutations in the CDKN1B gene; their disease has been called MEN type 4 (MEN4). Inactivating mutations in the type 1α regulatory subunit of protein kinase A (PKA) (the PRKAR1A gene), that lead to dysregulation and activation of the PKA pathway, are the main genetic cause of CNC, which is clinically characterised by primary pigmented adrenocortical disease (PPNAD), spotty skin pigmentation (lentigines), cardiac and other myxomas and acromegaly due to somatotropinomas or somatotrope hyperplasia. PMID:25592387

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

PubMed

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

Measuring the Interestingness of Articles in a Limited User Environment Prospectus

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

Pon, Raymond K.

2007-04-18

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

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Tapping into the Power of School Climate to Prevent Bullying: One Application of Schoolwide Positive Behavior Interventions and Supports

ERIC Educational Resources Information Center

Bosworth, Kris; Judkins, Maryann

2014-01-01

Preventing bullying requires a comprehensive approach that includes a focus on school climate. We review the climate features shown to reduce bullying, then illustrate how School-wide Positive Behavioral Interventions and Supports (SWPBIS) applies these principles in practice. SWPBIS, grounded in multiple theories--behaviorism, social learning…

Managing for featured, threatened, endangered, and sensitive species and unique habitats for ecosystem sustainability.

Treesearch

Bruce G. Marcot; Michael J. Wisdom; Hiram W. Li; Gonzalo C. Castillo

1994-01-01

The traditional approach to wildlife management has focused on single species—historically game species and more recently threatened and endangered species. Several newer approaches to managing for multiple species and biological diversity include managing coarse filters, ecological indicator species, indicator guilds, and use of species-habitat matrices. These and...

Language Development in Down Syndrome: From the Prelinguistic Period to the Acquisition of Literacy

ERIC Educational Resources Information Center

Abbeduto, Leonard; Warren, Steven F.; Conners, Frances A.

2007-01-01

Down syndrome (DS) is associated with abnormalities in multiple organ systems and a characteristic phenotype that includes numerous behavioral features. Language, however, is among the most impaired domains of functioning in DS and, perhaps, also the greatest barrier to independent meaningful inclusion in the community. In this article, we review…

Rad-hard computer elements for space applications

NASA Technical Reports Server (NTRS)

Krishnan, G. S.; Longerot, Carl D.; Treece, R. Keith

1993-01-01

Space Hardened CMOS computer elements emulating a commercial microcontroller and microprocessor family have been designed, fabricated, qualified, and delivered for a variety of space programs including NASA's multiple launch International Solar-Terrestrial Physics (ISTP) program, Mars Observer, and government and commercial communication satellites. Design techniques and radiation performance of the 1.25 micron feature size products are described.

Comparison of the Physical Education and Sports School Students' Multiple Intelligence Areas According to Demographic Features

ERIC Educational Resources Information Center

Aslan, Cem Sinan

2016-01-01

The aim of this study is to compare the multiple intelligence areas of a group of physical education and sports students according to their demographic features. In the study, "Multiple Intelligence Scale", consisting of 27 items, whose Turkish validity and reliability study have been done by Babacan (2012) and which is originally owned…

Comparative analysis and visualization of multiple collinear genomes

PubMed Central

2012-01-01

Background Genome browsers are a common tool used by biologists to visualize genomic features including genes, polymorphisms, and many others. However, existing genome browsers and visualization tools are not well-suited to perform meaningful comparative analysis among a large number of genomes. With the increasing quantity and availability of genomic data, there is an increased burden to provide useful visualization and analysis tools for comparison of multiple collinear genomes such as the large panels of model organisms which are the basis for much of the current genetic research. Results We have developed a novel web-based tool for visualizing and analyzing multiple collinear genomes. Our tool illustrates genome-sequence similarity through a mosaic of intervals representing local phylogeny, subspecific origin, and haplotype identity. Comparative analysis is facilitated through reordering and clustering of tracks, which can vary throughout the genome. In addition, we provide local phylogenetic trees as an alternate visualization to assess local variations. Conclusions Unlike previous genome browsers and viewers, ours allows for simultaneous and comparative analysis. Our browser provides intuitive selection and interactive navigation about features of interest. Dynamic visualizations adjust to scale and data content making analysis at variable resolutions and of multiple data sets more informative. We demonstrate our genome browser for an extensive set of genomic data sets composed of almost 200 distinct mouse laboratory strains. PMID:22536897

Neural network-based multiple robot simultaneous localization and mapping.

PubMed

Saeedi, Sajad; Paull, Liam; Trentini, Michael; Li, Howard

2011-12-01

In this paper, a decentralized platform for simultaneous localization and mapping (SLAM) with multiple robots is developed. Each robot performs single robot view-based SLAM using an extended Kalman filter to fuse data from two encoders and a laser ranger. To extend this approach to multiple robot SLAM, a novel occupancy grid map fusion algorithm is proposed. Map fusion is achieved through a multistep process that includes image preprocessing, map learning (clustering) using neural networks, relative orientation extraction using norm histogram cross correlation and a Radon transform, relative translation extraction using matching norm vectors, and then verification of the results. The proposed map learning method is a process based on the self-organizing map. In the learning phase, the obstacles of the map are learned by clustering the occupied cells of the map into clusters. The learning is an unsupervised process which can be done on the fly without any need to have output training patterns. The clusters represent the spatial form of the map and make further analyses of the map easier and faster. Also, clusters can be interpreted as features extracted from the occupancy grid map so the map fusion problem becomes a task of matching features. Results of the experiments from tests performed on a real environment with multiple robots prove the effectiveness of the proposed solution.

FEATURE 3, LARGE GUN POSITION, SHOWING MULTIPLE COMPARTMENTS, VIEW FACING ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

FEATURE 3, LARGE GUN POSITION, SHOWING MULTIPLE COMPARTMENTS, VIEW FACING SOUTH. - Naval Air Station Barbers Point, Anti-Aircraft Battery Complex-Large Gun Position, East of Coral Sea Road, northwest of Hamilton Road, Ewa, Honolulu County, HI

General-Purpose Software For Computer Graphics

NASA Technical Reports Server (NTRS)

Rogers, Joseph E.

1992-01-01

NASA Device Independent Graphics Library (NASADIG) is general-purpose computer-graphics package for computer-based engineering and management applications which gives opportunity to translate data into effective graphical displays for presentation. Features include two- and three-dimensional plotting, spline and polynomial interpolation, control of blanking of areas, multiple log and/or linear axes, control of legends and text, control of thicknesses of curves, and multiple text fonts. Included are subroutines for definition of areas and axes of plots; setup and display of text; blanking of areas; setup of style, interpolation, and plotting of lines; control of patterns and of shading of colors; control of legends, blocks of text, and characters; initialization of devices; and setting of mixed alphabets. Written in FORTRAN 77.

MRI predictors of treatment response for perianal fistulizing Crohn disease in children and young adults.

PubMed

Shenoy-Bhangle, Anuradha; Nimkin, Katherine; Goldner, Dana; Bradley, William F; Israel, Esther J; Gee, Michael S

2014-01-01

Magnetic resonance imaging (MRI) is considered the imaging standard for diagnosis and characterization of perianal complications associated with Crohn disease in children and adults. To define MRI criteria that could act as potential predictors of treatment response in fistulizing Crohn disease in children, in order to guide more informed study interpretation. We performed a retrospective database query to identify all children and young adults with Crohn disease who underwent serial MRI studies for assessment of perianal symptoms between 2003 and 2010. We examined imaging features of perianal disease including fistula number, type and length, presence and size of associated abscess, and disease response/progression on follow-up MRI. We reviewed imaging studies and electronic medical records. Statistical analysis, including logistic regression, was performed to associate MR imaging features with treatment response and disease progression. We included 36 patients (22 male, 14 female; age range 8-21 years). Of these, 32 had a second MRI exam and 4 had clinical evidence of complete response, obviating the need for repeat imaging. Of the parameters analyzed, presence of abscess, type of fistula according to the Parks classification, and multiplicity were not predictors of treatment outcome. Maximum length of the dominant fistula and aggregate fistula length in the case of multiple fistulae were the best predictors of treatment outcome. Maximum fistula length <2.5 cm was a predictor of treatment response, while aggregate fistula length ≥2.5 cm was a predictor of disease progression. Perianal fistula length is an important imaging feature to assess on MRI of fistulizing Crohn disease.

SCN2A encephalopathy

PubMed Central

Howell, Katherine B.; McMahon, Jacinta M.; Carvill, Gemma L.; Tambunan, Dimira; Mackay, Mark T.; Rodriguez-Casero, Victoria; Webster, Richard; Clark, Damian; Freeman, Jeremy L.; Calvert, Sophie; Olson, Heather E.; Mandelstam, Simone; Poduri, Annapurna; Mefford, Heather C.; Harvey, A. Simon

2015-01-01

Objective: De novo SCN2A mutations have recently been associated with severe infantile-onset epilepsies. Herein, we define the phenotypic spectrum of SCN2A encephalopathy. Methods: Twelve patients with an SCN2A epileptic encephalopathy underwent electroclinical phenotyping. Results: Patients were aged 0.7 to 22 years; 3 were deceased. Seizures commenced on day 1–4 in 8, week 2–6 in 2, and after 1 year in 2. Characteristic features included clusters of brief focal seizures with multiple hourly (9 patients), multiple daily (2), or multiple weekly (1) seizures, peaking at maximal frequency within 3 months of onset. Multifocal interictal epileptiform discharges were seen in all. Three of 12 patients had infantile spasms. The epileptic syndrome at presentation was epilepsy of infancy with migrating focal seizures (EIMFS) in 7 and Ohtahara syndrome in 2. Nine patients had improved seizure control with sodium channel blockers including supratherapeutic or high therapeutic phenytoin levels in 5. Eight had severe to profound developmental impairment. Other features included movement disorders (10), axial hypotonia (11) with intermittent or persistent appendicular spasticity, early handedness, and severe gastrointestinal symptoms. Mutations arose de novo in 11 patients; paternal DNA was unavailable in one. Conclusions: Review of our 12 and 34 other reported cases of SCN2A encephalopathy suggests 3 phenotypes: neonatal-infantile–onset groups with severe and intermediate outcomes, and a childhood-onset group. Here, we show that SCN2A is the second most common cause of EIMFS and, importantly, does not always have a poor developmental outcome. Sodium channel blockers, particularly phenytoin, may improve seizure control. PMID:26291284

TRICCS: A proposed teleoperator/robot integrated command and control system for space applications

NASA Technical Reports Server (NTRS)

Will, R. W.

1985-01-01

Robotic systems will play an increasingly important role in space operations. An integrated command and control system based on the requirements of space-related applications and incorporating features necessary for the evolution of advanced goal-directed robotic systems is described. These features include: interaction with a world model or domain knowledge base, sensor feedback, multiple-arm capability and concurrent operations. The system makes maximum use of manual interaction at all levels for debug, monitoring, and operational reliability. It is shown that the robotic command and control system may most advantageously be implemented as packages and tasks in Ada.

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.

New Optical Transforms For Statistical Image Recognition

NASA Astrophysics Data System (ADS)

Lee, Sing H.

1983-12-01

In optical implementation of statistical image recognition, new optical transforms on large images for real-time recognition are of special interest. Several important linear transformations frequently used in statistical pattern recognition have now been optically implemented, including the Karhunen-Loeve transform (KLT), the Fukunaga-Koontz transform (FKT) and the least-squares linear mapping technique (LSLMT).1-3 The KLT performs principle components analysis on one class of patterns for feature extraction. The FKT performs feature extraction for separating two classes of patterns. The LSLMT separates multiple classes of patterns by maximizing the interclass differences and minimizing the intraclass variations.

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

PubMed

Samuel, Oluwarotimi Williams; Geng, Yanjuan; Li, Xiangxin; Li, Guanglin

2017-10-28

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

FEATURE 3, LARGE GUN POSITION, SHOWING MULTIPLE COMPARTMENTS, VIEW FACING ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

FEATURE 3, LARGE GUN POSITION, SHOWING MULTIPLE COMPARTMENTS, VIEW FACING SOUTH (with scale stick). - Naval Air Station Barbers Point, Anti-Aircraft Battery Complex-Large Gun Position, East of Coral Sea Road, northwest of Hamilton Road, Ewa, Honolulu County, HI

Multiple feature extraction by using simultaneous wavelet transforms

NASA Astrophysics Data System (ADS)

Mazzaferri, Javier; Ledesma, Silvia; Iemmi, Claudio

2003-07-01

We propose here a method to optically perform multiple feature extraction by using wavelet transforms. The method is based on obtaining the optical correlation by means of a Vander Lugt architecture, where the scene and the filter are displayed on spatial light modulators (SLMs). Multiple phase filters containing the information about the features that we are interested in extracting are designed and then displayed on an SLM working in phase mostly mode. We have designed filters to simultaneously detect edges and corners or different characteristic frequencies contained in the input scene. Simulated and experimental results are shown.

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

Evaluating Cell Processes, Quality, and Biomarkers in Pluripotent Stem Cells Using Video Bioinformatics

PubMed Central

Lin, Sabrina C.; Bays, Brett C.; Omaiye, Esther; Bhanu, Bir; Talbot, Prue

2016-01-01

There is a foundational need for quality control tools in stem cell laboratories engaged in basic research, regenerative therapies, and toxicological studies. These tools require automated methods for evaluating cell processes and quality during in vitro passaging, expansion, maintenance, and differentiation. In this paper, an unbiased, automated high-content profiling toolkit, StemCellQC, is presented that non-invasively extracts information on cell quality and cellular processes from time-lapse phase-contrast videos. Twenty four (24) morphological and dynamic features were analyzed in healthy, unhealthy, and dying human embryonic stem cell (hESC) colonies to identify those features that were affected in each group. Multiple features differed in the healthy versus unhealthy/dying groups, and these features were linked to growth, motility, and death. Biomarkers were discovered that predicted cell processes before they were detectable by manual observation. StemCellQC distinguished healthy and unhealthy/dying hESC colonies with 96% accuracy by non-invasively measuring and tracking dynamic and morphological features over 48 hours. Changes in cellular processes can be monitored by StemCellQC and predictions can be made about the quality of pluripotent stem cell colonies. This toolkit reduced the time and resources required to track multiple pluripotent stem cell colonies and eliminated handling errors and false classifications due to human bias. StemCellQC provided both user-specified and classifier-determined analysis in cases where the affected features are not intuitive or anticipated. Video analysis algorithms allowed assessment of biological phenomena using automatic detection analysis, which can aid facilities where maintaining stem cell quality and/or monitoring changes in cellular processes are essential. In the future StemCellQC can be expanded to include other features, cell types, treatments, and differentiating cells. PMID:26848582

Evaluating Cell Processes, Quality, and Biomarkers in Pluripotent Stem Cells Using Video Bioinformatics.

PubMed

Zahedi, Atena; On, Vincent; Lin, Sabrina C; Bays, Brett C; Omaiye, Esther; Bhanu, Bir; Talbot, Prue

2016-01-01

There is a foundational need for quality control tools in stem cell laboratories engaged in basic research, regenerative therapies, and toxicological studies. These tools require automated methods for evaluating cell processes and quality during in vitro passaging, expansion, maintenance, and differentiation. In this paper, an unbiased, automated high-content profiling toolkit, StemCellQC, is presented that non-invasively extracts information on cell quality and cellular processes from time-lapse phase-contrast videos. Twenty four (24) morphological and dynamic features were analyzed in healthy, unhealthy, and dying human embryonic stem cell (hESC) colonies to identify those features that were affected in each group. Multiple features differed in the healthy versus unhealthy/dying groups, and these features were linked to growth, motility, and death. Biomarkers were discovered that predicted cell processes before they were detectable by manual observation. StemCellQC distinguished healthy and unhealthy/dying hESC colonies with 96% accuracy by non-invasively measuring and tracking dynamic and morphological features over 48 hours. Changes in cellular processes can be monitored by StemCellQC and predictions can be made about the quality of pluripotent stem cell colonies. This toolkit reduced the time and resources required to track multiple pluripotent stem cell colonies and eliminated handling errors and false classifications due to human bias. StemCellQC provided both user-specified and classifier-determined analysis in cases where the affected features are not intuitive or anticipated. Video analysis algorithms allowed assessment of biological phenomena using automatic detection analysis, which can aid facilities where maintaining stem cell quality and/or monitoring changes in cellular processes are essential. In the future StemCellQC can be expanded to include other features, cell types, treatments, and differentiating cells.

Severe leptospirosis with multiple organ failure successfully treated by plasma exchange and high-volume hemofiltration.

PubMed

Bourquin, Vincent; Ponte, Belén; Hirschel, Bernard; Pugin, Jérôme; Martin, Pierre-Yves; Saudan, Patrick

2011-01-01

Background. Leptospirosis is a spirochetal zoonosis with complex clinical features including renal and liver failure. Case report. We report the case of a Swiss fisherman presenting with leptospirosis. After initial improvement, refractory septic shock and severe liver and kidney failure developed. The expected mortality was estimated at 90% with clinical scores. The patient underwent plasma exchanges and high-volume hemofiltration (HVHF) with complete recovery of hepatic and kidney functions. Discussion. Plasma exchanges and HVHF may confer survival benefit on patients with severe leptospirosis, refractory septic shock, and multiple-organ failure.

Coordinating Multiple Spacecraft Assets for Joint Science Campaigns

NASA Technical Reports Server (NTRS)

Estlin, Tara; Chien, Steve; Castano, Rebecca; Gaines, Daniel; de Granville, Charles; Doubleday, Josh; Anderson, Robert C.; Knight, Russell; Bornstein, Benjamin; Rabideau, Gregg;

An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

PubMed

Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

2017-08-17

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

On the multiple depots vehicle routing problem with heterogeneous fleet capacity and velocity

NASA Astrophysics Data System (ADS)

Hanum, F.; Hartono, A. P.; Bakhtiar, T.

2018-03-01

This current manuscript concerns with the optimization problem arising in a route determination of products distribution. The problem is formulated in the form of multiple depots and time windowed vehicle routing problem with heterogeneous capacity and velocity of fleet. Model includes a number of constraints such as route continuity, multiple depots availability and serving time in addition to generic constraints. In dealing with the unique feature of heterogeneous velocity, we generate a number of velocity profiles along the road segments, which then converted into traveling-time tables. An illustrative example of rice distribution among villages by bureau of logistics is provided. Exact approach is utilized to determine the optimal solution in term of vehicle routes and starting time of service.

Networking Multiple Autonomous Air and Ocean Vehicles for Oceanographic Research and Monitoring

NASA Astrophysics Data System (ADS)

McGillivary, P. A.; Borges de Sousa, J.; Rajan, K.

2013-12-01

Autonomous underwater and surface vessels (AUVs and ASVs) are coming into wider use as components of oceanographic research, including ocean observing systems. Unmanned airborne vehicles (UAVs) are now available at modest cost, allowing multiple UAVs to be deployed with multiple AUVs and ASVs. For optimal use good communication and coordination among vehicles is essential. We report on the use of multiple AUVs networked in communication with multiple UAVs. The UAVs are augmented by inferential reasoning software developed at MBARI that allows UAVs to recognize oceanographic fronts and change their navigation and control. This in turn allows UAVs to automatically to map frontal features, as well as to direct AUVs and ASVs to proceed to such features and conduct sampling via onboard sensors to provide validation for airborne mapping. ASVs can also act as data nodes for communication between UAVs and AUVs, as well as collecting data from onboard sensors, while AUVs can sample the water column vertically. This allows more accurate estimation of phytoplankton biomass and productivity, and can be used in conjunction with UAV sampling to determine air-sea flux of gases (e.g. CO2, CH4, DMS) affecting carbon budgets and atmospheric composition. In particular we describe tests in July 2013 conducted off Sesimbra, Portugal in conjunction with the Portuguese Navy by the University of Porto and MBARI with the goal of tracking large fish in the upper water column with coordinated air/surface/underwater measurements. A thermal gradient was observed in the infrared by a low flying UAV, which was used to dispatch an AUV to obtain ground truth to demonstrate the event-response capabilities using such autonomous platforms. Additional field studies in the future will facilitate integration of multiple unmanned systems into research vessel operations. The strength of hardware and software tools described in this study is to permit fundamental oceanographic measurements of both ocean and atmosphere over temporal and spatial scales that have previously been problematic. The methods demonstrated are particularly suited to the study of oceanographic fronts and for tracking and mapping oil spills or plankton blooms. With the networked coordination of multiple autonomous systems, individual components may be changed out while ocean observations continue, allowing coarse to fine spatial studies of hydrographic features over temporal dimensions that would otherwise be difficult, including diurnal and tidal periods. Constraints on these methods currently involve coordination of data archiving systems into shipboard operating systems, familiarization of oceanographers with these methods, and existing nearshore airspace use constraints on UAVs. An important outcome of these efforts is to understand the methodology for using multiple heterogeneous autonomous vehicles for targeted science exploration.

Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.

Using the storm water management model to predict urban headwater stream hydrological response to climate and land cover change

Treesearch

J.Y. Wu; J.R. Thompson; R.K. Kolka; K.J. Franz; T.W. Stewart

2013-01-01

Streams are natural features in urban landscapes that can provide ecosystem services for urban residents. However, urban streams are under increasing pressure caused by multiple anthropogenic impacts, including increases in human population and associated impervious surface area, and accelerated climate change. The ability to anticipate these changes and better...

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Exploration of available feature detection and identification systems and their performance on radiographs

NASA Astrophysics Data System (ADS)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

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

PubMed Central

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

2016-01-01

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

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

Szymanski, J. J.; Brumby, Steven P.; Pope, P. A.

Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniquesmore » to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.« less

SketchBio: a scientist's 3D interface for molecular modeling and animation.

PubMed

Waldon, Shawn M; Thompson, Peter M; Hahn, Patrick J; Taylor, Russell M

2014-10-30

Because of the difficulties involved in learning and using 3D modeling and rendering software, many scientists hire programmers or animators to create models and animations. This both slows the discovery process and provides opportunities for miscommunication. Working with multiple collaborators, a tool was developed (based on a set of design goals) to enable them to directly construct models and animations. SketchBio is presented, a tool that incorporates state-of-the-art bimanual interaction and drop shadows to enable rapid construction of molecular structures and animations. It includes three novel features: crystal-by-example, pose-mode physics, and spring-based layout that accelerate operations common in the formation of molecular models. Design decisions and their consequences are presented, including cases where iterative design was required to produce effective approaches. The design decisions, novel features, and inclusion of state-of-the-art techniques enabled SketchBio to meet all of its design goals. These features and decisions can be incorporated into existing and new tools to improve their effectiveness.

Multiple squamous hyperplastic-fibrous inflammatory polyps of the oesophagus: a new feature of eosinophilic oesophagitis?

PubMed

Mulder, D J; Gander, S; Hurlbut, D J; Soboleski, D A; Smith, R G; Justinich, C J

2009-09-01

This report describes the unusual case of a 12-year-old boy with multiple polyps in the oesophagus and concurrent eosinophilic oesophagitis (EoE). Polyps were of a fibrous-inflammatory composition featuring eosinophils, mast cells, hyperplastic epithelium and fibrosis, which are all features described with EoE. EoE is an increasingly recognised clinicopathological disorder characterised by large numbers of eosinophils infiltrating the oesophageal mucosa. Polyps in the oesophagus are rare, have not previously been associated with EoE, and may represent a new feature of the disease.

PROCAMS - A second generation multispectral-multitemporal data processing system for agricultural mensuration

NASA Technical Reports Server (NTRS)

Erickson, J. D.; Nalepka, R. F.

1976-01-01

PROCAMS (Prototype Classification and Mensuration System) has been designed for the classification and mensuration of agricultural crops (specifically small grains including wheat, rye, oats, and barley) through the use of data provided by Landsat. The system includes signature extension as a major feature and incorporates multitemporal as well as early season unitemporal approaches for using multiple training sites. Also addressed are partial cloud cover and cloud shadows, bad data points and lines, as well as changing sun angle and atmospheric state variations.

Spatial redistribution of radiation in flip-chip photodiodes based on InAsSbP/InAs double heterostructures

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

Zakgeim, A. L.; Il’inskaya, N. D.; Karandashev, S. A.

2017-02-15

The spatial distribution of equilibrium and nonequilibrium (including luminescent) IR (infrared) radiation in flip-chip photodiodes based on InAsSbP/InAs double heterostructures (λ{sub max} = 3.4 μm) is measured and analyzed; the structural features of the photodiodes, including the reflective properties of the ohmic contacts, are taken into account. Optical area enhancement due to multiple internal reflection in photodiodes with different geometric characteristics is estimated.

Toshiba TDF-500 High Resolution Viewing And Analysis System

NASA Astrophysics Data System (ADS)

Roberts, Barry; Kakegawa, M.; Nishikawa, M.; Oikawa, D.

1988-06-01

A high resolution, operator interactive, medical viewing and analysis system has been developed by Toshiba and Bio-Imaging Research. This system provides many advanced features including high resolution displays, a very large image memory and advanced image processing capability. In particular, the system provides CRT frame buffers capable of update in one frame period, an array processor capable of image processing at operator interactive speeds, and a memory system capable of updating multiple frame buffers at frame rates whilst supporting multiple array processors. The display system provides 1024 x 1536 display resolution at 40Hz frame and 80Hz field rates. In particular, the ability to provide whole or partial update of the screen at the scanning rate is a key feature. This allows multiple viewports or windows in the display buffer with both fixed and cine capability. To support image processing features such as windowing, pan, zoom, minification, filtering, ROI analysis, multiplanar and 3D reconstruction, a high performance CPU is integrated into the system. This CPU is an array processor capable of up to 400 million instructions per second. To support the multiple viewer and array processors' instantaneous high memory bandwidth requirement, an ultra fast memory system is used. This memory system has a bandwidth capability of 400MB/sec and a total capacity of 256MB. This bandwidth is more than adequate to support several high resolution CRT's and also the fast processing unit. This fully integrated approach allows effective real time image processing. The integrated design of viewing system, memory system and array processor are key to the imaging system. It is the intention to describe the architecture of the image system in this paper.

The mitochondrial ND1 m.3337G>A mutation associated to multiple mitochondrial DNA deletions in a patient with Wolfram syndrome and cardiomyopathy

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

Mezghani, Najla; Mnif, Mouna; Mkaouar-Rebai, Emna, E-mail: emna_mkaouar@mail2world.com

Highlights: {yields} We reported a patient with Wolfram syndrome and dilated cardiomyopathy. {yields} We detected the ND1 mitochondrial m.3337G>A mutation in 3 tested tissues (blood leukocytes, buccal mucosa and skeletal muscle). {yields} Long-range PCR amplification revealed the presence of multiple mitochondrial deletions in the skeletal muscle. {yields} The deletions remove several tRNA and protein-coding genes. -- Abstract: Wolfram syndrome (WFS) is a rare hereditary disorder also known as DIDMOAD (diabetes insipidus, diabetes mellitus, optic atrophy, and deafness). It is a heterogeneous disease and full characterization of all clinical and biological features of this disorder is difficult. The wide spectrum ofmore » clinical expression, affecting several organs and tissues, and the similarity in phenotype between patients with Wolfram syndrome and those with certain types of respiratory chain diseases suggests mitochondrial DNA (mtDNA) involvement in Wolfram syndrome patients. We report a Tunisian patient with clinical features of moderate Wolfram syndrome including diabetes, dilated cardiomyopathy and neurological complications. The results showed the presence of the mitochondrial ND1 m.3337G>A mutation in almost homoplasmic form in 3 tested tissues of the proband (blood leukocytes, buccal mucosa and skeletal muscle). In addition, the long-range PCR amplifications revealed the presence of multiple deletions of the mitochondrial DNA extracted from the patient's skeletal muscle removing several tRNA and protein-coding genes. Our study reported a Tunisian patient with clinical features of moderate Wolfram syndrome associated with cardiomyopathy, in whom we detected the ND1 m.3337G>A mutation with mitochondrial multiple deletions.« less

Pathologic Progression, Possible Origin, and Management of Multiple Primary Intracranial Neuroendocrine Carcinomas.

PubMed

Cao, Jingwei; Xu, Wenzhe; Du, Zhenhui; Sun, Bin; Li, Feng; Liu, Yuguang

2017-10-01

Primary intracranial neuroendocrine carcinomas (NECs) are extremely rare malignant tumors with no previous reports of multiple ones in the literatures. The clinical presentation, preoperative and reexamined magnetic resonance imaging findings, as well as histopathologic studies of a 56-year-old female subject with multiple intracranial NECs mimicking multiple intracranial meningiomas, who underwent 3 operations with left parietal craniotomy, right occipital parietal craniotomy, and left frontal craniotomy, separately and chronologically, are presented in this article. Noteworthy, the first and second tumors were confirmed as NECs exhibiting histologic characteristics of typical anaplastic meningiomas with features of whorl formation, while the third tumor was a typical NEC with features of organoid cancer nests. In other words, the first 2 lesions were diagnosed as meningioma as opposed to NEC. It was only after the third surgery that the pathology for the first 2 cases was reviewed and had a revised diagnosis. After the third surgical resection, the patient further received whole brain radiotherapy and systemic chemotherapy (temozolomide combined with YH-16). At her 10-month follow-up, the patient achieved a good outcome. Multiple primary intracranial NECs are extremely rare. The tumor might be of arachnoidal or leptomeningeal origin, with histologic patterns that might lead to transformation and/or progression. Maximal surgical resection is warranted for symptomatic mass effect. Postoperative adjuvant treatments including radiotherapy and chemotherapy should be a recommended therapeutic modality. Copyright © 2017 Elsevier Inc. All rights reserved.

Fast linear feature detection using multiple directional non-maximum suppression.

PubMed

Sun, C; Vallotton, P

2009-05-01

The capacity to detect linear features is central to image analysis, computer vision and pattern recognition and has practical applications in areas such as neurite outgrowth detection, retinal vessel extraction, skin hair removal, plant root analysis and road detection. Linear feature detection often represents the starting point for image segmentation and image interpretation. In this paper, we present a new algorithm for linear feature detection using multiple directional non-maximum suppression with symmetry checking and gap linking. Given its low computational complexity, the algorithm is very fast. We show in several examples that it performs very well in terms of both sensitivity and continuity of detected linear features.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

An integrated condition-monitoring method for a milling process using reduced decomposition features

NASA Astrophysics Data System (ADS)

Liu, Jie; Wu, Bo; Wang, Yan; Hu, Youmin

2017-08-01

Complex and non-stationary cutting chatter affects productivity and quality in the milling process. Developing an effective condition-monitoring approach is critical to accurately identify cutting chatter. In this paper, an integrated condition-monitoring method is proposed, where reduced features are used to efficiently recognize and classify machine states in the milling process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition, and Shannon power spectral entropy is calculated to extract features from the decomposed signals. Principal component analysis is adopted to reduce feature size and computational cost. With the extracted feature information, the probabilistic neural network model is used to recognize and classify the machine states, including stable, transition, and chatter states. Experimental studies are conducted, and results show that the proposed method can effectively detect cutting chatter during different milling operation conditions. This monitoring method is also efficient enough to satisfy fast machine state recognition and classification.

The clinico-radiological paradox of cognitive function and MRI burden of white matter lesions in people with multiple sclerosis: A systematic review and meta-analysis.

PubMed

Mollison, Daisy; Sellar, Robin; Bastin, Mark; Mollison, Denis; Chandran, Siddharthan; Wardlaw, Joanna; Connick, Peter

2017-01-01

Moderate correlation exists between the imaging quantification of brain white matter lesions and cognitive performance in people with multiple sclerosis (MS). This may reflect the greater importance of other features, including subvisible pathology, or methodological limitations of the primary literature. To summarise the cognitive clinico-radiological paradox and explore the potential methodological factors that could influence the assessment of this relationship. Systematic review and meta-analysis of primary research relating cognitive function to white matter lesion burden. Fifty papers met eligibility criteria for review, and meta-analysis of overall results was possible in thirty-two (2050 participants). Aggregate correlation between cognition and T2 lesion burden was r = -0.30 (95% confidence interval: -0.34, -0.26). Wide methodological variability was seen, particularly related to key factors in the cognitive data capture and image analysis techniques. Resolving the persistent clinico-radiological paradox will likely require simultaneous evaluation of multiple components of the complex pathology using optimum measurement techniques for both cognitive and MRI feature quantification. We recommend a consensus initiative to support common standards for image analysis in MS, enabling benchmarking while also supporting ongoing innovation.

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

Feasibility of an International Multiple Sclerosis Rehabilitation Data Repository

PubMed Central

Bradford, Elissa Held; Baert, Ilse; Finlayson, Marcia; Feys, Peter

2018-01-01

Abstract Background: Multiple sclerosis (MS) rehabilitation evidence is limited due to methodological factors, which may be addressed by a data repository. We describe the perceived challenges of, motivators for, interest in participating in, and key features of an international MS rehabilitation data repository. Methods: A multimethod sequential investigation was performed with the results of two focus groups, using nominal group technique, and study aims informing the development of an online questionnaire. Percentage agreement and key quotations illustrated questionnaire findings. Subgroup comparisons were made between clinicians and researchers and between participants in North America and Europe. Results: Rehabilitation professionals from 25 countries participated (focus groups: n = 21; questionnaire: n = 166). The top ten challenges (C) and motivators (M) identified by the focus groups were database control/management (C); ethical/legal concerns (C); data quality (C); time, effort, and cost (C); best practice (M); uniformity (C); sustainability (C); deeper analysis (M); collaboration (M); and identifying research needs (M). Percentage agreement with questionnaire statements regarding challenges to, motivators for, interest in, and key features of a successful repository was at least 80%, 85%, 72%, and 83%, respectively, across each group of statements. Questionnaire subgroup analysis revealed a few differences (P < .05), including that clinicians more strongly identified with improving best practice as a motivator. Conclusions: Findings support clinician and researcher interest in and potential for success of an international MS rehabilitation data repository if prioritized challenges and motivators are addressed and key features are included. PMID:29507539

Feasibility of an International Multiple Sclerosis Rehabilitation Data Repository: Perceived Challenges and Motivators for Sharing Data.

PubMed

Bradford, Elissa Held; Baert, Ilse; Finlayson, Marcia; Feys, Peter; Wagner, Joanne

2018-01-01

Multiple sclerosis (MS) rehabilitation evidence is limited due to methodological factors, which may be addressed by a data repository. We describe the perceived challenges of, motivators for, interest in participating in, and key features of an international MS rehabilitation data repository. A multimethod sequential investigation was performed with the results of two focus groups, using nominal group technique, and study aims informing the development of an online questionnaire. Percentage agreement and key quotations illustrated questionnaire findings. Subgroup comparisons were made between clinicians and researchers and between participants in North America and Europe. Rehabilitation professionals from 25 countries participated (focus groups: n = 21; questionnaire: n = 166). The top ten challenges (C) and motivators (M) identified by the focus groups were database control/management (C); ethical/legal concerns (C); data quality (C); time, effort, and cost (C); best practice (M); uniformity (C); sustainability (C); deeper analysis (M); collaboration (M); and identifying research needs (M). Percentage agreement with questionnaire statements regarding challenges to, motivators for, interest in, and key features of a successful repository was at least 80%, 85%, 72%, and 83%, respectively, across each group of statements. Questionnaire subgroup analysis revealed a few differences (P < .05), including that clinicians more strongly identified with improving best practice as a motivator. Findings support clinician and researcher interest in and potential for success of an international MS rehabilitation data repository if prioritized challenges and motivators are addressed and key features are included.

Long-range dismount activity classification: LODAC

NASA Astrophysics Data System (ADS)

Garagic, Denis; Peskoe, Jacob; Liu, Fang; Cuevas, Manuel; Freeman, Andrew M.; Rhodes, Bradley J.

2014-06-01

Continuous classification of dismount types (including gender, age, ethnicity) and their activities (such as walking, running) evolving over space and time is challenging. Limited sensor resolution (often exacerbated as a function of platform standoff distance) and clutter from shadows in dense target environments, unfavorable environmental conditions, and the normal properties of real data all contribute to the challenge. The unique and innovative aspect of our approach is a synthesis of multimodal signal processing with incremental non-parametric, hierarchical Bayesian machine learning methods to create a new kind of target classification architecture. This architecture is designed from the ground up to optimally exploit correlations among the multiple sensing modalities (multimodal data fusion) and rapidly and continuously learns (online self-tuning) patterns of distinct classes of dismounts given little a priori information. This increases classification performance in the presence of challenges posed by anti-access/area denial (A2/AD) sensing. To fuse multimodal features, Long-range Dismount Activity Classification (LODAC) develops a novel statistical information theoretic approach for multimodal data fusion that jointly models multimodal data (i.e., a probabilistic model for cross-modal signal generation) and discovers the critical cross-modal correlations by identifying components (features) with maximal mutual information (MI) which is efficiently estimated using non-parametric entropy models. LODAC develops a generic probabilistic pattern learning and classification framework based on a new class of hierarchical Bayesian learning algorithms for efficiently discovering recurring patterns (classes of dismounts) in multiple simultaneous time series (sensor modalities) at multiple levels of feature granularity.

