Relevance feature selection of modal frequency-ambient condition pattern recognition in structural health assessment for reinforced concrete buildings

Directory of Open Access Journals (Sweden)

He-Qing Mu

2016-08-01

Full Text Available Modal frequency is an important indicator for structural health assessment. Previous studies have shown that this indicator is substantially affected by the fluctuation of ambient conditions, such as temperature and humidity. Therefore, recognizing the pattern between modal frequency and ambient conditions is necessary for reliable long-term structural health assessment. In this article, a novel machine-learning algorithm is proposed to automatically select relevance features in modal frequency-ambient condition pattern recognition based on structural dynamic response and ambient condition measurement. In contrast to the traditional feature selection approaches by examining a large number of combinations of extracted features, the proposed algorithm conducts continuous relevance feature selection by introducing a sophisticated hyperparameterization on the weight parameter vector controlling the relevancy of different features in the prediction model. The proposed algorithm is then utilized for structural health assessment for a reinforced concrete building based on 1-year daily measurements. It turns out that the optimal model class including the relevance features for each vibrational mode is capable to capture the pattern between the corresponding modal frequency and the ambient conditions.

Features of an emergency heat-conducting path in reactors about lead-bismuth and lead heat-carriers

International Nuclear Information System (INIS)

Beznosov, A.V.; Bokova, T.A.; Molodtsov, A.A.

2006-01-01

The reactor emergency heat removal systems should transfer heat from the surface of reactor core fuel element claddings to the primary circuit followed by heat transfer to the environment. One suggests three design approaches for emergency heat removal systems in lead-bismuth and lead cooled reactor circuits that take account of the peculiar nature of their features. Application of the discussed systems for emergency heat removal improves safety of lead-bismuth and lead cooled reactor plants [ru

Amygdala and auditory cortex exhibit distinct sensitivity to relevant acoustic features of auditory emotions.

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Pannese, Alessia; Grandjean, Didier; Frühholz, Sascha

2016-12-01

Discriminating between auditory signals of different affective value is critical to successful social interaction. It is commonly held that acoustic decoding of such signals occurs in the auditory system, whereas affective decoding occurs in the amygdala. However, given that the amygdala receives direct subcortical projections that bypass the auditory cortex, it is possible that some acoustic decoding occurs in the amygdala as well, when the acoustic features are relevant for affective discrimination. We tested this hypothesis by combining functional neuroimaging with the neurophysiological phenomena of repetition suppression (RS) and repetition enhancement (RE) in human listeners. Our results show that both amygdala and auditory cortex responded differentially to physical voice features, suggesting that the amygdala and auditory cortex decode the affective quality of the voice not only by processing the emotional content from previously processed acoustic features, but also by processing the acoustic features themselves, when these are relevant to the identification of the voice's affective value. Specifically, we found that the auditory cortex is sensitive to spectral high-frequency voice cues when discriminating vocal anger from vocal fear and joy, whereas the amygdala is sensitive to vocal pitch when discriminating between negative vocal emotions (i.e., anger and fear). Vocal pitch is an instantaneously recognized voice feature, which is potentially transferred to the amygdala by direct subcortical projections. These results together provide evidence that, besides the auditory cortex, the amygdala too processes acoustic information, when this is relevant to the discrimination of auditory emotions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sparse Matrix for ECG Identification with Two-Lead Features

Directory of Open Access Journals (Sweden)

Kuo-Kun Tseng

2015-01-01

Full Text Available Electrocardiograph (ECG human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.

Special features of self-compensation of halogen donor action in lead telluride

International Nuclear Information System (INIS)

Kajdanov, V.I.; Nemov, S.A.; Ravich, Yu.I.; Dereza, A.Yu.

1985-01-01

Specific features of self-compensation of halogen donor action in lead telluride are investigasted. Lead telluride samples with chlorine additions (with tellurium excess) and, besides, with bromine- and iodine additions were studied in order to reveal general regularities in alloyind with all halogen donor impurities. Experimental dependences of the difference between the electron and hole concentrations (n-p) in PbTe as a function of an amount of introduced halogen impurities (Ni) are presented for samples with a maximum compensation at 295 K. General features of the n-p=f(Ni) dependence are presented for all halogens. The hypothesis on the kinetic mechanism of increasing the efficiency of self-compensation of halogen donor action in lead telluride is suggested

MememxGATE: Unearthing Latent Content Features for Improved Search and Relevancy Ranking Across Scientific Literature

Science.gov (United States)

Wilson, B. D.; McGibbney, L. J.; Mattmann, C. A.; Ramirez, P.; Joyce, M.; Whitehall, K. D.

2015-12-01

Quantifying scientific relevancy is of increasing importance to NASA and the research community. Scientific relevancy may be defined by mapping the impacts of a particular NASA mission, instrument, and/or retrieved variables to disciplines such as climate predictions, natural hazards detection and mitigation processes, education, and scientific discoveries. Related to relevancy, is the ability to expose data with similar attributes. This in turn depends upon the ability for us to extract latent, implicit document features from scientific data and resources and make them explicit, accessible and useable for search activities amongst others. This paper presents MemexGATE; a server side application, command line interface and computing environment for running large scale metadata extraction, general architecture text engineering, document classification and indexing tasks over document resources such as social media streams, scientific literature archives, legal documentation, etc. This work builds on existing experiences using MemexGATE (funded, developed and validated through the DARPA Memex Progrjam PI Mattmann) for extracting and leveraging latent content features from document resources within the Materials Research domain. We extend the software functionality capability to the domain of scientific literature with emphasis on the expansion of gazetteer lists, named entity rules, natural language construct labeling (e.g. synonym, antonym, hyponym, etc.) efforts to enable extraction of latent content features from data hosted by wide variety of scientific literature vendors (AGU Meeting Abstract Database, Springer, Wiley Online, Elsevier, etc.) hosting earth science literature. Such literature makes both implicit and explicit references to NASA datasets and relationships between such concepts stored across EOSDIS DAAC's hence we envisage that a significant part of this effort will also include development and understanding of relevancy signals which can ultimately

Identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis by using the Delphi Technique

Science.gov (United States)

Halim, N. Z. A.; Sulaiman, S. A.; Talib, K.; Ng, E. G.

2018-02-01

This paper explains the process carried out in identifying the relevant features of the National Digital Cadastral Database (NDCDB) for spatial analysis. The research was initially a part of a larger research exercise to identify the significance of NDCDB from the legal, technical, role and land-based analysis perspectives. The research methodology of applying the Delphi technique is substantially discussed in this paper. A heterogeneous panel of 14 experts was created to determine the importance of NDCDB from the technical relevance standpoint. Three statements describing the relevant features of NDCDB for spatial analysis were established after three rounds of consensus building. It highlighted the NDCDB’s characteristics such as its spatial accuracy, functions, and criteria as a facilitating tool for spatial analysis. By recognising the relevant features of NDCDB for spatial analysis in this study, practical application of NDCDB for various analysis and purpose can be widely implemented.

A DSS framework for maintaining relevant features of the Small Business B2C Websites

OpenAIRE

Khatun, Madhury; Miah, Shah Jahan

2016-01-01

Managers are heavily engaged in strategic decision-making for businesses, particularly in a changing environment. One of the most important decisions for online small businesses, as part of their strategic planning, is selecting relevant features on their websites, both to attract and interact with consumers. However, only a few Australian small businesses use strategic tools for selecting their website features. As a result, businesses lose potential domestic sales in the business-to-consume...

Thin lead sheets in the decorative features in Pavia Charterhouse.

Science.gov (United States)

Colombo, Chiara; Realini, Marco; Sansonetti, Antonio; Rampazzi, Laura; Casadio, Francesca

2006-01-01

The facade of the church of the Pavia Charterhouse, built at the end of the 15th century, shows outstanding decorative features made of different stone materials, such as marbles, breccias and sandstones. Magnificent ornamental elements are made of thin lead sheets, and some marble slabs are inlaid with them. Metal elements are shaped in complex geometric and phytomorphic design, to form a Greek fret in black contrasting with the white Carrara marble. Lead pins were fixed to the back of the thin lead sheets with the aim of attaching the metal elements to the marble; in so doing the pins and the lead sheets constitute a single piece of metal. In some areas, lead elements have been lost, and they have been substituted with a black plaster, matching the colour of the metal. To the authors' knowledge, this kind of decorative technique is rare, and confirms the refinement of Renaissance Lombard architecture. This work reports on the results of an extensive survey of the white, orange and yellowish layers, which are present on the external surface of the lead. The thin lead sheets have been characterized and their state of conservation has been studied with the aid of Optical Microscopy, SEM-EDS, FTIR and Raman analyses. Lead sulphate, lead carbonates and oxides have been identified as decay products.

Application of Multilabel Learning Using the Relevant Feature for Each Label in Chronic Gastritis Syndrome Diagnosis

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Liu, Guo-Ping; Yan, Jian-Jun; Wang, Yi-Qin; Fu, Jing-Jing; Xu, Zhao-Xia; Guo, Rui; Qian, Peng

2012-01-01

Background. In Traditional Chinese Medicine (TCM), most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs). Methods. We employed a multilabel learning using the relevant feature for each label (REAL) algorithm to construct a syndrome diagnostic model for chronic gastritis (CG) in TCM. REAL combines feature selection methods to select the significant symptoms (signs) of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL), whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs) for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice. PMID:22719781

Application of Multilabel Learning Using the Relevant Feature for Each Label in Chronic Gastritis Syndrome Diagnosis

Directory of Open Access Journals (Sweden)

Guo-Ping Liu

2012-01-01

Full Text Available Background. In Traditional Chinese Medicine (TCM, most of the algorithms are used to solve problems of syndrome diagnosis that only focus on one syndrome, that is, single label learning. However, in clinical practice, patients may simultaneously have more than one syndrome, which has its own symptoms (signs. Methods. We employed a multilabel learning using the relevant feature for each label (REAL algorithm to construct a syndrome diagnostic model for chronic gastritis (CG in TCM. REAL combines feature selection methods to select the significant symptoms (signs of CG. The method was tested on 919 patients using the standard scale. Results. The highest prediction accuracy was achieved when 20 features were selected. The features selected with the information gain were more consistent with the TCM theory. The lowest average accuracy was 54% using multi-label neural networks (BP-MLL, whereas the highest was 82% using REAL for constructing the diagnostic model. For coverage, hamming loss, and ranking loss, the values obtained using the REAL algorithm were the lowest at 0.160, 0.142, and 0.177, respectively. Conclusion. REAL extracts the relevant symptoms (signs for each syndrome and improves its recognition accuracy. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice.

Oculomotor selection underlies feature retention in visual working memory.

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Hanning, Nina M; Jonikaitis, Donatas; Deubel, Heiner; Szinte, Martin

2016-02-01

Oculomotor selection, spatial task relevance, and visual working memory (WM) are described as three processes highly intertwined and sustained by similar cortical structures. However, because task-relevant locations always constitute potential saccade targets, no study so far has been able to distinguish between oculomotor selection and spatial task relevance. We designed an experiment that allowed us to dissociate in humans the contribution of task relevance, oculomotor selection, and oculomotor execution to the retention of feature representations in WM. We report that task relevance and oculomotor selection lead to dissociable effects on feature WM maintenance. In a first task, in which an object's location was encoded as a saccade target, its feature representations were successfully maintained in WM, whereas they declined at nonsaccade target locations. Likewise, we observed a similar WM benefit at the target of saccades that were prepared but never executed. In a second task, when an object's location was marked as task relevant but constituted a nonsaccade target (a location to avoid), feature representations maintained at that location did not benefit. Combined, our results demonstrate that oculomotor selection is consistently associated with WM, whereas task relevance is not. This provides evidence for an overlapping circuitry serving saccade target selection and feature-based WM that can be dissociated from processes encoding task-relevant locations. Copyright © 2016 the American Physiological Society.

Task relevance modulates the cortical representation of feature conjunctions in the target template.

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Reeder, Reshanne R; Hanke, Michael; Pollmann, Stefan

2017-07-03

Little is known about the cortical regions involved in representing task-related content in preparation for visual task performance. Here we used representational similarity analysis (RSA) to investigate the BOLD response pattern similarity between task relevant and task irrelevant feature dimensions during conjunction viewing and target template maintenance prior to visual search. Subjects were cued to search for a spatial frequency (SF) or orientation of a Gabor grating and we measured BOLD signal during cue and delay periods before the onset of a search display. RSA of delay period activity revealed that widespread regions in frontal, posterior parietal, and occipitotemporal cortices showed general representational differences between task relevant and task irrelevant dimensions (e.g., orientation vs. SF). In contrast, RSA of cue period activity revealed sensory-related representational differences between cue images (regardless of task) at the occipital pole and additionally in the frontal pole. Our data show that task and sensory information are represented differently during viewing and during target template maintenance, and that task relevance modulates the representation of visual information across the cortex.

Automated detection of heart ailments from 12-lead ECG using complex wavelet sub-band bi-spectrum features.

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Tripathy, Rajesh Kumar; Dandapat, Samarendra

2017-04-01

The complex wavelet sub-band bi-spectrum (CWSB) features are proposed for detection and classification of myocardial infarction (MI), heart muscle disease (HMD) and bundle branch block (BBB) from 12-lead ECG. The dual tree CW transform of 12-lead ECG produces CW coefficients at different sub-bands. The higher-order CW analysis is used for evaluation of CWSB. The mean of the absolute value of CWSB, and the number of negative phase angle and the number of positive phase angle features from the phase of CWSB of 12-lead ECG are evaluated. Extreme learning machine and support vector machine (SVM) classifiers are used to evaluate the performance of CWSB features. Experimental results show that the proposed CWSB features of 12-lead ECG and the SVM classifier are successful for classification of various heart pathologies. The individual accuracy values for MI, HMD and BBB classes are obtained as 98.37, 97.39 and 96.40%, respectively, using SVM classifier and radial basis function kernel function. A comparison has also been made with existing 12-lead ECG-based cardiac disease detection techniques.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

Predictive Feature Selection for Genetic Policy Search

Science.gov (United States)

2014-05-22

limited manual intervention are becoming increasingly desirable as more complex tasks in dynamic and high- tempo environments are explored. Reinforcement...states in many domains causes features relevant to the reward variations to be overlooked, which hinders the policy search. 3.4 Parameter Selection PFS...the current feature subset. This local minimum may be “deceptive,” meaning that it does not clearly lead to the global optimal policy ( Goldberg and

Healthy full-term infants' brain responses to emotionally and linguistically relevant sounds using a multi-feature mismatch negativity (MMN) paradigm.