Which ante mortem clinical features predict progressive supranuclear palsy pathology?

PubMed

Respondek, Gesine; Kurz, Carolin; Arzberger, Thomas; Compta, Yaroslau; Englund, Elisabet; Ferguson, Leslie W; Gelpi, Ellen; Giese, Armin; Irwin, David J; Meissner, Wassilios G; Nilsson, Christer; Pantelyat, Alexander; Rajput, Alex; van Swieten, John C; Troakes, Claire; Josephs, Keith A; Lang, Anthony E; Mollenhauer, Brit; Müller, Ulrich; Whitwell, Jennifer L; Antonini, Angelo; Bhatia, Kailash P; Bordelon, Yvette; Corvol, Jean-Christophe; Colosimo, Carlo; Dodel, Richard; Grossman, Murray; Kassubek, Jan; Krismer, Florian; Levin, Johannes; Lorenzl, Stefan; Morris, Huw; Nestor, Peter; Oertel, Wolfgang H; Rabinovici, Gil D; Rowe, James B; van Eimeren, Thilo; Wenning, Gregor K; Boxer, Adam; Golbe, Lawrence I; Litvan, Irene; Stamelou, Maria; Höglinger, Günter U

2017-07-01

Progressive supranuclear palsy (PSP) is a neuropathologically defined disease presenting with a broad spectrum of clinical phenotypes. To identify clinical features and investigations that predict or exclude PSP pathology during life, aiming at an optimization of the clinical diagnostic criteria for PSP. We performed a systematic review of the literature published since 1996 to identify clinical features and investigations that may predict or exclude PSP pathology. We then extracted standardized data from clinical charts of patients with pathologically diagnosed PSP and relevant disease controls and calculated the sensitivity, specificity, and positive predictive value of key clinical features for PSP in this cohort. Of 4166 articles identified by the database inquiry, 269 met predefined standards. The literature review identified clinical features predictive of PSP, including features of the following 4 functional domains: ocular motor dysfunction, postural instability, akinesia, and cognitive dysfunction. No biomarker or genetic feature was found reliably validated to predict definite PSP. High-quality original natural history data were available from 206 patients with pathologically diagnosed PSP and from 231 pathologically diagnosed disease controls (54 corticobasal degeneration, 51 multiple system atrophy with predominant parkinsonism, 53 Parkinson's disease, 73 behavioral variant frontotemporal dementia). We identified clinical features that predicted PSP pathology, including phenotypes other than Richardson's syndrome, with varying sensitivity and specificity. Our results highlight the clinical variability of PSP and the high prevalence of phenotypes other than Richardson's syndrome. The features of variant phenotypes with high specificity and sensitivity should serve to optimize clinical diagnosis of PSP. © 2017 International Parkinson and Movement Disorder Society. © 2017 International Parkinson and Movement Disorder Society.

Earpiece with sensors to measure/monitor multiple physiological variables

NASA Technical Reports Server (NTRS)

Cooper, Tommy G. (Inventor); Schulze, Arthur E. (Inventor)

2003-01-01

An apparatus and method for positioning sensors relative to one another and anatomic features in a non-invasive device for measuring and monitoring multiple physiological variables from a single site uses an earpiece incorporating a shielded pulse oximetry sensor (POS) having a miniaturized set of LEDs and photosensors configured for pulse oximetry measurements in the reflectance mode and located in the earpiece so as to position the POS against a rear wall of an ear canal. The earpiece also includes a thermopile of no larger than 7 mm. in diameter located on the earpiece to so as to position the thermopile past a second turn of an external auditory meatus so as to view the tympanic membrane. The thermopile includes a reference temperature sensor attached to its base for ambient temperature compensation.

Model of visual contrast gain control and pattern masking

NASA Technical Reports Server (NTRS)

Watson, A. B.; Solomon, J. A.

1997-01-01

We have implemented a model of contrast gain and control in human vision that incorporates a number of key features, including a contrast sensitivity function, multiple oriented bandpass channels, accelerating nonlinearities, and a devisive inhibitory gain control pool. The parameters of this model have been optimized through a fit to the recent data that describe masking of a Gabor function by cosine and Gabor masks [J. M. Foley, "Human luminance pattern mechanisms: masking experiments require a new model," J. Opt. Soc. Am. A 11, 1710 (1994)]. The model achieves a good fit to the data. We also demonstrate how the concept of recruitment may accommodate a variant of this model in which excitatory and inhibitory paths have a common accelerating nonlinearity, but which include multiple channels tuned to different levels of contrast.

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

NASA Astrophysics Data System (ADS)

Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

2018-02-01

Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2017-06-27

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

Use of whole-exome sequencing to determine the genetic basis of multiple mitochondrial respiratory chain complex deficiencies.

PubMed

Taylor, Robert W; Pyle, Angela; Griffin, Helen; Blakely, Emma L; Duff, Jennifer; He, Langping; Smertenko, Tania; Alston, Charlotte L; Neeve, Vivienne C; Best, Andrew; Yarham, John W; Kirschner, Janbernd; Schara, Ulrike; Talim, Beril; Topaloglu, Haluk; Baric, Ivo; Holinski-Feder, Elke; Abicht, Angela; Czermin, Birgit; Kleinle, Stephanie; Morris, Andrew A M; Vassallo, Grace; Gorman, Grainne S; Ramesh, Venkateswaran; Turnbull, Douglass M; Santibanez-Koref, Mauro; McFarland, Robert; Horvath, Rita; Chinnery, Patrick F

2014-07-02

Mitochondrial disorders have emerged as a common cause of inherited disease, but their diagnosis remains challenging. Multiple respiratory chain complex defects are particularly difficult to diagnose at the molecular level because of the massive number of nuclear genes potentially involved in intramitochondrial protein synthesis, with many not yet linked to human disease. To determine the molecular basis of multiple respiratory chain complex deficiencies. We studied 53 patients referred to 2 national centers in the United Kingdom and Germany between 2005 and 2012. All had biochemical evidence of multiple respiratory chain complex defects but no primary pathogenic mitochondrial DNA mutation. Whole-exome sequencing was performed using 62-Mb exome enrichment, followed by variant prioritization using bioinformatic prediction tools, variant validation by Sanger sequencing, and segregation of the variant with the disease phenotype in the family. Presumptive causal variants were identified in 28 patients (53%; 95% CI, 39%-67%) and possible causal variants were identified in 4 (8%; 95% CI, 2%-18%). Together these accounted for 32 patients (60% 95% CI, 46%-74%) and involved 18 different genes. These included recurrent mutations in RMND1, AARS2, and MTO1, each on a haplotype background consistent with a shared founder allele, and potential novel mutations in 4 possible mitochondrial disease genes (VARS2, GARS, FLAD1, and PTCD1). Distinguishing clinical features included deafness and renal involvement associated with RMND1 and cardiomyopathy with AARS2 and MTO1. However, atypical clinical features were present in some patients, including normal liver function and Leigh syndrome (subacute necrotizing encephalomyelopathy) seen in association with TRMU mutations and no cardiomyopathy with founder SCO2 mutations. It was not possible to confidently identify the underlying genetic basis in 21 patients (40%; 95% CI, 26%-54%). Exome sequencing enhances the ability to identify potential nuclear gene mutations in patients with biochemically defined defects affecting multiple mitochondrial respiratory chain complexes. Additional study is required in independent patient populations to determine the utility of this approach in comparison with traditional diagnostic methods.

IgD multiple myeloma: Clinical, biological features and prognostic value of the serum free light chain assay.

PubMed

Djidjik, R; Lounici, Y; Chergeulaïne, K; Berkouk, Y; Mouhoub, S; Chaib, S; Belhani, M; Ghaffor, M

2015-09-01

IgD multiple myeloma (MM) is a rare subtype of myeloma, it affects less than 2% of patients with MM. To evaluate the clinical and prognostic attributes of serum free light chains (sFLCs) analysis, we examined 17 cases of IgD MM. From 1998 to 2012, we obtained 1250 monoclonal gammapathies including 590 multiple myeloma and 17 patients had IgD MM. With preponderance of men patients with a mean age at diagnosis of: 59±12years. Patients with IgD MM have a short survival (Median survival=9months). The presenting features included: bone pain (75%), lymphadenopathy (16%), hepatomegaly (25%), splenomegaly (8%), associated AL amyloidosis (6%), renal impairment function (82%), infections (47%), hypercalcemia (37%) and anemia (93%). Serum electrophoresis showed a subtle M-spike (Mean=13.22±10g/L) in all patients associated to a hypogammaglobulinemia. There was an over-representation of Lambda light chain (65%); high serum β2-microglobulin in 91% and Bence Jones proteinuria was identified in 71%. The median rate of sFLCs κ was 19.05mg/L and 296.75mg/L for sFLCs λ. sFLCR was abnormal in 93% of patients and it showed concordance between baseline sFLCR and the survival (P=0.034). The contribution of FLC assay is crucial for the prognosis of patients with IgD MM. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Machine Learning Approach for Classifying Multiple Sclerosis Courses by Combining Clinical Data with Lesion Loads and Magnetic Resonance Metabolic Features.

PubMed

Ion-Mărgineanu, Adrian; Kocevar, Gabriel; Stamile, Claudio; Sima, Diana M; Durand-Dubief, Françoise; Van Huffel, Sabine; Sappey-Marinier, Dominique

2017-01-01

Purpose: The purpose of this study is classifying multiple sclerosis (MS) patients in the four clinical forms as defined by the McDonald criteria using machine learning algorithms trained on clinical data combined with lesion loads and magnetic resonance metabolic features. Materials and Methods: Eighty-seven MS patients [12 Clinically Isolated Syndrome (CIS), 30 Relapse Remitting (RR), 17 Primary Progressive (PP), and 28 Secondary Progressive (SP)] and 18 healthy controls were included in this study. Longitudinal data available for each MS patient included clinical (e.g., age, disease duration, Expanded Disability Status Scale), conventional magnetic resonance imaging and spectroscopic imaging. We extract N -acetyl-aspartate (NAA), Choline (Cho), and Creatine (Cre) concentrations, and we compute three features for each spectroscopic grid by averaging metabolite ratios (NAA/Cho, NAA/Cre, Cho/Cre) over good quality voxels. We built linear mixed-effects models to test for statistically significant differences between MS forms. We test nine binary classification tasks on clinical data, lesion loads, and metabolic features, using a leave-one-patient-out cross-validation method based on 100 random patient-based bootstrap selections. We compute F1-scores and BAR values after tuning Linear Discriminant Analysis (LDA), Support Vector Machines with gaussian kernel (SVM-rbf), and Random Forests. Results: Statistically significant differences were found between the disease starting points of each MS form using four different response variables: Lesion Load, NAA/Cre, NAA/Cho, and Cho/Cre ratios. Training SVM-rbf on clinical and lesion loads yields F1-scores of 71-72% for CIS vs. RR and CIS vs. RR+SP, respectively. For RR vs. PP we obtained good classification results (maximum F1-score of 85%) after training LDA on clinical and metabolic features, while for RR vs. SP we obtained slightly higher classification results (maximum F1-score of 87%) after training LDA and SVM-rbf on clinical, lesion loads and metabolic features. Conclusions: Our results suggest that metabolic features are better at differentiating between relapsing-remitting and primary progressive forms, while lesion loads are better at differentiating between relapsing-remitting and secondary progressive forms. Therefore, combining clinical data with magnetic resonance lesion loads and metabolic features can improve the discrimination between relapsing-remitting and progressive forms.

Familial endocrine myxolentiginosis.

PubMed

Panossian, D H; Marais, G E; Marais, H J

1995-11-01

We present an unusual case of a left atrial myxoma as a feature of a familial mesoectodermal disorder and review the literature. The new term "familial endocrine myxolentiginosis" is proposed, which is descriptive of the major clinical components of the syndrome. Myriad features of this disorder include (1) cardiac myxomas; (2) cutaneous myxomas; (3) multiple lentigines or blue nevi, particularly of the head and neck; (4) bilateral primary pigmented nodular adrenocortical hyperplasia; (5) unusual testicular tumors; (6) pituitary tumors; (7) myxoid fibroadenomas of the breast; (8) myxomatous disorder of the stroma of the breast; (9) ductal adenoma of the breast; and (10) psammomatous melanotic schwannoma. A tentative diagnosis is suggested by identifying two features and a definitive diagnosis is made by three or more features. The clinical and pathologic features of cardiac myxoma in familial endocrine myxolentiginosis are identical to those of familial cardiac myxoma: age < 40 years, atypical locations, multicentric origins, and recurrent presentations. A Venn diagram classification for cardiac myxomas is proposed. We include photographic, echocardiographic, biopsy, and adrenal computerized tomography documentation in our patient. Recognition of this disorder is important because of its clinical, surgical, and genetic implications. The availability of transesophageal echocardiographic technology should allow early diagnosis of this underdiagnosed entity. Clinicians should consider this entity in the differential diagnosis of their patients with any one of these manifestations.

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).

More are better, but the details matter: combinations of multiple Fresnel zone plates for improved resolution and efficiency in X-ray microscopy

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

Li, Kenan; Jacobsen, Chris

Fresnel zone plates used for X-ray nanofocusing face high-aspect-ratio nanofabrication challenges in combining narrow transverse features (for high spatial resolution) along with extended optical modulation along the X-ray beam direction (to improve efficiency). The stacking of multiple Fresnel zone plates along the beam direction has already been shown to offer improved characteristics of resolution and efficiency when compared with thin single zone plates. Using multislice wave propagation simulation methods, here a number of new schemes for the stacking of multiple Fresnel zone plates are considered. These include consideration of optimal thickness and spacing in the axial direction, and methods tomore » capture a fraction of the light otherwise diffracted into unwanted orders, and instead bring it into the desired first-order focus. In conclusion, the alignment tolerances for stacking multiple Fresnel zone plates are also considered.« less

Dynamical configurations of celestial systems comprised of multiple irregular bodies

NASA Astrophysics Data System (ADS)

Jiang, Yu; Zhang, Yun; Baoyin, Hexi; Li, Junfeng

2016-09-01

This manuscript considers the main features of the nonlinear dynamics of multiple irregular celestial body systems. The gravitational potential, static electric potential, and magnetic potential are considered. Based on the three established potentials, we show that three conservative values exist for this system, including a Jacobi integral. The equilibrium conditions for the system are derived and their stability analyzed. The equilibrium conditions of a celestial system comprised of n irregular bodies are reduced to 12n - 9 equations. The dynamical results are applied to simulate the motion of multiple-asteroid systems. The simulation is useful for the study of the stability of multiple irregular celestial body systems and for the design of spacecraft orbits to triple-asteroid systems discovered in the solar system. The dynamical configurations of the five triple-asteroid systems 45 Eugenia, 87 Sylvia, 93 Minerva, 216 Kleopatra, and 136617 1994CC, and the six-body system 134340 Pluto are calculated and analyzed.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

PubMed

Bolleman, Jerven T; Mungall, Christopher J; Strozzi, Francesco; Baran, Joachim; Dumontier, Michel; Bonnal, Raoul J P; Buels, Robert; Hoehndorf, Robert; Fujisawa, Takatomo; Katayama, Toshiaki; Cock, Peter J A

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

DOE PAGES

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco; ...

2016-06-13

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

Multiple cueing dissociates location- and feature-based repetition effects

PubMed Central

Hu, Kesong; Zhan, Junya; Li, Bingzhao; He, Shuchang; Samuel, Arthur G.

2014-01-01

There is an extensive literature on the phenomenon of inhibition of return (IOR): When attention is drawn to a peripheral location and then removed, response time is delayed if a target appears in the previously inspected location. Recent research suggests that non-spatial attribute repetition (i.e., if a target shares a feature like color with the earlier, cueing, stimulus) can have a similar inhibitory effect, at least when the target appears in the previously cued location. What remains unknown is whether location- and feature-based inhibitory effects can be dissociated. In the present study, we used a multiple cueing approach to investigate the properties of location- and feature-based repetition effects. In two experiments (detection, and discrimination), location-based IOR was absent but feature-based inhibition was consistently observed. Thus, the present results indicate that feature- and location-based inhibitory effects are dissociable. The results also provide support for the view that the attentional consequences of multiple cues reflect the overall center of gravity of the cues. We suggest that the repetition costs associated with feature and location repetition may be best understood as a consequence of the pattern of activation for object files associated with the stimuli present in the displays. PMID:24907677

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation

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

Bolleman, Jerven T.; Mungall, Christopher J.; Strozzi, Francesco

Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. In this paper, we have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned “omics” areas. Using the same data formatmore » to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe – and potentially merge – sequence annotations from multiple sources. Finally, data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores.« less

Test-retest reliability of the multiple sleep latency test in narcolepsy without cataplexy and idiopathic hypersomnia.

PubMed

Trotti, Lynn Marie; Staab, Beth A; Rye, David B

2013-08-15

Differentiation of narcolepsy without cataplexy from idiopathic hypersomnia relies entirely upon the multiple sleep latency test (MSLT). However, the test-retest reliability for these central nervous system hypersomnias has never been determined. Patients with narcolepsy without cataplexy, idiopathic hypersomnia, and physiologic hypersomnia who underwent two diagnostic multiple sleep latency tests were identified retrospectively. Correlations between the mean sleep latencies on the two studies were evaluated, and we probed for demographic and clinical features associated with reproducibility versus change in diagnosis. Thirty-six patients (58% women, mean age 34 years) were included. Inter -test interval was 4.2 ± 3.8 years (range 2.5 months to 16.9 years). Mean sleep latencies on the first and second tests were 5.5 (± 3.7 SD) and 7.3 (± 3.9) minutes, respectively, with no significant correlation (r = 0.17, p = 0.31). A change in diagnosis occurred in 53% of patients, and was accounted for by a difference in the mean sleep latency (N = 15, 42%) or the number of sleep onset REM periods (N = 11, 31%). The only feature predictive of a diagnosis change was a history of hypnagogic or hypnopompic hallucinations. The multiple sleep latency test demonstrates poor test-retest reliability in a clinical population of patients with central nervous system hypersomnia evaluated in a tertiary referral center. Alternative diagnostic tools are needed.

Uncovering multiple pathways to substance use: a comparison of methods for identifying population subgroups.

PubMed

Dierker, Lisa; Rose, Jennifer; Tan, Xianming; Li, Runze

2010-12-01

This paper describes and compares a selection of available modeling techniques for identifying homogeneous population subgroups in the interest of informing targeted substance use intervention. We present a nontechnical review of the common and unique features of three methods: (a) trajectory analysis, (b) functional hierarchical linear modeling (FHLM), and (c) decision tree methods. Differences among the techniques are described, including required data features, strengths and limitations in terms of the flexibility with which outcomes and predictors can be modeled, and the potential of each technique for helping to inform the selection of targets and timing of substance intervention programs.

Classifying four-category visual objects using multiple ERP components in single-trial ERP.

PubMed

Qin, Yu; Zhan, Yu; Wang, Changming; Zhang, Jiacai; Yao, Li; Guo, Xiaojuan; Wu, Xia; Hu, Bin

2016-08-01

Object categorization using single-trial electroencephalography (EEG) data measured while participants view images has been studied intensively. In previous studies, multiple event-related potential (ERP) components (e.g., P1, N1, P2, and P3) were used to improve the performance of object categorization of visual stimuli. In this study, we introduce a novel method that uses multiple-kernel support vector machine to fuse multiple ERP component features. We investigate whether fusing the potential complementary information of different ERP components (e.g., P1, N1, P2a, and P2b) can improve the performance of four-category visual object classification in single-trial EEGs. We also compare the classification accuracy of different ERP component fusion methods. Our experimental results indicate that the classification accuracy increases through multiple ERP fusion. Additional comparative analyses indicate that the multiple-kernel fusion method can achieve a mean classification accuracy higher than 72 %, which is substantially better than that achieved with any single ERP component feature (55.07 % for the best single ERP component, N1). We compare the classification results with those of other fusion methods and determine that the accuracy of the multiple-kernel fusion method is 5.47, 4.06, and 16.90 % higher than those of feature concatenation, feature extraction, and decision fusion, respectively. Our study shows that our multiple-kernel fusion method outperforms other fusion methods and thus provides a means to improve the classification performance of single-trial ERPs in brain-computer interface research.

A Paleocene penguin from New Zealand substantiates multiple origins of gigantism in fossil Sphenisciformes.

PubMed

Mayr, Gerald; Scofield, R Paul; De Pietri, Vanesa L; Tennyson, Alan J D

2017-12-12

One of the notable features of penguin evolution is the occurrence of very large species in the early Cenozoic, whose body size greatly exceeded that of the largest extant penguins. Here we describe a new giant species from the late Paleocene of New Zealand that documents the very early evolution of large body size in penguins. Kumimanu biceae, n. gen. et sp. is larger than all other fossil penguins that have substantial skeletal portions preserved. Several plesiomorphic features place the new species outside a clade including all post-Paleocene giant penguins. It is phylogenetically separated from giant Eocene and Oligocene penguin species by various smaller taxa, which indicates multiple origins of giant size in penguin evolution. That a penguin rivaling the largest previously known species existed in the Paleocene suggests that gigantism in penguins arose shortly after these birds became flightless divers. Our study therefore strengthens previous suggestions that the absence of very large penguins today is likely due to the Oligo-Miocene radiation of marine mammals.

Cancer stem cells and differentiation therapy.

PubMed

Jin, Xiong; Jin, Xun; Kim, Hyunggee

2017-10-01

Cancer stem cells can generate tumors from only a small number of cells, whereas differentiated cancer cells cannot. The prominent feature of cancer stem cells is its ability to self-renew and differentiate into multiple types of cancer cells. Cancer stem cells have several distinct tumorigenic abilities, including stem cell signal transduction, tumorigenicity, metastasis, and resistance to anticancer drugs, which are regulated by genetic or epigenetic changes. Like normal adult stem cells involved in various developmental processes and tissue homeostasis, cancer stem cells maintain their self-renewal capacity by activating multiple stem cell signaling pathways and inhibiting differentiation signaling pathways during cancer initiation and progression. Recently, many studies have focused on targeting cancer stem cells to eradicate malignancies by regulating stem cell signaling pathways, and products of some of these strategies are in preclinical and clinical trials. In this review, we describe the crucial features of cancer stem cells related to tumor relapse and drug resistance, as well as the new therapeutic strategy to target cancer stem cells named "differentiation therapy."

Multiple Representations-Based Face Sketch-Photo Synthesis.

PubMed

Peng, Chunlei; Gao, Xinbo; Wang, Nannan; Tao, Dacheng; Li, Xuelong; Li, Jie

2016-11-01

Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.

A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

NASA Technical Reports Server (NTRS)

Kautzmann, Frank N., III

1988-01-01

Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

Correction to: Comparison of multiple transcriptomes exposes unified and divergent features of quiescent and activated skeletal muscle stem cells.

PubMed

Pietrosemoli, Natalia; Mella, Sébastien; Yennek, Siham; Baghdadi, Meryem B; Sakai, Hiroshi; Sambasivan, Ramkumar; Pala, Francesca; Di Girolamo, Daniela; Tajbakhsh, Shahragim

2018-06-06

After publication of this article [1], the authors noted that the legends for supplementary files Figures S3 and S4 were truncated in the production process, therefore lacking some information concerning these Figures. The complete legends are included in this Correction. The authors apologize for any inconvenience that this might have caused.

Jaffe-Campanacci syndrome.

PubMed

Al-Rikabi, Ammar C; Ramaswamy, Jyothi C; Bhat, Venkatraman V

2005-01-01

This case report describes the clinical, radiological and histopathological features of the Jaffe-Campanacci syndrome as seen in a 6-year-old Qatari male patient who was initially misdiagnosed as a case of systemic neurofibromatosis. Our case has all the diagnostic stigmata of Jaffe-Campanacci syndrome as described in the literature and these include cafe au lait macules, skeletal deformities and multiple histologically confirmed non-ossifying fibromas of the long bones.

Learning to Look beyond the Boundaries of Representation: Using Technology to Examine Teaching (Overview for a Digital Exhibition: Learning from the Practice of Teaching)

ERIC Educational Resources Information Center

Hatch, Thomas; Grossman, Pam

2009-01-01

Leading a classroom discussion involves multiple components, including establishing norms for participation, assisting students in engaging in careful readings of text ahead of time, and modeling features of academic discourse. In other work, Grossman and her colleagues refer to this as the "decomposition" of practice--breaking down complex…

The CHAT System: An OS/360 MVT Time-Sharing Subsystem for Displays and Teletype. Technical Progress Report.

ERIC Educational Resources Information Center

Schultz, Gary D.

The design and operation of a time-sharing monitor are described. It runs under OS/360 MVT that supports multiple application program interaction with operators of CRT (cathode ray tube) display stations and of a teletype. Key design features discussed include: 1) an interface allowing application programs to be coded in either PL/I or assembler…

Multimodal Sparse Coding for Event Detection

DTIC Science & Technology

2015-10-13

classification tasks based on single modality. We present multimodal sparse coding for learning feature representations shared across multiple modalities...The shared representa- tions are applied to multimedia event detection (MED) and evaluated in compar- ison to unimodal counterparts, as well as other...and video tracks from the same multimedia clip, we can force the two modalities to share a similar sparse representation whose benefit includes robust

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,…

Feature point based 3D tracking of multiple fish from multi-view images

PubMed Central

Qian, Zhi-Ming

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly. PMID:28665966

Feature point based 3D tracking of multiple fish from multi-view images.

PubMed

Qian, Zhi-Ming; Chen, Yan Qiu

2017-01-01

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly.

Multiple essential MT1-MMP functions in tooth root formation, dentinogenesis, and tooth eruption

PubMed Central

Wimer, H.F.; Yamada, S.S.; Yang, T.; Holmbeck, K.; Foster, B.L.

2016-01-01

Membrane-type matrix metalloproteinase 1 (MT1-MMP) is a transmembrane zinc-endopeptidase that breaks down extracellular matrix components, including several collagens, during tissue development and physiological remodeling. MT1-MMP-deficient mice (MT1-MMP−/−) feature severe defects in connective tissues, such as impaired growth, osteopenia, fibrosis, and conspicuous loss of molar tooth eruption and root formation. In order to define the functions of MT1-MMP during root formation and tooth eruption, we analyzed the development of teeth and surrounding tissues in the absence of MT1-MMP. In situ hybridization showed that MT1-MMP was widely expressed in cells associated with teeth and surrounding connective tissues during development. Multiple defects in dentoalveolar tissues were associated with loss of MT1-MMP. Root formation was inhibited by defective structure and function of Hertwig's epithelial root sheath (HERS). However, no defect was found in creation of the eruption pathway, suggesting that tooth eruption was hampered by lack of alveolar bone modeling/remodeling coincident with reduced periodontal ligament (PDL) formation and integration with the alveolar bone. Additionally, we identified a significant defect in dentin formation and mineralization associated with the loss of MT1-MMP. To segregate these multiple defects and trace their cellular origin, conditional ablation of MT1-MMP was performed in epithelia and mesenchyme. Mice featuring selective loss of MT1-MMP activity in the epithelium were indistinguishable from wild type mice, and importantly, featured a normal HERS structure and molar eruption. In contrast, selective knock-out of MT1-MMP in Osterix-expressing mesenchymal cells, including osteoblasts and odontoblasts, recapitulated major defects from the global knock-out including altered HERS structure, short roots, defective dentin formation and mineralization, and reduced alveolar bone formation, although molars were able to erupt. These data indicate that MT1-MMP activity in the dental mesenchyme, and not in epithelial-derived HERS, is essential for proper tooth root formation and eruption. In summary, our studies point to an indispensable role for MT1-MMP-mediated matrix remodeling in tooth eruption through effects on bone formation, soft tissue remodeling and organization of the follicle/PDL region. PMID:26780723

Tracker Toolkit

NASA Technical Reports Server (NTRS)

Lewis, Steven J.; Palacios, David M.

2013-01-01

This software can track multiple moving objects within a video stream simultaneously, use visual features to aid in the tracking, and initiate tracks based on object detection in a subregion. A simple programmatic interface allows plugging into larger image chain modeling suites. It extracts unique visual features for aid in tracking and later analysis, and includes sub-functionality for extracting visual features about an object identified within an image frame. Tracker Toolkit utilizes a feature extraction algorithm to tag each object with metadata features about its size, shape, color, and movement. Its functionality is independent of the scale of objects within a scene. The only assumption made on the tracked objects is that they move. There are no constraints on size within the scene, shape, or type of movement. The Tracker Toolkit is also capable of following an arbitrary number of objects in the same scene, identifying and propagating the track of each object from frame to frame. Target objects may be specified for tracking beforehand, or may be dynamically discovered within a tripwire region. Initialization of the Tracker Toolkit algorithm includes two steps: Initializing the data structures for tracked target objects, including targets preselected for tracking; and initializing the tripwire region. If no tripwire region is desired, this step is skipped. The tripwire region is an area within the frames that is always checked for new objects, and all new objects discovered within the region will be tracked until lost (by leaving the frame, stopping, or blending in to the background).

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels

PubMed Central

Hyun, Seung Won; Wong, Weng Kee

2016-01-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs. PMID:26565557

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels.

PubMed

Hyun, Seung Won; Wong, Weng Kee

2015-11-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs.

Severe impulsiveness as the primary manifestation of multiple sclerosis in a young female.

PubMed

Lopez-Meza, Elmer; Corona-Vazquez, Teresa; Ruano-Calderon, Luis A; Ramirez-Bermudez, Jesus

2005-12-01

Severe impulsiveness in the absence of apparent neurological signs has rarely been reported as a clinical presentation of multiple sclerosis (MS). An 11-year-old female developed progressive and sustained personality disturbances including disinhibition, hypersexuality, drug abuse, aggressiveness and suicide attempts, without neurological signs. She was given several unsuccessful psychopharmacological and psychotherapeutic interventions. At age 21, a diagnosis of MS was made, confirmed by imaging, laboratory and neurophysiological studies. Although unusual, MS may produce pure neurobehavioral disturbances. In the present case, widespread demyelinization produced a complex behavioral disorder, with features compatible with orbitofrontal and Klüver-Bucy syndromes.

Angiostrongylus vasorum Causing Severe Granulomatous Hepatitis with Concurrent Multiple Acquired PSS.

PubMed

Cook, Simon; Priestnall, Simon L; Blake, Damer; Meeson, Richard L

2015-01-01

A 14 mo old female Jack Russell terrier presented with a 12 hr history of vomiting and inappetence. She was subsequently diagnosed with multiple acquired portosystemic shunts during an exploratory celiotomy. Gross and histopathological hepatic abnormalities were consistent with chronic disease, including features suggestive of portal hypertension that was potentially caused by migrating and resident Angiostrongylus vasorum larvae. Fecal analysis and polymerase chain reaction of hepatic tissue confirmed the presence of Angiostrongylus vasorum . The dog recovered clinically following empirical treatment and supportive care. A lack of parasite burden was confirmed 9 wk postdiagnosis; however, serum biochemical analysis at that time was suggestive of ongoing hepatic dysfunction.

Monoterpene and sesquiterpene synthases and the origin of terpene skeletal diversity in plants.

PubMed

Degenhardt, Jörg; Köllner, Tobias G; Gershenzon, Jonathan

2009-01-01

The multitude of terpene carbon skeletons in plants is formed by enzymes known as terpene synthases. This review covers the monoterpene and sesquiterpene synthases presenting an up-to-date list of enzymes reported and evidence for their ability to form multiple products. The reaction mechanisms of these enzyme classes are described, and information on how terpene synthase proteins mediate catalysis is summarized. Correlations between specific amino acid motifs and terpene synthase function are described, including an analysis of the relationships between active site sequence and cyclization type and a discussion of whether specific protein features might facilitate multiple product formation.

Particle capture device

DOEpatents

Jayne, John T.; Worsnop, Douglas R.

2016-02-23

In example embodiments, particle collection efficiency in aerosol analyzers and other particle measuring instruments is improved by a particle capture device that employs multiple collisions to decrease momentum of particles until the particles are collected (e.g., vaporized or come to rest). The particle collection device includes an aperture through which a focused particle beam enters. A collection enclosure is coupled to the aperture and has one or more internal surfaces against which particles of the focused beam collide. One or more features are employed in the collection enclosure to promote particles to collide multiple times within the enclosure, and thereby be vaporized or come to rest, rather than escape through the aperture.

Polyradiculopathies from schwannomatosis.

PubMed

Jia, Yuxia; Kraus, James A; Reddy, Hasini; Groff, Michael; Wong, Eric T

2011-01-01

We describe a case of schwannomatosis presenting as radicular pain and numbness in multiple radicular nerve distributions. There were multiple peripheral nerve tumors detected by magnetic resonance imaging (MRI) at the left vestibular nerve, cauda equina, right radial nerve, thoracic paraspinal nerve, and brachial plexi. Several resected tumors have features of schwannomas, including hypercellular Antoni A areas, hypocellular Antoni B areas, Verocay bodies, and hyalinized blood vessels. The specimens are also positive for immunohistochemical staining for INI1 with diffuse nuclear staining. The findings are consistent with sporadic form of schwannomatosis. This case highlights the importance of using MRI and INI1 immunohistochemistry to differentiate familial schwannomatosis, neurofibromatosis 2 (NF2)-associated schwannomatosis, and sporadic schwannomatosis.

Castleman's Disease: An Interesting Cause of Hematuria.

PubMed

Tolofari, Sotonye Karl; Chow, Wai-Man; Hussain, Basharat

2015-03-01

Castleman's disease is a rare benign lymphoproliferative disorder, characterized by benign growths of the lymph node tissue. It is associated with a number of malignancies, including Kaposi sarcoma, non-Hodgkin's and Hodgkins lymphoma, and POEMS syndrome. This report describes the case of a 38 year old gentleman, presenting with painless hematuria. Initial investigations, including flexible cystoscopy were unremarkable. However, subsequent imaging including CT Urogram and MR pelvis revealed multiple prevesical lesions. Histology obtained from excision biopsy revealed histological features consistent with Castleman's disease. In this report we discuss the nature, presentation and treatment modalities of this rare condition.

Neurologic and developmental features of the Smith-Magenis syndrome (del 17p11.2).

PubMed

Gropman, Andrea L; Duncan, Wallace C; Smith, Ann C M

2006-05-01

The Smith-Magenis syndrome is a rare, complex multisystemic disorder featuring, mental retardation and multiple congenital anomalies caused by a heterozygous interstitial deletion of chromosome 17p11.2. The phenotype of Smith-Magenis syndrome is characterized by a distinct pattern of features including infantile hypotonia, generalized complacency and lethargy in infancy, minor skeletal (brachycephaly, brachydactyly) and craniofacial features, ocular abnormalities, middle ear and laryngeal abnormalities including hoarse voice, as well as marked early expressive speech and language delays, psychomotor and growth retardation, and a 24-hour sleep disturbance. A striking neurobehavioral pattern of stereotypies, hyperactivity, polyembolokoilamania, onychotillomania, maladaptive and self-injurious and aggressive behavior is observed with increasing age. The diagnosis of Smith-Magenis syndrome is based upon the clinical recognition of a constellation of physical, developmental, and behavioral features in combination with a sleep disorder characterized by inverted circadian rhythm of melatonin secretion. Many of the features of Smith-Magenis syndrome are subtle in infancy and early childhood, and become more recognizable with advancing age. Infants are described as looking "cherubic" with a Down syndrome-like appearance, whereas with age the facial appearance is that of relative prognathism. Early diagnosis requires awareness of the often subtle clinical and neurobehavioral phenotype of the infant period. Speech delay with or without hearing loss is common. Most children are diagnosed in mid-childhood when the features of the disorder are most recognizable and striking. While improvements in cytogenetic analysis help to bring cases to clinical recognition at an earlier age, this review seeks to increase clinical awareness about Smith-Magenis syndrome by presenting the salient features observed at different ages including descriptions of the neurologic and behavioral features. Detailed review of the circadian rhythm disturbance unique to Smith-Magenis syndrome is presented. Suggestions for management of the behavioral and sleep difficulties are discussed in the context of the authors' personal experience in the setting of an ongoing Smith-Magenis syndrome natural history study.

Structure of Saturn's Rings from Cassini Diametric Radio Occultations

NASA Astrophysics Data System (ADS)

Marouf, E.; French, R.; Rappaport, N.; Kliore, A.; Flasar, M.; Nagy, A.; McGhee, C.; Schinder, P.; Anabtawi, A.; Asmar, S.; Barbinis, E.; Fleischman, D.; Goltz, G.; Johnston, D.; Rochblatt, D.; Thomson, F.; Wong, K.

2005-08-01

Cassini orbits around Saturn were designed to provide eight optimized radio occultation observations of Saturn's rings during summer, 2005. Three monochromatic radio signals (0.94, 3.6, and 13 cm-wavelength) were transmitted by Cassini through the rings and observed at multiple stations of the NASA Deep Space Network. A rich data set has been collected. Detailed structure of Ring B is revealed for the first time, including multi-feature dense ''core'' ˜ 6,000 km wide of normal optical depth > 4.3, a ˜ 5,500 km region of oscillations in optical depth ( ˜ 1.7 to ˜ 3.4) over characteristic radial scales of few hundred kilometers interior to the core, and a ˜ 5,000 km region exterior to the core of similar nature but smaller optical depth fluctuation ( ˜ 2.2 to ˜ 3.3). The innermost ˜ 7,000 km region is the thinnest (mean optical depth ˜ 1.2), and includes two unusually uniform regions and a prominent density wave. With few exceptions, the structure is nearly identical for the three radio signals (when detectable), indicating that Ring B is relatively devoid of centimeters and smaller size particles. The structure is largely circularly symmetric, except for radius > ˜ 116,600 km. In Ring A, numerous (> 40) density waves are clearly observed at multiple longitudes, different average background optical depth is observed among different occultations suggesting that the azimuthal asymmetry extends over most Ring A, and strong dependence of the observed structure on wavelength implies increase in the abundance of centimeter and smaller size particles with increasing radius. Multiple longitude observations of Ring C and the Cassini Division structure reveal remarkable variability of gaps and their embedded narrow eccentric ringlets, and a wake/wave like feature interior to the gap at ˜ 118,200 km (embedded moonlet?). Wavelength dependent structure of Ring C implies abundance of centimeter size particles everywhere and sorting by size within dense embedded features.

Origin of the Hadži ABC structure: An ab initio study

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

Van Hoozen, Brian L.; Petersen, Poul B.

2015-11-14

Medium and strong hydrogen bonds are well known to give rise to broad features in the vibrational spectrum often spanning several hundred wavenumbers. In some cases, these features can span over 1000 cm{sup −1} and even contain multiple broad peaks. One class of strongly hydrogen-bonded dimers that includes many different phosphinic, phosphoric, sulfinic, and selenic acid homodimers exhibits a three-peaked structure over 1500 cm{sup −1} broad. This unusual feature is often referred to as the Hadži ABC structure. The origin of this feature has been debated since its discovery in the 1950s. Only a couple of theoretical studies have attemptedmore » to interpret the origin of this feature; however, no previous study has been able to reproduce this feature from first principles. Here, we present the first ab initio calculation of the Hadži ABC structure. Using a reduced dimensionality calculation that includes four vibrational modes, we are able to reproduce the three-peak structure and much of the broadness of the feature. Our results indicate that Fermi resonances of the in-plane bend, out-of-plane bend, and combination of these bends play significant roles in explaining this feature. Much of the broadness of the feature and the ability of the OH stretch mode to couple with many overtone bending modes are captured by including an adiabatically separated dimer stretch mode in the model. This mode modulates the distance between the monomer units and accordingly the strength of the hydrogen-bonds causing the OH stretch frequency to shift from 2000 to 3000 cm{sup −1}. Using this model, we were also able to reproduce the vibrational spectrum of the deuterated isotopologue which consists of a single 500 cm{sup −1} broad feature. Whereas previous empirical studies have asserted that Fermi resonances contribute very little to this feature, our study indicates that while not appearing as a separate peak, a Fermi resonance of the in-plane bend contributes substantially to the feature.« less

Polar Expansion Dynamics in the Plant Kingdom: A Diverse and Multifunctional Journey on the Path to Pollen Tubes

PubMed Central

Domozych, David S.; Fujimoto, Chelsea; LaRue, Therese

2013-01-01

Polar expansion is a widespread phenomenon in plants spanning all taxonomic groups from the Charophycean Green Algae to pollen tubes in Angiosperms and Gymnosperms. Current data strongly suggests that many common features are shared amongst cells displaying polar growth mechanics including changes to the structural features of localized regions of the cell wall, mobilization of targeted secretion mechanisms, employment of the actin cytoskeleton for directing secretion and in many cases, endocytosis and coordinated interaction of multiple signal transduction mechanisms prompted by external biotic and abiotic cues. The products of polar expansion perform diverse functions including delivery of male gametes to the egg, absorption, anchorage, adhesion and photo-absorption efficacy. A comparative analysis of polar expansion dynamics is provided with special emphasis on those found in early divergent plants. PMID:27137370

Multiple sclerosis

MedlinePlus

... this page: //medlineplus.gov/ency/article/000737.htm Multiple sclerosis To use the sharing features on this page, please enable JavaScript. Multiple sclerosis (MS) is an autoimmune disease that affects the ...

Chronic cough: clinical characteristics and etiologies of 510 cases.

PubMed

Jiang, Guiyuan; Huang, Xinying; Li, Tianlin; Xu, Dongping

2016-12-20

To investigate the clinical features and underlying etiologies of chronic cough (CC). Five hundred and ten CC patients were enrolled. The phases, characteristics and associated clinical manifestations of CC among the gastroesophageal reflux cough (GERC), cough-variant asthma (CVA), and upper airway cough syndrome (UACS) groups were compared, and the diagnostic values of each group were evaluated by multiple regression analysis. In the 510 patients, 404 had CC with single etiology-GERC (n = 175), CVA (n = 134), and UACS (n = 95). The characteristic features of GERC included gastric acid backflow symptoms such as sour-tasting regurgitation, heartburn, endoscopic esophagitis, poststimulation cough, frequent throat clearing, daytime mono-cough, and feelings of heaviness and pain in the chest. Patients with CVA typically exhibited sensitivity to smog and other irritants; the cough occurred mostly at night, and was associated with positive bronchodilator and provocation test results. The typical features of UACS included a history and/or symptoms of rhinitis, retropharyngeal postnasal drip, and wet cough occurring mostly during the daytime. The diagnostic specificities of above factors were >70%. The most common causes of CC include GERC, CVA, and UACS, and their diagnosis is based on the characteristics of the underlying disease.

COME: a robust coding potential calculation tool for lncRNA identification and characterization based on multiple features.

PubMed

Hu, Long; Xu, Zhiyu; Hu, Boqin; Lu, Zhi John

2017-01-09

Recent genomic studies suggest that novel long non-coding RNAs (lncRNAs) are specifically expressed and far outnumber annotated lncRNA sequences. To identify and characterize novel lncRNAs in RNA sequencing data from new samples, we have developed COME, a coding potential calculation tool based on multiple features. It integrates multiple sequence-derived and experiment-based features using a decompose-compose method, which makes it more accurate and robust than other well-known tools. We also showed that COME was able to substantially improve the consistency of predication results from other coding potential calculators. Moreover, COME annotates and characterizes each predicted lncRNA transcript with multiple lines of supporting evidence, which are not provided by other tools. Remarkably, we found that one subgroup of lncRNAs classified by such supporting features (i.e. conserved local RNA secondary structure) was highly enriched in a well-validated database (lncRNAdb). We further found that the conserved structural domains on lncRNAs had better chance than other RNA regions to interact with RNA binding proteins, based on the recent eCLIP-seq data in human, indicating their potential regulatory roles. Overall, we present COME as an accurate, robust and multiple-feature supported method for the identification and characterization of novel lncRNAs. The software implementation is available at https://github.com/lulab/COME. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Liu, Yuan; Liang, Fuxun; Wang, Yongjun

2017-04-01

In recent years, updating the inventory of road infrastructures based on field work is labor intensive, time consuming, and costly. Fortunately, vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. However, robust recognition of road facilities from huge volumes of 3D point clouds is still a challenging issue because of complicated and incomplete structures, occlusions and varied point densities. Most existing methods utilize point or object based features to recognize object candidates, and can only extract limited types of objects with a relatively low recognition rate, especially for incomplete and small objects. To overcome these drawbacks, this paper proposes a semantic labeling framework by combing multiple aggregation levels (point-segment-object) of features and contextual features to recognize road facilities, such as road surfaces, road boundaries, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, and cars, for highway infrastructure inventory. The proposed method first identifies ground and non-ground points, and extracts road surfaces facilities from ground points. Non-ground points are segmented into individual candidate objects based on the proposed multi-rule region growing method. Then, the multiple aggregation levels of features and the contextual features (relative positions, relative directions, and spatial patterns) associated with each candidate object are calculated and fed into a SVM classifier to label the corresponding candidate object. The recognition performance of combining multiple aggregation levels and contextual features was compared with single level (point, segment, or object) based features using large-scale highway scene point clouds. Comparative studies demonstrated that the proposed semantic labeling framework significantly improves road facilities recognition precision (90.6%) and recall (91.2%), particularly for incomplete and small objects.

Explosive hazard detection using MIMO forward-looking ground penetrating radar

NASA Astrophysics Data System (ADS)

Shaw, Darren; Ho, K. C.; Stone, Kevin; Keller, James M.; Popescu, Mihail; Anderson, Derek T.; Luke, Robert H.; Burns, Brian

2015-05-01

This paper proposes a machine learning algorithm for subsurface object detection on multiple-input-multiple-output (MIMO) forward-looking ground-penetrating radar (FLGPR). By detecting hazards using FLGPR, standoff distances of up to tens of meters can be acquired, but this is at the degradation of performance due to high false alarm rates. The proposed system utilizes an anomaly detection prescreener to identify potential object locations. Alarm locations have multiple one-dimensional (ML) spectral features, two-dimensional (2D) spectral features, and log-Gabor statistic features extracted. The ability of these features to reduce the number of false alarms and increase the probability of detection is evaluated for both co-polarizations present in the Akela MIMO array. Classification is performed by a Support Vector Machine (SVM) with lane-based cross-validation for training and testing. Class imbalance and optimized SVM kernel parameters are considered during classifier training.

Multiple sclerosis in children: an update on clinical diagnosis, therapeutic strategies, and research

PubMed Central

Waldman, Amy; Ghezzi, Angelo; Bar-Or, Amit; Mikaeloff, Yann; Tardieu, Marc; Banwell, Brenda

2015-01-01

The clinical features, diagnostic challenges, neuroimaging appearance, therapeutic options, and pathobiological research progress in childhood—and adolescent—onset multiple sclerosis have been informed by many new insights in the past 7 years. National programmes in several countries, collaborative research efforts, and an established international paediatric multiple sclerosis study group have contributed to revised clinical diagnostic definitions, identified clinical features of multiple sclerosis that differ by age of onset, and made recommendations regarding the treatment of paediatric multiple sclerosis. The relative risks conveyed by genetic and environmental factors to paediatric multiple sclerosis have been the subject of several large cohort studies. MRI features have been characterised in terms of qualitative descriptions of lesion distribution and applicability of MRI aspects to multiple sclerosis diagnostic criteria, and quantitative studies have assessed total lesion burden and the effect of the disease on global and regional brain volume. Humoral-based and cell-based assays have identified antibodies against myelin, potassium-channel proteins, and T-cell profiles that support an adult-like T-cell repertoire and cellular reactivity against myelin in paediatric patients with multiple sclerosis. Finally, the safety and efficacy of standard first-line therapies in paediatric multiple sclerosis populations are now appreciated in more detail, and consensus views on the future conduct and feasibility of phase 3 trials for new drugs have been proposed. PMID:25142460

Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images

NASA Astrophysics Data System (ADS)

Leo, Patrick; Lee, George; Madabhushi, Anant

2016-03-01

Quantitative histomorphometry (QH) is the process of computerized extraction of features from digitized tissue slide images. Typically these features are used in machine learning classifiers to predict disease presence, behavior and outcome. Successful robust classifiers require features that both discriminate between classes of interest and are stable across data from multiple sites. Feature stability may be compromised by variation in slide staining and scanning procedures. These laboratory specific variables include dye batch, slice thickness and the whole slide scanner used to digitize the slide. The key therefore is to be able to identify features that are not only discriminating between the classes of interest (e.g. cancer and non-cancer or biochemical recurrence and non- recurrence) but also features that will not wildly fluctuate on slides representing the same tissue class but from across multiple different labs and sites. While there has been some recent efforts at understanding feature stability in the context of radiomics applications (i.e. feature analysis of radiographic images), relatively few attempts have been made at studying the trade-off between feature stability and discriminability for histomorphometric and digital pathology applications. In this paper we present two new measures, preparation-induced instability score (PI) and latent instability score (LI), to quantify feature instability across and within datasets. Dividing PI by LI yields a ratio for how often a feature for a specific tissue class (e.g. low grade prostate cancer) is different between datasets from different sites versus what would be expected from random chance alone. Using this ratio we seek to quantify feature vulnerability to variations in slide preparation and digitization. Since our goal is to identify stable QH features we evaluate these features for their stability and thus inclusion in machine learning based classifiers in a use case involving prostate cancer. Specifically we examine QH features which may predict 5 year biochemical recurrence for prostate cancer patients who have undergone radical prostatectomy from digital slide images of surgically excised tissue specimens, 5 year biochemical recurrence being a strong predictor of disease recurrence. In this study we evaluated the ability of our feature robustness indices to identify the most stable and predictive features of 5 year biochemical recurrence using digitized slide images of surgically excised prostate cancer specimens from 80 different patients across 4 different sites. A total of 242 features from 5 different feature families were investigated to identify the most stable QH features from our set. Our feature robustness indices (PI and LI) suggested that five feature families (graph, shape, co-occurring gland tensors, gland sub-graphs, texture) were susceptible to variations in slide preparation and digitization across various sites. The family least affected was shape features in which 19.3% of features varied across laboratories while the most vulnerable family, at 55.6%, was the gland disorder features. However the disorder features were the most stable within datasets being different between random halves of a dataset in an average of just 4.1% of comparisons while texture features were the most unstable being different at a rate of 4.7%. We also compared feature stability across two datasets before and after color normalization. Color normalization decreased feature stability with 8% and 34% of features different between the two datasets in two outcome groups prior to normalization and 49% and 51% different afterwards. Our results appear to suggest that evaluation of QH features across multiple sites needs to be undertaken to assess robustness and class discriminability alone should not represent the benchmark for selection of QH features to build diagnostic and prognostic digital pathology classifiers.

Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yang, Boyuan

2017-09-01

It is a challenging problem to design excellent dictionaries to sparsely represent diverse fault information and simultaneously discriminate different fault sources. Therefore, this paper describes and analyzes a novel multiple feature recognition framework which incorporates the tight frame learning technique with an adaptive subspace recognition strategy. The proposed framework consists of four stages. Firstly, by introducing the tight frame constraint into the popular dictionary learning model, the proposed tight frame learning model could be formulated as a nonconvex optimization problem which can be solved by alternatively implementing hard thresholding operation and singular value decomposition. Secondly, the noises are effectively eliminated through transform sparse coding techniques. Thirdly, the denoised signal is decoupled into discriminative feature subspaces by each tight frame filter. Finally, in guidance of elaborately designed fault related sensitive indexes, latent fault feature subspaces can be adaptively recognized and multiple faults are diagnosed simultaneously. Extensive numerical experiments are sequently implemented to investigate the sparsifying capability of the learned tight frame as well as its comprehensive denoising performance. Most importantly, the feasibility and superiority of the proposed framework is verified through performing multiple fault diagnosis of motor bearings. Compared with the state-of-the-art fault detection techniques, some important advantages have been observed: firstly, the proposed framework incorporates the physical prior with the data-driven strategy and naturally multiple fault feature with similar oscillation morphology can be adaptively decoupled. Secondly, the tight frame dictionary directly learned from the noisy observation can significantly promote the sparsity of fault features compared to analytical tight frames. Thirdly, a satisfactory complete signal space description property is guaranteed and thus weak feature leakage problem is avoided compared to typical learning methods.

Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.

PubMed

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-03-01

In this study, we report the evaluation of the residue-residue contacts predicted by our three different methods in the CASP12 experiment, focusing on studying the impact of multiple sequence alignment, residue coevolution, and machine learning on contact prediction. The first method (MULTICOM-NOVEL) uses only traditional features (sequence profile, secondary structure, and solvent accessibility) with deep learning to predict contacts and serves as a baseline. The second method (MULTICOM-CONSTRUCT) uses our new alignment algorithm to generate deep multiple sequence alignment to derive coevolution-based features, which are integrated by a neural network method to predict contacts. The third method (MULTICOM-CLUSTER) is a consensus combination of the predictions of the first two methods. We evaluated our methods on 94 CASP12 domains. On a subset of 38 free-modeling domains, our methods achieved an average precision of up to 41.7% for top L/5 long-range contact predictions. The comparison of the three methods shows that the quality and effective depth of multiple sequence alignments, coevolution-based features, and machine learning integration of coevolution-based features and traditional features drive the quality of predicted protein contacts. On the full CASP12 dataset, the coevolution-based features alone can improve the average precision from 28.4% to 41.6%, and the machine learning integration of all the features further raises the precision to 56.3%, when top L/5 predicted long-range contacts are evaluated. And the correlation between the precision of contact prediction and the logarithm of the number of effective sequences in alignments is 0.66. © 2017 Wiley Periodicals, Inc.

The 30/20 Gigahertz transponder study. [wideband multichannel transponders for a communications satellite

NASA Technical Reports Server (NTRS)

1980-01-01

Design features and performance parameters are described for three types of wideband multiple channel satellite transponders for use in a 30/20 GHz communications satellite, which provides high data rate trunking service to ten ground station terminals. The three types of transponder are frequency division multiplex (FDM), time division multiplex (TDM), and a hybrid transponder using a combination of FDM and TDM techniques. The wideband multiple beam trunking concept, the traffic distribution between the trunking terminals, and system design constraints are discussed. The receiver front end design, the frequency conversion scheme, and the local oscillator design are described including the thermal interface between the transponders and the satellite. The three designs are compared with regard to performance, weight, power, cost and initial technology. Simplified block diagrams of the baseline transponder designs are included.

JDet: interactive calculation and visualization of function-related conservation patterns in multiple sequence alignments and structures.

PubMed

Muth, Thilo; García-Martín, Juan A; Rausell, Antonio; Juan, David; Valencia, Alfonso; Pazos, Florencio

2012-02-15

We have implemented in a single package all the features required for extracting, visualizing and manipulating fully conserved positions as well as those with a family-dependent conservation pattern in multiple sequence alignments. The program allows, among other things, to run different methods for extracting these positions, combine the results and visualize them in protein 3D structures and sequence spaces. JDet is a multiplatform application written in Java. It is freely available, including the source code, at http://csbg.cnb.csic.es/JDet. The package includes two of our recently developed programs for detecting functional positions in protein alignments (Xdet and S3Det), and support for other methods can be added as plug-ins. A help file and a guided tutorial for JDet are also available.

A Framework for Assessing the Value of Investments in Nonclinical Prevention

PubMed Central

Roehrig, Charles; Russo, Pamela

2015-01-01

We present a high-level framework to show the process by which an investment in primary prevention produces value. We define primary prevention broadly to include investments in any of the determinants of health. Although it builds on previously developed frameworks, ours incorporates several additional features. It distinguishes direct and upstream determinants of health, a distinction that can help identify, describe, and track the impact of a policy or program on health and health care costs. It recognizes multiple dimensions of value, including the need to establish the nonhealth value of investments whose objectives are not limited to improvements in health (and whose costs should not be attributed solely to the health benefits). Finally, it emphasizes the need to describe value from the perspectives of the multiple stakeholders that can influence such investments. PMID:26652216

A Framework for Assessing the Value of Investments in Nonclinical Prevention.

PubMed

Miller, George; Roehrig, Charles; Russo, Pamela

2015-12-10

We present a high-level framework to show the process by which an investment in primary prevention produces value. We define primary prevention broadly to include investments in any of the determinants of health. Although it builds on previously developed frameworks, ours incorporates several additional features. It distinguishes direct and upstream determinants of health, a distinction that can help identify, describe, and track the impact of a policy or program on health and health care costs. It recognizes multiple dimensions of value, including the need to establish the nonhealth value of investments whose objectives are not limited to improvements in health (and whose costs should not be attributed solely to the health benefits). Finally, it emphasizes the need to describe value from the perspectives of the multiple stakeholders that can influence such investments.

High resolution crustal image of South California Continental Borderland: Reverse time imaging including multiples

NASA Astrophysics Data System (ADS)

Bian, A.; Gantela, C.

2014-12-01

Strong multiples were observed in marine seismic data of Los Angeles Regional Seismic Experiment (LARSE).It is crucial to eliminate these multiples in conventional ray-based or one-way wave-equation based depth image methods. As long as multiples contain information of target zone along travelling path, it's possible to use them as signal, to improve the illumination coverage thus enhance the image quality of structural boundaries. Reverse time migration including multiples is a two-way wave-equation based prestack depth image method that uses both primaries and multiples to map structural boundaries. Several factors, including source wavelet, velocity model, back ground noise, data acquisition geometry and preprocessing workflow may influence the quality of image. The source wavelet is estimated from direct arrival of marine seismic data. Migration velocity model is derived from integrated model building workflow, and the sharp velocity interfaces near sea bottom needs to be preserved in order to generate multiples in the forward and backward propagation steps. The strong amplitude, low frequency marine back ground noise needs to be removed before the final imaging process. High resolution reverse time image sections of LARSE Lines 1 and Line 2 show five interfaces: depth of sea-bottom, base of sedimentary basins, top of Catalina Schist, a deep layer and a possible pluton boundary. Catalina Schist shows highs in the San Clemente ridge, Emery Knoll, Catalina Ridge, under Catalina Basin on both the lines, and a minor high under Avalon Knoll. The high of anticlinal fold in Line 1 is under the north edge of Emery Knoll and under the San Clemente fault zone. An area devoid of any reflection features are interpreted as sides of an igneous plume.

Research on driver fatigue detection

NASA Astrophysics Data System (ADS)

Zhang, Ting; Chen, Zhong; Ouyang, Chao

2018-03-01

Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.

Emotion recognition based on multiple order features using fractional Fourier transform

NASA Astrophysics Data System (ADS)

Ren, Bo; Liu, Deyin; Qi, Lin

2017-07-01

In order to deal with the insufficiency of recently algorithms based on Two Dimensions Fractional Fourier Transform (2D-FrFT), this paper proposes a multiple order features based method for emotion recognition. Most existing methods utilize the feature of single order or a couple of orders of 2D-FrFT. However, different orders of 2D-FrFT have different contributions on the feature extraction of emotion recognition. Combination of these features can enhance the performance of an emotion recognition system. The proposed approach obtains numerous features that extracted in different orders of 2D-FrFT in the directions of x-axis and y-axis, and uses the statistical magnitudes as the final feature vectors for recognition. The Support Vector Machine (SVM) is utilized for the classification and RML Emotion database and Cohn-Kanade (CK) database are used for the experiment. The experimental results demonstrate the effectiveness of the proposed method.

Terminal-oriented computer-communication networks.

NASA Technical Reports Server (NTRS)

Schwartz, M.; Boorstyn, R. R.; Pickholtz, R. L.

1972-01-01

Four examples of currently operating computer-communication networks are described in this tutorial paper. They include the TYMNET network, the GE Information Services network, the NASDAQ over-the-counter stock-quotation system, and the Computer Sciences Infonet. These networks all use programmable concentrators for combining a multiplicity of terminals. Included in the discussion for each network is a description of the overall network structure, the handling and transmission of messages, communication requirements, routing and reliability consideration where applicable, operating data and design specifications where available, and unique design features in the area of computer communications.

General-Purpose Electronic System Tests Aircraft

NASA Technical Reports Server (NTRS)

Glover, Richard D.

1989-01-01

Versatile digital equipment supports research, development, and maintenance. Extended aircraft interrogation and display system is general-purpose assembly of digital electronic equipment on ground for testing of digital electronic systems on advanced aircraft. Many advanced features, including multiple 16-bit microprocessors, pipeline data-flow architecture, advanced operating system, and resident software-development tools. Basic collection of software includes program for handling many types of data and for displays in various formats. User easily extends basic software library. Hardware and software interfaces to subsystems provided by user designed for flexibility in configuration to meet user's requirements.

Feature generation and representations for protein-protein interaction classification.

PubMed

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

A multiple maximum scatter difference discriminant criterion for facial feature extraction.

PubMed

Song, Fengxi; Zhang, David; Mei, Dayong; Guo, Zhongwei

2007-12-01

Maximum scatter difference (MSD) discriminant criterion was a recently presented binary discriminant criterion for pattern classification that utilizes the generalized scatter difference rather than the generalized Rayleigh quotient as a class separability measure, thereby avoiding the singularity problem when addressing small-sample-size problems. MSD classifiers based on this criterion have been quite effective on face-recognition tasks, but as they are binary classifiers, they are not as efficient on large-scale classification tasks. To address the problem, this paper generalizes the classification-oriented binary criterion to its multiple counterpart--multiple MSD (MMSD) discriminant criterion for facial feature extraction. The MMSD feature-extraction method, which is based on this novel discriminant criterion, is a new subspace-based feature-extraction method. Unlike most other subspace-based feature-extraction methods, the MMSD computes its discriminant vectors from both the range of the between-class scatter matrix and the null space of the within-class scatter matrix. The MMSD is theoretically elegant and easy to calculate. Extensive experimental studies conducted on the benchmark database, FERET, show that the MMSD out-performs state-of-the-art facial feature-extraction methods such as null space method, direct linear discriminant analysis (LDA), eigenface, Fisherface, and complete LDA.

Methods Used in EnviroAtlas to Assess Urban Natural ...

EPA Pesticide Factsheets

Previous studies have positively correlated human exposures to natural features with health promoting outcomes such as increased physical activity, improved cognitive function, increased social engagement, and reduced ambient air pollution. When using remotely-sensed data to investigate these relationships, researchers must first identify an appropriate spatial resolution to characterize exposures. However, metric development has often been limited by the lack of fine-scale land cover data, especially across multiple communities. As a result, researchers commonly use coarse resolution imagery. EnviroAtlas, a U.S. Environmental Protection Agency web-based ecosystem services mapping tool, has developed 1-meter resolution land cover data across 16 diverse U.S. Census Urban Areas using aerial photography and supplemental data. Research maps derived from these foundational data include percent tree cover along busy roads, percent tree cover and green space along walkable streets, and percent natural vegetation bordering water bodies. EnviroAtlas has also developed multiple smoothed “heat maps” of proximity to specific types of features at every 1m point; these include total green space, tree cover, and water within 50m, 500m, and 1,000m buffers; walking distance to the nearest park entrance; and intersection density as an indicator of neighborhood walkability.EnviroAtlas variables are available to external researchers, public health professionals and planners t

Micro-Doppler analysis of multiple frequency continuous wave radar signatures

NASA Astrophysics Data System (ADS)

Anderson, Michael G.; Rogers, Robert L.

2007-04-01

Micro-Doppler refers to Doppler scattering returns produced by non rigid-body motion. Micro-Doppler gives rise to many detailed radar image features in addition to those associated with bulk target motion. Targets of different classes (for example, humans, animals, and vehicles) produce micro-Doppler images that are often distinguishable even by nonexpert observers. Micro-Doppler features have great potential for use in automatic target classification algorithms. Although the potential benefit of using micro-Doppler in classification algorithms is high, relatively little experimental (non-synthetic) micro-Doppler data exists. Much of the existing experimental data comes from highly cooperative targets (human or vehicle targets directly approaching the radar). This research involved field data collection and analysis of micro-Doppler radar signatures from non-cooperative targets. The data was collected using a low cost Xband multiple frequency continuous wave (MFCW) radar with three transmit frequencies. The collected MFCW radar signatures contain data from humans, vehicles, and animals. The presented data includes micro-Doppler signatures previously unavailable in the literature such as crawling humans and various animal species. The animal micro-Doppler signatures include deer, dog, and goat datasets. This research focuses on the analysis of micro-Doppler from noncooperative targets approaching the radar at various angles, maneuvers, and postures.

Neural Computations in a Dynamical System with Multiple Time Scales.

PubMed

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Manifold Regularized Multitask Feature Learning for Multimodality Disease Classification

PubMed Central

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2015-01-01

Multimodality based methods have shown great advantages in classification of Alzheimer’s disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis. PMID:25277605

Development of the Multiple Use Plug Hybrid for Nanosats (MUPHyN) miniature thruster

NASA Astrophysics Data System (ADS)

Eilers, Shannon

The Multiple Use Plug Hybrid for Nanosats (MUPHyN) prototype thruster incorporates solutions to several major challenges that have traditionally limited the deployment of chemical propulsion systems on small spacecraft. The MUPHyN thruster offers several features that are uniquely suited for small satellite applications. These features include 1) a non-explosive ignition system, 2) non-mechanical thrust vectoring using secondary fluid injection on an aerospike nozzle cooled with the oxidizer flow, 3) a non-toxic, chemically-stable combination of liquid and inert solid propellants, 4) a compact form factor enabled by the direct digital manufacture of the inert solid fuel grain. Hybrid rocket motors provide significant safety and reliability advantages over both solid composite and liquid propulsion systems; however, hybrid motors have found only limited use on operational vehicles due to 1) difficulty in modeling the fuel flow rate 2) poor volumetric efficiency and/or form factor 3) significantly lower fuel flow rates than solid rocket motors 4) difficulty in obtaining high combustion efficiencies. The features of the MUPHyN thruster are designed to offset and/or overcome these shortcomings. The MUPHyN motor design represents a convergence of technologies, including hybrid rocket regression rate modeling, aerospike secondary injection thrust vectoring, multiphase injector modeling, non-pyrotechnic ignition, and nitrous oxide regenerative cooling that address the traditional challenges that limit the use of hybrid rocket motors and aerospike nozzles. This synthesis of technologies is unique to the MUPHyN thruster design and no comparable work has been published in the open literature.

PFLOTRAN: Reactive Flow & Transport Code for Use on Laptops to Leadership-Class Supercomputers

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

Hammond, Glenn E.; Lichtner, Peter C.; Lu, Chuan

PFLOTRAN, a next-generation reactive flow and transport code for modeling subsurface processes, has been designed from the ground up to run efficiently on machines ranging from leadership-class supercomputers to laptops. Based on an object-oriented design, the code is easily extensible to incorporate additional processes. It can interface seamlessly with Fortran 9X, C and C++ codes. Domain decomposition parallelism is employed, with the PETSc parallel framework used to manage parallel solvers, data structures and communication. Features of the code include a modular input file, implementation of high-performance I/O using parallel HDF5, ability to perform multiple realization simulations with multiple processors permore » realization in a seamless manner, and multiple modes for multiphase flow and multicomponent geochemical transport. Chemical reactions currently implemented in the code include homogeneous aqueous complexing reactions and heterogeneous mineral precipitation/dissolution, ion exchange, surface complexation and a multirate kinetic sorption model. PFLOTRAN has demonstrated petascale performance using 2{sup 17} processor cores with over 2 billion degrees of freedom. Accomplishments achieved to date include applications to the Hanford 300 Area and modeling CO{sub 2} sequestration in deep geologic formations.« less

Application of machine learning on brain cancer multiclass classification

NASA Astrophysics Data System (ADS)

Panca, V.; Rustam, Z.

2017-07-01

Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

Classification of MR brain images by combination of multi-CNNs for AD diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Danni; Liu, Manhua; Fu, Jianliang; Wang, Yaping

2017-07-01

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and cognitive functions. Its early diagnosis is crucial for development of future treatment. Magnetic resonance images (MRI) play important role to help understand the brain anatomical changes related to AD. Conventional methods extract the hand-crafted features such as gray matter volumes and cortical thickness and train a classifier to distinguish AD from other groups. Different from these methods, this paper proposes to construct multiple deep 3D convolutional neural networks (3D-CNNs) to learn the various features from local brain images which are combined to make the final classification for AD diagnosis. First, a number of local image patches are extracted from the whole brain image and a 3D-CNN is built upon each local patch to transform the local image into more compact high-level features. Then, the upper convolution and fully connected layers are fine-tuned to combine the multiple 3D-CNNs for image classification. The proposed method can automatically learn the generic features from imaging data for classification. Our method is evaluated using T1-weighted structural MR brain images on 428 subjects including 199 AD patients and 229 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 87.15% and an AUC (area under the ROC curve) of 92.26% for AD classification, demonstrating the promising classification performances.

Cyto-histopathological and outcome features of the prepuce squamous cell carcinoma of a mixed breed dog

PubMed Central

2014-01-01

Abstract Background Squamous cell carcinomas (SCCs) are uncommon, high-grade tumors, predominantly composed of round cells in the prepuce. The aim of this study is to better define the clinicopathologic features of this neoplasm. Case report We conducted cyto-histopathologic analysis on the manifestations of the prepuce SCC by H & E staining in a terrier mix dog. Grossly, tumor was large, multiple erythematous patch, and ulcerated masses frequently affecting the prepuce and deeply invading to distal prepuce out from the ventro-lateral of penis and the tumor covered by a necrotic discharge. Cytological evaluation of fine-needle aspirates from the cutaneous mass from the prepuce comprised of round nuclei, coarse chromatin pattern, distinct nucleoli and nuclear pleomorphism. Furthermore, the neoplastic cells were pleomorphic, round to caudate in shape, exhibiting prominent anisokaryosis and anisocytosis with rare mitotic features. Microscopically, the lesions were predominantly composed of atypical round cells disposed in interlacing fascicles. Frequent findings include keratin formation, horn pearls, mitoses and cellular atypia. The cells showed distinct borders, ranged from polygonal to round or elongate and had moderate amounts of eosinophilic cytoplasm. Conclusion The histopathologic features coupled with the cytopathology findings led to a diagnosis of squamous cell carcinoma. To the authors’ knowledge, this is the first time that multiple erythematous plaques have undergone malignant transformation in a terrier mix dog. Virtual Slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5748771971272873 PMID:24903567

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

PubMed

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

2008-09-01

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

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.

P³DB 3.0: From plant phosphorylation sites to protein networks.

PubMed

Yao, Qiuming; Ge, Huangyi; Wu, Shangquan; Zhang, Ning; Chen, Wei; Xu, Chunhui; Gao, Jianjiong; Thelen, Jay J; Xu, Dong

2014-01-01

In the past few years, the Plant Protein Phosphorylation Database (P(3)DB, http://p3db.org) has become one of the most significant in vivo data resources for studying plant phosphoproteomics. We have substantially updated P(3)DB with respect to format, new datasets and analytic tools. In the P(3)DB 3.0, there are altogether 47 923 phosphosites in 16 477 phosphoproteins curated across nine plant organisms from 32 studies, which have met our multiple quality standards for acquisition of in vivo phosphorylation site data. Centralized by these phosphorylation data, multiple related data and annotations are provided, including protein-protein interaction (PPI), gene ontology, protein tertiary structures, orthologous sequences, kinase/phosphatase classification and Kinase Client Assay (KiC Assay) data--all of which provides context for the phosphorylation event. In addition, P(3)DB 3.0 incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase-substrate network, and domain co-occurrence network to help study phosphorylation from a systems point of view. Furthermore, the new P(3)DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes. Each of these new features supports the goal of making P(3)DB a comprehensive, systematic and interactive platform for phosphoproteomics research.