Science.gov (United States)

Kostilainen, Kaisamari; Wikström, Valtteri; Pakarinen, Satu; Videman, Mari; Karlsson, Linnea; Keskinen, Maria; Scheinin, Noora M; Karlsson, Hasse; Huotilainen, Minna

2018-03-23

We evaluated the feasibility of a multi-feature mismatch negativity (MMN) paradigm in studying auditory processing of healthy newborns. The aim was to examine the automatic change-detection and processing of semantic and emotional information in speech in newborns. Brain responses of 202 healthy newborns were recorded with a multi-feature paradigm including a Finnish bi-syllabic pseudo-word/ta-ta/as a standard stimulus, six linguistically relevant deviant stimuli and three emotionally relevant stimuli (happy, sad, angry). Clear responses to emotional sounds were found already at the early latency window 100-200 ms, whereas responses to linguistically relevant minor changes and emotional stimuli at the later latency window 300-500 ms did not reach significance. Moreover, significant interaction between gender and emotional stimuli was found in the early latency window. Further studies on using multi-feature paradigms with linguistic and emotional stimuli in newborns are needed, especially those containing of follow-ups, enabling the assessment of the predictive value of early variations between subjects. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Inferring feature relevances from metric learning

DEFF Research Database (Denmark)

Schulz, Alexander; Mokbel, Bassam; Biehl, Michael

2015-01-01

Powerful metric learning algorithms have been proposed in the last years which do not only greatly enhance the accuracy of distance-based classifiers and nearest neighbor database retrieval, but which also enable the interpretability of these operations by assigning explicit relevance weights...

Longitudinal MRI assessment: the identification of relevant features in the development of Posterior Fossa Syndrome in children

Science.gov (United States)

Spiteri, M.; Lewis, E.; Windridge, D.; Avula, S.

2015-03-01

Up to 25% of children who undergo brain tumour resection surgery in the posterior fossa develop posterior fossa syndrome (PFS). This syndrome is characterised by mutism and disturbance in speech. Our hypothesis is that there is a correlation between PFS and the occurrence of hypertrophic olivary degeneration (HOD) in lobes within the posterior fossa, known as the inferior olivary nuclei (ION). HOD is exhibited as an increase in size and intensity of the ION on an MR image. Intra-operative MRI (IoMRI) is used during surgical procedures at the Alder Hey Children's Hospital, Liver- pool, England, in the treatment of Posterior Fossa tumours and allows visualisation of the brain during surgery. The final MR scan on the IoMRI allows early assessment of the ION immediately after the surgical procedure. The longitudinal MRI data of 28 patients was analysed in a collaborative study with Alder Hey Children's Hospital, in order to identify the most relevant imaging features that relate to the development of PFS, specifically related to HOD. A semi-automated segmentation process was carried out to delineate the ION on each MRI. Feature selection techniques were used to identify the most relevant features amongst the MRI data, demographics and clinical data provided by the hospital. A support vector machine (SVM) was used to analyse the discriminative ability of the selected features. The results indicate the presence of HOD as the most efficient feature that correlates with the development of PFS, followed by the change in intensity and size of the ION and whether HOD occurred bilaterally or unilaterally.

Crossmodal integration enhances neural representation of task-relevant features in audiovisual face perception.

Science.gov (United States)

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Liu, Yongjian; Liang, Changhong; Sun, Pei

2015-02-01

Previous studies have shown that audiovisual integration improves identification performance and enhances neural activity in heteromodal brain areas, for example, the posterior superior temporal sulcus/middle temporal gyrus (pSTS/MTG). Furthermore, it has also been demonstrated that attention plays an important role in crossmodal integration. In this study, we considered crossmodal integration in audiovisual facial perception and explored its effect on the neural representation of features. The audiovisual stimuli in the experiment consisted of facial movie clips that could be classified into 2 gender categories (male vs. female) or 2 emotion categories (crying vs. laughing). The visual/auditory-only stimuli were created from these movie clips by removing the auditory/visual contents. The subjects needed to make a judgment about the gender/emotion category for each movie clip in the audiovisual, visual-only, or auditory-only stimulus condition as functional magnetic resonance imaging (fMRI) signals were recorded. The neural representation of the gender/emotion feature was assessed using the decoding accuracy and the brain pattern-related reproducibility indices, obtained by a multivariate pattern analysis method from the fMRI data. In comparison to the visual-only and auditory-only stimulus conditions, we found that audiovisual integration enhanced the neural representation of task-relevant features and that feature-selective attention might play a role of modulation in the audiovisual integration. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

Science.gov (United States)

Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

2016-03-01

Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection

Directory of Open Access Journals (Sweden)

Xin Ma

2015-01-01

Full Text Available The prediction of RNA-binding proteins is one of the most challenging problems in computation biology. Although some studies have investigated this problem, the accuracy of prediction is still not sufficient. In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR method, followed by incremental feature selection (IFS. We incorporated features of conjoint triad features and three novel features: binding propensity (BP, nonbinding propensity (NBP, and evolutionary information combined with physicochemical properties (EIPP. The results showed that these novel features have important roles in improving the performance of the predictor. Using the mRMR-IFS method, our predictor achieved the best performance (86.62% accuracy and 0.737 Matthews correlation coefficient. High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information.

Relevance of echo-structure and texture features

DEFF Research Database (Denmark)

Karemore, Gopal; Mullick, Jhinuk Basu; KV, Dr. Rajagopal

2010-01-01

Aim: Echostructure is an essential parameter for the evaluation of circumscribed lesions and can be described as a texture feature on ultrasound images. Present study evaluates the possibility of distinguishing between benign and malignant breast tumors using various texture features. Materials...... and Methods: 58 cases of breast tumor (29 each from benign and malignant) were documented under standardized conditions using a linear array machine and 7.5 MHz transducer. In each sonographic image, ROI of tumor was marked and then subjected to the evaluation of tumor status using five parameters of second...... performance ROC= 0.78(pbenign and malignant tumors. It also reveals that when evaluating images of a breast tumor...

WHEN RELEVANCE DECENTERS CRITICALITY: THE CASE OF THE SOUTH AFRICAN NATIONAL CRIME, VIOLENCE AND INJURY LEAD PROGRAMME

Directory of Open Access Journals (Sweden)

Mohamed Seedat

2010-11-01

Full Text Available Following the formal demise of political apartheid in SouthAfrica in 1994, critical and community-centred psychologistshave tended to obtain relevance through alignment with thetenets of social justice and the larger democratic project. Thisarticle draws on the experiences of the Crime, Violence andInjury Lead Programme (CVI to illustrate how particularformulations of scientific and social relevance function tomarginalize criticality and critical scholarship. The authorsuggests that relevance without criticality produces forms ofintellectual activity that privilege empiricist traditions, perpetrate a binary between research and research translation, andreproduce the myth that intervention work is atheoretical.The review of the CVI serves as a reminder of the challengesinherent in enactments of critical psychology. Among themany issues that critical psychology oriented initiatives likeCVI have to contend with is the task of developing theoreticaland other resources to move between co-operation and critiquein the service of democratic development.

Where Does It Lead? Imaging Features of Cardiovascular Implantable Electronic Devices on Chest Radiograph and CT

Energy Technology Data Exchange (ETDEWEB)

Lanzman, Rotem S.; Blondin, Dirk; Furst, Gunter; Scherer, Axel; R Miese, Falk; Kroepil, Patric [University of Duesseldorf, Medical Faculty, 40225 Duesseldorf (Germany); Winter, Joachim [University Hospital Duesseldorf, 40225 Duesseldorf (Germany); Abbara, Suhny [Massachusetts General Hospital, Boston, MA (US)

2011-10-15

Pacemakers and implantable cardioverter defibrillators (ICDs) are being increasingly employed in patients suffering from cardiac rhythm disturbances. The principal objective of this article is to familiarize radiologists with pacemakers and ICDs on chest radiographs and CT scans. Therefore, the preferred lead positions according to pacemaker types and anatomic variants are introduced in this study. Additionally, the imaging features of incorrect lead positions and defects, as well as complications subsequent to pacemaker implantation are demonstrated herein.

Where Does It Lead? Imaging Features of Cardiovascular Implantable Electronic Devices on Chest Radiograph and CT

International Nuclear Information System (INIS)

Lanzman, Rotem S.; Blondin, Dirk; Furst, Gunter; Scherer, Axel; R Miese, Falk; Kroepil, Patric; Winter, Joachim; Abbara, Suhny

2011-01-01

Pacemakers and implantable cardioverter defibrillators (ICDs) are being increasingly employed in patients suffering from cardiac rhythm disturbances. The principal objective of this article is to familiarize radiologists with pacemakers and ICDs on chest radiographs and CT scans. Therefore, the preferred lead positions according to pacemaker types and anatomic variants are introduced in this study. Additionally, the imaging features of incorrect lead positions and defects, as well as complications subsequent to pacemaker implantation are demonstrated herein.

Dysmorphic features and developmental outcome of 2-year-old children.

Science.gov (United States)

Seggers, Jorien; Haadsma, Maaike L; Bos, Arend F; Heineman, Maas Jan; Middelburg, Karin J; van den Heuvel, Edwin R; Hadders-Algra, Mijna

2014-11-01

The aim of this study was to assess the associations between dysmorphic features and neurological, mental, psychomotor, and behavioural development in order to improve our understanding of aetiological pathways leading to minor developmental problems. In our cross-sectional study, 272 generally healthy 2-year-olds (143 males, 129 females; median gestational age 39 weeks, [range 30-43wks]), born after a parental history of subfertility either with or without fertility treatment, were examined. Dysmorphic features were classified as abnormalities (clinically relevant or not), minor anomalies, or common variants according to Merks' classification system. Hempel's neurological assessment resulted in a neurological optimality score (NOS) and fluency score. Mental and psychomotor development were assessed with the Dutch version of the Bayley Scales of Infant Development and behavioural development with the Achenbach Child Behaviour Checklist. Of the different types of dysmorphic feature, clinically relevant abnormalities were most strongly associated with a lower NOS (difference -2.53, 95% confidence interval [CI] -4.23 to -0.83) and fluency score (difference -0.62, 95% CI -1.1 to -0.15). The presence of one or more abnormalities (clinically relevant or not) or one or more common variants was significantly associated with a lower NOS, and the presence of three or more minor anomalies was associated with lower fluency scores. Dysmorphic features were not associated with mental, psychomotor, or behavioural development. As dysmorphic features originate during the first trimester of pregnancy, the association between dysmorphic features and minor alterations in neurodevelopment may suggest an early ontogenetic origin of subtle neurological deviations. © 2014 Mac Keith Press.

Numerical Analysis for Relevant Features in Intrusion Detection (NARFid)

Science.gov (United States)

2009-03-01

Error and Average Correlation Coefficient. Mucciardi and Gose [63] discuss seven methods for selecting features. These methods seek to overcome the...POEmaxPOEmin). (2.37) With each iteration of selecting the next feature, ACC is also normalized in the same fashion. As stated by Mucciardi and Gose ...lan’s discussion [70] as described in Section 2.3.1. Mucciardi and Gose [63] provide the POEACC parameters that perform well in their experiments. As

Understanding psychiatric disorder by capturing ecologically relevant features of learning and decision-making.

Science.gov (United States)

Scholl, Jacqueline; Klein-Flügge, Miriam

2017-09-28

Recent research in cognitive neuroscience has begun to uncover the processes underlying increasingly complex voluntary behaviours, including learning and decision-making. Partly this success has been possible by progressing from simple experimental tasks to paradigms that incorporate more ecological features. More specifically, the premise is that to understand cognitions and brain functions relevant for real life, we need to introduce some of the ecological challenges that we have evolved to solve. This often entails an increase in task complexity, which can be managed by using computational models to help parse complex behaviours into specific component mechanisms. Here we propose that using computational models with tasks that capture ecologically relevant learning and decision-making processes may provide a critical advantage for capturing the mechanisms underlying symptoms of disorders in psychiatry. As a result, it may help develop mechanistic approaches towards diagnosis and treatment. We begin this review by mapping out the basic concepts and models of learning and decision-making. We then move on to consider specific challenges that emerge in realistic environments and describe how they can be captured by tasks. These include changes of context, uncertainty, reflexive/emotional biases, cost-benefit decision-making, and balancing exploration and exploitation. Where appropriate we highlight future or current links to psychiatry. We particularly draw examples from research on clinical depression, a disorder that greatly compromises motivated behaviours in real-life, but where simpler paradigms have yielded mixed results. Finally, we highlight several paradigms that could be used to help provide new insights into the mechanisms of psychiatric disorders. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Online feature selection with streaming features.

Science.gov (United States)

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

2013-05-01

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

Salient features, response and operation of Lead-Free Gulmarg Neutron Monitor

International Nuclear Information System (INIS)

Mufti, S.; Chatterjee, S.; Ishtiaq, P.M.; Darzi, M.A.; Mir, T.A.; Shah, G.N.

2016-01-01

Lead-Free Gulmarg Neutron Monitor (LFGNM) provides continuous ground level intensity measurements of atmospheric secondary neutrons produced in interactions of primary cosmic rays with the Earth's constituent atmosphere. We report the LFGNM detector salient features and simulation of its energy response for 10"−"1"1 MeV to 10"4 MeV energy incident neutrons using the FLUKA Monte Carlo package. An empirical calibration of the LFGNM detector carried out with a Pu–Be neutron source for maximising its few MeV neutron counting sensitivity is also presented. As an illustration of its functionality a single representative transient solar modulation event recorded by LFGNM depicting Forbush decrease in integrated neutron data for which the geospace consequences are well known is also presented. Performance of LFGNM under actual observation conditions for effectively responding to transient solar modulation is seen to compare well with other world-wide conventional neutron monitors.