Measurement of the underlying event in jet events from 7 proton-proton collisions with the ATLAS detector

NASA Astrophysics Data System (ADS)

Aad, G.; Abajyan, T.; Abbott, B.; Abdallah, J.; Khalek, S. Abdel; Abdinov, O.; Aben, R.; Abi, B.; Abolins, M.; AbouZeid, O. S.; Abramowicz, H.; Abreu, H.; Abulaiti, Y.; Acharya, B. S.; Adamczyk, L.; Adams, D. L.; Addy, T. N.; Adelman, J.; Adomeit, S.; Adye, T.; Agatonovic-Jovin, T.; Aguilar-Saavedra, J. A.; Agustoni, M.; Ahlen, S. P.; Ahmadov, F.; Aielli, G.; Åkesson, T. P. A.; Akimoto, G.; Akimov, A. V.; Albert, J.; Albrand, S.; Verzini, M. J. Alconada; Aleksa, M.; Aleksandrov, I. N.; Alexa, C.; Alexander, G.; Alexandre, G.; Alexopoulos, T.; Alhroob, M.; Alimonti, G.; Alio, L.; Alison, J.; Allbrooke, B. M. M.; Allison, L. J.; Allport, P. P.; Allwood-Spiers, S. E.; Almond, J.; Aloisio, A.; Alon, R.; Alonso, A.; Alonso, F.; Alpigiani, C.; Altheimer, A.; Gonzalez, B. Alvarez; Alviggi, M. G.; Amako, K.; Coutinho, Y. Amaral; Amelung, C.; Amidei, D.; Ammosov, V. V.; Santos, S. P. Amor Dos; Amorim, A.; Amoroso, S.; Amram, N.; Amundsen, G.; Anastopoulos, C.; Ancu, L. S.; Andari, N.; Andeen, T.; Anders, C. F.; Anders, G.; Anderson, K. J.; Andreazza, A.; Andrei, V.; Anduaga, X. S.; Angelidakis, S.; Anger, P.; Angerami, A.; Anghinolfi, F.; Anisenkov, A. V.; Anjos, N.; Annovi, A.; Antonaki, A.; Antonelli, M.; Antonov, A.; Antos, J.; Anulli, F.; Aoki, M.; Bella, L. Aperio; Apolle, R.; Arabidze, G.; Aracena, I.; Arai, Y.; Araque, J. P.; Arce, A. T. H.; Arguin, J.-F.; Argyropoulos, S.; Arik, M.; Armbruster, A. J.; Arnaez, O.; Arnal, V.; Arslan, O.; Artamonov, A.; Artoni, G.; Asai, S.; Asbah, N.; Ashkenazi, A.; Ask, S.; Åsman, B.; Asquith, L.; Assamagan, K.; Astalos, R.; Atkinson, M.; Atlay, N. B.; Auerbach, B.; Auge, E.; Augsten, K.; Aurousseau, M.; Avolio, G.; Azuelos, G.; Azuma, Y.; Baak, M. A.; Bacci, C.; Bach, A. M.; Bachacou, H.; Bachas, K.; Backes, M.; Backhaus, M.; Mayes, J. Backus; Badescu, E.; Bagiacchi, P.; Bagnaia, P.; Bai, Y.; Bailey, D. C.; Bain, T.; Baines, J. T.; Baker, O. K.; Baker, S.; Balek, P.; Balli, F.; Banas, E.; Banerjee, Sw.; Bangert, A.; Bannoura, A. A. E.; Bansal, V.; Bansil, H. S.; Barak, L.; Baranov, S. P.; Barber, T.; Barberio, E. L.; Barberis, D.; Barbero, M.; Barillari, T.; Barisonzi, M.; Barklow, T.; Barlow, N.; Barnett, B. M.; Barnett, R. M.; Barnovska, Z.; Baroncelli, A.; Barone, G.; Barr, A. J.; Barreiro, F.; da Costa, J. Barreiro Guimarães; Bartoldus, R.; Barton, A. E.; Bartos, P.; Bartsch, V.; Bassalat, A.; Basye, A.; Bates, R. L.; Batkova, L.; Batley, J. R.; Battistin, M.; Bauer, F.; Bawa, H. S.; Beau, T.; Beauchemin, P. H.; Beccherle, R.; Bechtle, P.; Beck, H. P.; Becker, K.; Becker, S.; Beckingham, M.; Becot, C.; Beddall, A. J.; Beddall, A.; Bedikian, S.; Bednyakov, V. A.; Bee, C. P.; Beemster, L. J.; Beermann, T. A.; Begel, M.; Behr, K.; Belanger-Champagne, C.; Bell, P. J.; Bell, W. H.; Bella, G.; Bellagamba, L.; Bellerive, A.; Bellomo, M.; Belloni, A.; Belotskiy, K.; Beltramello, O.; Benary, O.; Benchekroun, D.; Bendtz, K.; Benekos, N.; Benhammou, Y.; Noccioli, E. Benhar; Garcia, J. A. Benitez; Benjamin, D. P.; Bensinger, J. R.; Benslama, K.; Bentvelsen, S.; Berge, D.; Kuutmann, E. Bergeaas; Berger, N.; Berghaus, F.; Berglund, E.; Beringer, J.; Bernard, C.; Bernat, P.; Bernius, C.; Bernlochner, F. U.; Berry, T.; Berta, P.; Bertella, C.; Bertolucci, F.; Besana, M. I.; Besjes, G. J.; Bessidskaia, O.; Besson, N.; Betancourt, C.; Bethke, S.; Bhimji, W.; Bianchi, R. M.; Bianchini, L.; Bianco, M.; Biebel, O.; Bieniek, S. P.; Bierwagen, K.; Biesiada, J.; Biglietti, M.; De Mendizabal, J. Bilbao; Bilokon, H.; Bindi, M.; Binet, S.; Bingul, A.; Bini, C.; Black, C. W.; Black, J. E.; Black, K. M.; Blackburn, D.; Blair, R. E.; Blanchard, J.-B.; Blazek, T.; Bloch, I.; Blocker, C.; Blum, W.; Blumenschein, U.; Bobbink, G. J.; Bobrovnikov, V. S.; Bocchetta, S. 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Bruckman de; Bruncko, D.; Bruneliere, R.; Brunet, S.; Bruni, A.; Bruni, G.; Bruschi, M.; Bryngemark, L.; Buanes, T.; Buat, Q.; Bucci, F.; Buchholz, P.; Buckingham, R. M.; Buckley, A. G.; Buda, S. I.; Budagov, I. A.; Buehrer, F.; Bugge, L.; Bugge, M. K.; Bulekov, O.; Bundock, A. C.; Burckhart, H.; Burdin, S.; Burghgrave, B.; Burke, S.; Burmeister, I.; Busato, E.; Büscher, V.; Bussey, P.; Buszello, C. P.; Butler, B.; Butler, J. M.; Butt, A. I.; Buttar, C. M.; Butterworth, J. M.; Butti, P.; Buttinger, W.; Buzatu, A.; Byszewski, M.; Urbán, S. Cabrera; Caforio, D.; Cakir, O.; Calafiura, P.; Calderini, G.; Calfayan, P.; Calkins, R.; Caloba, L. P.; Calvet, D.; Calvet, S.; Toro, R. Camacho; Camarda, S.; Cameron, D.; Caminada, L. M.; Armadans, R. Caminal; Campana, S.; Campanelli, M.; Campoverde, A.; Canale, V.; Canepa, A.; Cantero, J.; Cantrill, R.; Cao, T.; Garrido, M. D. M. Capeans; Caprini, I.; Caprini, M.; Capua, M.; Caputo, R.; Cardarelli, R.; Carli, T.; Carlino, G.; Carminati, L.; Caron, S.; Carquin, E.; Carrillo-Montoya, G. D.; Carter, J. R.; Carvalho, J.; Casadei, D.; Casado, M. P.; Castaneda-Miranda, E.; Castelli, A.; Gimenez, V. Castillo; Castro, N. F.; Catastini, P.; Catinaccio, A.; Catmore, J. R.; Cattai, A.; Cattani, G.; Caughron, S.; Cavaliere, V.; Cavalli, D.; Cavalli-Sforza, M.; Cavasinni, V.; Ceradini, F.; Cerio, B.; Cerny, K.; Cerqueira, A. S.; Cerri, A.; Cerrito, L.; Cerutti, F.; Cerv, M.; Cervelli, A.; Cetin, S. A.; Chafaq, A.; Chakraborty, D.; Chalupkova, I.; Chan, K.; Chang, P.; Chapleau, B.; Chapman, J. D.; Charfeddine, D.; Charlton, D. G.; Chau, C. C.; Barajas, C. A. Chavez; Cheatham, S.; Chegwidden, A.; Chekanov, S.; Chekulaev, S. V.; Chelkov, G. A.; Chelstowska, M. A.; Chen, C.; Chen, H.; Chen, K.; Chen, L.; Chen, S.; Chen, X.; Chen, Y.; Cheng, H. C.; Cheng, Y.; Cheplakov, A.; El Moursli, R. Cherkaoui; Chernyatin, V.; Cheu, E.; Chevalier, L.; Chiarella, V.; Chiefari, G.; Childers, J. T.; Chilingarov, A.; Chiodini, G.; Chisholm, A. S.; Chislett, R. T.; Chitan, A.; Chizhov, M. V.; Chouridou, S.; Chow, B. K. B.; Christidi, I. A.; Chromek-Burckhart, D.; Chu, M. L.; Chudoba, J.; Chytka, L.; Ciapetti, G.; Ciftci, A. K.; Ciftci, R.; Cinca, D.; Cindro, V.; Ciocio, A.; Cirkovic, P.; Citron, Z. H.; Citterio, M.; Ciubancan, M.; Clark, A.; Clark, P. J.; Clarke, R. N.; Cleland, W.; Clemens, J. C.; Clement, B.; Clement, C.; Coadou, Y.; Cobal, M.; Coccaro, A.; Cochran, J.; Coffey, L.; Cogan, J. G.; Coggeshall, J.; Cole, B.; Cole, S.; Colijn, A. P.; Collins-Tooth, C.; Collot, J.; Colombo, T.; Colon, G.; Compostella, G.; Muiño, P. Conde; Coniavitis, E.; Conidi, M. C.; Connell, S. H.; Connelly, I. A.; Consonni, S. M.; Consorti, V.; Constantinescu, S.; Conta, C.; Conti, G.; Conventi, F.; Cooke, M.; Cooper, B. D.; Cooper-Sarkar, A. M.; Cooper-Smith, N. 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A.; Diglio, S.; Dimitrievska, A.; Dingfelder, J.; Dionisi, C.; Dita, P.; Dita, S.; Dittus, F.; Djama, F.; Djobava, T.; do Vale, M. A. B.; Do Valle Wemans, A.; Doan, T. K. O.; Dobos, D.; Dobson, E.; Doglioni, C.; Doherty, T.; Dohmae, T.; Dolejsi, J.; Dolezal, Z.; Dolgoshein, B. A.; Donadelli, M.; Donati, S.; Dondero, P.; Donini, J.; Dopke, J.; Doria, A.; Dova, M. T.; Doyle, A. T.; Dris, M.; Dubbert, J.; Dube, S.; Dubreuil, E.; Duchovni, E.; Duckeck, G.; Ducu, O. A.; Duda, D.; Dudarev, A.; Dudziak, F.; Duflot, L.; Duguid, L.; Dührssen, M.; Dunford, M.; Yildiz, H. Duran; Düren, M.; Durglishvili, A.; Dwuznik, M.; Dyndal, M.; Ebke, J.; Edson, W.; Edwards, N. C.; Ehrenfeld, W.; Eifert, T.; Eigen, G.; Einsweiler, K.; Ekelof, T.; El Kacimi, M.; Ellert, M.; Elles, S.; Ellinghaus, F.; Ellis, N.; Elmsheuser, J.; Elsing, M.; Emeliyanov, D.; Enari, Y.; Endner, O. C.; Endo, M.; Engelmann, R.; Erdmann, J.; Ereditato, A.; Eriksson, D.; Ernis, G.; Ernst, J.; Ernst, M.; Ernwein, J.; Errede, D.; Errede, S.; Ertel, E.; Escalier, M.; Esch, H.; Escobar, C.; Esposito, B.; Etienvre, A. I.; Etzion, E.; Evans, H.; Fabbri, L.; Facini, G.; Fakhrutdinov, R. M.; Falciano, S.; Faltova, J.; Fang, Y.; Fanti, M.; Farbin, A.; Farilla, A.; Farooque, T.; Farrell, S.; Farrington, S. M.; Farthouat, P.; Fassi, F.; Fassnacht, P.; Fassouliotis, D.; Favareto, A.; Fayard, L.; Federic, P.; Fedin, O. L.; Fedorko, W.; Fehling-Kaschek, M.; Feigl, S.; Feligioni, L.; Feng, C.; Feng, E. J.; Feng, H.; Fenyuk, A. B.; Perez, S. Fernandez; Fernando, W.; Ferrag, S.; Ferrando, J.; Ferrara, V.; Ferrari, A.; Ferrari, P.; Ferrari, R.; Ferreira de Lima, D. E.; Ferrer, A.; Ferrere, D.; Ferretti, C.; Parodi, A. Ferretto; Fiascaris, M.; Fiedler, F.; Filipčič, A.; Filipuzzi, M.; Filthaut, F.; Fincke-Keeler, M.; Finelli, K. D.; Fiolhais, M. C. N.; Fiorini, L.; Firan, A.; Fischer, J.; Fisher, M. J.; Fisher, W. C.; Fitzgerald, E. A.; Flechl, M.; Fleck, I.; Fleischmann, P.; Fleischmann, S.; Fletcher, G. T.; Fletcher, G.; Flick, T.; Floderus, A.; Castillo, L. R. Flores; Bustos, A. C. Florez; Flowerdew, M. J.; Formica, A.; Forti, A.; Fortin, D.; Fournier, D.; Fox, H.; Fracchia, S.; Francavilla, P.; Franchini, M.; Franchino, S.; Francis, D.; Franklin, M.; Franz, S.; Fraternali, M.; French, S. T.; Friedrich, C.; Friedrich, F.; Froidevaux, D.; Frost, J. A.; Fukunaga, C.; Torregrosa, E. Fullana; Fulsom, B. G.; Fuster, J.; Gabaldon, C.; Gabizon, O.; Gabrielli, A.; Gabrielli, A.; Gadatsch, S.; Gadomski, S.; Gagliardi, G.; Gagnon, P.; Galea, C.; Galhardo, B.; Gallas, E. J.; Gallo, V.; Gallop, B. J.; Gallus, P.; Galster, G.; Gan, K. K.; Gandrajula, R. P.; Gao, J.; Gao, Y. S.; Walls, F. M. Garay; Garberson, F.; García, C.; Navarro, J. E. García; Garcia-Sciveres, M.; Gardner, R. W.; Garelli, N.; Garonne, V.; Gatti, C.; Gaudio, G.; Gaur, B.; Gauthier, L.; Gauzzi, P.; Gavrilenko, I. L.; Gay, C.; Gaycken, G.; Gazis, E. N.; Ge, P.; Gecse, Z.; Gee, C. N. P.; Geerts, D. A. A.; Geich-Gimbel, Ch.; Gellerstedt, K.; Gemme, C.; Gemmell, A.; Genest, M. H.; Gentile, S.; George, M.; George, S.; Gerbaudo, D.; Gershon, A.; Ghazlane, H.; Ghodbane, N.; Giacobbe, B.; Giagu, S.; Giangiobbe, V.; Giannetti, P.; Gianotti, F.; Gibbard, B.; Gibson, S. M.; Gilchriese, M.; Gillam, T. P. S.; Gillberg, D.; Gingrich, D. M.; Giokaris, N.; Giordani, M. P.; Giordano, R.; Giorgi, F. M.; Giraud, P. F.; Giugni, D.; Giuliani, C.; Giulini, M.; Gjelsten, B. K.; Gkialas, I.; Gladilin, L. K.; Glasman, C.; Glatzer, J.; Glaysher, P. C. F.; Glazov, A.; Glonti, G. L.; Goblirsch-Kolb, M.; Goddard, J. R.; Godfrey, J.; Godlewski, J.; Goeringer, C.; Goldfarb, S.; Golling, T.; Golubkov, D.; Gomes, A.; Fajardo, L. S. Gomez; Gonçalo, R.; Da Costa, J. Goncalves Pinto Firmino; Gonella, L.; de la Hoz, S. González; Parra, G. Gonzalez; Silva, M. L. Gonzalez; Gonzalez-Sevilla, S.; Goossens, L.; Gorbounov, P. A.; Gordon, H. A.; Gorelov, I.; Gorini, B.; Gorini, E.; Gorišek, A.; Gornicki, E.; Goshaw, A. T.; Gössling, C.; Gostkin, M. I.; Gouighri, M.; Goujdami, D.; Goulette, M. P.; Goussiou, A. G.; Goy, C.; Gozpinar, S.; Grabas, H. M. X.; Graber, L.; Grabowska-Bold, I.; Grafström, P.; Grahn, K.-J.; Gramling, J.; Gramstad, E.; Grancagnolo, F.; Grancagnolo, S.; Grassi, V.; Gratchev, V.; Gray, H. M.; Graziani, E.; Grebenyuk, O. G.; Greenwood, Z. D.; Gregersen, K.; Gregor, I. M.; Grenier, P.; Griffiths, J.; Grillo, A. A.; Grimm, K.; Grinstein, S.; Gris, Ph.; Grishkevich, Y. V.; Grivaz, J.-F.; Grohs, J. P.; Grohsjean, A.; Gross, E.; Grosse-Knetter, J.; Grossi, G. C.; Groth-Jensen, J.; Grout, Z. J.; Grybel, K.; Guan, L.; Guescini, F.; Guest, D.; Gueta, O.; Guicheney, C.; Guido, E.; Guillemin, T.; Guindon, S.; Gul, U.; Gumpert, C.; Gunther, J.; Guo, J.; Gupta, S.; Gutierrez, P.; Ortiz, N. G. Gutierrez; Gutschow, C.; Guttman, N.; Guyot, C.; Gwenlan, C.; Gwilliam, C. 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Henriques; Henrot-Versille, S.; Hensel, C.; Herbert, G. H.; Jiménez, Y. Hernández; Herrberg-Schubert, R.; Herten, G.; Hertenberger, R.; Hervas, L.; Hesketh, G. G.; Hessey, N. P.; Hickling, R.; Higón-Rodriguez, E.; Hill, J. C.; Hiller, K. H.; Hillert, S.; Hillier, S. J.; Hinchliffe, I.; Hines, E.; Hirose, M.; Hirschbuehl, D.; Hobbs, J.; Hod, N.; Hodgkinson, M. C.; Hodgson, P.; Hoecker, A.; Hoeferkamp, M. R.; Hoffman, J.; Hoffmann, D.; Hofmann, J. I.; Hohlfeld, M.; Holmes, T. R.; Hong, T. M.; van Huysduynen, L. Hooft; Hostachy, J.-Y.; Hou, S.; Hoummada, A.; Howard, J.; Howarth, J.; Hrabovsky, M.; Hristova, I.; Hrivnac, J.; Hryn'ova, T.; Hsu, P. J.; Hsu, S.-C.; Hu, D.; Hu, X.; Huang, Y.; Hubacek, Z.; Hubaut, F.; Huegging, F.; Huffman, T. B.; Hughes, E. W.; Hughes, G.; Huhtinen, M.; Hülsing, T. A.; Hurwitz, M.; Huseynov, N.; Huston, J.; Huth, J.; Iacobucci, G.; Iakovidis, G.; Ibragimov, I.; Iconomidou-Fayard, L.; Ideal, E.; Iengo, P.; Igonkina, O.; Iizawa, T.; Ikegami, Y.; Ikematsu, K.; Ikeno, M.; Iliadis, D.; Ilic, N.; Inamaru, Y.; Ince, T.; Ioannou, P.; Iodice, M.; Iordanidou, K.; Ippolito, V.; Quiles, A. Irles; Isaksson, C.; Ishino, M.; Ishitsuka, M.; Ishmukhametov, R.; Issever, C.; Istin, S.; Ponce, J. M. Iturbe; Ivashin, A. V.; Iwanski, W.; Iwasaki, H.; Izen, J. M.; Izzo, V.; Jackson, B.; Jackson, J. N.; Jackson, M.; Jackson, P.; Jaekel, M. R.; Jain, V.; Jakobs, K.; Jakobsen, S.; Jakoubek, T.; Jakubek, J.; Jamin, D. O.; Jana, D. K.; Jansen, E.; Jansen, H.; Janssen, J.; Janus, M.; Jarlskog, G.; Javůrek, T.; Jeanty, L.; Jeng, G.-Y.; Jennens, D.; Jenni, P.; Jentzsch, J.; Jeske, C.; Jézéquel, S.; Ji, H.; Ji, W.; Jia, J.; Jiang, Y.; Belenguer, M. Jimenez; Jin, S.; Jinaru, A.; Jinnouchi, O.; Joergensen, M. D.; Johansson, K. E.; Johansson, P.; Johns, K. 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A.; Su, D.; Su, J.; Subramania, H. S.; Subramaniam, R.; Succurro, A.; Sugaya, Y.; Suhr, C.; Suk, M.; Sulin, V. V.; Sultansoy, S.; Sumida, T.; Sun, X.; Sundermann, J. E.; Suruliz, K.; Susinno, G.; Sutton, M. R.; Suzuki, Y.; Svatos, M.; Swedish, S.; Swiatlowski, M.; Sykora, I.; Sykora, T.; Ta, D.; Tackmann, K.; Taenzer, J.; Taffard, A.; Tafirout, R.; Taiblum, N.; Takahashi, Y.; Takai, H.; Takashima, R.; Takeda, H.; Takeshita, T.; Takubo, Y.; Talby, M.; Talyshev, A. A.; Tam, J. Y. C.; Tamsett, M. C.; Tan, K. G.; Tanaka, J.; Tanaka, R.; Tanaka, S.; Tanaka, S.; Tanasijczuk, A. J.; Tani, K.; Tannoury, N.; Tapprogge, S.; Tarem, S.; Tarrade, F.; Tartarelli, G. F.; Tas, P.; Tasevsky, M.; Tashiro, T.; Tassi, E.; Delgado, A. Tavares; Tayalati, Y.; Taylor, C.; Taylor, F. E.; Taylor, G. N.; Taylor, W.; Teischinger, F. A.; Castanheira, M. Teixeira Dias; Teixeira-Dias, P.; Temming, K. K.; Kate, H. Ten; Teng, P. K.; Terada, S.; Terashi, K.; Terron, J.; Terzo, S.; Testa, M.; Teuscher, R. J.; Therhaag, J.; Theveneaux-Pelzer, T.; Thoma, S.; Thomas, J. P.; Thomas-Wilsker, J.; Thompson, E. N.; Thompson, P. D.; Thompson, P. D.; Thompson, A. S.; Thomsen, L. A.; Thomson, E.; Thomson, M.; Thong, W. M.; Thun, R. P.; Tian, F.; Tibbetts, M. J.; Tikhomirov, V. O.; Tikhonov, Yu. A.; Timoshenko, S.; Tiouchichine, E.; Tipton, P.; Tisserant, S.; Todorov, T.; Todorova-Nova, S.; Toggerson, B.; Tojo, J.; Tokár, S.; Tokushuku, K.; Tollefson, K.; Tomlinson, L.; Tomoto, M.; Tompkins, L.; Toms, K.; Topilin, N. D.; Torrence, E.; Torres, H.; Pastor, E. Torró; Toth, J.; Touchard, F.; Tovey, D. R.; Tran, H. L.; Trefzger, T.; Tremblet, L.; Tricoli, A.; Trigger, I. M.; Trincaz-Duvoid, S.; Tripiana, M. F.; Triplett, N.; Trischuk, W.; Trocmé, B.; Troncon, C.; Trottier-McDonald, M.; Trovatelli, M.; True, P.; Trzebinski, M.; Trzupek, A.; Tsarouchas, C.; Tseng, J. C.-L.; Tsiareshka, P. V.; Tsionou, D.; Tsipolitis, G.; Tsirintanis, N.; Tsiskaridze, S.; Tsiskaridze, V.; Tskhadadze, E. G.; Tsukerman, I. I.; Tsulaia, V.; Tsuno, S.; Tsybychev, D.; Tua, A.; Tudorache, A.; Tudorache, V.; Tuna, A. N.; Tupputi, S. A.; Turchikhin, S.; Turecek, D.; Cakir, I. Turk; Turra, R.; Tuts, P. M.; Tykhonov, A.; Tylmad, M.; Tyndel, M.; Uchida, K.; Ueda, I.; Ueno, R.; Ughetto, M.; Ugland, M.; Uhlenbrock, M.; Ukegawa, F.; Unal, G.; Undrus, A.; Unel, G.; Ungaro, F. C.; Unno, Y.; Urbaniec, D.; Urquijo, P.; Usai, G.; Usanova, A.; Vacavant, L.; Vacek, V.; Vachon, B.; Valencic, N.; Valentinetti, S.; Valero, A.; Valery, L.; Valkar, S.; Gallego, E. Valladolid; Vallecorsa, S.; Ferrer, J. A. Valls; Van Der Deijl, P. C.; van der Geer, R.; van der Graaf, H.; Van Der Leeuw, R.; van der Ster, D.; Eldik, N. van; van Gemmeren, P.; Van Nieuwkoop, J.; van Vulpen, I.; van Woerden, M. C.; Vanadia, M.; Vandelli, W.; Vaniachine, A.; Vankov, P.; Vannucci, F.; Vardanyan, G.; Vari, R.; Varnes, E. W.; Varol, T.; Varouchas, D.; Vartapetian, A.; Varvell, K. E.; Vazeille, F.; Schroeder, T. Vazquez; Veatch, J.; Veloso, F.; Veneziano, S.; Ventura, A.; Ventura, D.; Venturi, M.; Venturi, N.; Venturini, A.; Vercesi, V.; Verducci, M.; Verkerke, W.; Vermeulen, J. C.; Vest, A.; Vetterli, M. C.; Viazlo, O.; Vichou, I.; Vickey, T.; Boeriu, O. E. Vickey; Viehhauser, G. H. A.; Viel, S.; Vigne, R.; Villa, M.; Perez, M. Villaplana; Vilucchi, E.; Vincter, M. G.; Vinogradov, V. B.; Virzi, J.; Vitells, O.; Vivarelli, I.; Vaque, F. Vives; Vlachos, S.; Vladoiu, D.; Vlasak, M.; Vogel, A.; Vokac, P.; Volpi, G.; Volpi, M.; von der Schmitt, H.; Radziewski, H. von; von Toerne, E.; Vorobel, V.; Vos, M.; Voss, R.; Vossebeld, J. H.; Vranjes, N.; Milosavljevic, M. Vranjes; Vrba, V.; Vreeswijk, M.; Anh, T. Vu; Vuillermet, R.; Vukotic, I.; Vykydal, Z.; Wagner, P.; Wagner, W.; Wahrmund, S.; Wakabayashi, J.; Walder, J.; Walker, R.; Walkowiak, W.; Wall, R.; Waller, P.; Walsh, B.; Wang, C.; Wang, C.; Wang, F.; Wang, H.; Wang, H.; Wang, J.; Wang, J.; Wang, K.; Wang, R.; Wang, S. M.; Wang, T.; Wang, X.; Warburton, A.; Ward, C. P.; Wardrope, D. R.; Warsinsky, M.; Washbrook, A.; Wasicki, C.; Watanabe, I.; Watkins, P. M.; Watson, A. T.; Watson, I. J.; Watson, M. F.; Watts, G.; Watts, S.; Waugh, B. M.; Webb, S.; Weber, M. S.; Weber, S. W.; Webster, J. S.; Weidberg, A. R.; Weigell, P.; Weinert, B.; Weingarten, J.; Weiser, C.; Weits, H.; Wells, P. S.; Wenaus, T.; Wendland, D.; Weng, Z.; Wengler, T.; Wenig, S.; Wermes, N.; Werner, M.; Werner, P.; Wessels, M.; Wetter, J.; Whalen, K.; White, A.; White, M. J.; White, R.; White, S.; Whiteson, D.; Wicke, D.; Wickens, F. J.; Wiedenmann, W.; Wielers, M.; Wienemann, P.; Wiglesworth, C.; Wiik-Fuchs, L. A. M.; Wijeratne, P. A.; Wildauer, A.; Wildt, M. A.; Wilkens, H. G.; Will, J. Z.; Williams, H. H.; Williams, S.; Willis, C.; Willocq, S.; Wilson, A.; Wilson, J. A.; Wingerter-Seez, I.; Winkelmann, S.; Winklmeier, F.; Wittgen, M.; Wittig, T.; Wittkowski, J.; Wollstadt, S. J.; Wolter, M. W.; Wolters, H.; Wosiek, B. K.; Wotschack, J.; Woudstra, M. J.; Wozniak, K. W.; Wright, M.; Wu, S. L.; Wu, X.; Wu, Y.; Wulf, E.; Wyatt, T. R.; Wynne, B. M.; Xella, S.; Xiao, M.; Xu, D.; Xu, L.; Yabsley, B.; Yacoob, S.; Yamada, M.; Yamaguchi, H.; Yamaguchi, Y.; Yamamoto, A.; Yamamoto, K.; Yamamoto, S.; Yamamura, T.; Yamanaka, T.; Yamauchi, K.; Yamazaki, Y.; Yan, Z.; Yang, H.; Yang, H.; Yang, U. K.; Yang, Y.; Yanush, S.; Yao, L.; Yao, W.-M.; Yasu, Y.; Yatsenko, E.; Wong, K. H. Yau; Ye, J.; Ye, S.; Yen, A. L.; Yildirim, E.; Yilmaz, M.; Yoosoofmiya, R.; Yorita, K.; Yoshida, R.; Yoshihara, K.; Young, C.; Young, C. J. S.; Youssef, S.; Yu, D. R.; Yu, J.; Yu, J. M.; Yu, J.; Yuan, L.; Yurkewicz, A.; Zabinski, B.; Zaidan, R.; Zaitsev, A. M.; Zaman, A.; Zambito, S.; Zanello, L.; Zanzi, D.; Zaytsev, A.; Zeitnitz, C.; Zeman, M.; Zemla, A.; Zengel, K.; Zenin, O.; Ženiš, T.; Zerwas, D.; della Porta, G. Zevi; Zhang, D.; Zhang, F.; Zhang, H.; Zhang, J.; Zhang, L.; Zhang, X.; Zhang, Z.; Zhao, Z.; Zhemchugov, A.; Zhong, J.; Zhou, B.; Zhou, L.; Zhou, N.; Zhu, C. G.; Zhu, H.; Zhu, J.; Zhu, Y.; Zhuang, X.; Zibell, A.; Zieminska, D.; Zimine, N. I.; Zimmermann, C.; Zimmermann, R.; Zimmermann, S.; Zimmermann, S.; Zinonos, Z.; Ziolkowski, M.; Zitoun, R.; Zobernig, G.; Zoccoli, A.; zur Nedden, M.; Zurzolo, G.; Zutshi, V.; Zwalinski, L.

2014-08-01

Distributions sensitive to the underlying event in QCD jet events have been measured with the ATLAS detector at the LHC, based on of proton-proton collision data collected at a centre-of-mass energy of 7 . Charged-particle mean and densities of all-particle and charged-particle multiplicity and have been measured in regions azimuthally transverse to the hardest jet in each event. These are presented both as one-dimensional distributions and with their mean values as functions of the leading-jet transverse momentum from 20 to 800 . The correlation of charged-particle mean with charged-particle multiplicity is also studied, and the densities include the forward rapidity region; these features provide extra data constraints for Monte Carlo modelling of colour reconnection and beam-remnant effects respectively. For the first time, underlying event observables have been computed separately for inclusive jet and exclusive dijet event selections, allowing more detailed study of the interplay of multiple partonic scattering and QCD radiation contributions to the underlying event. Comparisons to the predictions of different Monte Carlo models show a need for further model tuning, but the standard approach is found to generally reproduce the features of the underlying event in both types of event selection.

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

PubMed Central

Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r = 0.7033, MCCB social cognition r = 0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r = 0.7785, PANSS negative r = 0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. PMID:27177764

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

PubMed Central

Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

Evolutionary Algorithm Based Feature Optimization for Multi-Channel EEG Classification.

PubMed

Wang, Yubo; Veluvolu, Kalyana C

2017-01-01

The most BCI systems that rely on EEG signals employ Fourier based methods for time-frequency decomposition for feature extraction. The band-limited multiple Fourier linear combiner is well-suited for such band-limited signals due to its real-time applicability. Despite the improved performance of these techniques in two channel settings, its application in multiple-channel EEG is not straightforward and challenging. As more channels are available, a spatial filter will be required to eliminate the noise and preserve the required useful information. Moreover, multiple-channel EEG also adds the high dimensionality to the frequency feature space. Feature selection will be required to stabilize the performance of the classifier. In this paper, we develop a new method based on Evolutionary Algorithm (EA) to solve these two problems simultaneously. The real-valued EA encodes both the spatial filter estimates and the feature selection into its solution and optimizes it with respect to the classification error. Three Fourier based designs are tested in this paper. Our results show that the combination of Fourier based method with covariance matrix adaptation evolution strategy (CMA-ES) has the best overall performance.

[Clinical value of MRI united-sequences examination in diagnosis and differentiation of morphological sub-type of hilar and extrahepatic big bile duct cholangiocarcinoma].

PubMed

Yin, Long-Lin; Song, Bin; Guan, Ying; Li, Ying-Chun; Chen, Guang-Wen; Zhao, Li-Ming; Lai, Li

2014-09-01

To investigate MRI features and associated histological and pathological changes of hilar and extrahepatic big bile duct cholangiocarcinoma with different morphological sub-types, and its value in differentiating between nodular cholangiocarcinoma (NCC) and intraductal growing cholangiocarcinoma (IDCC). Imaging data of 152 patients with pathologically confirmed hilar and extrahepatic big bile duct cholangiocarcinoma were reviewed, which included 86 periductal infiltrating cholangiocarcinoma (PDCC), 55 NCC, and 11 IDCC. Imaging features of the three morphological sub-types were compared. Each of the subtypes demonstrated its unique imaging features. Significant differences (P < 0.05) were found between NCC and IDCC in tumor shape, dynamic enhanced pattern, enhancement degree during equilibrium phase, multiplicity or singleness of tumor, changes in wall and lumen of bile duct at the tumor-bearing segment, dilatation of tumor upstream or downstream bile duct, and invasion of adjacent organs. Imaging features reveal tumor growth patterns of hilar and extrahepatic big bile duct cholangiocarcinoma. MRI united-sequences examination can accurately describe those imaging features for differentiation diagnosis.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-29

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

Preprocessing Structured Clinical Data for Predictive Modeling and Decision Support

PubMed Central

Oliveira, Mónica Duarte; Janela, Filipe; Martins, Henrique M. G.

2016-01-01

Summary Background EHR systems have high potential to improve healthcare delivery and management. Although structured EHR data generates information in machine-readable formats, their use for decision support still poses technical challenges for researchers due to the need to preprocess and convert data into a matrix format. During our research, we observed that clinical informatics literature does not provide guidance for researchers on how to build this matrix while avoiding potential pitfalls. Objectives This article aims to provide researchers a roadmap of the main technical challenges of preprocessing structured EHR data and possible strategies to overcome them. Methods Along standard data processing stages – extracting database entries, defining features, processing data, assessing feature values and integrating data elements, within an EDPAI framework –, we identified the main challenges faced by researchers and reflect on how to address those challenges based on lessons learned from our research experience and on best practices from related literature. We highlight the main potential sources of error, present strategies to approach those challenges and discuss implications of these strategies. Results Following the EDPAI framework, researchers face five key challenges: (1) gathering and integrating data, (2) identifying and handling different feature types, (3) combining features to handle redundancy and granularity, (4) addressing data missingness, and (5) handling multiple feature values. Strategies to address these challenges include: cross-checking identifiers for robust data retrieval and integration; applying clinical knowledge in identifying feature types, in addressing redundancy and granularity, and in accommodating multiple feature values; and investigating missing patterns adequately. Conclusions This article contributes to literature by providing a roadmap to inform structured EHR data preprocessing. It may advise researchers on potential pitfalls and implications of methodological decisions in handling structured data, so as to avoid biases and help realize the benefits of the secondary use of EHR data. PMID:27924347

The mediational significance of negative/depressive affect in the relationship of childhood maltreatment and eating disorder features in adolescent psychiatric inpatients.

PubMed

Hopwood, C J; Ansell, E B; Fehon, D C; Grilo, C M

2011-03-01

Childhood maltreatment is a risk factor for eating disorder and negative/depressive affect appears to mediate this relation. However, the specific elements of eating- and body-related psychopathology that are influenced by various forms of childhood maltreatment remain unclear, and investigations among adolescents and men/boys have been limited. This study investigated the mediating role of negative affect/depression across multiple types of childhood maltreatment and eating disorder features in hospitalized adolescent boys and girls. Participants were 148 adolescent psychiatric inpatients who completed an assessment battery including measures of specific forms of childhood maltreatment (sexual, emotional, and physical abuse), negative/depressive affect, and eating disorder features (dietary restriction, binge eating, and body dissatisfaction). Findings suggest that for girls, negative/depressive affect significantly mediates the relationships between childhood maltreatment and eating disorder psychopathology, although effects varied somewhat across types of maltreatment and eating disorder features. Generalization of mediation effects to boys was limited.