SIP-FS: a novel feature selection for data representation

Directory of Open Access Journals (Sweden)

Yiyou Guo

2018-02-01

Full Text Available Abstract Multiple features are widely used to characterize real-world datasets. It is desirable to select leading features with stability and interpretability from a set of distinct features for a comprehensive data description. However, most of existing feature selection methods focus on the predictability (e.g., prediction accuracy of selected results yet neglect stability. To obtain compact data representation, a novel feature selection method is proposed to improve stability, and interpretability without sacrificing predictability (SIP-FS. Instead of mutual information, generalized correlation is adopted in minimal redundancy maximal relevance to measure the relation between different feature types. Several feature types (each contains a certain number of features can then be selected and evaluated quantitatively to determine what types contribute to a specific class, thereby enhancing the so-called interpretability of features. Moreover, stability is introduced in the criterion of SIP-FS to obtain consistent results of ranking. We conduct experiments on three publicly available datasets using one-versus-all strategy to select class-specific features. The experiments illustrate that SIP-FS achieves significant performance improvements in terms of stability and interpretability with desirable prediction accuracy and indicates advantages over several state-of-the-art approaches.

Is the OECD acute worm toxicity test environmentally relevant? The effect of mineral form on calculated lead toxicity

International Nuclear Information System (INIS)

Davies, N.A.Nicola A.; Hodson, M.E.Mark E.; Black, S.Stuart

2003-01-01

The current OECD acute worm toxicity test does not relate well to ambient conditions. - In a series of experiments the toxicity of lead to worms in soil was determined following the draft OECD earthworm reproduction toxicity protocol except that lead was added as solid lead nitrate, carbonate and sulphide rather than as lead nitrate solution as would normally be the case. The compounds were added to the test soil to give lead concentrations of 625-12500 μg Pb g -1 of soil. Calculated toxicities of the lead decreased in the order nitrate>carbonate>sulphide, the same order as the decrease in the solubility of the metal compounds used. The 7-day LC 50 (lethal concentration when 50% of the population is killed) for the nitrate was 5321±275 μg Pb g -1 of soil and this did not change with time. The LC 50 values for carbonate and sulphide could not be determined at the concentration ranges used. The only parameter sensitive enough to distinguish the toxicities of the three compounds was cocoon (egg) production. The EC 50 s for cocoon production (the concentration to produce a 50% reduction in cocoon production) were 993, 8604 and 10246 μg Pb g -1 of soil for lead nitrate, carbonate and sulphide, respectively. Standard toxicity tests need to take into account the form in which the contaminant is present in the soil to be of environmental relevance

Culturally Relevant Cyberbullying Prevention

OpenAIRE

Phillips, Gregory John

2017-01-01

In this action research study, I, along with a student intervention committee of 14 members, developed a cyberbullying intervention for a large urban high school on the west coast. This high school contained a predominantly African American student population. I aimed to discover culturally relevant cyberbullying prevention strategies for African American students. The intervention committee selected video safety messages featuring African American actors as the most culturally relevant cyber...

Relational Leading

DEFF Research Database (Denmark)

Larsen, Mette Vinther; Rasmussen, Jørgen Gulddahl

2015-01-01

This first chapter presents the exploratory and curious approach to leading as relational processes – an approach that pervades the entire book. We explore leading from a perspective that emphasises the unpredictable challenges and triviality of everyday life, which we consider an interesting......, relevant and realistic way to examine leading. The chapter brings up a number of concepts and contexts as formulated by researchers within the field, and in this way seeks to construct a first understanding of relational leading....

Feature Extraction

CERN Document Server

CERN. Geneva

2015-01-01

Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

Science.gov (United States)

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2015-07-08

Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex. The ability to perceive the world is limited by the brain's processing capacity. Attention affords adaptive behavior by selectively prioritizing processing of relevant stimuli based on their features (location, color, orientation, etc.). We found that attentional mechanisms for selection of different features belonging to the same object operate independently and in parallel: concurrent attentional selection of two stimulus features is simply the sum of attending to each of those

Many roads may lead to Rome: Selected features of quality control within environmental assessment systems in the US, NL, CA, and UK

Energy Technology Data Exchange (ETDEWEB)

Günther, Markus, E-mail: markus.guenther@tu-berlin.de; Geißler, Gesa; Köppel, Johann

2017-01-15

As there is no one-and-only concept on how to precisely define and establish quality control (QC) or quality assurance (QA) in the making of environmental assessments (EA), this paper presents selected features of international approaches that address quality in EA systems in the USA, the Netherlands, Canada, and the United Kingdom. Based on explanative case studies, we highlight the embedding of specific quality control features within the EA systems, the objectives and processes, and relevant transparency challenges. Such features of QC/QA approaches can be considered in cases where substantial quality control and assurance efforts are still missing. Yet further research needs to be conducted on the efficacy of these approaches, which remains beyond the scope of this study. - Highlights: • We present four tools for quality control and assurance from different EA systems. • Approaches vary in institutional setting, objectives, procedures, and transparency. • Highlighted features might provide guidance in cases where QC/QA is still lacking.

Who Leads China's Leading Universities?

Science.gov (United States)

Huang, Futao

2017-01-01

This study attempts to identify the major characteristics of two different groups of institutional leaders in China's leading universities. The study begins with a review of relevant literature and theory. Then, there is a brief introduction to the selection of party secretaries, deputy secretaries, presidents and vice presidents in leading…

Analyzing locomotion synthesis with feature-based motion graphs.

Science.gov (United States)

Mahmudi, Mentar; Kallmann, Marcelo

2013-05-01

We propose feature-based motion graphs for realistic locomotion synthesis among obstacles. Among several advantages, feature-based motion graphs achieve improved results in search queries, eliminate the need of postprocessing for foot skating removal, and reduce the computational requirements in comparison to traditional motion graphs. Our contributions are threefold. First, we show that choosing transitions based on relevant features significantly reduces graph construction time and leads to improved search performances. Second, we employ a fast channel search method that confines the motion graph search to a free channel with guaranteed clearance among obstacles, achieving faster and improved results that avoid expensive collision checking. Lastly, we present a motion deformation model based on Inverse Kinematics applied over the transitions of a solution branch. Each transition is assigned a continuous deformation range that does not exceed the original transition cost threshold specified by the user for the graph construction. The obtained deformation improves the reachability of the feature-based motion graph and in turn also reduces the time spent during search. The results obtained by the proposed methods are evaluated and quantified, and they demonstrate significant improvements in comparison to traditional motion graph techniques.

Classification Using Markov Blanket for Feature Selection

DEFF Research Database (Denmark)

Zeng, Yifeng; Luo, Jian

2009-01-01

Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

Feature Selection with the Boruta Package

OpenAIRE

Kursa, Miron B.; Rudnicki, Witold R.

2010-01-01

This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

DETERMINATION OF RELEVANT FEATURES OF A SCALE MODEL FOR A 55 000 DWT BULK CARRIER NECESSARY TO STUDY THE SHIP MANEUVERABILITY

Directory of Open Access Journals (Sweden)

ALECU TOMA

2016-06-01

Full Text Available The study method of a ship behavior based on practical tests on scale models is widely used both leading scientists and engineers, architects and researchers in the naval field. In this paper we propose to determine the parameters of a ship handling characteristics relevant to study the 55,000 dwt bulk carrier using a scale model. Scientific background for practical experimentation of this techniques necessary to built a scale model ship consists in applying the principles of similarity or "similitude". The scale model achieved by applying the laws of similarity must allow, through approximations available in certain circumstances, finding relevant parameters needed to simplify and solve the Navier-Stokes equations. These parameters are necessary for modeling the interaction between hull of the real ship and the fluid motion.

DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm

KAUST Repository

Soufan, Othman

2015-02-26

Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem\\'s dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filteringmethods thatmay be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs.

DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm

KAUST Repository

Soufan, Othman; Kleftogiannis, Dimitrios A.; Kalnis, Panos; Bajic, Vladimir B.

2015-01-01

Many scientific problems can be formulated as classification tasks. Data that harbor relevant information are usually described by a large number of features. Frequently, many of these features are irrelevant for the class prediction. The efficient implementation of classification models requires identification of suitable combinations of features. The smaller number of features reduces the problem's dimensionality and may result in higher classification performance. We developed DWFS, a web-based tool that allows for efficient selection of features for a variety of problems. DWFS follows the wrapper paradigm and applies a search strategy based on Genetic Algorithms (GAs). A parallel GA implementation examines and evaluates simultaneously large number of candidate collections of features. DWFS also integrates various filteringmethods thatmay be applied as a pre-processing step in the feature selection process. Furthermore, weights and parameters in the fitness function of GA can be adjusted according to the application requirements. Experiments using heterogeneous datasets from different biomedical applications demonstrate that DWFS is fast and leads to a significant reduction of the number of features without sacrificing performance as compared to several widely used existing methods. DWFS can be accessed online at www.cbrc.kaust.edu.sa/dwfs.

Feature Selection with the Boruta Package

Directory of Open Access Journals (Sweden)

Miron B. Kursa

2010-10-01

Full Text Available This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

Online Capacity Estimation of Lithium-Ion Batteries Based on Novel Feature Extraction and Adaptive Multi-Kernel Relevance Vector Machine

Directory of Open Access Journals (Sweden)

Yang Zhang

2015-11-01

Full Text Available Prognostics is necessary to ensure the reliability and safety of lithium-ion batteries for hybrid electric vehicles or satellites. This process can be achieved by capacity estimation, which is a direct fading indicator for assessing the state of health of a battery. However, the capacity of a lithium-ion battery onboard is difficult to monitor. This paper presents a data-driven approach for online capacity estimation. First, six novel features are extracted from cyclic charge/discharge cycles and used as indirect health indicators. An adaptive multi-kernel relevance machine (MKRVM based on accelerated particle swarm optimization algorithm is used to determine the optimal parameters of MKRVM and characterize the relationship between extracted features and battery capacity. The overall estimation process comprises offline and online stages. A supervised learning step in the offline stage is established for model verification to ensure the generalizability of MKRVM for online application. Cross-validation is further conducted to validate the performance of the proposed model. Experiment and comparison results show the effectiveness, accuracy, efficiency, and robustness of the proposed approach for online capacity estimation of lithium-ion batteries.

Performance of Dower's inverse transform and Frank lead system for Identification of Myocardial Infarction.

Science.gov (United States)

Aranda, A; Bonizzi, P; Karel, J; Peeters, R

2015-08-01

This study performs a comparison between Dower's inverse transform and Frank lead system for Myocardial Infarction (MI) identification. We have selected a set of relevant features for MI detection from the vectorcardiogram and used the lasso method after that to build a model for the Dower's inverse transform and one for the Frank leads system. Then we analyzed the performance between both models on MI detection. The proposed methods have been tested using PhysioNet PTB database that contains 550 records from which 368 are MIs. Two main conclusions are coming from this study. The first one is that Dower's inverse transform performs equally well than Frank leads in identification of MI patients. The second one is that lead positions have a large influence on the accuracy of MI patient identification.

Kernel-Based Relevance Analysis with Enhanced Interpretability for Detection of Brain Activity Patterns

Directory of Open Access Journals (Sweden)

Andres M. Alvarez-Meza

2017-10-01

Full Text Available We introduce Enhanced Kernel-based Relevance Analysis (EKRA that aims to support the automatic identification of brain activity patterns using electroencephalographic recordings. EKRA is a data-driven strategy that incorporates two kernel functions to take advantage of the available joint information, associating neural responses to a given stimulus condition. Regarding this, a Centered Kernel Alignment functional is adjusted to learning the linear projection that best discriminates the input feature set, optimizing the required free parameters automatically. Our approach is carried out in two scenarios: (i feature selection by computing a relevance vector from extracted neural features to facilitating the physiological interpretation of a given brain activity task, and (ii enhanced feature selection to perform an additional transformation of relevant features aiming to improve the overall identification accuracy. Accordingly, we provide an alternative feature relevance analysis strategy that allows improving the system performance while favoring the data interpretability. For the validation purpose, EKRA is tested in two well-known tasks of brain activity: motor imagery discrimination and epileptic seizure detection. The obtained results show that the EKRA approach estimates a relevant representation space extracted from the provided supervised information, emphasizing the salient input features. As a result, our proposal outperforms the state-of-the-art methods regarding brain activity discrimination accuracy with the benefit of enhanced physiological interpretation about the task at hand.

On Feature Relevance in Image-Based Prediction Models: An Empirical Study

DEFF Research Database (Denmark)

Konukoglu, E.; Ganz, Melanie; Van Leemput, Koen

2013-01-01

Determining disease-related variations of the anatomy and function is an important step in better understanding diseases and developing early diagnostic systems. In particular, image-based multivariate prediction models and the “relevant features” they produce are attracting attention from the co...

Users’ attention behaviors and features in internet forum

Directory of Open Access Journals (Sweden)

Yong-Zhong Sha

2015-11-01

Full Text Available Purpose: Attention resource is scarce. Organizing community activities in online forums faces the challenge of attracting users’ limited attention. Understanding how users of online forums allocate, maintain, and change their attentional focus and what features of online forms influence their attention behaviors is critical for effective information design. This paper seeks understanding of users’ attention behaviors and features when they participate in discussions in online forums. Design/methodology/approach: A conceptual model was established to explore the indicator system of attention’s measurement. The related attention data were collected from Alexa Access Statistics Tool and Katie community. Then this paper computed the correlation coefficient and regression relationship between the indicators of visual attention and cognitive attention. Thereafter this paper analyzed and discussed users’ attention behaviors and features in Internet forum. Findings: Relevant bivariate correlation analysis and regression analysis discovers that Internet forum's attention is mainly as visual attention in users’ early involvement. Attention resources can be transformed. In a deep participation, users’ cognitive attention is more significant. Meanwhile cognitive attention behaviors’ further development will lead to the phenomenon that cognitive attention input is prone to increase faster in the early duration. That means in-depth discussion and interaction are more likely to appear in the early stages of participation. Research limitations/implications: There are some limitations about this study. The indicators are not comprehensive enough because factors affecting the distribution of attention resources in Internet forums are complex. We didn’t distinguish different types of Internet forums when we collected the relevant data. Future research will focus more on how to obtain comprehensive attention data. Originality/value: T his paper

The Improved Relevance Voxel Machine

DEFF Research Database (Denmark)

Ganz, Melanie; Sabuncu, Mert; Van Leemput, Koen

The concept of sparse Bayesian learning has received much attention in the machine learning literature as a means of achieving parsimonious representations of features used in regression and classification. It is an important family of algorithms for sparse signal recovery and compressed sensing....... Hence in its current form it is reminiscent of a greedy forward feature selection algorithm. In this report, we aim to solve the problems of the original RVoxM algorithm in the spirit of [7] (FastRVM).We call the new algorithm Improved Relevance Voxel Machine (IRVoxM). Our contributions...... and enables basis selection from overcomplete dictionaries. One of the trailblazers of Bayesian learning is MacKay who already worked on the topic in his PhD thesis in 1992 [1]. Later on Tipping and Bishop developed the concept of sparse Bayesian learning [2, 3] and Tipping published the Relevance Vector...

Doubly sparse factor models for unifying feature transformation and feature selection

International Nuclear Information System (INIS)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato; Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko

2010-01-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Doubly sparse factor models for unifying feature transformation and feature selection

Energy Technology Data Exchange (ETDEWEB)

Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato [ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama (Japan); Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko, E-mail: okada@k.u-tokyo.ac.j [Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki (Japan)

2010-06-01

A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

Overproduction of Upper-Layer Neurons in the Neocortex Leads to Autism-like Features in Mice

Directory of Open Access Journals (Sweden)

Wei-Qun Fang

2014-12-01

Full Text Available Summary: The functional integrity of the neocortex depends upon proper numbers of excitatory and inhibitory neurons; however, the consequences of dysregulated neuronal production during the development of the neocortex are unclear. As excess cortical neurons are linked to the neurodevelopmental disorder autism, we investigated whether the overproduction of neurons leads to neocortical malformation and malfunction in mice. We experimentally increased the number of pyramidal neurons in the upper neocortical layers by using the small molecule XAV939 to expand the intermediate progenitor population. The resultant overpopulation of neurons perturbs development of dendrites and spines of excitatory neurons and alters the laminar distribution of interneurons. Furthermore, these phenotypic changes are accompanied by dysregulated excitatory and inhibitory synaptic connection and balance. Importantly, these mice exhibit behavioral abnormalities resembling those of human autism. Thus, our findings collectively suggest a causal relationship between neuronal overproduction and autism-like features, providing developmental insights into the etiology of autism. : Fang et al. generated a mouse model with excessive excitatory neurons in the neocortex by manipulating embryonic neurogenesis. Overproduction of neurons results in autism-like anatomical and behavioral features. These findings suggest a causal relationship between overproduction of neurons and cortical malfunction and provide developmental insights into the etiology of autism.

Dietary lead intakes for mother/child pairs and relevance to pharmacokinetic models.

Science.gov (United States)

Gulson, B L; Mahaffey, K R; Vidal, M; Jameson, C W; Law, A J; Mizon, K J; Smith, A J; Korsch, M J

1997-12-01

Blood and environmental samples, including a quarterly 6-day duplicate diet, for nine mother/child pairs from Eastern Europe have been monitored for 12 to >24 months with high precision stable lead isotope analysis to evaluate the changes that occur when the subjects moved from one environment (Eastern Europe) to another with different stable lead isotopes (Australia). The children were between 6 and 11 years of age and the mothers were between 29 and 37 years of age. These data were compared with an Australian control mother/child pair, aged 31 and 6 years, respectively. A rationale for undertaking this study of mother/child pairs was to evaluate if there were differences in the patterns and clearance rates of lead from blood in children compared with their mothers. Blood lead concentrations ranged from 2.1 to 3.9 microg/dl in the children and between 1.8 and 4.5 microg/dl in the mothers, but the mean of differences between each mother and her child did not differ significantly from zero. Duplicate diets contained from 2.4 to 31.8 microg Pb/kg diet; the mean+/- standard deviation was 5.5 +/- 2.1 microg Pb/kg and total daily dietary intakes ranged from 1.6 to 21.3 microg/day. Mean daily dietary intakes relative to body weight showed that the intake for children was approximately double that for the mothers (0.218 vs. 0. 113 microg Pb/kg body weight/day). The correlations between blood lead concentration and mean daily dietary intake either relative to body weight or total dietary intake did not reach statistical significance (p>0.05). Estimation of the lead coming from skeletal (endogenous) sources relative to the contribution from environmental (exogenous) sources ranges from 8 to 70% for the mothers and 12 to 66% for the children. The difference between mothers and children is not statistically significant (p = 0.28). The children do not appear to achieve the Australian lead isotopic profile at a faster rate than their mothers. These data provide evidence that

On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

Directory of Open Access Journals (Sweden)

Julien Becker

Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

Learning about the internal structure of categories through classification and feature inference.

Science.gov (United States)

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

Long range correlations, leading particle spectrum and correlations with leading particles

International Nuclear Information System (INIS)

Ilgenfritz, E.M.

1976-05-01

The unitary cluster emission model by de Groot and Ruijgrok is discussed as an approach to understand the leading particle behaviour. Consequences of the model concerning co--rrelations between leading particles and produced particles in the central region are considered. No satisfactory agreement was found. Production of leading clusters is argued for being an essential feature of these correlations. (author)

Feature Selection via Chaotic Antlion Optimization.

Directory of Open Access Journals (Sweden)

Hossam M Zawbaa

Full Text Available Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting while minimizing the number of features used.We propose an optimization approach for the feature selection problem that considers a "chaotic" version of the antlion optimizer method, a nature-inspired algorithm that mimics the hunting mechanism of antlions in nature. The balance between exploration of the search space and exploitation of the best solutions is a challenge in multi-objective optimization. The exploration/exploitation rate is controlled by the parameter I that limits the random walk range of the ants/prey. This variable is increased iteratively in a quasi-linear manner to decrease the exploration rate as the optimization progresses. The quasi-linear decrease in the variable I may lead to immature convergence in some cases and trapping in local minima in other cases. The chaotic system proposed here attempts to improve the tradeoff between exploration and exploitation. The methodology is evaluated using different chaotic maps on a number of feature selection datasets. To ensure generality, we used ten biological datasets, but we also used other types of data from various sources. The results are compared with the particle swarm optimizer and with genetic algorithm variants for feature selection using a set of quality metrics.

Relevance Feedback in Content Based Image Retrieval: A Review

Directory of Open Access Journals (Sweden)

Manesh B. Kokare

2011-01-01

Full Text Available This paper provides an overview of the technical achievements in the research area of relevance feedback (RF in content-based image retrieval (CBIR. Relevance feedback is a powerful technique in CBIR systems, in order to improve the performance of CBIR effectively. It is an open research area to the researcher to reduce the semantic gap between low-level features and high level concepts. The paper covers the current state of art of the research in relevance feedback in CBIR, various relevance feedback techniques and issues in relevance feedback are discussed in detail.

Astrophysical relevance of γ transition energies

International Nuclear Information System (INIS)

Rauscher, Thomas

2008-01-01

The relevant γ energy range is explicitly identified where additional γ strength must be located to have an impact on astrophysically relevant reactions. It is shown that folding the energy dependences of the transmission coefficients and the level density leads to maximal contributions for γ energies of 2≤E γ ≤4 unless quantum selection rules allow isolated states to contribute. Under this condition, electric dipole transitions dominate. These findings allow us to more accurately judge the relevance of modifications of the γ strength for astrophysics

Relevant Features of a Triethylene Glycol Dimethyl Ether-Based Electrolyte for Application in Lithium Battery.

Science.gov (United States)

Carbone, Lorenzo; Di Lecce, Daniele; Gobet, Mallory; Munoz, Stephen; Devany, Matthew; Greenbaum, Steve; Hassoun, Jusef

2017-05-24

Triethylene glycol dimethyl ether (TREGDME) dissolving lithium trifluoromethanesulfonate (LiCF 3 SO 3 ) is studied as a suitable electrolyte medium for lithium battery. Thermal and rheological characteristics, transport properties of the dissolved species, and the electrochemical behavior in lithium cell represent the most relevant investigated properties of the new electrolyte. The self-diffusion coefficients, the lithium transference numbers, the ionic conductivity, and the ion association degree of the solution are determined by pulse field gradient nuclear magnetic resonance and electrochemical impedance spectroscopy. The study sheds light on the determinant role of the lithium nitrate (LiNO 3 ) addition for allowing cell operation by improving the electrode/electrolyte interfaces and widening the voltage stability window. Accordingly, an electrochemical activation procedure of the Li/LiFePO 4 cell using the upgraded electrolyte leads to the formation of stable interfaces at the electrodes surface as clearly evidenced by cyclic voltammetry, impedance spectroscopy, and ex situ scanning electron microscopy. Therefore, the lithium battery employing the TREGDME-LiCF 3 SO 3 -LiNO 3 solution shows a stable galvanostatic cycling, a high efficiency, and a notable rate capability upon the electrochemical conditions adopted herein.

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

Science.gov (United States)

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.

Feature Vector Construction Method for IRIS Recognition

Science.gov (United States)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

Analysis of respiratory events in obstructive sleep apnea syndrome: Inter-relations and association to simple nocturnal features.

Science.gov (United States)

Ghandeharioun, H; Rezaeitalab, F; Lotfi, R

2016-01-01

This study carefully evaluates the association of different respiration-related events to each other and to simple nocturnal features in obstructive sleep apnea-hypopnea syndrome (OSAS). The events include apneas, hypopneas, respiratory event-related arousals and snores. We conducted a statistical study on 158 adults who underwent polysomnography between July 2012 and May 2014. To monitor relevance, along with linear statistical strategies like analysis of variance and bootstrapping a correlation coefficient standard error, the non-linear method of mutual information is also applied to illuminate vague results of linear techniques. Based on normalized mutual information weights (NMIW), indices of apnea are 1.3 times more relevant to AHI values than those of hypopnea. NMIW for the number of blood oxygen desaturation below 95% is considerable (0.531). The next relevant feature is "respiratory arousals index" with NMIW of 0.501. Snore indices (0.314), and BMI (0.203) take the next place. Based on NMIW values, snoring events are nearly one-third (29.9%) more dependent to hypopneas than RERAs. 1. The more sever the OSAS is, the more frequently the apneic events happen. 2. The association of snore with hypopnea/RERA revealed which is routinely ignored in regression-based OSAS modeling. 3. The statistical dependencies of oximetry features potentially can lead to home-based screening of OSAS. 4. Poor ESS-AHI relevance in the database under study indicates its disability for the OSA diagnosis compared to oximetry. 5. Based on poor RERA-snore/ESS relevance, detailed history of the symptoms plus polysomnography is suggested for accurate diagnosis of RERAs. Copyright © 2015 Sociedade Portuguesa de Pneumologia. Published by Elsevier España, S.L.U. All rights reserved.

An Empirical Study of Wrappers for Feature Subset Selection based on a Parallel Genetic Algorithm: The Multi-Wrapper Model

KAUST Repository

Soufan, Othman

2012-09-01

Feature selection is the first task of any learning approach that is applied in major fields of biomedical, bioinformatics, robotics, natural language processing and social networking. In feature subset selection problem, a search methodology with a proper criterion seeks to find the best subset of features describing data (relevance) and achieving better performance (optimality). Wrapper approaches are feature selection methods which are wrapped around a classification algorithm and use a performance measure to select the best subset of features. We analyze the proper design of the objective function for the wrapper approach and highlight an objective based on several classification algorithms. We compare the wrapper approaches to different feature selection methods based on distance and information based criteria. Significant improvement in performance, computational time, and selection of minimally sized feature subsets is achieved by combining different objectives for the wrapper model. In addition, considering various classification methods in the feature selection process could lead to a global solution of desirable characteristics.

Hardware-efficient robust biometric identification from 0.58 second template and 12 features of limb (Lead I) ECG signal using logistic regression classifier.

Science.gov (United States)

Sahadat, Md Nazmus; Jacobs, Eddie L; Morshed, Bashir I

2014-01-01

The electrocardiogram (ECG), widely known as a cardiac diagnostic signal, has recently been proposed for biometric identification of individuals; however reliability and reproducibility are of research interest. In this paper, we propose a template matching technique with 12 features using logistic regression classifier that achieved high reliability and identification accuracy. Non-invasive ECG signals were captured using our custom-built ambulatory EEG/ECG embedded device (NeuroMonitor). ECG data were collected from healthy subjects (10), between 25-35 years, for 10 seconds per trial. The number of trials from each subject was 10. From each trial, only 0.58 seconds of Lead I ECG data were used as template. Hardware-efficient fiducial point detection technique was implemented for feature extraction. To obtain repeated random sub-sampling validation, data were randomly separated into training and testing sets at a ratio of 80:20. Test data were used to find the classification accuracy. ECG template data with 12 extracted features provided the best performance in terms of accuracy (up to 100%) and processing complexity (computation time of 1.2ms). This work shows that a single limb (Lead I) ECG can robustly identify an individual quickly and reliably with minimal contact and data processing using the proposed algorithm.

Lead pollution: lead content in milk from cows fed on contaminated forages

Energy Technology Data Exchange (ETDEWEB)

Sapetti, C; Arduino, E; Durio, P

1973-01-01

Lead toxicity is reviewed, and the history of the lead poisoning is described. Much of the lead pollution in soil is due to automobile exhaust. Two milk cows were fed forage with added lead acetate. The 20 kg of lead corresponded to 50 ppm, a level that is often found in hays near major highways. The cows milk was then analyzed for lead content. During the first and second phase of administration of lead salts, the milk cows did not show any evident symptoms of intoxication. The lead in the milk did have a marked correlation with the administered lead. The lead doses did not last long enough for chronic symptoms to begin. The dosage of lead in milk, due to the facility of drawing samples and the relevant levels of response, could represent a valid method for diagnosing incipient chronic intoxications.

Relevant feature set estimation with a knock-out strategy and random forests

DEFF Research Database (Denmark)

Ganz, Melanie; Greve, Douglas N; Fischl, Bruce

2015-01-01

unintuitive and difficult to determine. In this article, we propose a novel MVPA method for group analysis of high-dimensional data that overcomes the drawbacks of the current techniques. Our approach explicitly aims to identify all relevant variations using a "knock-out" strategy and the Random Forest...