Face detection in color images using skin color, Laplacian of Gaussian, and Euler number

NASA Astrophysics Data System (ADS)

Saligrama Sundara Raman, Shylaja; Kannanedhi Narasimha Sastry, Balasubramanya Murthy; Subramanyam, Natarajan; Senkutuvan, Ramya; Srikanth, Radhika; John, Nikita; Rao, Prateek

2010-02-01

In this a paper, a feature based approach to face detection has been proposed using an ensemble of algorithms. The method uses chrominance values and edge features to classify the image as skin and nonskin regions. The edge detector used for this purpose is Laplacian of Gaussian (LoG) which is found to be appropriate when images having multiple faces with noise in them. Eight connectivity analysis of these regions will segregate them as probable face or nonface. The procedure is made more robust by identifying local features within these skin regions which include number of holes, percentage of skin and the golden ratio. The method proposed has been tested on color face images of various races obtained from different sources and its performance is found to be encouraging as the color segmentation cleans up almost all the complex facial features. The result obtained has a calculated accuracy of 86.5% on a test set of 230 images.

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.

Flexibility, Diversity, and Cooperativity: Pillars of Enzyme Catalysis

PubMed Central

Hammes, Gordon G.; Benkovic, Stephen J.; Hammes-Schiffer, Sharon

2011-01-01

This brief review discusses our current understanding of the molecular basis of enzyme catalysis. A historical development is presented, beginning with steady state kinetics and progressing through modern fast reaction methods, NMR, and single molecule fluorescence techniques. Experimental results are summarized for ribonuclease, aspartate aminotransferase, and especially dihydrofolate reductase (DHFR). Multiple intermediates, multiple conformations, and cooperative conformational changes are shown to be an essential part of virtually all enzyme mechanisms. In the case of DHFR, theoretical investigations have provided detailed information about the movement of atoms within the enzyme-substrate complex as the reaction proceeds along the collective reaction coordinate for hydride transfer. A general mechanism is presented for enzyme catalysis that includes multiple intermediates and a complex, multidimensional standard free energy surface. Protein flexibility, diverse protein conformations, and cooperative conformational changes are important features of this model. PMID:22029278

Microcephaly, ectodermal dysplasia, multiple skeletal anomalies and distinctive facial appearance: delineation of cerebro-dermato-osseous-dysplasia.

PubMed

Castori, Marco; Pascolini, Giulia; Parisi, Valentina; Sana, Maria Elena; Novelli, Antonio; Nürnberg, Peter; Iascone, Maria; Grammatico, Paola

2015-04-01

In 1980, a novel multiple malformation syndrome has been described in a 17-year-old woman with micro- and turricephaly, intellectual disability, distinctive facial appearance, congenital atrichia, and multiple skeletal anomalies mainly affecting the limbs. Four further sporadic patients and a couple of affected sibs are also reported with a broad clinical variability. Here, we describe a 4-year-old girl strikingly resembling the original report. Phenotype comparison identified a recurrent pattern of multisystem features involving the central nervous system, and skin and bones in five sporadic patients (including ours), while the two sibs and a further sporadic case show significant phenotypic divergence. Marked clinical variability within the same entity versus syndrome splitting is discussed and the term "cerebro-dermato-osseous dysplasia" is introduced to define this condition. © 2015 Wiley Periodicals, Inc.

XML Encoding of Features Describing Rule-Based Modeling of Reaction Networks with Multi-Component Molecular Complexes

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2011-01-01

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833

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.

Autoimmune neuropathies associated to rheumatic diseases.

PubMed

Martinez, Alberto R M; Faber, Ingrid; Nucci, Anamarli; Appenzeller, Simone; França, Marcondes C

2017-04-01

Systemic manifestations are frequent in autoimmune rheumatic diseases and include peripheral nervous system damage. Neuron cell body, axons and myelin sheath may all be affected in this context. This involvement results in severe and sometimes disabling symptoms. Sensory, motor and autonomic features may be present in different patterns that emerge as peculiar clinical pictures. Prompt recognition of these neuropathies is pivotal to guide treatment and reduce the risks of long term disability. In this review, we aim to describe the main immune-mediated neuropathies associated to rheumatic diseases: sensory neuronopathies, multiple mononeuropathies and chronic inflammatory demyelinating polyradiculoneuropathy, with an emphasis on clinical features and therapeutic options. Copyright © 2017 Elsevier B.V. All rights reserved.

Network flexibility of the IRIDIUM (R) Global Mobile Satellite System

NASA Technical Reports Server (NTRS)

Hutcheson, Jonathan; Laurin, Mala

1995-01-01

The IRIDIUM system is a global personal communications system supported by a constellation of 66 low earth orbit (LEO) satellites and a collection of earth-based 'gateway' switching installations. Like traditional wireless cellular systems, coverage is achieved by a grid of cells in which bandwidth is reused for spectral efficiency. Unlike any cellular system ever built, the moving cells can be shared by multiple switching facilities. Noteworthy features of the IRIDIUM system include inter-satellite links, a GSM-based telephony architecture, and a geographically controlled system access process. These features, working in concert, permit flexible and reliable administration of the worldwide service area by gateway operators. This paper will explore this unique concept.

Acoustic design of the QCSEE propulsion systems

NASA Technical Reports Server (NTRS)

Loeffler, I. J.; Smith, E. B.; Sowers, H. D.

1976-01-01

Acoustic design features and techniques employed in the Quiet Clean Short-Haul Experimental Engine (QCSEE) Program are described. The role of jet/flap noise in selecting the engine fan pressure ratio for powered lift propulsion systems is discussed. The QCSEE acoustic design features include a hybrid inlet (near-sonic throat velocity with acoustic treatment); low fan and core pressure ratios; low fan tip speeds; gear-driven fans; high and low frequency stacked core noise treatment; multiple-thickness treatment; bulk absorber treatment; and treatment on the stator vanes. The QCSEE designs represent and anticipated acoustic technology improvement of 12 to 16 PNdb relative to the noise levels of the low-noise engines used on current wide-body commercial jet transport aircraft.

Detecting multiple moving objects in crowded environments with coherent motion regions

DOEpatents

Cheriyadat, Anil M.; Radke, Richard J.

2013-06-11

Coherent motion regions extend in time as well as space, enforcing consistency in detected objects over long time periods and making the algorithm robust to noisy or short point tracks. As a result of enforcing the constraint that selected coherent motion regions contain disjoint sets of tracks defined in a three-dimensional space including a time dimension. An algorithm operates directly on raw, unconditioned low-level feature point tracks, and minimizes a global measure of the coherent motion regions. At least one discrete moving object is identified in a time series of video images based on the trajectory similarity factors, which is a measure of a maximum distance between a pair of feature point tracks.

Combining feature extraction and classification for fNIRS BCIs by regularized least squares optimization.

PubMed

Heger, Dominic; Herff, Christian; Schultz, Tanja

2014-01-01

In this paper, we show that multiple operations of the typical pattern recognition chain of an fNIRS-based BCI, including feature extraction and classification, can be unified by solving a convex optimization problem. We formulate a regularized least squares problem that learns a single affine transformation of raw HbO(2) and HbR signals. We show that this transformation can achieve competitive results in an fNIRS BCI classification task, as it significantly improves recognition of different levels of workload over previously published results on a publicly available n-back data set. Furthermore, we visualize the learned models and analyze their spatio-temporal characteristics.

Multiple sclerosis - discharge

MedlinePlus

... this page: //medlineplus.gov/ency/patientinstructions/000129.htm Multiple sclerosis - discharge To use the sharing features on this ... Your doctor has told you that you have multiple sclerosis (MS). This disease affects the brain and spinal ...

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.

Rotavirus Infections - Multiple Languages

MedlinePlus

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Cosmetic Dentistry - Multiple Languages

MedlinePlus

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Salmonella Infections - Multiple Languages

MedlinePlus

... Are Here: Home → Multiple Languages → All Health Topics → Salmonella Infections URL of this page: https://medlineplus.gov/ ... V W XYZ List of All Topics All Salmonella Infections - Multiple Languages To use the sharing features ...

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

Retrobulbar anaplastic astrocytoma in a dog: clinicopathological and ultrasonographic features.

PubMed

Martín, E; Pérez, J; Mozos, E; López, R; Molleda, J M

2000-08-01

An 11-year-old entire female German shepherd dog was presented with a progressive non-painful exophthalmos of the right eye. Ultrasonographic examination revealed a solid and well-defined orbital mass compressing the globe. Thoracic radiography revealed multiple pulmonary metastases of different sizes. The histopathological and immunohistochemical features of both the retrobulbar tumour and pulmonary metastases were consistent with an anaplastic astrocytoma. This represents an unusual case of an extracranial astrocytoma with multiple pulmonary metastases. The clinical features and the ultrasonographic, histopathological and immunohistochemical findings are described.

Subject-specific and pose-oriented facial features for face recognition across poses.

PubMed

Lee, Ping-Han; Hsu, Gee-Sern; Wang, Yun-Wen; Hung, Yi-Ping

2012-10-01

Most face recognition scenarios assume that frontal faces or mug shots are available for enrollment to the database, faces of other poses are collected in the probe set. Given a face from the probe set, one needs to determine whether a match in the database exists. This is under the assumption that in forensic applications, most suspects have their mug shots available in the database, and face recognition aims at recognizing the suspects when their faces of various poses are captured by a surveillance camera. This paper considers a different scenario: given a face with multiple poses available, which may or may not include a mug shot, develop a method to recognize the face with poses different from those captured. That is, given two disjoint sets of poses of a face, one for enrollment and the other for recognition, this paper reports a method best for handling such cases. The proposed method includes feature extraction and classification. For feature extraction, we first cluster the poses of each subject's face in the enrollment set into a few pose classes and then decompose the appearance of the face in each pose class using Embedded Hidden Markov Model, which allows us to define a set of subject-specific and pose-priented (SSPO) facial components for each subject. For classification, an Adaboost weighting scheme is used to fuse the component classifiers with SSPO component features. The proposed method is proven to outperform other approaches, including a component-based classifier with local facial features cropped manually, in an extensive performance evaluation study.

Eddy current analysis of cracks grown from surface defects and non-metallic particles

NASA Astrophysics Data System (ADS)

Cherry, Matthew R.; Hutson, Alisha; Aldrin, John C.; Shank, Jared

2018-04-01

Eddy current methods are sensitive to any discrete change in conductivity. Traditionally this has been used to determine the presence of a crack. However, other features that are not cracks such as non-metallic inclusions, carbide stringers and surface voids can cause an eddy current indication that could potentially lead to a reject of an in-service component. These features may not actually be lifelimiting, meaning NDE methods could reject components with remaining useful life. In-depth analysis of signals from eddy current sensors could provide a means of sorting between rejectable indications and false-calls from geometric and non-conductive features. In this project, cracks were grown from voids and non-metallic inclusions in a nickel-based super-alloy and eddy current analysis was performed on multiple intermediate steps of fatigue. Data were collected with multiple different ECT probes and at multiple frequencies, and the results were analyzed. The results show how cracks growing from non-metallic features can skew eddy current signals and make characterization a challenge. Modeling and simulation was performed with multiple analysis codes, and the models were found to be in good agreement with the data for cracks growing away from voids and non-metallic inclusions.

xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data.

PubMed

Uppal, Karan; Soltow, Quinlyn A; Strobel, Frederick H; Pittard, W Stephen; Gernert, Kim M; Yu, Tianwei; Jones, Dean P

2013-01-16

Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract m/z features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation. xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1) improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2) evaluate sample quality and feature consistency, 3) detect feature overlap between datasets, and 4) characterize high-resolution m/z matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites. xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.

Policy Driven Development: Flexible Policy Insertion for Large Scale Systems.

PubMed

Demchak, Barry; Krüger, Ingolf

2012-07-01

The success of a software system depends critically on how well it reflects and adapts to stakeholder requirements. Traditional development methods often frustrate stakeholders by creating long latencies between requirement articulation and system deployment, especially in large scale systems. One source of latency is the maintenance of policy decisions encoded directly into system workflows at development time, including those involving access control and feature set selection. We created the Policy Driven Development (PDD) methodology to address these development latencies by enabling the flexible injection of decision points into existing workflows at runtime , thus enabling policy composition that integrates requirements furnished by multiple, oblivious stakeholder groups. Using PDD, we designed and implemented a production cyberinfrastructure that demonstrates policy and workflow injection that quickly implements stakeholder requirements, including features not contemplated in the original system design. PDD provides a path to quickly and cost effectively evolve such applications over a long lifetime.

Clinical profile of depressive disorder in children.

PubMed

Krishnakumar, P; Geeta, M G

2006-06-01

The aim of this retrospective study was to evaluate the risk factors, clinical features and co-morbid disorders of depressive disorder in children below the age of 12 years. Children who attended the child guidance clinic between January 2000 and December 2003 formed the subjects for the study. The diagnosis of depressive disorder was based on DSMIV diagnostic criteria for Major Depressive Disorder, Single episode. There were 26 boys and 19 girls. Stress at school and in the family was significantly associated with depressive disorder. Children with depressive disorder had significantly more family members affected with mental illnesses. The clinical features included diminished interest in play and activities, excessive tiredness, low self- esteem, problems with concentration, multiple somatic complaints, behavior symptoms like anger and aggression, recent deterioration in school performance and suicidal behavior. Majority of children had other associated psychiatric disorders which included dysthymic disorder, anxiety disorders, conduct disorder and conversion disorder.

Perceptual representation and effectiveness of local figure–ground cues in natural contours

PubMed Central

Sakai, Ko; Matsuoka, Shouhei; Kurematsu, Ken; Hatori, Yasuhiro

2015-01-01

A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure–ground segregation. Although previous studies have reported local contour features that evoke figure–ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural contour shapes. We performed similarity tests between local contours, and examined the contribution of the contour features to the perceptual similarities between the contours. The local contours were sampled from natural contours so that their distribution was uniform in the space composed of the three contour features. This sampling ensured the equal appearance frequency of the factors and a wide variety of contour shapes including those comprised of contradictory factors that induce figure in the opposite directions. This sampling from natural contours is advantageous in order to randomly pickup a variety of contours that satisfy a wide range of cue combinations. Multidimensional scaling analyses showed that the combinations of convexity, closure, and symmetry contribute to perceptual similarity, thus they are perceptual quantities. Second, we examined whether the three features contribute to local figure–ground perception. We performed psychophysical experiments to judge the direction of the figure along the local contours, and examined the contribution of the features to the figure–ground judgment. Multiple linear regression analyses showed that closure was a significant factor, but that convexity and symmetry were not. These results indicate that closure is dominant in the local figure–ground perception with natural contours when the other cues coexist with equal probability including contradictory cases. PMID:26579057

Perceptual representation and effectiveness of local figure-ground cues in natural contours.

PubMed

Sakai, Ko; Matsuoka, Shouhei; Kurematsu, Ken; Hatori, Yasuhiro

2015-01-01

A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure-ground segregation. Although previous studies have reported local contour features that evoke figure-ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural contour shapes. We performed similarity tests between local contours, and examined the contribution of the contour features to the perceptual similarities between the contours. The local contours were sampled from natural contours so that their distribution was uniform in the space composed of the three contour features. This sampling ensured the equal appearance frequency of the factors and a wide variety of contour shapes including those comprised of contradictory factors that induce figure in the opposite directions. This sampling from natural contours is advantageous in order to randomly pickup a variety of contours that satisfy a wide range of cue combinations. Multidimensional scaling analyses showed that the combinations of convexity, closure, and symmetry contribute to perceptual similarity, thus they are perceptual quantities. Second, we examined whether the three features contribute to local figure-ground perception. We performed psychophysical experiments to judge the direction of the figure along the local contours, and examined the contribution of the features to the figure-ground judgment. Multiple linear regression analyses showed that closure was a significant factor, but that convexity and symmetry were not. These results indicate that closure is dominant in the local figure-ground perception with natural contours when the other cues coexist with equal probability including contradictory cases.

Confocal and dermoscopic features of basal cell carcinoma in Gorlin-Goltz syndrome: A case report.

PubMed

Casari, Alice; Argenziano, Giuseppe; Moscarella, Elvira; Lallas, Aimilios; Longo, Caterina

2017-05-01

Gorlin-Goltz (GS) syndrome is an autosomal dominant disease linked to a mutation in the PTCH gene. Major criteria include the onset of multiple basal cell carcinoma (BCC), keratocystic odontogenic tumours in the jaws and bifid ribs. Dermoscopy and reflectance confocal microscopy represent imaging tools that are able to increase the diagnostic accuracy of skin cancer in a totally noninvasive manner, without performing punch biopsies. Here we present a case of a young woman in whom the combined approach of dermoscopy and RCM led to the identification of multiple small inconspicuous lesions as BCC and thus to the diagnosis of GS syndrome. © 2016 The Australasian College of Dermatologists.

Generalized Landauer equation: Absorption-controlled diffusion processes

NASA Astrophysics Data System (ADS)

Godoy, Salvador; García-Colín, L. S.; Micenmacher, Victor

1999-05-01

The exact expression of the one-dimensional Boltzmann multiple-scattering coefficients, for the passage of particles through a slab of a given material, is obtained in terms of the single-scattering cross section of the material, including absorption. The remarkable feature of the result is that for multiple scattering in a metal, free from absorption, one recovers the well-known Landauer result for conduction electrons. In the case of particles, such as neutrons, moving through a weak absorbing media, Landuer's formula is modified due to the absorption cross section. For photons, in a strong absorbing media, one recovers the Lambert-Beer equation. In this latter case one may therefore speak of absorption-controlled diffusive processes.

Domain decomposition methods in computational fluid dynamics

NASA Technical Reports Server (NTRS)

Gropp, William D.; Keyes, David E.

1991-01-01

The divide-and-conquer paradigm of iterative domain decomposition, or substructuring, has become a practical tool in computational fluid dynamic applications because of its flexibility in accommodating adaptive refinement through locally uniform (or quasi-uniform) grids, its ability to exploit multiple discretizations of the operator equations, and the modular pathway it provides towards parallelism. These features are illustrated on the classic model problem of flow over a backstep using Newton's method as the nonlinear iteration. Multiple discretizations (second-order in the operator and first-order in the preconditioner) and locally uniform mesh refinement pay dividends separately, and they can be combined synergistically. Sample performance results are included from an Intel iPSC/860 hypercube implementation.

Application of Handheld Laser-Induced Breakdown Spectroscopy (LIBS) to Geochemical Analysis.

PubMed

Connors, Brendan; Somers, Andrew; Day, David

2016-05-01

While laser-induced breakdown spectroscopy (LIBS) has been in use for decades, only within the last two years has technology progressed to the point of enabling true handheld, self-contained instruments. Several instruments are now commercially available with a range of capabilities and features. In this paper, the SciAps Z-500 handheld LIBS instrument functionality and sub-systems are reviewed. Several assayed geochemical sample sets, including igneous rocks and soils, are investigated. Calibration data are presented for multiple elements of interest along with examples of elemental mapping in heterogeneous samples. Sample preparation and the data collection method from multiple locations and data analysis are discussed. © The Author(s) 2016.

Polyradiculopathies from Schwannomatosis

PubMed Central

Jia, Yuxia; Kraus, James A.; Reddy, Hasini; Groff, Michael; Wong, Eric T

2011-01-01

We describe a case of schwannomatosis presenting as radicular pain and numbness in multiple radicular nerve distributions. There were multiple peripheral nerve tumors detected by magnetic resonance imaging (MRI) at the left vestibular nerve, cauda equina, right radial nerve, thoracic paraspinal nerve, and brachial plexi. Several resected tumors have features of schwannomas, including hypercellular Antoni A areas, hypocellular Antoni B areas, Verocay bodies, and hyalinized blood vessels. The specimens are also positive for immunohistochemical staining for INI1 with diffuse nuclear staining. The findings are consistent with sporadic form of schwannomatosis. This case highlights the importance of using MRI and INI1 immunohistochemistry to differentiate familial schwannomatosis, neurofibromatosis 2 (NF2)-associated schwannomatosis, and sporadic schwannomatosis. PMID:21643503

Investigation of automated feature extraction using multiple data sources

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Perkins, Simon J.; Pope, Paul A.; Theiler, James P.; David, Nancy A.; Porter, Reid B.

2003-04-01

An increasing number and variety of platforms are now capable of collecting remote sensing data over a particular scene. For many applications, the information available from any individual sensor may be incomplete, inconsistent or imprecise. However, other sources may provide complementary and/or additional data. Thus, for an application such as image feature extraction or classification, it may be that fusing the mulitple data sources can lead to more consistent and reliable results. Unfortunately, with the increased complexity of the fused data, the search space of feature-extraction or classification algorithms also greatly increases. With a single data source, the determination of a suitable algorithm may be a significant challenge for an image analyst. With the fused data, the search for suitable algorithms can go far beyond the capabilities of a human in a realistic time frame, and becomes the realm of machine learning, where the computational power of modern computers can be harnessed to the task at hand. We describe experiments in which we investigate the ability of a suite of automated feature extraction tools developed at Los Alamos National Laboratory to make use of multiple data sources for various feature extraction tasks. We compare and contrast this software's capabilities on 1) individual data sets from different data sources 2) fused data sets from multiple data sources and 3) fusion of results from multiple individual data sources.

Non-marfan idiopathic medionecrosis (cystic medial necrosis) presenting with multiple visceral artery aneurysms and diffuse connective tissue fragility: Two brothers

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

Kubota, Jun; Tsunemura, Mami; Amano, Shigeko

1997-05-15

Two brothers with multiple visceral artery aneurysms or dilatations and diffuse connective tissue fragility who did not have clinical features of Marfan syndrome are reported. One presented with retroperitoneal hemorrhage during angiography, and idiopathic medionecrosis was proved by resection of the aneurysms. These cases belong to the heterogeneous group of Marfan syndrome. The angiographical features (multiple dilation of visceral arteries) suggests fragility of connective tissue and is predictive of hazards during and after a catheterization and operation.

Experience improves feature extraction in Drosophila.

PubMed

Peng, Yueqing; Xi, Wang; Zhang, Wei; Zhang, Ke; Guo, Aike

2007-05-09

Previous exposure to a pattern in the visual scene can enhance subsequent recognition of that pattern in many species from honeybees to humans. However, whether previous experience with a visual feature of an object, such as color or shape, can also facilitate later recognition of that particular feature from multiple visual features is largely unknown. Visual feature extraction is the ability to select the key component from multiple visual features. Using a visual flight simulator, we designed a novel protocol for visual feature extraction to investigate the effects of previous experience on visual reinforcement learning in Drosophila. We found that, after conditioning with a visual feature of objects among combinatorial shape-color features, wild-type flies exhibited poor ability to extract the correct visual feature. However, the ability for visual feature extraction was greatly enhanced in flies trained previously with that visual feature alone. Moreover, we demonstrated that flies might possess the ability to extract the abstract category of "shape" but not a particular shape. Finally, this experience-dependent feature extraction is absent in flies with defective MBs, one of the central brain structures in Drosophila. Our results indicate that previous experience can enhance visual feature extraction in Drosophila and that MBs are required for this experience-dependent visual cognition.

Segmentation of prostate boundaries from ultrasound images using statistical shape model.

PubMed

Shen, Dinggang; Zhan, Yiqiang; Davatzikos, Christos

2003-04-01

This paper presents a statistical shape model for the automatic prostate segmentation in transrectal ultrasound images. A Gabor filter bank is first used to characterize the prostate boundaries in ultrasound images in both multiple scales and multiple orientations. The Gabor features are further reconstructed to be invariant to the rotation of the ultrasound probe and incorporated in the prostate model as image attributes for guiding the deformable segmentation. A hierarchical deformation strategy is then employed, in which the model adaptively focuses on the similarity of different Gabor features at different deformation stages using a multiresolution technique, i.e., coarse features first and fine features later. A number of successful experiments validate the algorithm.

Carriers of the astronomical 2175 ? extinction feature

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

Bradley, J; Dai, Z; Ernie, R

2004-07-20

The 2175 {angstrom} extinction feature is by far the strongest spectral signature of interstellar dust observed by astronomers. Forty years after its discovery the origin of the feature and the nature of the carrier remain controversial. The feature is enigmatic because although its central wavelength is almost invariant its bandwidth varies strongly from one sightline to another, suggesting multiple carriers or a single carrier with variable properties. Using a monochromated transmission electron microscope and valence electron energy-loss spectroscopy we have detected a 5.7 eV (2175 {angstrom}) feature in submicrometer-sized interstellar grains within interplanetary dust particles (IDPs) collected in the stratosphere.more » The carriers are organic carbon and amorphous silicates that are abundant and closely associated with one another both in IDPs and in the interstellar medium. Multiple carriers rather than a single carrier may explain the invariant central wavelength and variable bandwidth of the astronomical 2175 {angstrom} feature.« less

Visualizing Human Migration Trhough Space and Time

NASA Astrophysics Data System (ADS)

Zambotti, G.; Guan, W.; Gest, J.

2015-07-01

Human migration has been an important activity in human societies since antiquity. Since 1890, approximately three percent of the world's population has lived outside of their country of origin. As globalization intensifies in the modern era, human migration persists even as governments seek to more stringently regulate flows. Understanding this phenomenon, its causes, processes and impacts often starts from measuring and visualizing its spatiotemporal patterns. This study builds a generic online platform for users to interactively visualize human migration through space and time. This entails quickly ingesting human migration data in plain text or tabular format; matching the records with pre-established geographic features such as administrative polygons; symbolizing the migration flow by circular arcs of varying color and weight based on the flow attributes; connecting the centroids of the origin and destination polygons; and allowing the user to select either an origin or a destination feature to display all flows in or out of that feature through time. The method was first developed using ArcGIS Server for world-wide cross-country migration, and later applied to visualizing domestic migration patterns within China between provinces, and between states in the United States, all through multiple years. The technical challenges of this study include simplifying the shapes of features to enhance user interaction, rendering performance and application scalability; enabling the temporal renderers to provide time-based rendering of features and the flow among them; and developing a responsive web design (RWD) application to provide an optimal viewing experience. The platform is available online for the public to use, and the methodology is easily adoptable to visualizing any flow, not only human migration but also the flow of goods, capital, disease, ideology, etc., between multiple origins and destinations across space and time.

Herbal Medicine - Multiple Languages

MedlinePlus

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Whooping Cough - Multiple Languages

MedlinePlus

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What's new in multiple sclerosis spasticity research? Poster session highlights.

PubMed

Linker, Ralf

2017-11-01

Each year at the Multiple Sclerosis Experts Summit, relevant research in the field of multiple sclerosis spasticity is featured in poster sessions. The main studies presented at this year's meeting are summarized herein.

Zika Virus - Multiple Languages

MedlinePlus

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Pacemakers and Implantable Defibrillators - Multiple Languages

MedlinePlus

... Multiple Languages → All Health Topics → Pacemakers and Implantable Defibrillators URL of this page: https://medlineplus.gov/languages/ ... List of All Topics All Pacemakers and Implantable Defibrillators - Multiple Languages To use the sharing features on ...

Diabetic Foot - Multiple Languages

MedlinePlus

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Panic Disorder - Multiple Languages

MedlinePlus

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Domestic Violence - Multiple Languages

MedlinePlus

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Elder Abuse - Multiple Languages

MedlinePlus

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Head Lice - Multiple Languages

MedlinePlus

... Are Here: Home → Multiple Languages → All Health Topics → Head Lice URL of this page: https://medlineplus.gov/languages/ ... V W XYZ List of All Topics All Head Lice - Multiple Languages To use the sharing features on ...

Genital Warts - Multiple Languages

MedlinePlus

... Are Here: Home → Multiple Languages → All Health Topics → Genital Warts URL of this page: https://medlineplus.gov/languages/ ... V W XYZ List of All Topics All Genital Warts - Multiple Languages To use the sharing features on ...

Acoustic features of objects matched by an echolocating bottlenose dolphin.

PubMed

Delong, Caroline M; Au, Whitlow W L; Lemonds, David W; Harley, Heidi E; Roitblat, Herbert L

2006-03-01

The focus of this study was to investigate how dolphins use acoustic features in returning echolocation signals to discriminate among objects. An echolocating dolphin performed a match-to-sample task with objects that varied in size, shape, material, and texture. After the task was completed, the features of the object echoes were measured (e.g., target strength, peak frequency). The dolphin's error patterns were examined in conjunction with the between-object variation in acoustic features to identify the acoustic features that the dolphin used to discriminate among the objects. The present study explored two hypotheses regarding the way dolphins use acoustic information in echoes: (1) use of a single feature, or (2) use of a linear combination of multiple features. The results suggested that dolphins do not use a single feature across all object sets or a linear combination of six echo features. Five features appeared to be important to the dolphin on four or more sets: the echo spectrum shape, the pattern of changes in target strength and number of highlights as a function of object orientation, and peak and center frequency. These data suggest that dolphins use multiple features and integrate information across echoes from a range of object orientations.

Experimental models of demyelination and remyelination.

PubMed

Torre-Fuentes, L; Moreno-Jiménez, L; Pytel, V; Matías-Guiu, J A; Gómez-Pinedo, U; Matías-Guiu, J

2017-08-29

Experimental animal models constitute a useful tool to deepen our knowledge of central nervous system disorders. In the case of multiple sclerosis, however, there is no such specific model able to provide an overview of the disease; multiple models covering the different pathophysiological features of the disease are therefore necessary. We reviewed the different in vitro and in vivo experimental models used in multiple sclerosis research. Concerning in vitro models, we analysed cell cultures and slice models. As for in vivo models, we examined such models of autoimmunity and inflammation as experimental allergic encephalitis in different animals and virus-induced demyelinating diseases. Furthermore, we analysed models of demyelination and remyelination, including chemical lesions caused by cuprizone, lysolecithin, and ethidium bromide; zebrafish; and transgenic models. Experimental models provide a deeper understanding of the different pathogenic mechanisms involved in multiple sclerosis. Choosing one model or another depends on the specific aims of the study. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Microfabricated Fountain Pens for High-Density DNA Arrays

PubMed Central

Reese, Matthew O.; van Dam, R. Michae; Scherer, Axel; Quake, Stephen R.

2003-01-01

We used photolithographic microfabrication techniques to create very small stainless steel fountain pens that were installed in place of conventional pens on a microarray spotter. Because of the small feature size produced by the microfabricated pens, we were able to print arrays with up to 25,000 spots/cm2, significantly higher than can be achieved by other deposition methods. This feature density is sufficiently large that a standard microscope slide can contain multiple replicates of every gene in a complex organism such as a mouse or human. We tested carryover during array printing with dye solution, labeled DNA, and hybridized DNA, and we found it to be indistinguishable from background. Hybridization also showed good sequence specificity to printed oligonucleotides. In addition to improved slide capacity, the microfabrication process offers the possibility of low-cost mass-produced pens and the flexibility to include novel pen features that cannot be machined with conventional techniques. PMID:12975313

Electromyogram whitening for improved classification accuracy in upper limb prosthesis control.

PubMed

Liu, Lukai; Liu, Pu; Clancy, Edward A; Scheme, Erik; Englehart

2013-09-01

Time and frequency domain features of the surface electromyogram (EMG) signal acquired from multiple channels have frequently been investigated for use in controlling upper-limb prostheses. A common control method is EMG-based motion classification. We propose the use of EMG signal whitening as a preprocessing step in EMG-based motion classification. Whitening decorrelates the EMG signal and has been shown to be advantageous in other EMG applications including EMG amplitude estimation and EMG-force processing. In a study of ten intact subjects and five amputees with up to 11 motion classes and ten electrode channels, we found that the coefficient of variation of time domain features (mean absolute value, average signal length and normalized zero crossing rate) was significantly reduced due to whitening. When using these features along with autoregressive power spectrum coefficients, whitening added approximately five percentage points to classification accuracy when small window lengths were considered.

MRMer, an interactive open source and cross-platform system for data extraction and visualization of multiple reaction monitoring experiments.

PubMed

Martin, Daniel B; Holzman, Ted; May, Damon; Peterson, Amelia; Eastham, Ashley; Eng, Jimmy; McIntosh, Martin

2008-11-01

Multiple reaction monitoring (MRM) mass spectrometry identifies and quantifies specific peptides in a complex mixture with very high sensitivity and speed and thus has promise for the high throughput screening of clinical samples for candidate biomarkers. We have developed an interactive software platform, called MRMer, for managing highly complex MRM-MS experiments, including quantitative analyses using heavy/light isotopic peptide pairs. MRMer parses and extracts information from MS files encoded in the platform-independent mzXML data format. It extracts and infers precursor-product ion transition pairings, computes integrated ion intensities, and permits rapid visual curation for analyses exceeding 1000 precursor-product pairs. Results can be easily output for quantitative comparison of consecutive runs. Additionally MRMer incorporates features that permit the quantitative analysis experiments including heavy and light isotopic peptide pairs. MRMer is open source and provided under the Apache 2.0 license.

Chromosome catastrophes involve replication mechanisms generating complex genomic rearrangements

PubMed Central

Liu, Pengfei; Erez, Ayelet; Sreenath Nagamani, Sandesh C.; Dhar, Shweta U.; Kołodziejska, Katarzyna E.; Dharmadhikari, Avinash V.; Cooper, M. Lance; Wiszniewska, Joanna; Zhang, Feng; Withers, Marjorie A.; Bacino, Carlos A.; Campos-Acevedo, Luis Daniel; Delgado, Mauricio R.; Freedenberg, Debra; Garnica, Adolfo; Grebe, Theresa A.; Hernández-Almaguer, Dolores; Immken, LaDonna; Lalani, Seema R.; McLean, Scott D.; Northrup, Hope; Scaglia, Fernando; Strathearn, Lane; Trapane, Pamela; Kang, Sung-Hae L.; Patel, Ankita; Cheung, Sau Wai; Hastings, P. J.; Stankiewicz, Paweł; Lupski, James R.; Bi, Weimin

2011-01-01

SUMMARY Complex genomic rearrangements (CGR) consisting of two or more breakpoint junctions have been observed in genomic disorders. Recently, a chromosome catastrophe phenomenon termed chromothripsis, in which numerous genomic rearrangements are apparently acquired in one single catastrophic event, was described in multiple cancers. Here we show that constitutionally acquired CGRs share similarities with cancer chromothripsis. In the 17 CGR cases investigated we observed localization and multiple copy number changes including deletions, duplications and/or triplications, as well as extensive translocations and inversions. Genomic rearrangements involved varied in size and complexities; in one case, array comparative genomic hybridization revealed 18 copy number changes. Breakpoint sequencing identified characteristic features, including small templated insertions at breakpoints and microhomology at breakpoint junctions, which have been attributed to replicative processes. The resemblance between CGR and chromothripsis suggests similar mechanistic underpinnings. Such chromosome catastrophic events appear to reflect basic DNA metabolism operative throughout an organism’s life cycle. PMID:21925314

Scalable Lunar Surface Networks and Adaptive Orbit Access

NASA Technical Reports Server (NTRS)

Wang, Xudong

2015-01-01

Teranovi Technologies, Inc., has developed innovative network architecture, protocols, and algorithms for both lunar surface and orbit access networks. A key component of the overall architecture is a medium access control (MAC) protocol that includes a novel mechanism of overlaying time division multiple access (TDMA) and carrier sense multiple access with collision avoidance (CSMA/CA), ensuring scalable throughput and quality of service. The new MAC protocol is compatible with legacy Institute of Electrical and Electronics Engineers (IEEE) 802.11 networks. Advanced features include efficiency power management, adaptive channel width adjustment, and error control capability. A hybrid routing protocol combines the advantages of ad hoc on-demand distance vector (AODV) routing and disruption/delay-tolerant network (DTN) routing. Performance is significantly better than AODV or DTN and will be particularly effective for wireless networks with intermittent links, such as lunar and planetary surface networks and orbit access networks.

Consumers' Preferences for Electronic Nicotine Delivery System Product Features: A Structured Content Analysis.