Specificities of reactor coolant pumps units with lead and lead-bismuth coolant

International Nuclear Information System (INIS)

Beznosov, A.V.; Anotonenkov, M.A.; Bokov, P.A.; Baranova, V.S.; Kustov, M.S.

2009-01-01

The analysis results of impact of lead and lead-bismuth coolants specific properties on the coolants flow features in flow channels of the main and auxiliary circulating pumps are presented. Impossibility of cavitation initiation in flow channels of vane pumps pumping lead and lead-bismuth coolants was demonstrated. The experimental research results of discontinuity of heavy liquid metal coolant column were presented and conditions of gas cavitation initiation in coolant flow were discussed. Invalidity of traditional calculation methods of water and sodium coolants circulation pumps calculations for lead and lead-bismuth coolants circulation pumps was substantiated [ru

A unified framework for image retrieval using keyword and visual features.

Science.gov (United States)

Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

2005-07-01

In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

Streptococcus pyogenes biofilms – formation, biology,and clinical relevance

Directory of Open Access Journals (Sweden)

Tomas eFiedler

2015-02-01

Full Text Available Streptococcus pyogenes (group A streptococci, GAS is an exclusive human bacterial pathogen. The virulence potential of this species is tremendous. Interactions with humans range from asymptomatic carriage over mild and superficial infections of skin and mucosal membranes up to systemic purulent toxic-invasive disease manifestations. Particularly the latter are a severe threat for predisposed patients and lead to significant death tolls worldwide. This places GAS among the most important Gram-positive bacterial pathogens. Many recent reviews have highlighted the GAS repertoire of virulence factors, regulators and regulatory circuits/networks that enable GAS to colonize the host and to deal with all levels of the host immune defense. This covers in vitro and in vivo studies, including animal infection studies based on mice and more relevant, macaque monkeys. It is now appreciated that GAS, like many other bacterial species, do not necessarily exclusively live in a planktonic lifestyle. GAS is capable of microcolony and biofilm formation on host cells and tissues. We are now beginning to understand that this feature significantly contributes to GAS pathogenesis. In this review we will discuss the current knowledge on GAS biofilm formation, the biofilm-phenotype associated virulence factors, regulatory aspects of biofilm formation, the clinical relevance, and finally contemporary treatment regimens and future treatment options.

Distinguishing the relevant features of frequent suicide attempters.

Science.gov (United States)

Lopez-Castroman, Jorge; Perez-Rodriguez, Maria de las Mercedes; Jaussent, Isabelle; Alegria, Analucia A; Artes-Rodriguez, Antonio; Freed, Peter; Guillaume, Sébastien; Jollant, Fabrice; Leiva-Murillo, Jose Miguel; Malafosse, Alain; Oquendo, Maria A; de Prado-Cumplido, Mario; Saiz-Ruiz, Jeronimo; Baca-Garcia, Enrique; Courtet, Philippe

2011-05-01

In spite of the high prevalence of suicide behaviours and the magnitude of the resultant burden, little is known about why individuals reattempt. We aim to investigate the relationships between clinical risk factors and the repetition of suicidal attempts. 1349 suicide attempters were consecutively recruited in the Emergency Room (ER) of two academic hospitals in France and Spain. Patients were extensively assessed and demographic and clinical data obtained. Data mining was used to determine the minimal number of variables that blinded the rest in relation to the number of suicide attempts. Using this set, a probabilistic graph ranking relationships with the target variable was constructed. The most common diagnoses among suicide attempters were affective disorders, followed by anxiety disorders. Risk of frequent suicide attempt was highest among middle-aged subjects, and diminished progressively with advancing age of onset at first attempt. Anxiety disorders significantly increased the risk of presenting frequent suicide attempts. Pathway analysis also indicated that frequent suicide attempts were linked to greater odds for alcohol and substance abuse disorders and more intensive treatment. Novel statistical methods found several clinical features that were associated with a history of frequent suicide attempts. The identified pathways may promote new hypothesis-driven studies of suicide attempts and preventive strategies. Copyright © 2010 Elsevier Ltd. All rights reserved.

Relevance-based control over visual attention is fast and interdependent with stimulus-driven capture

DEFF Research Database (Denmark)

Nordfang, Maria; Bundesen, Claus

2012-01-01

or distractor) was a color singleton, but the probability that the singleton was a target was just the same as the probability that a nonsingleton was a target. Participants showed significant effects of both feature contrast and task relevance. The probability of correctly reporting a singleton target...... that high local feature contrast attracts attention independently of task-relevance. Yet, recent studies have provided evidence that effects of task-irrelevant feature contrast interact with the task-relevance of the object in question (Nordfang, 2011). In a new experiment, display size was kept constant...... was significantly higher than the probability of reporting a nonsingleton target. The probability of correctly reporting a given target also was significantly higher for the displays with 2 targets and 6 distractors than for the 8-target displays, revealing selectivity based on task-relevance. This effect...

Temporal Feature Integration for Music Organisation

DEFF Research Database (Denmark)

Meng, Anders

2006-01-01

This Ph.D. thesis focuses on temporal feature integration for music organisation. Temporal feature integration is the process of combining all the feature vectors of a given time-frame into a single new feature vector in order to capture relevant information in the frame. Several existing methods...... for handling sequences of features are formulated in the temporal feature integration framework. Two datasets for music genre classification have been considered as valid test-beds for music organisation. Human evaluations of these, have been obtained to access the subjectivity on the datasets. Temporal...... ranking' approach is proposed for ranking the short-time features at larger time-scales according to their discriminative power in a music genre classification task. The multivariate AR (MAR) model has been proposed for temporal feature integration. It effectively models local dynamical structure...

On the relevance of sharp gamma-ray features for indirect dark matter searches

International Nuclear Information System (INIS)

Bringmann, Torsten; Calore, Francesca; Weniger, Christoph

2011-06-01

Gamma rays from the annihilation of dark matter particles in the Galactic halo provide a particularly promising means of indirectly detecting dark matter. Here, we demonstrate that pronounced spectral features near the kinematic cutoff at the dark matter particles' mass, which is a generic prediction for most models, can significantly improve the sensitivity of gamma-ray telescopes to dark matter signals. We derive projected limits on such features (including the traditionally looked-for line signals) and show that these can be very efficient in constraining the nature of dark matter. (orig.)

Robust Feature Selection from Microarray Data Based on Cooperative Game Theory and Qualitative Mutual Information

Directory of Open Access Journals (Sweden)

Atiyeh Mortazavi

2016-01-01

Full Text Available High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.

Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval

Directory of Open Access Journals (Sweden)

A. Kushki

2009-02-01

Full Text Available This paper proposes a novel XML-based system for retrieval of presentation slides to address the growing data mining needs in presentation archives for educational and scholarly settings. In particular, contextual information, such as structural and formatting features, is extracted from the open format XML representation of presentation slides. In response to a textual user query, each extracted feature is used to compute a fuzzy relevance score for each slide in the database. The fuzzy scores from the various features are then combined through a hierarchical scheme to generate a single relevance score per slide. Various fusion operators and their properties are examined with respect to their effect on retrieval performance. Experimental results indicate a significant increase in retrieval performance measured in terms of precision-recall. The improvements are attributed to both the incorporation of the contextual features and the hierarchical feature combination scheme.

Dietary lead intakes for mother/child pairs and relevance to pharmacokinetic models.

OpenAIRE

Gulson, B L; Mahaffey, K R; Vidal, M; Jameson, C W; Law, A J; Mizon, K J; Smith, A J; Korsch, M J

1997-01-01

Blood and environmental samples, including a quarterly 6-day duplicate diet, for nine mother/child pairs from Eastern Europe have been monitored for 12 to >24 months with high precision stable lead isotope analysis to evaluate the changes that occur when the subjects moved from one environment (Eastern Europe) to another with different stable lead isotopes (Australia). The children were between 6 and 11 years of age and the mothers were between 29 and 37 years of age. These data were compared...

T-ray relevant frequencies for osteosarcoma classification

Science.gov (United States)

Withayachumnankul, W.; Ferguson, B.; Rainsford, T.; Findlay, D.; Mickan, S. P.; Abbott, D.

2006-01-01

We investigate the classification of the T-ray response of normal human bone cells and human osteosarcoma cells, grown in culture. Given the magnitude and phase responses within a reliable spectral range as features for input vectors, a trained support vector machine can correctly classify the two cell types to some extent. Performance of the support vector machine is deteriorated by the curse of dimensionality, resulting from the comparatively large number of features in the input vectors. Feature subset selection methods are used to select only an optimal number of relevant features for inputs. As a result, an improvement in generalization performance is attainable, and the selected frequencies can be used for further describing different mechanisms of the cells, responding to T-rays. We demonstrate a consistent classification accuracy of 89.6%, while the only one fifth of the original features are retained in the data set.

Brain responses to language-relevant musical features in adolescent cochlear implant users before and after an intensive music training program

DEFF Research Database (Denmark)

Petersen, Bjørn; Weed, Ethan; Hansen, Mads

Brain responses to language-relevant musical features in adolescent cochlear implant users before and after an intensive music training program Petersen B.1,2, Weed E.1,3, Hansen M.1,4, Sørensen S.D.3 , Sandmann P.5 , Vuust P.1,2 1Center of Functionally Integrative Neuroscience, Aarhus University......, rhythm and intensity). Difference waves for the rhythm deviant were analyzed in the time window between 300 and 320 ms. Separate mixed-model ANOVAs were performed for left and right fronto-central electrodes. Paired t-tests were used to analyze the behavioral data. Here we present preliminary analyses...... of ERP responses to the rhythm deviant stimuli and results from a behavioral rhythm discrimination test. For both left and right electrode sites we found a main effect of group, driven by higher mean amplitude in the NH group. There was no main effect of training. Left hemisphere sites showed...

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

Science.gov (United States)

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

2005-01-01

1969 to 2003, 34 years. Simulations are now in widespread use in medical education and medical personnel evaluation. Outcomes research on the use and effectiveness of simulation technology in medical education is scattered, inconsistent and varies widely in methodological rigor and substantive focus. Review and synthesize existing evidence in educational science that addresses the question, 'What are the features and uses of high-fidelity medical simulations that lead to most effective learning?'. The search covered five literature databases (ERIC, MEDLINE, PsycINFO, Web of Science and Timelit) and employed 91 single search terms and concepts and their Boolean combinations. Hand searching, Internet searches and attention to the 'grey literature' were also used. The aim was to perform the most thorough literature search possible of peer-reviewed publications and reports in the unpublished literature that have been judged for academic quality. Four screening criteria were used to reduce the initial pool of 670 journal articles to a focused set of 109 studies: (a) elimination of review articles in favor of empirical studies; (b) use of a simulator as an educational assessment or intervention with learner outcomes measured quantitatively; (c) comparative research, either experimental or quasi-experimental; and (d) research that involves simulation as an educational intervention. Data were extracted systematically from the 109 eligible journal articles by independent coders. Each coder used a standardized data extraction protocol. Qualitative data synthesis and tabular presentation of research methods and outcomes were used. Heterogeneity of research designs, educational interventions, outcome measures and timeframe precluded data synthesis using meta-analysis. Coding accuracy for features of the journal articles is high. The extant quality of the published research is generally weak. The weight of the best available evidence suggests that high-fidelity medical

Demands on attention and the role of response priming in visual discrimination of feature conjunctions.

Science.gov (United States)

Fournier, Lisa R; Herbert, Rhonda J; Farris, Carrie

2004-10-01

This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved

YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

KAUST Repository

Kleftogiannis, Dimitrios A.; Theofilatos, Konstantinos; Likothanassis, Spiros; Mavroudi, Seferina

2015-01-01

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

KAUST Repository

Kleftogiannis, Dimitrios A.

2015-01-23

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise

OpenAIRE

Ahveninen, Jyrki; Hämäläinen, Matti; Jääskeläinen, Iiro P.; Ahlfors, Seppo P.; Huang, Samantha; Lin, Fa-Hsuan; Raij, Tommi; Sams, Mikko; Vasios, Christos E.; Belliveau, John W.

2011-01-01

How can we concentrate on relevant sounds in noisy environments? A “gain model” suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A “tuning model” suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMR...

Optimized maintenance concept of safety relevant valves related to ageing management features in nuclear power plants

International Nuclear Information System (INIS)

Koring, R.

2007-01-01

This paper presents the existing concept in E.ON Kernkraft and its sound application to ageing management issues by focussing on group 2 components such as safety relevant valves. It is demonstrated how the maintenance concept of safety relevant valves is supported by a valve diagnostic system accompanied by an applied procedure to assess the measured results with respect to the required functionality and ageing phenomena. Furthermore this concept has been developed to optimize the existing preventive maintenance of the safety relevant valves by implementing condition oriented aspects derived from the diagnostic results. The main issue of this maintenance concept is to demonstrate the high level of the secured function, reliability and performance of the safety relevant valves within an integrated ageing management. Additionally it offers improvements of all preventive maintenance issues as maintenance periods and the component related volume, spare parts management and costs. (author)

Relevancy of human exposure via house dust to the contaminants lead and asbestos

NARCIS (Netherlands)

Oomen AG; Lijzen JPA; SIR; LER

2004-01-01

The present report addresses the issues whether house dust is likely to contribute substantially to the exposure of humans, in particular for the contaminants lead and asbestos. House dust consists for 30-70% of soil material, indicating that contaminated soil can lead to contaminated house dust. It

Enhanced feature integration in musicians

DEFF Research Database (Denmark)

Hansen, Niels Christian; Højlund, Andreas; Møller, Cecilie

the classical oddball control paradigm which used identical sounds. This novel finding supports the dependent processing hypothesis suggesting that musicians recruit overlapping neural resources facilitating more holistic representations of domain-relevant stimuli. These specialised refinements in predictive......Distinguishing and integrating features of sensory input is essential to human survival and no less paramount in music perception and cognition. Yet, little is known about training-induced plasticity of neural mechanisms for auditory feature integration. This study aimed to contrast the two...

Supervised Variational Relevance Learning, An Analytic Geometric Feature Selection with Applications to Omic Datasets.

Science.gov (United States)

Boareto, Marcelo; Cesar, Jonatas; Leite, Vitor B P; Caticha, Nestor

2015-01-01

We introduce Supervised Variational Relevance Learning (Suvrel), a variational method to determine metric tensors to define distance based similarity in pattern classification, inspired in relevance learning. The variational method is applied to a cost function that penalizes large intraclass distances and favors small interclass distances. We find analytically the metric tensor that minimizes the cost function. Preprocessing the patterns by doing linear transformations using the metric tensor yields a dataset which can be more efficiently classified. We test our methods using publicly available datasets, for some standard classifiers. Among these datasets, two were tested by the MAQC-II project and, even without the use of further preprocessing, our results improve on their performance.

Optimized feature subsets for epileptic seizure prediction studies.

Science.gov (United States)

Direito, Bruno; Ventura, Francisco; Teixeira, César; Dourado, António

2011-01-01

The reduction of the number of EEG features to give as inputs to epilepsy seizure predictors is a needed step towards the development of a transportable device for real-time warning. This paper presents a comparative study of three feature selection methods, based on Support Vector Machines. Minimum-Redundancy Maximum-Relevance, Recursive Feature Elimination, Genetic Algorithms, show that, for three patients of the European Database on Epilepsy, the most important univariate features are related to spectral information and statistical moments.

Lead users' ideas on core features to support physical activity in rheumatoid arthritis: a first step in the development of an internet service using participatory design.

Science.gov (United States)

Revenäs, Åsa; Opava, Christina H; Åsenlöf, Pernilla

2014-03-22

Despite the growing evidence of the benefits of physical activity (PA) in individuals with rheumatoid arthritis (RA), the majority is not physically active enough. An innovative strategy is to engage lead users in the development of PA interventions provided over the internet. The aim was to explore lead users' ideas and prioritization of core features in a future internet service targeting adoption and maintenance of healthy PA in people with RA. Six focus group interviews were performed with a purposively selected sample of 26 individuals with RA. Data were analyzed with qualitative content analysis and quantification of participants' prioritization of most important content. Six categories were identified as core features for a future internet service: up-to-date and evidence-based information and instructions, self-regulation tools, social interaction, personalized set-up, attractive design and content, and access to the internet service. The categories represented four themes, or core aspects, important to consider in the design of the future service: (1) content, (2) customized options, (3) user interface and (4) access and implementation. This is, to the best of our knowledge, the first study involving people with RA in the development of an internet service to support the adoption and maintenance of PA.Participants helped identifying core features and aspects important to consider and further explore during the next phase of development. We hypothesize that involvement of lead users will make transfer from theory to service more adequate and user-friendly and therefore will be an effective mean to facilitate PA behavior change.

Memory for Physical Features of Discourse as a Function of Their Relevance.

Science.gov (United States)

Fisher, Ronald P.; Cuervo, Asela

Memory for sex of the speaker and language of presentation of a spoken message was high and reliably better when the features were instrumental for comprehending the message than when they were not. This suggests that the physical characteristics of an event may be deeply or elaborately encoded when they are meaningful in light of the task…

Zinc and lead detoxifying abilities of humic substances relevant to environmental bacterial species.

Science.gov (United States)

Perelomov, L V; Sarkar, Binoy; Sizova, O I; Chilachava, K B; Shvikin, A Y; Perelomova, I V; Atroshchenko, Y M

2018-04-30

The effect of humic substances (HS) and their different fractions (humic acids (HA) and hymatomelanic acids (HMA)) on the toxicity of zinc and lead to different strains of bacteria was studied. All tested bacteria demonstrated a lower resistance to zinc than lead showing minimum inhibitory concentrations of 0.1 - 0.3mM and 0.3-0.5mM, respectively. The highest resistance to lead was characteristic of Pseudomonas chlororaphis PCL1391 and Rhodococcus RS67, while Pseudomonas chlororaphis PCL1391 showed the greatest resistance to zinc. The combined fractions of HS and HA alone reduced zinc toxicity at all added concentrations of the organic substances (50 - 200mgL -1 ) to all microorganisms, while hymatomelanic acids reduced zinc toxicity to Pseudomonas chlororaphis PCL1391 at 200mgL -1 organic concentration only. The HS fractions imparted similar effects on lead toxicity also. This study demonstrated that heavy metal toxicity to bacteria could be reduced through complexation with HS and their fractions. This was particularly true when the metal-organic complexes held a high stability, and low solubility and bioavailability. Copyright © 2018 Elsevier Inc. All rights reserved.

Feature selection for splice site prediction: A new method using EDA-based feature ranking

Directory of Open Access Journals (Sweden)

Rouzé Pierre

2004-05-01

Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

Sequence features responsible for intron retention in human

Directory of Open Access Journals (Sweden)

Sakabe Noboru

2007-02-01

Full Text Available Abstract Background One of the least common types of alternative splicing is the complete retention of an intron in a mature transcript. Intron retention (IR is believed to be the result of intron, rather than exon, definition associated with failure of the recognition of weak splice sites flanking short introns. Although studies on individual retained introns have been published, few systematic surveys of large amounts of data have been conducted on the mechanisms that lead to IR. Results TTo understand how sequence features are associated with or control IR, and to produce a generalized model that could reveal previously unknown signals that regulate this type of alternative splicing, we partitioned intron retention events observed in human cDNAs into two groups based on the relative abundance of both isoforms and compared relevant features. We found that a higher frequency of IR in human is associated with individual introns that have weaker splice sites, genes with shorter intron lengths, higher expression levels and lower density of both a set of exon splicing silencers (ESSs and the intronic splicing enhancer GGG. Both groups of retained introns presented events conserved in mouse, in which the retained introns were also short and presented weaker splice sites. Conclusion Although our results confirmed that weaker splice sites are associated with IR, they showed that this feature alone cannot explain a non-negligible fraction of events. Our analysis suggests that cis-regulatory elements are likely to play a crucial role in regulating IR and also reveals previously unknown features that seem to influence its occurrence. These results highlight the importance of considering the interplay among these features in the regulation of the relative frequency of IR.

Study on the P-wave feature time course as early predictors of paroxysmal atrial fibrillation

International Nuclear Information System (INIS)

Martínez, Arturo; Alcaraz, Raúl; Rieta, José J

2012-01-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice, increasing the risk of stroke and all-cause mortality. Its mechanisms are poorly understood, thus leading to different theories and controversial interpretation of its behavior. In this respect, it is unknown why AF is self-terminating in certain individuals, which is called paroxysmal AF (PAF), and not in others. Within the context of biomedical signal analysis, predicting the onset of PAF with a reasonable advance has been a clinical challenge in recent years. By predicting arrhythmia onset, the loss of normal sinus rhythm could be addressed by means of preventive treatments, thus minimizing risks for the patients and improving their quality of life. Traditionally, the study of PAF onset has been undertaken through a variety of features characterizing P-wave spatial diversity from the standard 12-lead electrocardiogram (ECG) or from signal-averaged ECGs. However, the variability of features from the P-wave time course before PAF onset has not been exploited yet. This work introduces a new alternative to assess time diversity of the P-wave features from single-lead ECG recordings. Furthermore, the method is able to assess the risk of arrhythmia 1 h before its onset, which is a relevant advance in order to provide clinically useful PAF risk predictors. Results were in agreement with the electrophysiological changes taking place in the atria. Hence, P-wave features presented an increasing variability as PAF onset approximates, thus suggesting intermittently disturbed conduction in the atrial tissue. In addition, high PAF risk prediction accuracy, greater than 90%, has been reached in the two considered scenarios, i.e. discrimination between healthy individuals and PAF patients and between patients far from PAF and close to PAF onset. Nonetheless, more long-term studies have to be analyzed and validated in future works. (paper)

Knowledge-based driver assistance systems traffic situation description and situation feature relevance

CERN Document Server

Huelsen, Michael

2014-01-01

The comprehension of a traffic situation plays a major role in driving a vehicle. Interpretable information forms a basis for future projection, decision making and action performing, such as navigating, maneuvering and driving control. Michael Huelsen provides an ontology-based generic traffic situation description capable of supplying various advanced driver assistance systems with relevant information about the current traffic situation of a vehicle and its environment. These systems are enabled to perform reasonable actions and approach visionary goals such as injury and accident free driv

Real-time hypothesis driven feature extraction on parallel processing architectures

DEFF Research Database (Denmark)

Granmo, O.-C.; Jensen, Finn Verner

2002-01-01

the problem of higher-order feature-content/feature-feature correlation, causally complexly interacting features are identified through Bayesian network d-separation analysis and combined into joint features. When used on a moderately complex object-tracking case, the technique is able to select...... extraction, which selectively extract relevant features one-by-one, have in some cases achieved real-time performance on single processing element architectures. In this paperwe propose a novel technique which combines the above two approaches. Features are selectively extracted in parallelizable sets...

Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.

Science.gov (United States)

Gutta, Sandeep; Cheng, Qi

2016-03-01

Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.

Language identification using excitation source features

CERN Document Server

Rao, K Sreenivasa

2015-01-01

This book discusses the contribution of excitation source information in discriminating language. The authors focus on the excitation source component of speech for enhancement of language identification (LID) performance. Language specific features are extracted using two different modes: (i) Implicit processing of linear prediction (LP) residual and (ii) Explicit parameterization of linear prediction residual. The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual; and in explicit parameterization approach, LP residual signal is processed in spectral domain to extract the relevant language specific features. The authors further extract source features from these modes, which are combined for enhancing the performance of LID systems. The proposed excitation source features are also investigated for LID in background noisy environments. Each chapter of this book provides the motivatio...

LFR safety features through intrinsic negative reactivity feedbacks

International Nuclear Information System (INIS)

Grasso, Giacomo

2012-01-01

The safety of Lead-cooled Fast Reactors can rely on intrinsic features such as: • the impossibility of Lead boiling, hence the unreliability of core (only) voiding; • the buoyancy of Control Rods in Lead, allowing their safe positioning also below the active region. For heightening the safety features of LFRs in safety analyses it could be required to approach the evaluation of the reactivity coefficients from a more physical point of view, including more elementary mechanisms, each one related to the proper driving temperature

Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex.

Science.gov (United States)

Downer, Joshua D; Rapone, Brittany; Verhein, Jessica; O'Connor, Kevin N; Sutter, Mitchell L

2017-05-24

Sensory environments often contain an overwhelming amount of information, with both relevant and irrelevant information competing for neural resources. Feature attention mediates this competition by selecting the sensory features needed to form a coherent percept. How attention affects the activity of populations of neurons to support this process is poorly understood because population coding is typically studied through simulations in which one sensory feature is encoded without competition. Therefore, to study the effects of feature attention on population-based neural coding, investigations must be extended to include stimuli with both relevant and irrelevant features. We measured noise correlations ( r noise ) within small neural populations in primary auditory cortex while rhesus macaques performed a novel feature-selective attention task. We found that the effect of feature-selective attention on r noise depended not only on the population tuning to the attended feature, but also on the tuning to the distractor feature. To attempt to explain how these observed effects might support enhanced perceptual performance, we propose an extension of a simple and influential model in which shifts in r noise can simultaneously enhance the representation of the attended feature while suppressing the distractor. These findings present a novel mechanism by which attention modulates neural populations to support sensory processing in cluttered environments. SIGNIFICANCE STATEMENT Although feature-selective attention constitutes one of the building blocks of listening in natural environments, its neural bases remain obscure. To address this, we developed a novel auditory feature-selective attention task and measured noise correlations ( r noise ) in rhesus macaque A1 during task performance. Unlike previous studies showing that the effect of attention on r noise depends on population tuning to the attended feature, we show that the effect of attention depends on the tuning

Automatic processing of unattended object features by functional connectivity

Directory of Open Access Journals (Sweden)

Katja Martina Mayer

2013-05-01

Full Text Available Observers can selectively attend to object features that are relevant for a task. However, unattended task-irrelevant features may still be processed and possibly integrated with the attended features. This study investigated the neural mechanisms for processing both task-relevant (attended and task-irrelevant (unattended object features. The Garner paradigm was adapted for functional magnetic resonance imaging (fMRI to test whether specific brain areas process the conjunction of features or whether multiple interacting areas are involved in this form of feature integration. Observers attended to shape, colour, or non-rigid motion of novel objects while unattended features changed from trial to trial (change blocks or remained constant (no-change blocks during a given block. This block manipulation allowed us to measure the extent to which unattended features affected neural responses which would reflect the extent to which multiple object features are automatically processed. We did not find Garner interference at the behavioural level. However, we designed the experiment to equate performance across block types so that any fMRI results could not be due solely to differences in task difficulty between change and no-change blocks. Attention to specific features localised several areas known to be involved in object processing. No area showed larger responses on change blocks compared to no-change blocks. However, psychophysiological interaction analyses revealed that several functionally-localised areas showed significant positive interactions with areas in occipito-temporal and frontal areas that depended on block type. Overall, these findings suggest that both regional responses and functional connectivity are crucial for processing multi-featured objects.

An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity

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Yu Wang

2014-01-01

Full Text Available Feature space heterogeneity often exists in many real world data sets so that some features are of different importance for classification over different subsets. Moreover, the pattern of feature space heterogeneity might dynamically change over time as more and more data are accumulated. In this paper, we develop an incremental classification algorithm, Supervised Clustering for Classification with Feature Space Heterogeneity (SCCFSH, to address this problem. In our approach, supervised clustering is implemented to obtain a number of clusters such that samples in each cluster are from the same class. After the removal of outliers, relevance of features in each cluster is calculated based on their variations in this cluster. The feature relevance is incorporated into distance calculation for classification. The main advantage of SCCFSH lies in the fact that it is capable of solving a classification problem with feature space heterogeneity in an incremental way, which is favorable for online classification tasks with continuously changing data. Experimental results on a series of data sets and application to a database marketing problem show the efficiency and effectiveness of the proposed approach.