PubMed

Kistler, Christine E; Crutchfield, Trisha M; Sutfin, Erin L; Ranney, Leah M; Berman, Micah L; Zarkin, Gary A; Goldstein, Adam O

2017-06-07

To inform potential governmental regulations, we aimed to develop a list of electronic nicotine delivery system (ENDS) product features important to U.S. consumers by age and gender. We employed qualitative data methods. Participants were eligible if they had used an ENDS at least once. Groups were selected by age and gender (young adult group aged 18-25, n = 11; middle-age group aged 26-64, n = 9; and women's group aged 26-64, n = 9). We conducted five individual older adult interviews (aged 68-80). Participants discussed important ENDS features. We conducted a structured content analysis of the group and interview responses. Of 34 participants, 68% were white and 56% were female. Participants mentioned 12 important ENDS features, including: (1) user experience; (2) social acceptability; (3) cost; (4) health risks/benefits; (5) ease of use; (6) flavors; (7) smoking cessation aid; (8) nicotine content; (9) modifiability; (10) ENDS regulation; (11) bridge between tobacco cigarettes; (12) collectability. The most frequently mentioned ENDS feature was modifiability for young adults, user experience for middle-age and older adults, and flavor for the women's group. This study identified multiple features important to ENDS consumers. Groups differed in how they viewed various features by age and gender. These results can inform ongoing regulatory efforts.

Consumers’ Preferences for Electronic Nicotine Delivery System Product Features: A Structured Content Analysis

PubMed Central

Kistler, Christine E.; Crutchfield, Trisha M.; Sutfin, Erin L.; Ranney, Leah M.; Berman, Micah L.; Zarkin, Gary A.; Goldstein, Adam O.

2017-01-01

To inform potential governmental regulations, we aimed to develop a list of electronic nicotine delivery system (ENDS) product features important to U.S. consumers by age and gender. We employed qualitative data methods. Participants were eligible if they had used an ENDS at least once. Groups were selected by age and gender (young adult group aged 18–25, n = 11; middle-age group aged 26–64, n = 9; and women’s group aged 26–64, n = 9). We conducted five individual older adult interviews (aged 68–80). Participants discussed important ENDS features. We conducted a structured content analysis of the group and interview responses. Of 34 participants, 68% were white and 56% were female. Participants mentioned 12 important ENDS features, including: (1) user experience; (2) social acceptability; (3) cost; (4) health risks/benefits; (5) ease of use; (6) flavors; (7) smoking cessation aid; (8) nicotine content; (9) modifiability; (10) ENDS regulation; (11) bridge between tobacco cigarettes; (12) collectability. The most frequently mentioned ENDS feature was modifiability for young adults, user experience for middle-age and older adults, and flavor for the women’s group. This study identified multiple features important to ENDS consumers. Groups differed in how they viewed various features by age and gender. These results can inform ongoing regulatory efforts. PMID:28590444

An international standard for observation data

NASA Astrophysics Data System (ADS)

Cox, Simon

2010-05-01

A generic information model for observations and related features supports data exchange both within and between different scientific and technical communities. Observations and Measurements (O&M) formalizes a neutral terminology for observation data and metadata. It was based on a model developed for medical observations, and draws on experience from geology and mineral exploration, in-situ monitoring, remote sensing, intelligence, biodiversity studies, ocean observations and climate simulations. Hundreds of current deployments of Sensor Observation Services (SOS), covering multiple disciplines, provide validation of the O&M model. A W3C Incubator group on 'Semantic Sensor Networks' is now using O&M as one of the bases for development of a formal ontology for sensor networks. O&M defines the information describing observation acts and their results, including the following key terms: observation, result, observed-property, feature-of-interest, procedure, phenomenon-time, and result-time. The model separates of the (meta-)data associated with the observation procedure, the observed feature, and the observation event itself. Observation results may take various forms, including scalar quantities, categories, vectors, grids, or any data structure required to represent the value of some property of some observed feature. O&M follows the ISO/TC 211 General Feature Model so non-geometric properties must be associated with typed feature instances. This requires formalization of information that may be trivial when working within some earth-science sub-disciplines (e.g. temperature, pressure etc. are associated with the atmosphere or ocean, and not just a location) but is critical to cross-disciplinary applications. It also allows the same structure and terminology to be used for in-situ, ex-situ and remote sensing observations, as well as for simulations. For example: a stream level observation is an in-situ monitoring application where the feature-of-interest is a reach, the observed property is water-level, and the result is a time-series of heights; stream quality is usually determined by ex-situ observation where the feature-of-interest is a specimen that is recovered from the stream, the observed property is water-quality, and the result is a set of measures of various parameters, or an assessment derived from these; on the other hand, distribution of surface temperature of a water body is typically determined through remote-sensing, where at observation time the procedure is located distant from the feature-of-interest, and the result is an image or grid. Observations usually involve sampling of an ultimate feature-of-interest. In the environmental sciences common sampling strategies are used. Spatial sampling is classified primarily by topological dimension (point, curve, surface, volume) and is supported by standard processing and visualisation tools. Specimens are used for ex-situ processing in most disciplines. Sampling features are often part of complexes (e.g. specimens are sub-divided; specimens are retrieved from points along a transect; sections are taken across tracts), so relationships between instances must be recorded. And observational campaigns involve collections of sampling features. The sampling feature model is a core part of O&M, and application experience has shown that describing the relationships between sampling features and observations is generally critical to successful use of the model. O&M was developed through Open Geospatial Consortium (OGC) as part of the Sensor Web Enablement (SWE) initiative. Other SWE standards include SensorML, SOS, Sensor Planning Service (SPS). The OGC O&M standard (Version 1) had two parts: part 1 describes observation events, and part 2 provides a schema sampling features. A revised version of O&M (Version 2) is to be published in a single document as ISO 19156. O&M Version 1 included an XML encoding for data exchange, which is used as the payload for SOS responses. The new version will provide a UML model only. Since an XML encoding may be generated following a rule, such as that presented in ISO 19136 (GML 3.2), it is not included in the standard directly. O&M Version 2 thus supports multiple physical implementations and versions.

The Flow Dimension and Aquifer Heterogeneity: Field evidence and Numerical Analyses

NASA Astrophysics Data System (ADS)

Walker, D. D.; Cello, P. A.; Valocchi, A. J.; Roberts, R. M.; Loftis, B.

2008-12-01

The Generalized Radial Flow approach to hydraulic test interpretation infers the flow dimension to describe the geometry of the flow field during a hydraulic test. Noninteger values of the flow dimension often are inferred for tests in highly heterogeneous aquifers, yet subsequent modeling studies typically ignore the flow dimension. Monte Carlo analyses of detailed numerical models of aquifer tests examine the flow dimension for several stochastic models of heterogeneous transmissivity, T(x). These include multivariate lognormal, fractional Brownian motion, a site percolation network, and discrete linear features with lengths distributed as power-law. The behavior of the simulated flow dimensions are compared to the flow dimensions observed for multiple aquifer tests in a fractured dolomite aquifer in the Great Lakes region of North America. The combination of multiple hydraulic tests, observed fracture patterns, and the Monte Carlo results are used to screen models of heterogeneity and their parameters for subsequent groundwater flow modeling. The comparison shows that discrete linear features with lengths distributed as a power-law appear to be the most consistent with observations of the flow dimension in fractured dolomite aquifers.

A novel mutation in ETFDH manifesting as severe neonatal-onset multiple acyl-CoA dehydrogenase deficiency.

PubMed

van der Westhuizen, Francois H; Smuts, Izelle; Honey, Engela; Louw, Roan; Schoonen, Maryke; Jonck, Lindi-Maryn; Dercksen, Marli

2018-01-15

Neonatal-onset multiple acyl-CoA dehydrogenase deficiency (MADD type I) is an autosomal recessive disorder of the electron transfer flavoprotein function characterized by a severe clinical and biochemical phenotype, including congenital abnormalities with unresponsiveness to riboflavin treatment as distinguishing features. From a retrospective study, relying mainly on metabolic data, we have identified a novel mutation, c.1067G>A (p.Gly356Glu) in exon 8 of ETFDH, in three South African Caucasian MADD patients with the index patient presenting the hallmark features of type I MADD and two patients with compound heterozygous (c.1067G>A+c.1448C>T) mutations presenting with MADD type III. SDS-PAGE western blot confirmed the significant effect of this mutation on ETFDH structural instability. The identification of this novel mutation in three families originating from the South African Afrikaner population is significant to direct screening and strategies for this disease, which amongst the organic acidemias routinely screened for, is relatively frequently observed in this population group. Copyright © 2017 Elsevier B.V. All rights reserved.

Object-based benefits without object-based representations.

PubMed

Fougnie, Daryl; Cormiea, Sarah M; Alvarez, George A

2013-08-01

Influential theories of visual working memory have proposed that the basic units of memory are integrated object representations. Key support for this proposal is provided by the same object benefit: It is easier to remember multiple features of a single object than the same set of features distributed across multiple objects. Here, we replicate the object benefit but demonstrate that features are not stored as single, integrated representations. Specifically, participants could remember 10 features better when arranged in 5 objects compared to 10 objects, yet memory for one object feature was largely independent of memory for the other object feature. These results rule out the possibility that integrated representations drive the object benefit and require a revision of the concept of object-based memory representations. We propose that working memory is object-based in regard to the factors that enhance performance but feature based in regard to the level of representational failure. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Rotator Cuff Injuries - Multiple Languages

MedlinePlus

... Are Here: Home → Multiple Languages → All Health Topics → Rotator Cuff Injuries URL of this page: https://medlineplus.gov/ ... V W XYZ List of All Topics All Rotator Cuff Injuries - Multiple Languages To use the sharing features ...

Robust object matching for persistent tracking with heterogeneous features.

PubMed

Guo, Yanlin; Hsu, Steve; Sawhney, Harpreet S; Kumar, Rakesh; Shan, Ying

2007-05-01

This paper addresses the problem of matching vehicles across multiple sightings under variations in illumination and camera poses. Since multiple observations of a vehicle are separated in large temporal and/or spatial gaps, thus prohibiting the use of standard frame-to-frame data association, we employ features extracted over a sequence during one time interval as a vehicle fingerprint that is used to compute the likelihood that two or more sequence observations are from the same or different vehicles. Furthermore, since our domain is aerial video tracking, in order to deal with poor image quality and large resolution and quality variations, our approach employs robust alignment and match measures for different stages of vehicle matching. Most notably, we employ a heterogeneous collection of features such as lines, points, and regions in an integrated matching framework. Heterogeneous features are shown to be important. Line and point features provide accurate localization and are employed for robust alignment across disparate views. The challenges of change in pose, aspect, and appearances across two disparate observations are handled by combining a novel feature-based quasi-rigid alignment with flexible matching between two or more sequences. However, since lines and points are relatively sparse, they are not adequate to delineate the object and provide a comprehensive matching set that covers the complete object. Region features provide a high degree of coverage and are employed for continuous frames to provide a delineation of the vehicle region for subsequent generation of a match measure. Our approach reliably delineates objects by representing regions as robust blob features and matching multiple regions to multiple regions using Earth Mover's Distance (EMD). Extensive experimentation under a variety of real-world scenarios and over hundreds of thousands of Confirmatory Identification (CID) trails has demonstrated about 95 percent accuracy in vehicle reacquisition with both visible and Infrared (IR) imaging cameras.

Test-Retest Reliability of the Multiple Sleep Latency Test in Narcolepsy without Cataplexy and Idiopathic Hypersomnia

PubMed Central

Trotti, Lynn Marie; Staab, Beth A.; Rye, David B.

2013-01-01

Study Objectives: Differentiation of narcolepsy without cataplexy from idiopathic hypersomnia relies entirely upon the multiple sleep latency test (MSLT). However, the test-retest reliability for these central nervous system hypersomnias has never been determined. Methods: Patients with narcolepsy without cataplexy, idiopathic hypersomnia, and physiologic hypersomnia who underwent two diagnostic multiple sleep latency tests were identified retrospectively. Correlations between the mean sleep latencies on the two studies were evaluated, and we probed for demographic and clinical features associated with reproducibility versus change in diagnosis. Results: Thirty-six patients (58% women, mean age 34 years) were included. Inter -test interval was 4.2 ± 3.8 years (range 2.5 months to 16.9 years). Mean sleep latencies on the first and second tests were 5.5 (± 3.7 SD) and 7.3 (± 3.9) minutes, respectively, with no significant correlation (r = 0.17, p = 0.31). A change in diagnosis occurred in 53% of patients, and was accounted for by a difference in the mean sleep latency (N = 15, 42%) or the number of sleep onset REM periods (N = 11, 31%). The only feature predictive of a diagnosis change was a history of hypnagogic or hypnopompic hallucinations. Conclusions: The multiple sleep latency test demonstrates poor test-retest reliability in a clinical population of patients with central nervous system hypersomnia evaluated in a tertiary referral center. Alternative diagnostic tools are needed. Citation: Trotti LM; Staab BA; Rye DB. Test- retest reliability of the multiple sleep latency test in narcolepsy without cataplexy and idiopathic hypersomnia. J Clin Sleep Med 2013;9(8):789-795. PMID:23946709

Fine-Scale Environmental Indicators of Public Health and Well ...

EPA Pesticide Factsheets

Urban ecosystem services contribute to public health and well-being by buffering natural and man-made hazards, and by promoting healthful lifestyles that include physical activity, social interaction, and engagement with nature. As part of the EnviroAtlas online mapping tool, EPA and its research partners have identified urban environmental features that have been linked in the scientific literature to specific aspects of public health and well-being. Examples of these features include tree cover along walkable roads, overall neighborhood green space, green window views, and proximity to parks. Associated aspects of health and well-being include physical fitness, social capital, school performance, and longevity. In many previous studies, stronger associations were observed in disproportionately vulnerable populations such as children, the elderly, and those of lower socioeconomic status.EnviroAtlas researchers have estimated and mapped a suite of urban environmental features by synthesizing newly-generated one-meter resolution landcover data, downscaled census population data, and existing datasets such as roads and waterways. Resulting geospatial metrics represent health-related indicators of urban ecosystem services supply and demand at the census block-group and finer. They have been developed using consistent methods to facilitate comparisons between neighborhoods and across multiple U.S. communities. Demographic overlays, also available in EnviroAtl

The Role of Attention in the Maintenance of Feature Bindings in Visual Short-term Memory

ERIC Educational Resources Information Center

Johnson, Jeffrey S.; Hollingworth, Andrew; Luck, Steven J.

2008-01-01

This study examined the role of attention in maintaining feature bindings in visual short-term memory. In a change-detection paradigm, participants attempted to detect changes in the colors and orientations of multiple objects; the changes consisted of new feature values in a feature-memory condition and changes in how existing feature values were…

Toxicity resulting from exposure to oven cleaners as reported to the UK National Poisons Information Service (NPIS) from 2009 to 2015.

PubMed

Day, Rachael C; Bradberry, Sally M; Sandilands, Euan A; Thomas, Simon H L; Thompson, John P; Vale, J Allister

2017-08-01

Oven cleaning products contain corrosive substances, typically sodium or potassium hydroxide. To determine the reported toxicity from exposure to oven cleaning products. Telephone enquiries to the UK National Poisons Information Service regarding oven cleaning products were analysed retrospectively for the period January 2009 to December 2015. There were 796 enquiries relating to 780 patients. Ninety-six percent of the products involved in the reported exposures contained sodium hydroxide and/or potassium hydroxide. Ingestion alone (n = 285) or skin contact alone (n = 208) accounted for the majority of cases; inhalation alone (n = 101), eye contact alone (n = 97), and multiple routes of exposure (n = 89) accounted for the remainder. Ninety-five percent of patients exposed by inhalation, 94% exposed dermally and 85% reporting eye exposure, developed features of toxicity. Patients exposed by multiple routes developed symptoms in 70% of cases. Only 103 of the 285 patients ingested oven cleaner directly, whereas 182 patients ingested food they considered to have been contaminated with oven cleaner. In 100 of the 103 direct ingestions where the features and World Health Organisation/International Programme on Chemical Safety/European Commission/European Association of Poison Centres and Clinical Toxicologists Poisoning Severity Score were known, 56 reported symptoms which were minor in 51 cases. The most common features following ingestion were vomiting (n = 26), abdominal pain (n = 22) or pharyngitis (n = 15). Skin burns (n = 91) predominantly involving the hands or arms, occurred in 44% of dermal exposures. Following inhalation, patients frequently developed respiratory features (n = 52) including coughing and chest pain/tightness. Eye pain (n = 43) and conjunctivitis (n = 33) commonly occurred following ocular exposure. Most (71%) patients exposed to an oven cleaner irrespective of the route of exposure developed features of toxicity, though in most cases only minor features developed; moderate or severe features ensued in ∼4%. Those patients exposed dermally, ophthalmically or by inhalation developed features more frequently (≥85%) than those who ingested a product directly (56%).

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.

Timber sale planning and analysis system: A user`s guide to the TSPAS sale program. Forest Service general technical report

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

Schuster, E.G.; Jones, J.G.; Meacham, M.L.

1995-08-01

Presents a guide to operation and interpretation of TSPAS Sale Program (TSPAS SP), a menu-driven computer program that is one of two programs in the Timber Sale Planning and Analysis System. TSPAS SP is intended to help field teams design and evaluate timber sale alternatives. TSPAS SP evaluate current and long-term timber implications along with associated nontimber outputs. Features include multiple entries and products, real value change, and graphical input. Guide includes user instructions, a glossary, a listing of data needs, and an explanation of error messages.

Aptamer-conjugated nanoparticles for cancer cell detection.

PubMed

Medley, Colin D; Bamrungsap, Suwussa; Tan, Weihong; Smith, Joshua E

2011-02-01

Aptamer-conjugated nanoparticles (ACNPs) have been used for a variety of applications, particularly dual nanoparticles for magnetic extraction and fluorescent labeling. In this type of assay, silica-coated magnetic and fluorophore-doped silica nanoparticles are conjugated to highly selective aptamers to detect and extract targeted cells in a variety of matrixes. However, considerable improvements are required in order to increase the selectivity and sensitivity of this two-particle assay to be useful in a clinical setting. To accomplish this, several parameters were investigated, including nanoparticle size, conjugation chemistry, use of multiple aptamer sequences on the nanoparticles, and use of multiple nanoparticles with different aptamer sequences. After identifying the best-performing elements, the improvements made to this assay's conditional parameters were combined to illustrate the overall enhanced sensitivity and selectivity of the two-particle assay using an innovative multiple aptamer approach, signifying a critical feature in the advancement of this technique.

SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of Normal Aging on Memory for Multiple Contextual Features

ERIC Educational Resources Information Center

Gagnon, Sylvain; Soulard, Kathleen; Brasgold, Melissa; Kreller, Joshua

2007-01-01

Twenty-four younger (18-35 years) and 24 older adult participants (65 or older) were exposed to three experimental conditions involving the memorization words and their associated contextual features, with contextual feature complexity increasing from Conditions 1 to 3. In Condition 1, words presented varied only on one binary feature (color,…

Understanding Evolutionary Potential in Virtual CPU Instruction Set Architectures

PubMed Central

Bryson, David M.; Ofria, Charles

2013-01-01

We investigate fundamental decisions in the design of instruction set architectures for linear genetic programs that are used as both model systems in evolutionary biology and underlying solution representations in evolutionary computation. We subjected digital organisms with each tested architecture to seven different computational environments designed to present a range of evolutionary challenges. Our goal was to engineer a general purpose architecture that would be effective under a broad range of evolutionary conditions. We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow. We also tested a variety of methods to regulate expression: (4) explicit labels that allow programs to dynamically refer to specific genome positions, (5) position-relative search instructions, and (6) multiple new flow control instructions, including conditionals and jumps. Each of these features also adds complication to the instruction set and risks slowing evolution due to epistatic interactions. Two features (multiple argument specification and separated I/O) demonstrated substantial improvements in the majority of test environments, along with versions of each of the remaining architecture modifications that show significant improvements in multiple environments. However, some tested modifications were detrimental, though most exhibit no systematic effects on evolutionary potential, highlighting the robustness of digital evolution. Combined, these observations enhance our understanding of how instruction architecture impacts evolutionary potential, enabling the creation of architectures that support more rapid evolution of complex solutions to a broad range of challenges. PMID:24376669

Protein fold recognition using geometric kernel data fusion.

PubMed

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

Neural correlates of processing facial identity based on features versus their spacing.

PubMed

Maurer, D; O'Craven, K M; Le Grand, R; Mondloch, C J; Springer, M V; Lewis, T L; Grady, C L

2007-04-08

Adults' expertise in recognizing facial identity involves encoding subtle differences among faces in the shape of individual facial features (featural processing) and in the spacing among features (a type of configural processing called sensitivity to second-order relations). We used fMRI to investigate the neural mechanisms that differentiate these two types of processing. Participants made same/different judgments about pairs of faces that differed only in the shape of the eyes and mouth, with minimal differences in spacing (featural blocks), or pairs of faces that had identical features but differed in the positions of those features (spacing blocks). From a localizer scan with faces, objects, and houses, we identified regions with comparatively more activity for faces, including the fusiform face area (FFA) in the right fusiform gyrus, other extrastriate regions, and prefrontal cortices. Contrasts between the featural and spacing conditions revealed distributed patterns of activity differentiating the two conditions. A region of the right fusiform gyrus (near but not overlapping the localized FFA) showed greater activity during the spacing task, along with multiple areas of right frontal cortex, whereas left prefrontal activity increased for featural processing. These patterns of activity were not related to differences in performance between the two tasks. The results indicate that the processing of facial features is distinct from the processing of second-order relations in faces, and that these functions are mediated by separate and lateralized networks involving the right fusiform gyrus, although the FFA as defined from a localizer scan is not differentially involved.

Motor Vehicle Safety - Multiple Languages

MedlinePlus

... Are Here: Home → Multiple Languages → All Health Topics → Motor Vehicle Safety URL of this page: https://medlineplus.gov/languages/ ... V W XYZ List of All Topics All Motor Vehicle Safety - Multiple Languages To use the sharing features on ...

A non-viscous-featured fractograph in metallic glasses

NASA Astrophysics Data System (ADS)

Yang, G. N.; Shao, Y.; Yao, K. F.

2016-02-01

A fractograph of non-viscous feature but pure shear-offsets was found in three-point bending samples of a ductile Pd-Cu-Si metallic glass. A sustainable shear band multiplication with large plasticity during notch propagation was observed. Such non-viscous-featured fractograph was formed by a crack propagation manner of continual multiple shear bands formation in front of the crack-tip, instead of the conventional rapid fracture along shear bands. With a 2D model of crack propagation by multiple shear bands, we showed that such fracture process was achieved by a faster stress relaxation than shear-softening effect in the sample. This study confirmed that the viscous fracture along shear bands could be not a necessary process in ductile metallic glasses fracture, and could provide new ways to understand the plasticity in the shear-softened metallic glasses.

Relationships between Genetic Variations of PNPLA3, TM6SF2 and Histological Features of Nonalcoholic Fatty Liver Disease in Japan.

PubMed

Akuta, Norio; Kawamura, Yusuke; Arase, Yasuji; Suzuki, Fumitaka; Sezaki, Hitomi; Hosaka, Tetsuya; Kobayashi, Masahiro; Kobayashi, Mariko; Saitoh, Satoshi; Suzuki, Yoshiyuki; Ikeda, Kenji; Kumada, Hiromitsu

2016-05-23

It is important to determine the noninvasive parameters of histological features in nonalcoholic fatty liver disease (NAFLD). The aim of this study was to investigate the value of genetic variations as surrogate markers of histological features. The parameters that affected the histological features of NAFLD were investigated in 211 Japanese patients with biopsy-proven NAFLD. The relationships between genetic variations in PNPLA3 rs738409 or TM6SF2 rs58542926 and histological features were analyzed. Furthermore, the impact of genetic variations that affected the pathological criteria for the diagnosis of nonalcoholic steatohepatitis (NASH) (Matteoni classification and NAFLD activity score) was evaluated. The fibrosis stage of PNPLA3 GG was significantly more progressive than that of CG by multiple comparisons. Multivariate analysis identified PNPLA3 genotypes as predictors of fibrosis of stage 2 or more, but the impact tended to decrease at stage 3 or greater. There were no significant differences among the histological features of the three genotypes of TM6SF2. PNPLA3 genotypes partly affected the definition of NASH by the NAFLD activity score, but TM6SF2 genotypes did not affect the definition of NASH. In Japanese patients with biopsy-proven NAFLD, PNPLA3 genotypes may partly affect histological features, including stage of fibrosis, but the TM6SF2 genotype does not affect histological features.

CHARGED PARTICLE MULTIPLICITIES IN ULTRA-RELATIVISTIC AU+AU AND CU+CU COLLISIONS

NASA Astrophysics Data System (ADS)

Back, B. B.; Alver, B.; Back, B. B.; Baker, M. D.; Ballintijn, M.; Barton, D. S.; Betts, R. R.; Bickley, A. A.; Bindel, R.; Busza, W.; Carroll, A.; Chai, Z.; Chetluru, V.; Decowski, M. P.; Garcia, E.; Gburek, T.; George, N.; Gulbrandsen, K.; Halliwell, C.; Hamblen, J.; Harnarine, I.; Hauer, M.; Henderson, C.; Hofman, D. J.; Hollis, R. S.; Holynski, R.; Holzman, B.; Iordanova, A.; Johnson, E.; Kane, J. L.; Khan, N.; Kulinich, P.; Kuo, C. M.; Li, W.; Lin, W. T.; Loizides, C.; Manly, S.; Mignerey, A. C.; Nouicer, R.; Olszewski, A.; Pak, R.; Reed, C.; Richardson, E.; Roland, C.; Roland, G.; Sagerer, J.; Seals, H.; Sedykh, I.; Smith, C. E.; Stankiewicz, M. A.; Steinberg, P.; Stephans, G. S. F.; Sukhanov, A.; Szostak, A.; Tonjes, M. B.; Trzupek, A.; Vale, C.; Vannieuwenhuizen, G. J.; Vaurynovich, S. S.; Verdier, R.; Veres, G. I.; Walters, P.; Wenger, E.; Willhelm, D.; Wolfs, F. L. H.; Wosiek, B.; Wozniak, K.; Wyngaardt, S.; Wyslouch, B.

The PHOBOS collaboration has carried out a systematic study of charged particle multiplicities in Cu+Cu and Au+Au collisions at the Relativistic Heavy-Ion Collider (RHIC) at Brookhaven National Laboratory. A unique feature of the PHOBOS detector is its ability to measure charged particles over a very wide angular range from 0.5° to 179.5° corresponding to |η| <5.4. The general features of the charged particle multiplicity distributions as a function of pseudo-rapidity, collision energy and centrality, as well as system size, are discussed.

The atmospheres of Saturn and Titan in the near-infrared: First results of Cassini/Vims

USGS Publications Warehouse

Baines, K.H.; Momary, T.W.; Buratti, B.J.; Matson, D.L.; Nelson, R.M.; Drossart, P.; Sicardy, B.; Formisano, V.; Bellucci, G.; Coradini, A.; Griffith, C.; Brown, R.H.; Bibring, J.-P.; Langevin, Y.; Capaccioni, F.; Cerroni, P.; Clark, R.N.; Combes, M.; Cruikshank, D.P.; Jaumann, R.; McCordt, T.B.; Mennella, V.; Nicholson, P.D.; Sotin, Christophe

2006-01-01

The wide spectral coverage and extensive spatial, temporal, and phase-angle mapping capabilities of the Visual Infrared Mapping Spectrometer (VIMS) onboard the Cassini-Huygens Orbiter are producing fundamental new insights into the nature of the atmospheres of Saturn and Titan. For both bodies, VIMS maps over time and solar phase angles provide information for a multitude of atmospheric constituents and aerosol layers, providing new insights into atmospheric structure and dynamical and chemical processes. For Saturn, salient early results include evidence for phosphine depletion in relatively dark and less cloudy belts at temperate and mid-latitudes compared to the relatively bright and cloudier Equatorial Region, consistent with traditional theories of belts being regions of relative downwelling. Additional Saturn results include (1) the mapping of enhanced trace gas absorptions at the south pole, and (2) the first high phase-angle, high-spatial-resolution imagery of CH4 fluorescence. An additional fundamental new result is the first nighttime near-infrared mapping of Saturn, clearly showing discrete meteorological features relatively deep in the atmosphere beneath the planet's sunlit haze and cloud layers, thus revealing a new dynamical regime at depth where vertical dynamics is relatively more important than zonal dynamics in determining cloud morphology. Zonal wind measurements at deeper levels than previously available are achieved by tracking these features over multiple days, thereby providing measurements of zonal wind shears within Saturn's troposphere when compared to cloudtop movements measured in reflected sunlight. For Titan, initial results include (1) the first detection and mapping of thermal emission spectra of CO, CO2, and CH3D on Titan's nightside limb, (2) the mapping of CH4 fluorescence over the dayside bright limb, extending to ??? 750 km altitude, (3) wind measurements of ???0.5 ms-1, favoring prograde, from the movement of a persistent (multiple months) south polar cloud near 88??S latitude, and (4) the imaging of two transient mid-southern-latitude cloud features. ?? Springer Science+Business Media, Inc. 2006.

What Is Leukodystrophy

MedlinePlus

... having the disease. Are the leukodystrophies related to Multiple Sclerosis? The leukodystrophies do share some common features with multiple sclerosis (MS). Like the leukodystrophies, MS is caused by ...

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

An interactive portal to empower cancer survivors: a qualitative study on user expectations.

PubMed

Kuijpers, Wilma; Groen, Wim G; Loos, Romy; Oldenburg, Hester S A; Wouters, Michel W J M; Aaronson, Neil K; van Harten, Wim H

2015-09-01

Portals are increasingly used to improve patient empowerment, but are still uncommon in oncology. In this study, we explored cancer survivors' and health professionals' expectations of possible features of an interactive portal. We conducted three focus groups with breast cancer survivors (n = 21), two with lung cancer survivors (n = 14), and four with health professionals (n = 31). Drafts of possible features of an interactive portal were presented as static screenshots: survivorship care plan (SCP), access to electronic medical record (EMR), appointments, e-consultation, online patient community, patient reported outcomes (PROs) plus feedback, telemonitoring service, online rehabilitation program, and online psychosocial self-management program. This presentation was followed by an open discussion. Focus groups were audiotaped, transcribed verbatim, and data were analyzed using content analysis. Important themes included fulfillment of information needs, communication, motivation, quality of feedback, and supervision. Cancer survivors were primarily interested in features that could fulfill their information needs: SCP, access to their EMR, and an overview of appointments. Health professionals considered PROs and telemonitoring as most useful features, as these provide relevant information about survivors' health status. We recommend to minimally include these features in an interactive portal for cancer survivors. This is the first study that evaluated the expectations of cancer survivors and health professionals concerning an interactive portal. Both groups were positive about the introduction of such a portal, although their preferences for the various features differed. These findings reflect their unique perspective and emphasize the importance of involving multiple stakeholders in the actual design process.

Paleopathological Study of Dwarfism-Related Skeletal Dysplasia in a Late Joseon Dynasty (South Korean) Population.

PubMed

Woo, Eun Jin; Lee, Won-Joon; Hu, Kyung-Seok; Hwang, Jae Joon

2015-01-01

Skeletal dysplasias related to genetic etiologies have rarely been reported for past populations. This report presents the skeletal characteristics of an individual with dwarfism-related skeletal dysplasia from South Korea. To assess abnormal deformities, morphological features, metric data, and computed tomography scans are analyzed. Differential diagnoses include achondroplasia or hypochondroplasia, chondrodysplasia, multiple epiphyseal dysplasia, thalassemia-related hemolytic anemia, and lysosomal storage disease. The diffused deformities in the upper-limb bones and several coarsened features of the craniofacial bones indicate the most likely diagnosis to have been a certain type of lysosomal storage disease. The skeletal remains of EP-III-4-No.107 from the Eunpyeong site, although incomplete and fragmented, provide important clues to the paleopathological diagnosis of skeletal dysplasias.

Acquired pendular nystagmus

PubMed Central

Kang, Sarah; Shaikh, Aasef G.

2017-01-01

Acquired pendular nystagmus is comprised of quasi-sinusoidal oscillations of the eyes significantly affecting gaze holding and clarity of vision. The most common causes of acquired pendular nystagmus include demyelinating disorders such as multiple sclerosis and the syndrome of ocular palatal tremor. However, several other deficits, such as pharmacological intoxication, metabolic and genetic disorders, and granulomatous disorders can lead to syndromes mimicking acquired pendular nystagmus. Study of the kinematic features of acquired pendular nystagmus has suggested a putative pathophysiology of an otherwise mysterious neurological disorder. Here we review clinical features of neurological deficits that co-occur with acquired pendular nystagmus. Subsequent discussion of the pathophysiology of individual forms of pendular nystagmus speculates on mechanisms of the underlying disease while providing insights into pharmacotherapy of nystagmus. PMID:28320194

Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening

NASA Astrophysics Data System (ADS)

Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te

2018-03-01

Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p  =  0.002 518), sigma (p  =  0.002 781), uniformity (p  =  0.032 41), and entropy (p  =  0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.

Localized thin-section CT with radiomics feature extraction and machine learning to classify early-detected pulmonary nodules from lung cancer screening.

PubMed

Tu, Shu-Ju; Wang, Chih-Wei; Pan, Kuang-Tse; Wu, Yi-Cheng; Wu, Chen-Te

2018-03-14

Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive predictive value is low. To address these problems, a technical approach is greatly needed for accurate malignancy differentiation among these early-detected nodules. We studied the clinical feasibility of an additional protocol of localized thin-section CT for further assessment on recalled patients from lung cancer screening tests. Our approach of localized thin-section CT was integrated with radiomics features extraction and machine learning classification which was supervised by pathological diagnosis. Localized thin-section CT images of 122 nodules were retrospectively reviewed and 374 radiomics features were extracted. In this study, 48 nodules were benign and 74 malignant. There were nine patients with multiple nodules and four with synchronous multiple malignant nodules. Different machine learning classifiers with a stratified ten-fold cross-validation were used and repeated 100 times to evaluate classification accuracy. Of the image features extracted from the thin-section CT images, 238 (64%) were useful in differentiating between benign and malignant nodules. These useful features include CT density (p  =  0.002 518), sigma (p  =  0.002 781), uniformity (p  =  0.032 41), and entropy (p  =  0.006 685). The highest classification accuracy was 79% by the logistic classifier. The performance metrics of this logistic classification model was 0.80 for the positive predictive value, 0.36 for the false-positive rate, and 0.80 for the area under the receiver operating characteristic curve. Our approach of direct risk classification supervised by the pathological diagnosis with localized thin-section CT and radiomics feature extraction may support clinical physicians in determining truly malignant nodules and therefore reduce problems in lung cancer screening.

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.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Identification of More Feasible MicroRNA-mRNA Interactions within Multiple Cancers Using Principal Component Analysis Based Unsupervised Feature Extraction.

PubMed

Taguchi, Y-H

2016-05-10

MicroRNA(miRNA)-mRNA interactions are important for understanding many biological processes, including development, differentiation and disease progression, but their identification is highly context-dependent. When computationally derived from sequence information alone, the identification should be verified by integrated analyses of mRNA and miRNA expression. The drawback of this strategy is the vast number of identified interactions, which prevents an experimental or detailed investigation of each pair. In this paper, we overcome this difficulty by the recently proposed principal component analysis (PCA)-based unsupervised feature extraction (FE), which reduces the number of identified miRNA-mRNA interactions that properly discriminate between patients and healthy controls without losing biological feasibility. The approach is applied to six cancers: hepatocellular carcinoma, non-small cell lung cancer, esophageal squamous cell carcinoma, prostate cancer, colorectal/colon cancer and breast cancer. In PCA-based unsupervised FE, the significance does not depend on the number of samples (as in the standard case) but on the number of features, which approximates the number of miRNAs/mRNAs. To our knowledge, we have newly identified miRNA-mRNA interactions in multiple cancers based on a single common (universal) criterion. Moreover, the number of identified interactions was sufficiently small to be sequentially curated by literature searches.

Natural history of multiple sclerosis from the Indian perspective: Experience from a tertiary care hospital.