Integrated techniques to evaluate the features of sedimentary rocks of archaeological areas of Sicily

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Maria Brai

2004-02-01

Full Text Available Sicily includes a great variety of lithologies, giving a high complexity to the geologic landscape. Their prevalent lithology is sedimentary. It is well known that rocks of sedimentary origin, compared with metamorphic and volcanic deposits, can be relatively soft and hence fairly easy to model. Nevertheless, this workability advantage is a drawback for Cultural Heritage applications. In fact, these materials show a high porosity, with pore-size distributions that lead to deterioration through absorption of water. In this paper, several sedimentary rocks used in historical Cultural Heritage items of Sicily, from "Magna Graecia" to nowadays, are classified for mineralogical features, chemical composition, and for porosity. Particularly, some samples collected in quarries relevant to the archaeological sites of 41 Agrigento, Segesta and Selinunte will be considered and characterized using integrated techniques (XRD, XRF, NMR and CT. Data on samples obtained in laboratory will be compared with the relevant values measured in situ on monuments of historical-cultural interest of the quoted archaeological places.

Feature Selection Using Adaboost for Face Expression Recognition

National Research Council Canada - National Science Library

Silapachote, Piyanuch; Karuppiah, Deepak R; Hanson, Allen R

2005-01-01

We propose a classification technique for face expression recognition using AdaBoost that learns by selecting the relevant global and local appearance features with the most discriminating information...

Classifying Written Texts Through Rhythmic Features

NARCIS (Netherlands)

Balint, Mihaela; Dascalu, Mihai; Trausan-Matu, Stefan

2016-01-01

Rhythm analysis of written texts focuses on literary analysis and it mainly considers poetry. In this paper we investigate the relevance of rhythmic features for categorizing texts in prosaic form pertaining to different genres. Our contribution is threefold. First, we define a set of rhythmic

A redundancy-removing feature selection algorithm for nominal data

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Zhihua Li

2015-10-01

Full Text Available No order correlation or similarity metric exists in nominal data, and there will always be more redundancy in a nominal dataset, which means that an efficient mutual information-based nominal-data feature selection method is relatively difficult to find. In this paper, a nominal-data feature selection method based on mutual information without data transformation, called the redundancy-removing more relevance less redundancy algorithm, is proposed. By forming several new information-related definitions and the corresponding computational methods, the proposed method can compute the information-related amount of nominal data directly. Furthermore, by creating a new evaluation function that considers both the relevance and the redundancy globally, the new feature selection method can evaluate the importance of each nominal-data feature. Although the presented feature selection method takes commonly used MIFS-like forms, it is capable of handling high-dimensional datasets without expensive computations. We perform extensive experimental comparisons of the proposed algorithm and other methods using three benchmarking nominal datasets with two different classifiers. The experimental results demonstrate the average advantage of the presented algorithm over the well-known NMIFS algorithm in terms of the feature selection and classification accuracy, which indicates that the proposed method has a promising performance.

The Features of Female Managers' Personality Traits in Organization

Science.gov (United States)

Gabdreeva, Guzel Sh.; Khalfieva, Alisa R.

2016-01-01

The relevance of the "female" management features study is driven by the active penetration of women to management in various fields and the emergence of a new social category "Business-women". The article contains the results of a study aimed to identify the features of personal properties and structure of low-level,…

Soil is an important pathway of human lead exposure.

OpenAIRE

Mielke, H W; Reagan, P L

1998-01-01

This review shows the equal or greater importance of leaded gasoline-contaminated dust compared to lead-based paint to the child lead problem, and that soil lead, resulting from leaded gasoline and pulverized lead-based paint, is at least or more important than lead-based paint (intact and not pulverized) as a pathway of human lead exposure. Because lead-based paint is a high-dose source, the biologically relevant dosage is similar to lead in soil. Both lead-based paint and soil lead are asso...

The relevance of segments reports – measurement methodology

Directory of Open Access Journals (Sweden)

Tomasz Zimnicki

2017-09-01

Full Text Available The segment report is one of the areas of financial statements, and it obliges a company to provide infor-mation about the economic situation in each of its activity areas. The article evaluates the change of segment reporting standards from IAS14R to IFRS8 in the context of feature relevance. It presents the construction of a measure which allows the relevance of segment disclosures to be determined. The created measure was used to study periodical reports published by companies listed on the main market of the Warsaw Stock Exchange from three reporting periods – 2008, 2009 and 2013. Based on the re-search results, it was found that the change of segment reporting standards from IAS14R to IFRS8 in the context of relevance was legitimate.

Applying machine learning and image feature extraction techniques to the problem of cerebral aneurysm rupture

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Steren Chabert

2017-01-01

Full Text Available Cerebral aneurysm is a cerebrovascular disorder characterized by a bulging in a weak area in the wall of an artery that supplies blood to the brain. It is relevant to understand the mechanisms leading to the apparition of aneurysms, their growth and, more important, leading to their rupture. The purpose of this study is to study the impact on aneurysm rupture of the combination of different parameters, instead of focusing on only one factor at a time as is frequently found in the literature, using machine learning and feature extraction techniques. This discussion takes relevance in the context of the complex decision that the physicians have to take to decide which therapy to apply, as each intervention bares its own risks, and implies to use a complex ensemble of resources (human resources, OR, etc. in hospitals always under very high work load. This project has been raised in our actual working team, composed of interventional neuroradiologist, radiologic technologist, informatics engineers and biomedical engineers, from Valparaiso public Hospital, Hospital Carlos van Buren, and from Universidad de Valparaíso – Facultad de Ingeniería and Facultad de Medicina. This team has been working together in the last few years, and is now participating in the implementation of an “interdisciplinary platform for innovation in health”, as part of a bigger project leaded by Universidad de Valparaiso (PMI UVA1402. It is relevant to emphasize that this project is made feasible by the existence of this network between physicians and engineers, and by the existence of data already registered in an orderly manner, structured and recorded in digital format. The present proposal arises from the description in nowadays literature that the actual indicators, whether based on morphological description of the aneurysm, or based on characterization of biomechanical factor or others, these indicators were shown not to provide sufficient information in order

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

Science.gov (United States)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Data driven analysis of rain events: feature extraction, clustering, microphysical /macro physical relationship

Science.gov (United States)

Djallel Dilmi, Mohamed; Mallet, Cécile; Barthes, Laurent; Chazottes, Aymeric

2017-04-01

The study of rain time series records is mainly carried out using rainfall rate or rain accumulation parameters estimated on a fixed integration time (typically 1 min, 1 hour or 1 day). In this study we used the concept of rain event. In fact, the discrete and intermittent natures of rain processes make the definition of some features inadequate when defined on a fixed duration. Long integration times (hour, day) lead to mix rainy and clear air periods in the same sample. Small integration time (seconds, minutes) will lead to noisy data with a great sensibility to detector characteristics. The analysis on the whole rain event instead of individual short duration samples of a fixed duration allows to clarify relationships between features, in particular between macro physical and microphysical ones. This approach allows suppressing the intra-event variability partly due to measurement uncertainties and allows focusing on physical processes. An algorithm based on Genetic Algorithm (GA) and Self Organising Maps (SOM) is developed to obtain a parsimonious characterisation of rain events using a minimal set of variables. The use of self-organizing map (SOM) is justified by the fact that it allows to map a high dimensional data space in a two-dimensional space while preserving as much as possible the initial space topology in an unsupervised way. The obtained SOM allows providing the dependencies between variables and consequently removing redundant variables leading to a minimal subset of only five features (the event duration, the rain rate peak, the rain event depth, the event rain rate standard deviation and the absolute rain rate variation of order 0.5). To confirm relevance of the five selected features the corresponding SOM is analyzed. This analysis shows clearly the existence of relationships between features. It also shows the independence of the inter-event time (IETp) feature or the weak dependence of the Dry percentage in event (Dd%e) feature. This confirms

Feature-specific encoding flexibility in visual working memory.

Directory of Open Access Journals (Sweden)

Aki Kondo

Full Text Available The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location, and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape can be flexibly added to object representations.

Feature-specific encoding flexibility in visual working memory.

Science.gov (United States)

Kondo, Aki; Saiki, Jun

2012-01-01

The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location), and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape) can be flexibly added to object representations.

Gas cooled leads

International Nuclear Information System (INIS)

Shutt, R.P.; Rehak, M.L.; Hornik, K.E.

1993-01-01

The intent of this paper is to cover as completely as possible and in sufficient detail the topics relevant to lead design. The first part identifies the problems associated with lead design, states the mathematical formulation, and shows the results of numerical and analytical solutions. The second part presents the results of a parametric study whose object is to determine the best choice for cooling method, material, and geometry. These findings axe applied in a third part to the design of high-current leads whose end temperatures are determined from the surrounding equipment. It is found that cooling method or improved heat transfer are not critical once good heat exchange is established. The range 5 5 but extends over a large of values. Mass flow needed to prevent thermal runaway varies linearly with current above a given threshold. Below that value, the mass flow is constant with current. Transient analysis shows no evidence of hysteresis. If cooling is interrupted, the mass flow needed to restore the lead to its initially cooled state grows exponentially with the time that the lead was left without cooling

Baltic salmon activates immune relevant genes in fin tissue when responding to Gyrodactylus salaris infection

DEFF Research Database (Denmark)

Kania, Per Walther; Larsen, Thomas Bjerre; Ingerslev, Hans C.

2007-01-01

A series of immune relevant genes are expressed when the Baltic salmon responds on infections with the ectoparasite Gyrodactylus salaris which leads to a decrease of the parasite infection......A series of immune relevant genes are expressed when the Baltic salmon responds on infections with the ectoparasite Gyrodactylus salaris which leads to a decrease of the parasite infection...

Motivation factors for suicidal behavior and their clinical relevance in admitted psychiatric patients.

Directory of Open Access Journals (Sweden)

Naoki Hayashi

Full Text Available Suicidal behavior (SB is a major, worldwide health concern. To date there is limited understanding of the associated motivational aspects which accompany this self-initiated conduct.To develop a method for identifying motivational features associated with SB by studying admitted psychiatric patients, and to examine their clinical relevance.By performing a factor analytic study using data obtained from a patient sample exhibiting high suicidality and a variety of SB methods, Motivations for SB Scale (MSBS was constructed to measure the features. Data included assessments of DSM-IV psychiatric and personality disorders, suicide intent, depressive symptomatology, overt aggression, recent life events (RLEs and methods of SB, collated from structured interviews. Association of identified features with clinical variables was examined by correlation analyses and MANCOVA.Factor analyses elicited a 4-factor solution composed of Interpersonal-testing (IT, Interpersonal-change (IC, Self-renunciation (SR and Self-sustenance (SS. These factors were classified according to two distinctions, namely interpersonal vs. intra-personal directedness, and the level of assumed influence by SB or the relationship to prevailing emotions. Analyses revealed meaningful links between patient features and clinical variables. Interpersonal-motivations (IT and IC were associated with overt aggression, low suicidality and RLE discord or conflict, while SR was associated with depression, high suicidality and RLE separation or death. Borderline personality disorder showed association with IC and SS. When self-strangulation was set as a reference SB method, self-cutting and overdose-taking were linked to IT and SS, respectively.The factors extracted in this study largely corresponded to factors from previous studies, implying that they may be useful in a wider clinical context. The association of these features with SB-related factors suggests that they constitute an integral part

DYNAMIC FEATURE SELECTION FOR WEB USER IDENTIFICATION ON LINGUISTIC AND STYLISTIC FEATURES OF ONLINE TEXTS

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A. A. Vorobeva

2017-01-01

Full Text Available The paper deals with identification and authentication of web users participating in the Internet information processes (based on features of online texts.In digital forensics web user identification based on various linguistic features can be used to discover identity of individuals, criminals or terrorists using the Internet to commit cybercrimes. Internet could be used as a tool in different types of cybercrimes (fraud and identity theft, harassment and anonymous threats, terrorist or extremist statements, distribution of illegal content and information warfare. Linguistic identification of web users is a kind of biometric identification, it can be used to narrow down the suspects, identify a criminal and prosecute him. Feature set includes various linguistic and stylistic features extracted from online texts. We propose dynamic feature selection for each web user identification task. Selection is based on calculating Manhattan distance to k-nearest neighbors (Relief-f algorithm. This approach improves the identification accuracy and minimizes the number of features. Experiments were carried out on several datasets with different level of class imbalance. Experiment results showed that features relevance varies in different set of web users (probable authors of some text; features selection for each set of web users improves identification accuracy by 4% at the average that is approximately 1% higher than with the use of static set of features. The proposed approach is most effective for a small number of training samples (messages per user.

Automatic classification and detection of clinically relevant images for diabetic retinopathy

Science.gov (United States)

Xu, Xinyu; Li, Baoxin

2008-03-01

We proposed a novel approach to automatic classification of Diabetic Retinopathy (DR) images and retrieval of clinically-relevant DR images from a database. Given a query image, our approach first classifies the image into one of the three categories: microaneurysm (MA), neovascularization (NV) and normal, and then it retrieves DR images that are clinically-relevant to the query image from an archival image database. In the classification stage, the query DR images are classified by the Multi-class Multiple-Instance Learning (McMIL) approach, where images are viewed as bags, each of which contains a number of instances corresponding to non-overlapping blocks, and each block is characterized by low-level features including color, texture, histogram of edge directions, and shape. McMIL first learns a collection of instance prototypes for each class that maximizes the Diverse Density function using Expectation- Maximization algorithm. A nonlinear mapping is then defined using the instance prototypes and maps every bag to a point in a new multi-class bag feature space. Finally a multi-class Support Vector Machine is trained in the multi-class bag feature space. In the retrieval stage, we retrieve images from the archival database who bear the same label with the query image, and who are the top K nearest neighbors of the query image in terms of similarity in the multi-class bag feature space. The classification approach achieves high classification accuracy, and the retrieval of clinically-relevant images not only facilitates utilization of the vast amount of hidden diagnostic knowledge in the database, but also improves the efficiency and accuracy of DR lesion diagnosis and assessment.

Designing attractive gamification features for collaborative storytelling websites.

Science.gov (United States)

Hsu, Shang Hwa; Chang, Jen-Wei; Lee, Chun-Chia

2013-06-01

Gamification design is considered as the predictor of collaborative storytelling websites' success. Although aforementioned studies have mentioned a broad range of factors that may influence gamification, they neither depicted the actual design features nor relative attractiveness among them. This study aims to identify attractive gamification features for collaborative storytelling websites. We first constructed a hierarchical system structure of gamification design of collaborative storytelling websites and conducted a focus group interview with eighteen frequent users to identify 35gamification features. After that, this study determined the relative attractiveness of these gamification features by administrating an online survey to 6333 collaborative storytelling websites users. The results indicated that the top 10 most attractive gamification features could account for more than 50% of attractiveness among these 35 gamification features. The feature of unpredictable time pressure is important to website users, yet not revealed in previous relevant studies. Implications of the findings were discussed.