PubMed

Jena, Subhransu S; Alexander, Mathew; Aaron, Sanjith; Mathew, Vivek; Thomas, Maya Mary; Patil, Anil K; Sivadasan, Ajith; Muthusamy, Karthik; Mani, Sunithi; Rebekah, J Grace

2015-01-01

Multiple sclerosis (MS) has a spectrum of heterogeneity, as seen in western and eastern hemispheres, in the clinical features, topography of involvement and differences in natural history. To study the clinical spectrum, imaging, and electrophysiological as well as cerebrospinal fluid (CSF) characteristics and correlate them with outcome. Retrospective analysis of MS patients during a period of 20 years. Cases were selected according to recent McDonald's criteria (2010), They were managed in the Department of Neurology, Christian Medical College, Vellore. Chi-square and Fisher's exact tests were used for categorical variables. Multiple binary logistic regressions were done to assess significance. Kaplan-Meier curves were drawn to estimate the time to irreversible disability. A total of 157 patients with female preponderance (55%) were included. The inter quartile range duration of follow-up was 9.1 (8.2, 11) years for 114 patients, who were included for final outcome analysis. Relapsing remitting MS (RRMS) (54.1%) was the most common type of MS seen. RRMS had a significantly better outcome (odds ratio: 0.12, 95% confidence interval: 0.02-0.57, P = 0.008) compared to progressive form of MS (primary progressive, secondary progressive). The Expanded Disability Status Scale score of patients at presentation and at final follow-up was 4.4 ± 1.31 and 4.1 ± 2.31, respectively. During the first presentation, polysymptomatic manifestations like motor and sphincteric involvement, incomplete recovery from the first attack; and, during the disease course, bowel, bladder, cerebellar and pyramidal affliction, predicted a worse outcome. A high incidence of optico-spinal presentation, predominance of RRMS and a low yield on cerebrospinal fluid (CSF) studies are the major findings of our study. A notable feature was the analysis of prognostic markers of disability.

Optimizing multiple sequence alignments using a genetic algorithm based on three objectives: structural information, non-gaps percentage and totally conserved columns.

PubMed

Ortuño, Francisco M; Valenzuela, Olga; Rojas, Fernando; Pomares, Hector; Florido, Javier P; Urquiza, Jose M; Rojas, Ignacio

2013-09-01

Multiple sequence alignments (MSAs) are widely used approaches in bioinformatics to carry out other tasks such as structure predictions, biological function analyses or phylogenetic modeling. However, current tools usually provide partially optimal alignments, as each one is focused on specific biological features. Thus, the same set of sequences can produce different alignments, above all when sequences are less similar. Consequently, researchers and biologists do not agree about which is the most suitable way to evaluate MSAs. Recent evaluations tend to use more complex scores including further biological features. Among them, 3D structures are increasingly being used to evaluate alignments. Because structures are more conserved in proteins than sequences, scores with structural information are better suited to evaluate more distant relationships between sequences. The proposed multiobjective algorithm, based on the non-dominated sorting genetic algorithm, aims to jointly optimize three objectives: STRIKE score, non-gaps percentage and totally conserved columns. It was significantly assessed on the BAliBASE benchmark according to the Kruskal-Wallis test (P < 0.01). This algorithm also outperforms other aligners, such as ClustalW, Multiple Sequence Alignment Genetic Algorithm (MSA-GA), PRRP, DIALIGN, Hidden Markov Model Training (HMMT), Pattern-Induced Multi-sequence Alignment (PIMA), MULTIALIGN, Sequence Alignment Genetic Algorithm (SAGA), PILEUP, Rubber Band Technique Genetic Algorithm (RBT-GA) and Vertical Decomposition Genetic Algorithm (VDGA), according to the Wilcoxon signed-rank test (P < 0.05), whereas it shows results not significantly different to 3D-COFFEE (P > 0.05) with the advantage of being able to use less structures. Structural information is included within the objective function to evaluate more accurately the obtained alignments. The source code is available at http://www.ugr.es/~fortuno/MOSAStrE/MO-SAStrE.zip.

Multizone accretional evolution of planetesimal swarms

NASA Technical Reports Server (NTRS)

Spaute, D.; Davis, D. R.; Weidenschilling, S. J.

1990-01-01

The general features of a new numerical simulation of planetesimal accretion which models multiple heliocentric distance zones, together with a detailed model for the planetesimal size and orbital distribution in each zone, are described. A restricted version of this model which allows only a single heliocentric distance zone has been used to test the validity of the code by comparing with results from earlier authors when the same physical phenomena are included. Generally, very good agreement is found.

Improved data visualization techniques for analyzing macromolecule structural changes.

PubMed

Kim, Jae Hyun; Iyer, Vidyashankara; Joshi, Sangeeta B; Volkin, David B; Middaugh, C Russell

2012-10-01

The empirical phase diagram (EPD) is a colored representation of overall structural integrity and conformational stability of macromolecules in response to various environmental perturbations. Numerous proteins and macromolecular complexes have been analyzed by EPDs to summarize results from large data sets from multiple biophysical techniques. The current EPD method suffers from a number of deficiencies including lack of a meaningful relationship between color and actual molecular features, difficulties in identifying contributions from individual techniques, and a limited ability to be interpreted by color-blind individuals. In this work, three improved data visualization approaches are proposed as techniques complementary to the EPD. The secondary, tertiary, and quaternary structural changes of multiple proteins as a function of environmental stress were first measured using circular dichroism, intrinsic fluorescence spectroscopy, and static light scattering, respectively. Data sets were then visualized as (1) RGB colors using three-index EPDs, (2) equiangular polygons using radar charts, and (3) human facial features using Chernoff face diagrams. Data as a function of temperature and pH for bovine serum albumin, aldolase, and chymotrypsin as well as candidate protein vaccine antigens including a serine threonine kinase protein (SP1732) and surface antigen A (SP1650) from S. pneumoniae and hemagglutinin from an H1N1 influenza virus are used to illustrate the advantages and disadvantages of each type of data visualization technique. Copyright © 2012 The Protein Society.

Improved data visualization techniques for analyzing macromolecule structural changes

PubMed Central

Kim, Jae Hyun; Iyer, Vidyashankara; Joshi, Sangeeta B; Volkin, David B; Middaugh, C Russell

2012-01-01

The empirical phase diagram (EPD) is a colored representation of overall structural integrity and conformational stability of macromolecules in response to various environmental perturbations. Numerous proteins and macromolecular complexes have been analyzed by EPDs to summarize results from large data sets from multiple biophysical techniques. The current EPD method suffers from a number of deficiencies including lack of a meaningful relationship between color and actual molecular features, difficulties in identifying contributions from individual techniques, and a limited ability to be interpreted by color-blind individuals. In this work, three improved data visualization approaches are proposed as techniques complementary to the EPD. The secondary, tertiary, and quaternary structural changes of multiple proteins as a function of environmental stress were first measured using circular dichroism, intrinsic fluorescence spectroscopy, and static light scattering, respectively. Data sets were then visualized as (1) RGB colors using three-index EPDs, (2) equiangular polygons using radar charts, and (3) human facial features using Chernoff face diagrams. Data as a function of temperature and pH for bovine serum albumin, aldolase, and chymotrypsin as well as candidate protein vaccine antigens including a serine threonine kinase protein (SP1732) and surface antigen A (SP1650) from S. pneumoniae and hemagglutinin from an H1N1 influenza virus are used to illustrate the advantages and disadvantages of each type of data visualization technique. PMID:22898970

Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius.

PubMed

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.

Automatic detection of wheezes by evaluation of multiple acoustic feature extraction methods and C-weighted SVM

NASA Astrophysics Data System (ADS)

Sosa, Germán. D.; Cruz-Roa, Angel; González, Fabio A.

2015-01-01

This work addresses the problem of lung sound classification, in particular, the problem of distinguishing between wheeze and normal sounds. Wheezing sound detection is an important step to associate lung sounds with an abnormal state of the respiratory system, usually associated with tuberculosis or another chronic obstructive pulmonary diseases (COPD). The paper presents an approach for automatic lung sound classification, which uses different state-of-the-art sound features in combination with a C-weighted support vector machine (SVM) classifier that works better for unbalanced data. Feature extraction methods used here are commonly applied in speech recognition and related problems thanks to the fact that they capture the most informative spectral content from the original signals. The evaluated methods were: Fourier transform (FT), wavelet decomposition using Wavelet Packet Transform bank of filters (WPT) and Mel Frequency Cepstral Coefficients (MFCC). For comparison, we evaluated and contrasted the proposed approach against previous works using different combination of features and/or classifiers. The different methods were evaluated on a set of lung sounds including normal and wheezing sounds. A leave-two-out per-case cross-validation approach was used, which, in each fold, chooses as validation set a couple of cases, one including normal sounds and the other including wheezing sounds. Experimental results were reported in terms of traditional classification performance measures: sensitivity, specificity and balanced accuracy. Our best results using the suggested approach, C-weighted SVM and MFCC, achieve a 82.1% of balanced accuracy obtaining the best result for this problem until now. These results suggest that supervised classifiers based on kernel methods are able to learn better models for this challenging classification problem even using the same feature extraction methods.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

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

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Autoimmune comorbidities in multiple sclerosis: what is the influence on brain volumes? A case-control MRI study.

PubMed

Lorefice, Lorena; Fenu, Giuseppe; Pitzalis, Roberta; Scalas, Giulia; Frau, Jessica; Coghe, Giancarlo; Musu, Luigina; Sechi, Vincenzo; Barracciu, Maria Antonietta; Marrosu, Maria Giovanna; Cocco, Eleonora

2018-05-01

Several studies indicated that multiple sclerosis (MS) is frequently associated with other autoimmune diseases. However, it is little known if the coexistence of these conditions may influence the radiologic features of MS, and in particular the brain volumes. To evaluate the effect of autoimmune comorbidities on brain atrophy in a large case-control MS population. A group of MS patients affected by a second autoimmune disorder, and a control MS group without any comorbidity, were recruited. Patients underwent a brain MRI and volumes of whole brain (WB), white matter (WM), and gray matter (GM) with cortical GM were estimated by SIENAX. The sample included 286 MS patients, of which 30 (10.5%) subjects with type 1 diabetes (T1D), 53 (18.5%) with autoimmune thyroiditis (AT) and 4 (0.1%) with celiac disease. Multiple regression analysis found an association between T1D and lower GM (p = 0.038) and cortical GM (p = 0.036) volumes, independent from MS clinical features and related to T1D duration (p < 0.01), while no association was observed with AT and celiac disease. Our data support the importance of considering T1D as possible factors influencing the brain atrophy in MS. Further studies are needed to confirm our data and to clarify the underlying mechanisms.

Tracking Multiple Video Targets with an Improved GM-PHD Tracker

PubMed Central

Zhou, Xiaolong; Yu, Hui; Liu, Honghai; Li, Youfu

2015-01-01

Tracking multiple moving targets from a video plays an important role in many vision-based robotic applications. In this paper, we propose an improved Gaussian mixture probability hypothesis density (GM-PHD) tracker with weight penalization to effectively and accurately track multiple moving targets from a video. First, an entropy-based birth intensity estimation method is incorporated to eliminate the false positives caused by noisy video data. Then, a weight-penalized method with multi-feature fusion is proposed to accurately track the targets in close movement. For targets without occlusion, a weight matrix that contains all updated weights between the predicted target states and the measurements is constructed, and a simple, but effective method based on total weight and predicted target state is proposed to search the ambiguous weights in the weight matrix. The ambiguous weights are then penalized according to the fused target features that include spatial-colour appearance, histogram of oriented gradient and target area and further re-normalized to form a new weight matrix. With this new weight matrix, the tracker can correctly track the targets in close movement without occlusion. For targets with occlusion, a robust game-theoretical method is used. Finally, the experiments conducted on various video scenarios validate the effectiveness of the proposed penalization method and show the superior performance of our tracker over the state of the art. PMID:26633422

Measurement of the underlying event in jet events from 7 TeV proton–proton collisions with the ATLAS detector

DOE PAGES

Aad, G.; Abajyan, T.; Abbott, B.; ...

2014-08-12

Distributions sensitive to the underlying event in QCD jet events have been measured with the ATLAS detector at the LHC, based on 37 pb -1 of proton–proton collision data collected at a centre-of-mass energy of 7 TeV. Charged-particle mean p T and densities of all-particle E T and charged-particle multiplicity and p T have been measured in regions azimuthally transverse to the hardest jet in each event. These are presented both as one-dimensional distributions and with their mean values as functions of the leading-jet transverse momentum from 20 to 800 GeV. The correlation of charged-particle mean p T with charged-particlemore » multiplicity is also studied, and the E T densities include the forward rapidity region; these features provide extra data constraints for Monte Carlo modelling of colour reconnection and beam-remnant effects respectively. For the first time, underlying event observables have been computed separately for inclusive jet and exclusive dijet event selections, allowing more detailed study of the interplay of multiple partonic scattering and QCD radiation contributions to the underlying event. Comparisons to the predictions of different Monte Carlo models show a need for further model tuning, but the standard approach is found to generally reproduce the features of the underlying event in both types of event selection.« less

Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer

PubMed Central

2012-01-01

Background Automated classification of histopathology involves identification of multiple classes, including benign, cancerous, and confounder categories. The confounder tissue classes can often mimic and share attributes with both the diseased and normal tissue classes, and can be particularly difficult to identify, both manually and by automated classifiers. In the case of prostate cancer, they may be several confounding tissue types present in a biopsy sample, posing as major sources of diagnostic error for pathologists. Two common multi-class approaches are one-shot classification (OSC), where all classes are identified simultaneously, and one-versus-all (OVA), where a “target” class is distinguished from all “non-target” classes. OSC is typically unable to handle discrimination of classes of varying similarity (e.g. with images of prostate atrophy and high grade cancer), while OVA forces several heterogeneous classes into a single “non-target” class. In this work, we present a cascaded (CAS) approach to classifying prostate biopsy tissue samples, where images from different classes are grouped to maximize intra-group homogeneity while maximizing inter-group heterogeneity. Results We apply the CAS approach to categorize 2000 tissue samples taken from 214 patient studies into seven classes: epithelium, stroma, atrophy, prostatic intraepithelial neoplasia (PIN), and prostate cancer Gleason grades 3, 4, and 5. A series of increasingly granular binary classifiers are used to split the different tissue classes until the images have been categorized into a single unique class. Our automatically-extracted image feature set includes architectural features based on location of the nuclei within the tissue sample as well as texture features extracted on a per-pixel level. The CAS strategy yields a positive predictive value (PPV) of 0.86 in classifying the 2000 tissue images into one of 7 classes, compared with the OVA (0.77 PPV) and OSC approaches (0.76 PPV). Conclusions Use of the CAS strategy increases the PPV for a multi-category classification system over two common alternative strategies. In classification problems such as histopathology, where multiple class groups exist with varying degrees of heterogeneity, the CAS system can intelligently assign class labels to objects by performing multiple binary classifications according to domain knowledge. PMID:23110677

Gorlin-Goltz Syndrome: An Uncommon Cause of Facial Pain and Asymmetry.

PubMed

Pickrell, Brent B; Nguyen, Harrison P; Buchanan, Edward P

2015-10-01

Gorlin-Goltz syndrome is an underdiagnosed autosomal dominant disorder with variable expressivity that is characterized by an increased predisposition to tumorigenesis of multiple types. The major clinical features include multiple basal cell carcinomas (BCCs) appearing in early childhood, palmar and plantar pits, odontogenic keratocysts of the oral cavity, skeletal defects, craniofacial dysmorphism, and ectopic intracranial calcification. The authors present the clinical course of a 12-year-old girl presenting with facial asymmetry and pain because of previously undiagnosed Gorlin-Goltz syndrome. Early diagnosis and attentive management by a multidisciplinary team are paramount to improving outcomes in patients with this disorder, and this report serves as a paradigm for maintaining a high clinical suspicion, which must be accompanied by an appropriate radiologic workup.

MSAViewer: interactive JavaScript visualization of multiple sequence alignments.

PubMed

Yachdav, Guy; Wilzbach, Sebastian; Rauscher, Benedikt; Sheridan, Robert; Sillitoe, Ian; Procter, James; Lewis, Suzanna E; Rost, Burkhard; Goldberg, Tatyana

2016-11-15

The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is 'web ready': written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/Supplementary information: Supplementary data are available at Bioinformatics online. msa@bio.sh. © The Author 2016. Published by Oxford University Press.

Nonlinear Optical Image Processing with Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.; Deiss, Ron (Technical Monitor)

1994-01-01

The transmission properties of some bacteriorhodopsin film spatial light modulators are uniquely suited to allow nonlinear optical image processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude transmission feature of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. The bacteriorhodopsin film displays the logarithmic amplitude response for write beam intensities spanning a dynamic range greater than 2.0 orders of magnitude. We present experimental results demonstrating the principle and capability for several different image and noise situations, including deterministic noise and speckle. Using the bacteriorhodopsin film, we successfully filter out image noise from the transformed image that cannot be removed from the original image.

MSAViewer: interactive JavaScript visualization of multiple sequence alignments

PubMed Central

Yachdav, Guy; Wilzbach, Sebastian; Rauscher, Benedikt; Sheridan, Robert; Sillitoe, Ian; Procter, James; Lewis, Suzanna E.; Rost, Burkhard; Goldberg, Tatyana

2016-01-01

Summary: The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is ‘web ready’: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. Availability and Implementation: The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: msa@bio.sh PMID:27412096

Multiple Viral Infection Detected from Influenza-Like Illness Cases in Indonesia.

PubMed

Adam, Kindi; Pangesti, Krisna Nur Andriana; Setiawaty, Vivi

2017-01-01

Influenza is one of the common etiologies of the upper respiratory tract infection (URTI). However, influenza virus only contributes about 20 percent of influenza-like illness patients. The aim of the study is to investigate the other viral etiologies from ILI cases in Indonesia. Of the 334 samples, 266 samples (78%) were positive at least for one virus, including 107 (42%) cases of multiple infections. Influenza virus is the most detected virus. The most frequent combination of viruses identified was adenovirus and human rhinovirus. This recent study demonstrated high detection rate of several respiratory viruses from ILI cases in Indonesia. Further studies to determine the relationship between viruses and clinical features are needed to improve respiratory disease control program.

Multiradar tracking for theater missile defense

NASA Astrophysics Data System (ADS)

Sviestins, Egils

1995-09-01

A prototype system for tracking tactical ballistic missiles using multiple radars has been developed. The tracking is based on measurement level fusion (`true' multi-radar) tracking. Strobes from passive sensors can also be used. We describe various features of the system with some emphasis on the filtering technique. This is based on the Interacting Multiple Model framework where the states are Free Flight, Drag, Boost, and Auxiliary. Measurement error modeling includes the signal to noise ratio dependence; outliers and miscorrelations are handled in the same way. The launch point is calculated within one minute from the detection of the missile. The impact point, and its uncertainty region, is calculated continually by extrapolating the track state vector using the equations of planetary motion.

A Novel Mitochondrial DNA Deletion in Patient with Pearson Syndrome.

PubMed

Khasawneh, Rame; Alsokhni, Hala; Alzghoul, Bayan; Momani, Asim; Abualsheikh, Nazih; Kamal, Nazmi; Qatawneh, Mousa

2018-04-01

Arteriovenous Pearson syndrome is a very rare multisystemic mitochondrial disease characterized by sideroblastic anemia and exocrine pancreatic insufficiency. It is usually fatal in infancy. We reported a four-month-old infant presented with fever and pancytopenia. Bone marrow examination showed hypoplastic changes and sideroblastic features. Molecular Study showed a novel hetroplasmic mitochondrial deletions (m. 10760 -m. 15889+) in multiple genes (ND4,ND5,ND6, CYTB). In our patient the pathogenic mutation was 5.1 kb heteroplasmic deletions in multiple genes that are important and crucial for intact oxidative phosphorylation pathway and ATP production in the mitochondrial DNA. This mutation was not reported in literature including the mitomap.org website (which was last edited on Nov 30, 2017 and accessed on Jan 13, 2018).

Capacity for visual features in mental rotation

PubMed Central

Xu, Yangqing; Franconeri, Steven L.

2015-01-01

Although mental rotation is a core component of scientific reasoning, we still know little about its underlying mechanism. For instance - how much visual information can we rotate at once? Participants rotated a simple multi-part shape, requiring them to maintain attachments between features and moving parts. The capacity of this aspect of mental rotation was strikingly low – only one feature could remain attached to one part. Behavioral and eyetracking data showed that this single feature remained ‘glued’ via a singular focus of attention, typically on the object’s top. We argue that the architecture of the human visual system is not suited for keeping multiple features attached to multiple parts during mental rotation. Such measurement of the capacity limits may prove to be a critical step in dissecting the suite of visuospatial tools involved in mental rotation, leading to insights for improvement of pedagogy in science education contexts. PMID:26174781

Visual feature integration and focused attention: response competition from multiple distractor features.

PubMed

Lavie, N

1997-05-01

Predictions from Treisman's feature integration theory of attention were tested in a variant of the response-competition paradigm. Subjects made choice responses to particular color-shape conjunctions (e.g., a purple cross vs. a green circle) while withholding their responses to the opposite conjunctions (i.e., a purple circle vs. a green cross). The results showed that compatibility effects were based on both distractor color and shape. For unattended distractors in preknown irrelevant positions, compatibility effects were equivalent for conjunctive distractors (e.g., a purple cross and a blue triangle) and for disjunctive distractors (e.g., a purple triangle and a blue cross). Manipulation of attention to the distractors positions resulted in larger compatibility effects from conjoined features. These results accord with Treisman's claim that correct conjunction information is unavailable under conditions of inattention, and they provide new information on response-competition effects from multiple features.

Capacity for Visual Features in Mental Rotation.

PubMed

Xu, Yangqing; Franconeri, Steven L

2015-08-01

Although mental rotation is a core component of scientific reasoning, little is known about its underlying mechanisms. For instance, how much visual information can someone rotate at once? We asked participants to rotate a simple multipart shape, requiring them to maintain attachments between features and moving parts. The capacity of this aspect of mental rotation was strikingly low: Only one feature could remain attached to one part. Behavioral and eye-tracking data showed that this single feature remained "glued" via a singular focus of attention, typically on the object's top. We argue that the architecture of the human visual system is not suited for keeping multiple features attached to multiple parts during mental rotation. Such measurement of capacity limits may prove to be a critical step in dissecting the suite of visuospatial tools involved in mental rotation, leading to insights for improvement of pedagogy in science-education contexts. © The Author(s) 2015.

Dynamic Integration of Task-Relevant Visual Features in Posterior Parietal Cortex

PubMed Central

Freedman, David J.

2014-01-01

Summary The primate visual system consists of multiple hierarchically organized cortical areas, each specialized for processing distinct aspects of the visual scene. For example, color and form are encoded in ventral pathway areas such as V4 and inferior temporal cortex, while motion is preferentially processed in dorsal pathway areas such as the middle temporal area. Such representations often need to be integrated perceptually to solve tasks which depend on multiple features. We tested the hypothesis that the lateral intraparietal area (LIP) integrates disparate task-relevant visual features by recording from LIP neurons in monkeys trained to identify target stimuli composed of conjunctions of color and motion features. We show that LIP neurons exhibit integrative representations of both color and motion features when they are task relevant, and task-dependent shifts of both direction and color tuning. This suggests that LIP plays a role in flexibly integrating task-relevant sensory signals. PMID:25199703

Speeded induction under uncertainty: the influence of multiple categories and feature conjunctions.

PubMed

Newell, Ben R; Paton, Helen; Hayes, Brett K; Griffiths, Oren

2010-12-01

When people are uncertain about the category membership of an item (e.g., Is it a dog or a dingo?), research shows that they tend to rely only on the dominant or most likely category when making inductions (e.g., How likely is it to befriend me?). An exception has been reported using speeded induction judgments where participants appeared to use information from multiple categories to make inductions (Verde, Murphy, & Ross, 2005). In two speeded induction studies, we found that participants tended to rely on the frequency with which features co-occurred when making feature predictions, independently of category membership. This pattern held whether categories were considered implicitly (Experiment 1) or explicitly (Experiment 2) prior to feature induction. The results converge with other recent work suggesting that people often rely on feature conjunction information, rather than category boundaries, when making inductions under uncertainty.

Novel and general approach to linear filter design for contrast-to-noise ratio enhancement of magnetic resonance images with multiple interfering features in the scene

NASA Astrophysics Data System (ADS)

Soltanian-Zadeh, Hamid; Windham, Joe P.

1992-04-01

Maximizing the minimum absolute contrast-to-noise ratios (CNRs) between a desired feature and multiple interfering processes, by linear combination of images in a magnetic resonance imaging (MRI) scene sequence, is attractive for MRI analysis and interpretation. A general formulation of the problem is presented, along with a novel solution utilizing the simple and numerically stable method of Gram-Schmidt orthogonalization. We derive explicit solutions for the case of two interfering features first, then for three interfering features, and, finally, using a typical example, for an arbitrary number of interfering feature. For the case of two interfering features, we also provide simplified analytical expressions for the signal-to-noise ratios (SNRs) and CNRs of the filtered images. The technique is demonstrated through its applications to simulated and acquired MRI scene sequences of a human brain with a cerebral infarction. For these applications, a 50 to 100% improvement for the smallest absolute CNR is obtained.

Structured Light-Based 3D Reconstruction System for Plants.

PubMed

Nguyen, Thuy Tuong; Slaughter, David C; Max, Nelson; Maloof, Julin N; Sinha, Neelima

2015-07-29

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

Dedifferentiated chondrosarcoma with telangiectatic osteosarcoma‐like features

PubMed Central

Okada, K; Hasegawa, T; Tateishi, U; Endo, M; Itoi, E

2006-01-01

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. PMID:17071806

Automatic Visual Tracking and Social Behaviour Analysis with Multiple Mice

PubMed Central

Giancardo, Luca; Sona, Diego; Huang, Huiping; Sannino, Sara; Managò, Francesca; Scheggia, Diego; Papaleo, Francesco; Murino, Vittorio

2013-01-01

Social interactions are made of complex behavioural actions that might be found in all mammalians, including humans and rodents. Recently, mouse models are increasingly being used in preclinical research to understand the biological basis of social-related pathologies or abnormalities. However, reliable and flexible automatic systems able to precisely quantify social behavioural interactions of multiple mice are still missing. Here, we present a system built on two components. A module able to accurately track the position of multiple interacting mice from videos, regardless of their fur colour or light settings, and a module that automatically characterise social and non-social behaviours. The behavioural analysis is obtained by deriving a new set of specialised spatio-temporal features from the tracker output. These features are further employed by a learning-by-example classifier, which predicts for each frame and for each mouse in the cage one of the behaviours learnt from the examples given by the experimenters. The system is validated on an extensive set of experimental trials involving multiple mice in an open arena. In a first evaluation we compare the classifier output with the independent evaluation of two human graders, obtaining comparable results. Then, we show the applicability of our technique to multiple mice settings, using up to four interacting mice. The system is also compared with a solution recently proposed in the literature that, similarly to us, addresses the problem with a learning-by-examples approach. Finally, we further validated our automatic system to differentiate between C57B/6J (a commonly used reference inbred strain) and BTBR T+tf/J (a mouse model for autism spectrum disorders). Overall, these data demonstrate the validity and effectiveness of this new machine learning system in the detection of social and non-social behaviours in multiple (>2) interacting mice, and its versatility to deal with different experimental settings and scenarios. PMID:24066146

An integrated and accessible sample data library for Mars sample return science

NASA Astrophysics Data System (ADS)

Tuite, M. L., Jr.; Williford, K. H.

2015-12-01

Over the course of the next decade or more, many thousands of geological samples will be collected and analyzed in a variety of ways by researchers at the Jet Propulsion Laboratory (California Institute of Technology) in order to facilitate discovery and contextualize observations made of Mars rocks both in situ and here on Earth if samples are eventually returned. Integration of data from multiple analyses of samples including petrography, thin section and SEM imaging, isotope and organic geochemistry, XRF, XRD, and Raman spectrometry is a challenge and a potential obstacle to discoveries that require supporting lines of evidence. We report the development of a web-accessible repository, the Sample Data Library (SDL) for the sample-based data that are generated by the laboratories and instruments that comprise JPL's Center for Analysis of Returned Samples (CARS) in order to facilitate collaborative interpretation of potential biosignatures in Mars-analog geological samples. The SDL is constructed using low-cost, open-standards-based Amazon Web Services (AWS), including web-accessible storage, relational data base services, and a virtual web server. The data structure is sample-centered with a shared registry for assigning unique identifiers to all samples including International Geo-Sample Numbers. Both raw and derived data produced by instruments and post-processing workflows are automatically uploaded to online storage and linked via the unique identifiers. Through the web interface, users are able to find all the analyses associated with a single sample or search across features shared by multiple samples, sample localities, and analysis types. Planned features include more sophisticated search and analytical interfaces as well as data discoverability through NSF's EarthCube program.

Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning.

PubMed

Sung, Yao-Ting; Chen, Ju-Ling; Cha, Ji-Her; Tseng, Hou-Chiang; Chang, Tao-Hsing; Chang, Kuo-En

2015-06-01

Multilevel linguistic features have been proposed for discourse analysis, but there have been few applications of multilevel linguistic features to readability models and also few validations of such models. Most traditional readability formulae are based on generalized linear models (GLMs; e.g., discriminant analysis and multiple regression), but these models have to comply with certain statistical assumptions about data properties and include all of the data in formulae construction without pruning the outliers in advance. The use of such readability formulae tends to produce a low text classification accuracy, while using a support vector machine (SVM) in machine learning can enhance the classification outcome. The present study constructed readability models by integrating multilevel linguistic features with SVM, which is more appropriate for text classification. Taking the Chinese language as an example, this study developed 31 linguistic features as the predicting variables at the word, semantic, syntax, and cohesion levels, with grade levels of texts as the criterion variable. The study compared four types of readability models by integrating unilevel and multilevel linguistic features with GLMs and an SVM. The results indicate that adopting a multilevel approach in readability analysis provides a better representation of the complexities of both texts and the reading comprehension process.

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

The emergence of polychronization and feature binding in a spiking neural network model of the primate ventral visual system.

PubMed

Eguchi, Akihiro; Isbister, James B; Ahmad, Nasir; Stringer, Simon

2018-07-01

We present a hierarchical neural network model, in which subpopulations of neurons develop fixed and regularly repeating temporal chains of spikes (polychronization), which respond specifically to randomized Poisson spike trains representing the input training images. The performance is improved by including top-down and lateral synaptic connections, as well as introducing multiple synaptic contacts between each pair of pre- and postsynaptic neurons, with different synaptic contacts having different axonal delays. Spike-timing-dependent plasticity thus allows the model to select the most effective axonal transmission delay between neurons. Furthermore, neurons representing the binding relationship between low-level and high-level visual features emerge through visually guided learning. This begins to provide a way forward to solving the classic feature binding problem in visual neuroscience and leads to a new hypothesis concerning how information about visual features at every spatial scale may be projected upward through successive neuronal layers. We name this hypothetical upward projection of information the "holographic principle." (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Robust kernel representation with statistical local features for face recognition.

PubMed

Yang, Meng; Zhang, Lei; Shiu, Simon Chi-Keung; Zhang, David

2013-06-01

Factors such as misalignment, pose variation, and occlusion make robust face recognition a difficult problem. It is known that statistical features such as local binary pattern are effective for local feature extraction, whereas the recently proposed sparse or collaborative representation-based classification has shown interesting results in robust face recognition. In this paper, we propose a novel robust kernel representation model with statistical local features (SLF) for robust face recognition. Initially, multipartition max pooling is used to enhance the invariance of SLF to image registration error. Then, a kernel-based representation model is proposed to fully exploit the discrimination information embedded in the SLF, and robust regression is adopted to effectively handle the occlusion in face images. Extensive experiments are conducted on benchmark face databases, including extended Yale B, AR (A. Martinez and R. Benavente), multiple pose, illumination, and expression (multi-PIE), facial recognition technology (FERET), face recognition grand challenge (FRGC), and labeled faces in the wild (LFW), which have different variations of lighting, expression, pose, and occlusions, demonstrating the promising performance of the proposed method.

Bisphosphonate-related osteonecrosis of the jaw in a multiple myeloma patient: A case report with characteristic radiographic features.

PubMed

Lee, Byung-Do; Park, Moo-Rim; Kwon, Kyung-Hwan

2015-09-01

A 59-year-old male who had suffered from multiple myeloma for nine years and had been administered bisphosphonates for seven years visited a dental hospital for pain relief due to extensive caries in his left maxillary molars. The molars were extracted, leaving an exposed wound for three months. The radiograph showed sequestra formation and irregular bone destruction in the left maxilla. Sudden pain and gingival swelling in the right mandibular molar area occurred six months later. The interseptum of the right lower second molar was observed to be necrotic during surgery. These findings coincided with the features of bisphosphonate-related osteonecrosis of the jaw (BRONJ). In this case, the long intravenous administration of bisphosphonates and tooth extraction were likely the etiologic factors of BRONJ in a patient with multiple myeloma; moreover, the bilateral occurrence of BRONJ is a characteristic feature.

[Cornelia de Lange Syndrome and multiple hormonal deficiency, an unusual association. Clinical case].

PubMed

Mora-Bautista, Víctor M; Mendoza-Rojas, Víctor; Contreras-García, Gustavo A

2017-06-01

Cornelia de Lange syndrome is a genetic disease characterized by distinctive facial features, failure to thrive, microcephaly and several malformations associated. Its main endocrinological features are anomalies of the genitalia. We present a 13-year-old boy, who suffered from complicated aspiration pneumonia and showed Cornelia de Lange syndrome phenotype, with global developmental delay, suction-swallowing abnormalities, short stature and abnormal genitalia associated. His bone age was delayed, so he underwent full endocrinological panel. Central hypothyroidism, growth hormone deficiency and low luteinizing hormone-follicle-stimulating hormone levels were observed and multiple pituitary hormone deficiencies diagnosis was made. Basal cortisol, adrenocorticotropic hormone and prolactin levels were normal. He received thyroid hormonal substitution. Multiple pituitary hormone deficiencies are an unusual feature of De Lange syndrome. We suggest evaluating all different endocrine axes in these patients. Sociedad Argentina de Pediatría.

Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

PubMed

Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

2018-01-01

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation

NASA Astrophysics Data System (ADS)

Vijverberg, Koen; Ghafoorian, Mohsen; van Uden, Inge W. M.; de Leeuw, Frank-Erik; Platel, Bram; Heskes, Tom

2016-03-01

Cerebral small vessel disease (SVD) is a disorder frequently found among the old people and is associated with deterioration in cognitive performance, parkinsonism, motor and mood impairments. White matter hyperintensities (WMH) as well as lacunes, microbleeds and subcortical brain atrophy are part of the spectrum of image findings, related to SVD. Accurate segmentation of WMHs is important for prognosis and diagnosis of multiple neurological disorders such as MS and SVD. Almost all of the published (semi-)automated WMH detection models employ multiple complex hand-crafted features, which require in-depth domain knowledge. In this paper we propose to apply a single-layer network unsupervised feature learning (USFL) method to avoid hand-crafted features, but rather to automatically learn a more efficient set of features. Experimental results show that a computer aided detection system with a USFL system outperforms a hand-crafted approach. Moreover, since the two feature sets have complementary properties, a hybrid system that makes use of both hand-crafted and unsupervised learned features, shows a significant performance boost compared to each system separately, getting close to the performance of an independent human expert.

FAST TRACK PAPER: A construct of internal multiples from surface data only: the concept of virtual seismic events

NASA Astrophysics Data System (ADS)

Ikelle, Luc T.

2006-02-01

We here describe one way of constructing internal multiples from surface seismic data only. The key feature of our construct of internal multiples is the introduction of the concept of virtual seismic events. Virtual events here are events, which are not directly recorded in standard seismic data acquisition, but their existence allows us to construct internal multiples with scattering points at the sea surface; the standard construct of internal multiples does not include any scattering points at the sea surface. The mathematical and computational operations invoked in our construction of virtual events and internal multiples are similar to those encountered in the construction of free-surface multiples based on the Kirchhoff or Born scattering theory. For instance, our construct operates on one temporal frequency at a time, just like free-surface demultiple algorithms; other internal multiple constructs tend to require all frequencies for the computation of an internal multiple at a given frequency. It does not require any knowledge of the subsurface nor an explicit knowledge of specific interfaces that are responsible for the generation of internal multiples in seismic data. However, our construct requires that the data be divided into two, three or four windows to avoid generating primaries. This segmentation of the data also allows us to select a range of periods of internal multiples that one wishes to construct because, in the context of the attenuation of internal multiples, it is important to avoid generating short-period internal multiples that may constructively average to form primaries at the seismic scale.

Searching for neurodegeneration in multiple sclerosis at clinical onset: Diagnostic value of biomarkers.

PubMed

Novakova, Lenka; Axelsson, Markus; Malmeström, Clas; Imberg, Henrik; Elias, Olle; Zetterberg, Henrik; Nerman, Olle; Lycke, Jan

2018-01-01

Neurodegeneration occurs during the early stages of multiple sclerosis. It is an essential, devastating part of the pathophysiology. Tools for measuring the degree of neurodegeneration could improve diagnostics and patient characterization. This study aimed to determine the diagnostic value of biomarkers of degeneration in patients with recent clinical onset of suspected multiple sclerosis, and to evaluate these biomarkers for characterizing disease course. This cross-sectional study included 271 patients with clinical features of suspected multiple sclerosis onset and was the baseline of a prospective study. After diagnostic investigations, the patients were classified into the following disease groups: patients with clinically isolated syndrome (n = 4) or early relapsing remitting multiple sclerosis (early RRMS; n = 93); patients with relapsing remitting multiple sclerosis with disease durations ≥2 years (established RRMS; n = 39); patients without multiple sclerosis, but showing symptoms (symptomatic controls; n = 89); and patients diagnosed with other diseases (n = 46). In addition, we included healthy controls (n = 51) and patients with progressive multiple sclerosis (n = 23). We analyzed six biomarkers of neurodegeneration: cerebrospinal fluid neurofilament light chain levels; cerebral spinal fluid glial fibrillary acidic protein; cerebral spinal fluid tau; retinal nerve fiber layer thickness; macula volume; and the brain parenchymal fraction. Except for increased cerebral spinal fluid neurofilament light chain levels, median 670 ng/L (IQR 400-2110), we could not find signs of early degeneration in the early disease group with recent clinical onset. However, the intrathecal immunoglobin G production and cerebral spinal fluid neurofilament light chain levels showed diagnostic value. Moreover, elevated levels of cerebral spinal fluid glial fibrillary acidic protein, thin retinal nerve fiber layers, and low brain parenchymal fractions were associated with progressive disease, but not with the other phenotypes. Thin retinal nerve fiber layers and low brain parenchymal fractions, which indicated neurodegeneration, were associated with longer disease duration. In clinically suspected multiple sclerosis, intrathecal immunoglobin G production and neurofilament light chain levels had diagnostic value. Therefore, these biomarkers could be included in diagnostic work-ups for multiple sclerosis. We found that the thickness of the retinal nerve fiber layer and the brain parenchymal fraction were not different between individuals that were healthy, symptomatic, or newly diagnosed with multiple sclerosis. This finding suggested that neurodegeneration had not reached a significant magnitude in patients with a recent clinical onset of multiple sclerosis.

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

PubMed

Ito, Motohiro; Kawahara, Jun I

2016-01-01

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

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

PubMed

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

Hadoop neural network for parallel and distributed feature selection.

PubMed

Hodge, Victoria J; O'Keefe, Simon; Austin, Jim

2016-06-01

In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Novel interstitial deletion of 10q24.3-25.1 associated with multiple congenital anomalies including lobar holoprosencephaly, cleft lip and palate, and hypoplastic kidneys.

PubMed

Peltekova, Iskra T; Hurteau-Millar, Julie; Armour, Christine M

2014-12-01

Chromosome 10q deletions are rare and phenotypically diverse. Such deletions differ in length and occur in numerous regions on the long arm of chromosome 10, accounting for the wide clinical variability. Commonly reported findings include dysmorphic facial features, microcephaly, developmental delay, and genitourinary abnormalities. Here, we report on a female patient with a novel interstitial 5.54 Mb deletion at 10q24.31-q25.1. This patient had findings in common with a previously reported patient with an overlapping deletion, including renal anomalies and an orofacial cleft, but also demonstrated lobar holoprosencephaly and a Dandy-Walker malformation, features which have not been previously reported with 10q deletions. An analysis of the region deleted in our patient showed numerous genes, such as KAZALD1, PAX2, SEMA4G, ACTRA1, INA, and FGF8, whose putative functions may have played a role in the phenotype seen in our patient. © 2014 Wiley Periodicals, Inc.

Therapies for the bone in mucopolysaccharidoses

PubMed Central

Tomatsu, Shunji; Alméciga-Díaz, Carlos J.; Montaño, Adriana M.; Yabe, Hiromasa; Tanaka, Akemi; Dung, Vu Chi; Giugliani, Roberto; Kubaski, Francyne; Mason, Robert W.; Yasuda, Eriko; Sawamoto, Kazuki; Mackenzie, William; Suzuki, Yasuyuki; Orii, Kenji E.; Barrera, Luis A.; Sly, William S.; Orii, Tadao

2014-01-01

Patients with mucopolysaccharidoses (MPS) have accumulation of glycosaminoglycans in multiple tissues which may cause coarse facial features, mental retardation, recurrent ear and nose infections, inguinal and umbilical hernias, hepatosplenomegaly, and skeletal deformities. Clinical features related to bone lesions may include marked short stature, cervical stenosis, pectus carinatum, small lungs, joint rigidity (but laxity for MPS IV), kyphoscoliosis, lumbar gibbus, and genu valgum. Patients with MPS are often wheelchair-bound and physical handicaps increase with age as a result of progressive skeletal dysplasia, abnormal joint mobility, and osteoarthritis, leading to 1) stenosis of the upper cervical region, 2) restrictive small lung, 3) hip dysplasia, 4) restriction of joint movement, and 5) surgical complications. Patients often need multiple orthopedic procedures including cervical decompression and fusion, carpal tunnel release, hip reconstruction and replacement, and femoral or tibial osteotomy through their lifetime. Current measures to intervene in bone disease progression are not perfect and palliative, and improved therapies are urgently required. Enzyme replacement therapy (ERT), hematopoietic stem cell transplantation (HSCT), and gene therapy are available or in development for some types of MPS. Delivery of sufficient enzyme to bone, especially avascular cartilage, to prevent or ameliorate the devastating skeletal dysplasias remains an unmet challenge. The use of an anti-inflammatory drug is also under clinical study. Therapies should start at a very early stage prior to irreversible bone lesion, and damage since the severity of skeletal dysplasia is associated with level of activity during daily life. This review illustrates a current overview of therapies and their impact for bone lesions in MPS including ERT, HSCT, gene therapy, and anti-inflammatory drugs. PMID:25537451

Sequence alignment visualization in HTML5 without Java.

PubMed

Gille, Christoph; Birgit, Weyand; Gille, Andreas

2014-01-01

Java has been extensively used for the visualization of biological data in the web. However, the Java runtime environment is an additional layer of software with an own set of technical problems and security risks. HTML in its new version 5 provides features that for some tasks may render Java unnecessary. Alignment-To-HTML is the first HTML-based interactive visualization for annotated multiple sequence alignments. The server side script interpreter can perform all tasks like (i) sequence retrieval, (ii) alignment computation, (iii) rendering, (iv) identification of a homologous structural models and (v) communication with BioDAS-servers. The rendered alignment can be included in web pages and is displayed in all browsers on all platforms including touch screen tablets. The functionality of the user interface is similar to legacy Java applets and includes color schemes, highlighting of conserved and variable alignment positions, row reordering by drag and drop, interlinked 3D visualization and sequence groups. Novel features are (i) support for multiple overlapping residue annotations, such as chemical modifications, single nucleotide polymorphisms and mutations, (ii) mechanisms to quickly hide residue annotations, (iii) export to MS-Word and (iv) sequence icons. Alignment-To-HTML, the first interactive alignment visualization that runs in web browsers without additional software, confirms that to some extend HTML5 is already sufficient to display complex biological data. The low speed at which programs are executed in browsers is still the main obstacle. Nevertheless, we envision an increased use of HTML and JavaScript for interactive biological software. Under GPL at: http://www.bioinformatics.org/strap/toHTML/.

Drawing on Text Features for Reading Comprehension and Composing

ERIC Educational Resources Information Center

Risko, Victoria J.; Walker-Dalhouse, Doris

2011-01-01

Students read multiple-genre texts such as graphic novels, poetry, brochures, digitized texts with videos, and informational and narrative texts. Features such as overlapping illustrations and implied cause-and-effect relationships can affect students' comprehension. Teaching with these texts and drawing attention to organizational features hold…

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.

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.

Prescribing patterns of psychotropic medications and clinical features in patients with major depressive disorder with and without comorbid dysthymia in China.

PubMed

Feng, Yuan; Sha, Sha; Hu, Chen; Wang, Gang; Ungvari, Gabor S; Chiu, Helen F K; Ng, Chee H; Si, Tian-Mei; Chen, Da-Fang; Fang, Yi-Ru; Lu, Zheng; Yang, Hai-Chen; Hu, Jian; Chen, Zhi-Yu; Huang, Yi; Sun, Jing; Wang, Xiao-Ping; Li, Hui-Chun; Zhang, Jin-Bei; Xiang, Yu-Tao

2017-03-01

Little has been reported about the demographic and clinical features of major depressive disorder (MDD) with comorbid dysthymia in Chinese patients. This study examined the frequency of comorbid dysthymia in Chinese MDD patients together with the demographic and clinical correlates and prescribing patterns of psychotropic drugs. Consecutively collected sample of 1178 patients with MDD were examined in 13 major psychiatric hospitals in China. Patients' demographic and clinical characteristics and psychotropic drugs prescriptions were recorded using a standardized protocol and data collection procedure. The diagnosis of dysthymia was established using the Mini International Neuropsychiatric Interview. Medications ascertained included antidepressants, antipsychotics, benzodiazepines, and mood stabilizers. One hundred and three (8.7%) patients fulfilled criteria for dysthymia. In multiple logistic regression analyses, compared to non-dysthymia counterparts, MDD patients with dysthymia had more depressive episodes with atypical features including increased appetite, sleep, and weight gain, more frequent lifetime depressive episodes, and less likelihood of family history of psychiatric disorders. There was no significant difference in the pattern of psychotropic prescription between the 2 groups. There are important differences in the demographic and clinical features of comorbid dysthymia in Chinese MDD patients compared with previous reports. The clinical profile found in this study has implications for treatment decisions. © 2016 John Wiley & Sons Australia, Ltd.

Caring for Multiples

MedlinePlus

... birth and infant mortality. Solving premature birth Featured articles Accomplishments and lessons learned since the establishment of ... The impact of premature birth on society Featured articles How long should you wait before getting pregnant ...

Capability of geometric features to classify ships in SAR imagery

NASA Astrophysics Data System (ADS)

Lang, Haitao; Wu, Siwen; Lai, Quan; Ma, Li

2016-10-01

Ship classification in synthetic aperture radar (SAR) imagery has become a new hotspot in remote sensing community for its valuable potential in many maritime applications. Several kinds of ship features, such as geometric features, polarimetric features, and scattering features have been widely applied on ship classification tasks. Compared with polarimetric features and scattering features, which are subject to SAR parameters (e.g., sensor type, incidence angle, polarization, etc.) and environment factors (e.g., sea state, wind, wave, current, etc.), geometric features are relatively independent of SAR and environment factors, and easy to be extracted stably from SAR imagery. In this paper, the capability of geometric features to classify ships in SAR imagery with various resolution has been investigated. Firstly, the relationship between the geometric feature extraction accuracy and the SAR imagery resolution is analyzed. It shows that the minimum bounding rectangle (MBR) of ship can be extracted exactly in terms of absolute precision by the proposed automatic ship-sea segmentation method. Next, six simple but effective geometric features are extracted to build a ship representation for the subsequent classification task. These six geometric features are composed of length (f1), width (f2), area (f3), perimeter (f4), elongatedness (f5) and compactness (f6). Among them, two basic features, length (f1) and width (f2), are directly extracted based on the MBR of ship, the other four are derived from those two basic features. The capability of the utilized geometric features to classify ships are validated on two data set with different image resolutions. The results show that the performance of ship classification solely by geometric features is close to that obtained by the state-of-the-art methods, which obtained by a combination of multiple kinds of features, including scattering features and geometric features after a complex feature selection process.

Struggling readers learning with graphic-rich digital science text: Effects of a Highlight & Animate Feature and Manipulable Graphics

NASA Astrophysics Data System (ADS)

Defrance, Nancy L.

Technology offers promise of 'leveling the playing field' for struggling readers. That is, instructional support features within digital texts may enable all readers to learn. This quasi-experimental study examined the effects on learning of two support features, which offered unique opportunities to interact with text. The Highlight & Animate Feature highlighted an important idea in prose, while simultaneously animating its representation in an adjacent graphic. It invited readers to integrate ideas depicted in graphics and prose, using each one to interpret the other. The Manipulable Graphics had parts that the reader could operate to discover relationships among phenomena. It invited readers to test or refine the ideas that they brought to, or gleaned from, the text. Use of these support features was compulsory. Twenty fifth grade struggling readers read a graphic-rich digital science text in a clinical interview setting, under one of two conditions: using either the Highlight & Animate Feature or the Manipulable Graphics. Participants in both conditions made statistically significant gains on a multiple choice measure of knowledge of the topic of the text. While there were no significant differences by condition in the amount of knowledge gained; there were significant differences in the quality of knowledge expressed. Transcripts revealed that understandings about light and vision, expressed by those who used the Highlight & Animate Feature, were more often conceptually and linguistically 'complete.' That is, their understandings included both a description of phenomena as well as an explanation of underlying scientific principles, which participants articulated using the vocabulary of the text. This finding may be attributed to the multiple opportunities to integrate graphics (depicting the behavior of phenomena) and prose (providing the scientific explanation of that phenomena), which characterized the Highlight & Animate Condition. Those who used the Manipulable Graphics were more likely to express complete understandings when they were able to structure a systematic investigation of the graphic and when the graphic was designed to confront their own naive conceptions about light and vision. The Manipulable Graphics also provided a foothold for those who entered the study with very little prior knowledge of the topic.

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

PubMed

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

2018-03-23

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

Limits in feature-based attention to multiple colors.

PubMed

Liu, Taosheng; Jigo, Michael

2017-11-01

Attention to a feature enhances the sensory representation of that feature. Although much has been learned about the properties of attentional modulation when attending to a single feature, the effectiveness of attending to multiple features is not well understood. We investigated this question in a series of experiments using a color-detection task while varying the number of attended colors in a cueing paradigm. Observers were shown either a single cue, two cues, or no cue (baseline) before detecting a coherent color target. We measured detection threshold by varying the coherence level of the target. Compared to the baseline condition, we found consistent facilitation of detection performance in the one-cue and two-cue conditions, but performance in the two-cue condition was lower than that in the one-cue condition. In the final experiment, we presented a 50% valid cue to emulate the situation in which observers were only able to attend a single color in the two-cue condition, and found equivalent detection thresholds with the standard two-cue condition. These results indicate a limit in attending to two colors and further imply that observers could effectively attend a single color at a time. Such a limit is likely due to an inability to maintain multiple active attentional templates for colors.

Constructing a Database from Multiple 2D Images for Camera Pose Estimation and Robot Localization

NASA Technical Reports Server (NTRS)

Wolf, Michael; Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.; Padgett, Curtis W.

2012-01-01

The LMDB (Landmark Database) Builder software identifies persistent image features (landmarks) in a scene viewed multiple times and precisely estimates the landmarks 3D world positions. The software receives as input multiple 2D images of approximately the same scene, along with an initial guess of the camera poses for each image, and a table of features matched pair-wise in each frame. LMDB Builder aggregates landmarks across an arbitrarily large collection of frames with matched features. Range data from stereo vision processing can also be passed to improve the initial guess of the 3D point estimates. The LMDB Builder aggregates feature lists across all frames, manages the process to promote selected features to landmarks, and iteratively calculates the 3D landmark positions using the current camera pose estimations (via an optimal ray projection method), and then improves the camera pose estimates using the 3D landmark positions. Finally, it extracts image patches for each landmark from auto-selected key frames and constructs the landmark database. The landmark database can then be used to estimate future camera poses (and therefore localize a robotic vehicle that may be carrying the cameras) by matching current imagery to landmark database image patches and using the known 3D landmark positions to estimate the current pose.

Classification and data acquisition with incomplete data

NASA Astrophysics Data System (ADS)

Williams, David P.

In remote-sensing applications, incomplete data can result when only a subset of sensors (e.g., radar, infrared, acoustic) are deployed at certain regions. The limitations of single sensor systems have spurred interest in employing multiple sensor modalities simultaneously. For example, in land mine detection tasks, different sensor modalities are better-suited to capture different aspects of the underlying physics of the mines. Synthetic aperture radar sensors may be better at detecting surface mines, while infrared sensors may be better at detecting buried mines. By employing multiple sensor modalities to address the detection task, the strengths of the disparate sensors can be exploited in a synergistic manner to improve performance beyond that which would be achievable with either single sensor alone. When multi-sensor approaches are employed, however, incomplete data can be manifested. If each sensor is located on a separate platform ( e.g., aircraft), each sensor may interrogate---and hence collect data over---only partially overlapping areas of land. As a result, some data points may be characterized by data (i.e., features) from only a subset of the possible sensors employed in the task. Equivalently, this scenario implies that some data points will be missing features. Increasing focus in the future on using---and fusing data from---multiple sensors will make such incomplete-data problems commonplace. In many applications involving incomplete data, it is possible to acquire the missing data at a cost. In multi-sensor remote-sensing applications, data is acquired by deploying sensors to data points. Acquiring data is usually an expensive, time-consuming task, a fact that necessitates an intelligent data acquisition process. Incomplete data is not limited to remote-sensing applications, but rather, can arise in virtually any data set. In this dissertation, we address the general problem of classification when faced with incomplete data. We also address the closely related problem of active data acquisition, which develops a strategy to acquire missing features and labels that will most benefit the classification task. We first address the general problem of classification with incomplete data, maintaining the view that all data (i.e., information) is valuable. We employ a logistic regression framework within which we formulate a supervised classification algorithm for incomplete data. This principled, yet flexible, framework permits several interesting extensions that allow all available data to be utilized. One extension incorporates labeling error, which permits the usage of potentially imperfectly labeled data in learning a classifier. A second major extension converts the proposed algorithm to a semi-supervised approach by utilizing unlabeled data via graph-based regularization. Finally, the classification algorithm is extended to the case in which (image) data---from which features are extracted---are available from multiple resolutions. Taken together, this family of incomplete-data classification algorithms exploits all available data in a principled manner by avoiding explicit imputation. Instead, missing data is integrated out analytically with the aid of an estimated conditional density function (conditioned on the observed features). This feat is accomplished by invoking only mild assumptions. We also address the problem of active data acquisition by determining which missing data should be acquired to most improve performance. Specifically, we examine this data acquisition task when the data to be acquired can be either labels or features. The proposed approach is based on a criterion that accounts for the expected benefit of the acquisition. This approach, which is applicable for any general missing data problem, exploits the incomplete-data classification framework introduced in the first part of this dissertation. This data acquisition approach allows for the acquisition of both labels and features. Moreover, several types of feature acquisition are permitted, including the acquisition of individual or multiple features for individual or multiple data points, which may be either labeled or unlabeled. Furthermore, if different types of data acquisition are feasible for a given application, the algorithm will automatically determine the most beneficial type of data to acquire. Experimental results on both benchmark machine learning data sets and real (i.e., measured) remote-sensing data demonstrate the advantages of the proposed incomplete-data classification and active data acquisition algorithms.

Understanding genetics: Analysis of secondary students' conceptual status

NASA Astrophysics Data System (ADS)

Tsui, Chi-Yan; Treagust, David F.

2007-02-01

This article explores the conceptual change of students in Grades 10 and 12 in three Australian senior high schools when the teachers included computer multimedia to a greater or lesser extent in their teaching of a genetics course. The study, underpinned by a multidimensional conceptual-change framework, used an interpretive approach and a case-based design with multiple data collection methods. Over 4-8 weeks, the students learned genetics in classroom lessons that included BioLogica activities, which feature multiple representations. Results of the online tests and interview tasks revealed that most students improved their understanding of genetics as evidenced in the development of genetics reasoning. However, using Thorley's (1990) status analysis categories, a cross-case analysis of the gene conceptions of 9 of the 26 students interviewed indicated that only 4 students' postinstructional conceptions were intelligible-plausible-fruitful. Students' conceptual change was consistent with classroom teaching and learning. Findings suggested that multiple representations supported conceptual understanding of genetics but not in all students. It was also shown that status can be a viable hallmark enabling researchers to identify students' conceptual change that would otherwise be less accessible. Thorley's method for analyzing conceptual status is discussed.

Coordinating an Autonomous Earth-Observing Sensorweb

NASA Technical Reports Server (NTRS)

Sherwood, Robert; Cichy, Benjamin; Tran, Daniel; Chien, Steve; Rabideau, Gregg; Davies, Ashley; Castano, Rebecca; frye, Stuart; Mandl, Dan; Shulman, Seth;

Optical devices featuring textured semiconductor layers

DOEpatents

Moustakas, Theodore D [Dover, MA; Cabalu, Jasper S [Cary, NC

2011-10-11

A semiconductor sensor, solar cell or emitter, or a precursor therefor, has a substrate and one or more textured semiconductor layers deposited onto the substrate. The textured layers enhance light extraction or absorption. Texturing in the region of multiple quantum wells greatly enhances internal quantum efficiency if the semiconductor is polar and the quantum wells are grown along the polar direction. Electroluminescence of LEDs of the invention is dichromatic, and results in variable color LEDs, including white LEDs, without the use of phosphor.

Optical devices featuring textured semiconductor layers

DOEpatents

Moustakas, Theodore D [Dover, MA; Cabalu, Jasper S [Cary, NC

2012-08-07

A semiconductor sensor, solar cell or emitter, or a precursor therefor, has a substrate and one or more textured semiconductor layers deposited onto the substrate. The textured layers enhance light extraction or absorption. Texturing in the region of multiple quantum wells greatly enhances internal quantum efficiency if the semiconductor is polar and the quantum wells are grown along the polar direction. Electroluminescence of LEDs of the invention is dichromatic, and results in variable color LEDs, including white LEDs, without the use of phosphor.

pytc: Open-Source Python Software for Global Analyses of Isothermal Titration Calorimetry Data.

PubMed

Duvvuri, Hiranmayi; Wheeler, Lucas C; Harms, Michael J

2018-05-08

Here we describe pytc, an open-source Python package for global fits of thermodynamic models to multiple isothermal titration calorimetry experiments. Key features include simplicity, the ability to implement new thermodynamic models, a robust maximum likelihood fitter, a fast Bayesian Markov-Chain Monte Carlo sampler, rigorous implementation, extensive documentation, and full cross-platform compatibility. pytc fitting can be done using an application program interface or via a graphical user interface. It is available for download at https://github.com/harmslab/pytc .

Human Factors Research Task 2006-8722;111: AIMSsim Feature Development II

DTIC Science & Technology

2008-01-01

originally scheduled to end in May 2007. The SOW was amended in May to set the target end date to August 31st, 2007, without any change to the budget...work task identified in the SOW is described below. More details can be found in the User and System manuals. 1. Multiple USB joysticks: This consisted...machine for changing the course of the experiment or saving responses/data. 9. SGE cleanup: This was originally included in the SOW to allow for

Spacecraft Trajectory Analysis and Mission Planning Simulation (STAMPS) Software

NASA Technical Reports Server (NTRS)

Puckett, Nancy; Pettinger, Kris; Hallstrom,John; Brownfield, Dana; Blinn, Eric; Williams, Frank; Wiuff, Kelli; McCarty, Steve; Ramirez, Daniel; Lamotte, Nicole;

The Control of Single-color and Multiple-color Visual Search by Attentional Templates in Working Memory and in Long-term Memory.

PubMed

Grubert, Anna; Carlisle, Nancy B; Eimer, Martin

2016-12-01

The question whether target selection in visual search can be effectively controlled by simultaneous attentional templates for multiple features is still under dispute. We investigated whether multiple-color attentional guidance is possible when target colors remain constant and can thus be represented in long-term memory but not when they change frequently and have to be held in working memory. Participants searched for one, two, or three possible target colors that were specified by cue displays at the start of each trial. In constant-color blocks, the same colors remained task-relevant throughout. In variable-color blocks, target colors changed between trials. The contralateral delay activity (CDA) to cue displays increased in amplitude as a function of color memory load in variable-color blocks, which indicates that cued target colors were held in working memory. In constant-color blocks, the CDA was much smaller, suggesting that color representations were primarily stored in long-term memory. N2pc components to targets were measured as a marker of attentional target selection. Target N2pcs were attenuated and delayed during multiple-color search, demonstrating less efficient attentional deployment to color-defined target objects relative to single-color search. Importantly, these costs were the same in constant-color and variable-color blocks. These results demonstrate that attentional guidance by multiple-feature as compared with single-feature templates is less efficient both when target features remain constant and can be represented in long-term memory and when they change across trials and therefore have to be maintained in working memory.

Multisensory connections of monkey auditory cerebral cortex

PubMed Central

Smiley, John F.; Falchier, Arnaud

2009-01-01

Functional studies have demonstrated multisensory responses in auditory cortex, even in the primary and early auditory association areas. The features of somatosensory and visual responses in auditory cortex suggest that they are involved in multiple processes including spatial, temporal and object-related perception. Tract tracing studies in monkeys have demonstrated several potential sources of somatosensory and visual inputs to auditory cortex. These include potential somatosensory inputs from the retroinsular (RI) and granular insula (Ig) cortical areas, and from the thalamic posterior (PO) nucleus. Potential sources of visual responses include peripheral field representations of areas V2 and prostriata, as well as the superior temporal polysensory area (STP) in the superior temporal sulcus, and the magnocellular medial geniculate thalamic nucleus (MGm). Besides these sources, there are several other thalamic, limbic and cortical association structures that have multisensory responses and may contribute cross-modal inputs to auditory cortex. These connections demonstrated by tract tracing provide a list of potential inputs, but in most cases their significance has not been confirmed by functional experiments. It is possible that the somatosensory and visual modulation of auditory cortex are each mediated by multiple extrinsic sources. PMID:19619628

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Feature-level analysis of a novel smartphone application for smoking cessation.

PubMed

Heffner, Jaimee L; Vilardaga, Roger; Mercer, Laina D; Kientz, Julie A; Bricker, Jonathan B

2015-01-01

Currently, there are over 400 smoking cessation smartphone apps available, downloaded an estimated 780,000 times per month. No prior studies have examined how individuals engage with specific features of cessation apps and whether use of these features is associated with quitting. Using data from a pilot trial of a novel smoking cessation app, we examined: (i) the 10 most-used app features, and (ii) prospective associations between feature usage and quitting. Participants (n = 76) were from the experimental arm of a randomized, controlled pilot trial of an app for smoking cessation called "SmartQuit," which includes elements of both Acceptance and Commitment Therapy (ACT) and traditional cognitive behavioral therapy (CBT). Utilization data were automatically tracked during the 8-week treatment phase. Thirty-day point prevalence smoking abstinence was assessed at 60-day follow-up. The most-used features - quit plan, tracking, progress, and sharing - were mostly CBT. Only two of the 10 most-used features were prospectively associated with quitting: viewing the quit plan (p = 0.03) and tracking practice of letting urges pass (p = 0.03). Tracking ACT skill practice was used by fewer participants (n = 43) but was associated with cessation (p = 0.01). In this exploratory analysis without control for multiple comparisons, viewing a quit plan (CBT) as well as tracking practice of letting urges pass (ACT) were both appealing to app users and associated with successful quitting. Aside from these features, there was little overlap between a feature's popularity and its prospective association with quitting. Tests of causal associations between feature usage and smoking cessation are now needed.

Enchondromatosis with features of dysspondyloenchondromatosis and Maffucci syndrome.

PubMed

Haga, N; Nakamura, K; Taniguchi, K; Nakamura, S

1998-01-01

We report a girl with multiple enchondromatosis, unequal leg length, short stature, congenital scoliosis, lymphangioma, and cutaneous hemangiomata. The skeletal findings were consistent with the clinical and radiological features of dysspondyloenchondromatosis except that short stature was not apparent in the neonatal period. Dysspondyloenchondromatosis is a rare disorder, one of the several types of multiple enchondromatosis with spinal abnormalities. In previous reports of this condition the association of vascular lesions usually found in Maffucci syndrome has not been described.

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.

oPOSSUM: integrated tools for analysis of regulatory motif over-representation

PubMed Central

Ho Sui, Shannan J.; Fulton, Debra L.; Arenillas, David J.; Kwon, Andrew T.; Wasserman, Wyeth W.

2007-01-01

The identification of over-represented transcription factor binding sites from sets of co-expressed genes provides insights into the mechanisms of regulation for diverse biological contexts. oPOSSUM, an internet-based system for such studies of regulation, has been improved and expanded in this new release. New features include a worm-specific version for investigating binding sites conserved between Caenorhabditis elegans and C. briggsae, as well as a yeast-specific version for the analysis of co-expressed sets of Saccharomyces cerevisiae genes. The human and mouse applications feature improvements in ortholog mapping, sequence alignments and the delineation of multiple alternative promoters. oPOSSUM2, introduced for the analysis of over-represented combinations of motifs in human and mouse genes, has been integrated with the original oPOSSUM system. Analysis using user-defined background gene sets is now supported. The transcription factor binding site models have been updated to include new profiles from the JASPAR database. oPOSSUM is available at http://www.cisreg.ca/oPOSSUM/ PMID:17576675

Health Risks of an Inactive Lifestyle - Multiple Languages

MedlinePlus

... Are Here: Home → Multiple Languages → All Health Topics → Health Risks of an Inactive Lifestyle URL of this page: https://medlineplus.gov/languages/ ... V W XYZ List of All Topics All Health Risks of an Inactive Lifestyle - Multiple Languages To use the sharing features on ...

Central serous choroidopathy in the Hallermann-Streiff Syndrome.

PubMed

Blair, N P; Brockhurst, R J; Lee, W

1981-08-01

Central serous choroidopathy was observed in a young patient with the Hallermann-Streiff syndrome. Typical features of this syndrome include microphthalmos, proportionate dwarfism, dyscephaly with birdlike facies, dental abnormalities, and hypotrichosis. Exceptional aspects of this case include age of onset (11 years), high hyperopic refractive error (+ 13.00 sphere), and multiple recurrences caused by six separate documented leaks from the choroid. Fundus changes previously reported in the Hallermann-Streiff syndrome, interpreted as chorioretinal pigmentary changes, may have been secondary to previous undiagnosed central serous choroidopathy. Periodic ophthalmoscopy should be performed and may detect unrecognized episodes of central serous choroidopathy for which photocoagulation would be beneficial.

Method for making devices having intermetallic structures and intermetallic devices made thereby

DOEpatents

Paul, Brian Kevin; Wilson, Richard Dean; Alman, David Eli

2004-01-06

A method and system for making a monolithic intermetallic structure are presented. The structure is made from lamina blanks which comprise multiple layers of metals which are patternable, or intermetallic lamina blanks that are patternable. Lamina blanks are patterned, stacked and registered, and processed to form a monolithic intermetallic structure. The advantages of a patterned monolithic intermetallic structure include physical characteristics such as melting temperature, thermal conductivity, and corrosion resistance. Applications are broad, and include among others, use as a microreactor, heat recycling device, and apparatus for producing superheated steam. Monolithic intermetallic structures may contain one or more catalysts within the internal features.

CAMAC driver for the RSX-11M V3 operating system

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

Tippie, J. W.; Cannon, P. H.

1977-01-01

A driver for Kinetic Systems 3911A dedicated crate controller and 3992 serial highway driver for RSX-11M is described. The implementation includes a modified UCB structure. With this structure, multiple active I/O requests are supported to a single controller. The completion of an I/O request may be tied to external events via a WAIT-FOR-LAM command. Features of the driver include the ability to pass a list of FNA's in a single QIO call, serial highway overhead transparent at the QIO level, and special control commands to the driver passed in the FNA list. 1 figure.

The 30/20 GHz demonstration system SSUS-D/BSE

NASA Technical Reports Server (NTRS)

1981-01-01

The systems consisting of a 30/20 GHz communication satellite featuring a multiple fixed beam and scanning beam antenna, SS-TDMA, onboard processing and high power TWT's and IMPATT amplifiers, a trunking space-diversity Earth station, a customer premise system (CPS) portable Earth station and a Master Control Station. Hardware, software and personnel are included to build and launch one satellite and to carry on a two year experimentation and demonstration period of advanced Ka-band systems concepts and technology. Included are first level plans identifying all tasks, a schedule for system development and an assessment of critical technology and risk and a preliminary experiments plan.

Database of historically documented springs and spring flow measurements in Texas

USGS Publications Warehouse

Heitmuller, Franklin T.; Reece, Brian D.

2003-01-01

Springs are naturally occurring features that convey excess ground water to the land surface; they represent a transition from ground water to surface water. Water issues through one opening, multiple openings, or numerous seeps in the rock or soil. The database of this report provides information about springs and spring flow in Texas including spring names, identification numbers, location, and, if available, water source and use. This database does not include every spring in Texas, but is limited to an aggregation of selected digital and hard-copy data of the U.S. Geological Survey (USGS), the Texas Water Development Board (TWDB), and Capitol Environmental Services.

Inducing Order from Disordered Copolymers: On Demand Generation of Triblock Morphologies Including Networks

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

Tureau, Maëva S.; Kuan, Wei-Fan; Rong, Lixia

Disordered block copolymers are generally impractical in nanopatterning applications due to their inability to self-assemble into well-defined nanostructures. However, inducing order in low molecular weight disordered systems permits the design of periodic structures with smaller characteristic sizes. Here, we have induced nanoscale phase separation from disordered triblock copolymer melts to form well-ordered lamellae, hexagonally packed cylinders, and a triply periodic gyroid network structure, using a copolymer/homopolymer blending approach, which incorporates constituent homopolymers into selective block domains. This versatile blending approach allows one to precisely target multiple nanostructures from a single disordered material and can be applied to a wide varietymore » of triblock copolymer systems for nanotemplating and nanoscale separation applications requiring nanoscale feature sizes and/or high areal feature densities.« less

Improving the interactivity and functionality of Web-based radiology teaching files with the Java programming language.

PubMed

Eng, J

1997-01-01

Java is a programming language that runs on a "virtual machine" built into World Wide Web (WWW)-browsing programs on multiple hardware platforms. Web pages were developed with Java to enable Web-browsing programs to overlay transparent graphics and text on displayed images so that the user could control the display of labels and annotations on the images, a key feature not available with standard Web pages. This feature was extended to include the presentation of normal radiologic anatomy. Java programming was also used to make Web browsers compatible with the Digital Imaging and Communications in Medicine (DICOM) file format. By enhancing the functionality of Web pages, Java technology should provide greater incentive for using a Web-based approach in the development of radiology teaching material.

Acquired pendular nystagmus.

PubMed

Kang, Sarah; Shaikh, Aasef G

2017-04-15

Acquired pendular nystagmus is comprised of quasi-sinusoidal oscillations of the eyes significantly affecting gaze holding and clarity of vision. The most common causes of acquired pendular nystagmus include demyelinating disorders such as multiple sclerosis and the syndrome of ocular palatal tremor. However, several other deficits, such as pharmacological intoxication, metabolic and genetic disorders, and granulomatous disorders can lead to syndromes mimicking acquired pendular nystagmus. Study of the kinematic features of acquired pendular nystagmus has suggested a putative pathophysiology of an otherwise mysterious neurological disorder. Here we review clinical features of neurological deficits that co-occur with acquired pendular nystagmus. Subsequent discussion of the pathophysiology of individual forms of pendular nystagmus speculates on mechanisms of the underlying disease while providing insights into pharmacotherapy of nystagmus. Copyright © 2017 Elsevier B.V. All rights reserved.

Paleopathological Study of Dwarfism-Related Skeletal Dysplasia in a Late Joseon Dynasty (South Korean) Population

PubMed Central

Woo, Eun Jin; Lee, Won-Joon; Hu, Kyung-Seok; Hwang, Jae Joon

2015-01-01

Skeletal dysplasias related to genetic etiologies have rarely been reported for past populations. This report presents the skeletal characteristics of an individual with dwarfism-related skeletal dysplasia from South Korea. To assess abnormal deformities, morphological features, metric data, and computed tomography scans are analyzed. Differential diagnoses include achondroplasia or hypochondroplasia, chondrodysplasia, multiple epiphyseal dysplasia, thalassemia-related hemolytic anemia, and lysosomal storage disease. The diffused deformities in the upper-limb bones and several coarsened features of the craniofacial bones indicate the most likely diagnosis to have been a certain type of lysosomal storage disease. The skeletal remains of EP-III-4-No.107 from the Eunpyeong site, although incomplete and fragmented, provide important clues to the paleopathological diagnosis of skeletal dysplasias. PMID:26488291