New Perspectives on Rodent Models of Advanced Paternal Age: Relevance to Autism

Directory of Open Access Journals (Sweden)

Claire J Foldi

2011-06-01

Full Text Available Offspring of older fathers have an increased risk of various adverse health outcomes, including autism and schizophrenia. With respect to biological mechanisms for this association, there are many more germline cell divisions in the life history of a sperm relative to that of an oocyte. This leads to more opportunities for copy error mutations in germ cells from older fathers. Evidence also suggests that epigenetic patterning in the sperm from older men is altered. Rodent models provide an experimental platform to examine the association between paternal age and brain development. Several rodent models of advanced paternal age (APA have been published with relevance to intermediate phenotypes related to autism. All four published APA models vary in key features creating a lack of consistency with respect to behavioural phenotypes. A consideration of common phenotypes that emerge from these APA-related mouse models may be informative in the exploration of the molecular and neurobiological correlates of APA.

Stimulus-response correspondence effect as a function of temporal overlap between relevant and irrelevant information processing.

Science.gov (United States)

Wang, Dong-Yuan Debbie; Richard, F Dan; Ray, Brittany

2016-01-01

The stimulus-response correspondence (SRC) effect refers to advantages in performance when stimulus and response correspond in dimensions or features, even if the common features are irrelevant to the task. Previous research indicated that the SRC effect depends on the temporal course of stimulus information processing. The current study investigated how the temporal overlap between relevant and irrelevant stimulus processing influences the SRC effect. In this experiment, the irrelevant stimulus (a previously associated tone) preceded the relevant stimulus (a coloured rectangle). The irrelevant and relevant stimuli onset asynchrony was varied to manipulate the temporal overlap between the irrelevant and relevant stimuli processing. Results indicated that the SRC effect size varied as a quadratic function of the temporal overlap between the relevant stimulus and irrelevant stimulus. This finding extends previous experimental observations that the SRC effect size varies in an increasing or decreasing function with reaction time. The current study demonstrated a quadratic function between effect size and the temporal overlap.

Why relevance theory is relevant for lexicography

DEFF Research Database (Denmark)

Bothma, Theo; Tarp, Sven

2014-01-01

This article starts by providing a brief summary of relevance theory in information science in relation to the function theory of lexicography, explaining the different types of relevance, viz. objective system relevance and the subjective types of relevance, i.e. topical, cognitive, situational...... that is very important for lexicography as well as for information science, viz. functional relevance. Since all lexicographic work is ultimately aimed at satisfying users’ information needs, the article then discusses why the lexicographer should take note of all these types of relevance when planning a new...... dictionary project, identifying new tasks and responsibilities of the modern lexicographer. The article furthermore discusses how relevance theory impacts on teaching dictionary culture and reference skills. By integrating insights from lexicography and information science, the article contributes to new...

Neighbors Based Discriminative Feature Difference Learning for Kinship Verification

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a discriminative feature difference learning method for facial image based kinship verification. To transform feature difference of an image pair to be discriminative for kinship verification, a linear transformation matrix for feature difference between an image pair...... than the commonly used feature concatenation, leading to a low complexity. Furthermore, there is no positive semi-definitive constrain on the transformation matrix while there is in metric learning methods, leading to an easy solution for the transformation matrix. Experimental results on two public...... databases show that the proposed method combined with a SVM classification method outperforms or is comparable to state-of-the-art kinship verification methods. © Springer International Publishing AG, Part of Springer Science+Business Media...

Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram

Directory of Open Access Journals (Sweden)

Jongshill Lee

2012-01-01

Full Text Available We propose a new method for personal identification using the derived vectorcardiogram (dVCG, which is derived from the limb leads electrocardiogram (ECG. The dVCG was calculated from the standard limb leads ECG using the precalculated inverse transform matrix. Twenty-one features were extracted from the dVCG, and some or all of these 21 features were used in support vector machine (SVM learning and in tests. The classification accuracy was 99.53%, which is similar to the previous dVCG analysis using the standard 12-lead ECG. Our experimental results show that it is possible to identify a person by features extracted from a dVCG derived from limb leads only. Hence, only three electrodes have to be attached to the person to be identified, which can reduce the effort required to connect electrodes and calculate the dVCG.

Component Composition Using Feature Models

DEFF Research Database (Denmark)

Eichberg, Michael; Klose, Karl; Mitschke, Ralf

2010-01-01

interface description languages. If this variability is relevant when selecting a matching component then human interaction is required to decide which components can be bound. We propose to use feature models for making this variability explicit and (re-)enabling automatic component binding. In our...... approach, feature models are one part of service specifications. This enables to declaratively specify which service variant is provided by a component. By referring to a service's variation points, a component that requires a specific service can list the requirements on the desired variant. Using...... these specifications, a component environment can then determine if a binding of the components exists that satisfies all requirements. The prototypical environment Columbus demonstrates the feasibility of the approach....

Hydrogen generation comparison between lead-calcium and lead-antimony batteries in nuclear power plant

International Nuclear Information System (INIS)

Zhao Hongjun; Qi Suoni; Shen Yan; Li Jia

2014-01-01

Battery type selection is performed with the help of technical information supplied by vendors, and according to relevant criteria. Analysis and comparison of the hydrogen generation differences between two different lead-acid battery types are carried out through calculation. The analysis result may provide suggestions for battery type selection in nuclear power plant. (authors)

Lecture 1: Experimental evidence for collective and thermal features in heavy ion reactions

International Nuclear Information System (INIS)

Moretto, L.G.

1979-01-01

The set of degrees of freedom playing a relevant role in deep inelastic processes is discussed. General considerations concerning the dynamic regimes prevailing during the nucleus--nucleus interaction lead to interesting conclusions regarding classical and quantal features as well as to the applicability of transport theories. The damping associated with the relative distance coordinate is considered and the evidence for thermal equilibrium between fragments is presented. The role of the E1 mode and of all the other odd isovector modes on the charge distrbution at fixed mass asymmetry is discussed and the posssible evidence for quantal fluctuations is analyzed. The mass asymmetry degree of freedom is considered in terms of the experimental mass distributions. The origin of the two components, deep inelastic and fusion--fission, is explained in terms of different dynamical regimes leading to greatly different interaction times. The rotational degrees of freedom are discussed in terms of γ-ray multiplicities and sequential fission. The problem of angular momentum fractionation along the mass asymmetry coordinate is considered and the depolarization and misalignment of the fragment spins are discussed. 43 references

Personality Features of Motorists

Directory of Open Access Journals (Sweden)

Andrej Justinek

1997-12-01

Full Text Available Justinek tries to answer the question whether or not motorists have specific personality features which predispose them for safe and well-mannered driving. A good driver should have sensory abilities which enable psycho-motor coordiation of a vehicle, intellectual and cognitive features that are important for solving problems in new, unknown situations, and emotional and motivational trails defining a driver's maturity. Justmek advocates the belief that in training future drivers greater attention should be paid to developing these features which are vital for safe driving and appropriate behaviour of drivers in traffic. He also suggests certain learning methods leading to development of the above­ mentioned personality traits. Justinek introduces the notion of the 'philosophy of driving' as an essential educational category in training future drivers.

Hematologic features among anemic Cameroonian pregnant women

African Journals Online (AJOL)

Introduction: iron deficiency anemia is the leading cause of anemia worldwide. It may also be the leading cause of anemia in pregnancy, although this has not yet been demonstrated in our country. The aim of the study was to describe hematologic features of Cameroonian anemic pregnant women. Methods: this cross ...

Tensor-based Multi-view Feature Selection with Applications to Brain Diseases

Science.gov (United States)

Cao, Bokai; He, Lifang; Kong, Xiangnan; Yu, Philip S.; Hao, Zhifeng; Ragin, Ann B.

2015-01-01

In the era of big data, we can easily access information from multiple views which may be obtained from different sources or feature subsets. Generally, different views provide complementary information for learning tasks. Thus, multi-view learning can facilitate the learning process and is prevalent in a wide range of application domains. For example, in medical science, measurements from a series of medical examinations are documented for each subject, including clinical, imaging, immunologic, serologic and cognitive measures which are obtained from multiple sources. Specifically, for brain diagnosis, we can have different quantitative analysis which can be seen as different feature subsets of a subject. It is desirable to combine all these features in an effective way for disease diagnosis. However, some measurements from less relevant medical examinations can introduce irrelevant information which can even be exaggerated after view combinations. Feature selection should therefore be incorporated in the process of multi-view learning. In this paper, we explore tensor product to bring different views together in a joint space, and present a dual method of tensor-based multi-view feature selection (dual-Tmfs) based on the idea of support vector machine recursive feature elimination. Experiments conducted on datasets derived from neurological disorder demonstrate the features selected by our proposed method yield better classification performance and are relevant to disease diagnosis. PMID:25937823

Determination of lead isotopic composition of airborne particulate matter by ICPMS: implications for lead atmospheric emissions in Canada

International Nuclear Information System (INIS)

Celo, V.; Dabek-Zlotorzynska, E.

2009-01-01

Full text: Quadrupole ICPMS was used for determination of trace metal concentrations and lead isotopic composition in fine particulate matter (PM 2.5 ) collected at selected sites within the Canadian National Air Pollution Surveillance network, from February 2005 to February 2007. High enrichment factors indicated that lead is mostly of anthropogenic origin and consequently, the lead isotopic composition is directly related to that of pollution sources. The 206 Pb/ 207 Pb and 208 Pb/ 207 Pb ratios were measured and the results were compared to the isotopic signatures of lead from different sources. Various approaches were used to assess the impact of relevant sources and the meteorological conditions in the occurrence and distribution of lead in Canadian atmospheric aerosols. (author)

Environmental Assessment of Lead at Camp Edwards, Massachusetts, Small Arms Ranges

National Research Council Canada - National Science Library

Clausen, Jay L; Korte, Nic; Bostick, Benjamin; Rice, Benjamin; Walsh, Matthew; Nelson, Andrew

2007-01-01

... has or will result in lead mobilization to groundwater. A review of relevant literature and case studies demonstrates lead is toxic to humans and wildlife and, therefore, exposure must be minimized...

Lead-acid battery technologies fundamentals, materials, and applications

CERN Document Server

Jung, Joey; Zhang, Jiujun

2015-01-01

Lead-Acid Battery Technologies: Fundamentals, Materials, and Applications offers a systematic and state-of-the-art overview of the materials, system design, and related issues for the development of lead-acid rechargeable battery technologies. Featuring contributions from leading scientists and engineers in industry and academia, this book:Describes the underlying science involved in the operation of lead-acid batteriesHighlights advances in materials science and engineering for materials fabricationDelivers a detailed discussion of the mathematical modeling of lead-acid batteriesAnalyzes the

NetProt: Complex-based Feature Selection.

Science.gov (United States)

Goh, Wilson Wen Bin; Wong, Limsoon

2017-08-04

Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

Neuron's eye view: Inferring features of complex stimuli from neural responses.

Directory of Open Access Journals (Sweden)

Xin Chen

2017-08-01

Full Text Available Experiments that study neural encoding of stimuli at the level of individual neurons typically choose a small set of features present in the world-contrast and luminance for vision, pitch and intensity for sound-and assemble a stimulus set that systematically varies along these dimensions. Subsequent analysis of neural responses to these stimuli typically focuses on regression models, with experimenter-controlled features as predictors and spike counts or firing rates as responses. Unfortunately, this approach requires knowledge in advance about the relevant features coded by a given population of neurons. For domains as complex as social interaction or natural movement, however, the relevant feature space is poorly understood, and an arbitrary a priori choice of features may give rise to confirmation bias. Here, we present a Bayesian model for exploratory data analysis that is capable of automatically identifying the features present in unstructured stimuli based solely on neuronal responses. Our approach is unique within the class of latent state space models of neural activity in that it assumes that firing rates of neurons are sensitive to multiple discrete time-varying features tied to the stimulus, each of which has Markov (or semi-Markov dynamics. That is, we are modeling neural activity as driven by multiple simultaneous stimulus features rather than intrinsic neural dynamics. We derive a fast variational Bayesian inference algorithm and show that it correctly recovers hidden features in synthetic data, as well as ground-truth stimulus features in a prototypical neural dataset. To demonstrate the utility of the algorithm, we also apply it to cluster neural responses and demonstrate successful recovery of features corresponding to monkeys and faces in the image set.

Involuntary top-down control by search-irrelevant features: Visual working memory biases attention in an object-based manner.

Science.gov (United States)

Foerster, Rebecca M; Schneider, Werner X

2018-03-01

Many everyday tasks involve successive visual-search episodes with changing targets. Converging evidence suggests that these targets are retained in visual working memory (VWM) and bias attention from there. It is unknown whether all or only search-relevant features of a VWM template bias attention during search. Bias signals might be configured exclusively to task-relevant features so that only search-relevant features bias attention. Alternatively, VWM might maintain objects in the form of bound features. Then, all template features will bias attention in an object-based manner, so that biasing effects are ranked by feature relevance. Here, we investigated whether search-irrelevant VWM template features bias attention. Participants had to saccade to a target opposite a distractor. A colored cue depicted the target prior to each search trial. The target was predefined only by its identity, while its color was irrelevant. When target and cue matched not only in identity (search-relevant) but also in color (search-irrelevant), saccades went more often and faster directly to the target than without any color match (Experiment 1). When introducing a cue-distractor color match (Experiment 2), direct target saccades were most likely when target and cue matched in the search-irrelevant color and least likely in case of a cue-distractor color match. When cue and target were never colored the same (Experiment 3), cue-colored distractors still captured the eyes more often than different-colored distractors despite color being search-irrelevant. As participants were informed about the misleading color, the result argues against a strategical and voluntary usage of color. Instead, search-irrelevant features biased attention obligatorily arguing for involuntary top-down control by object-based VWM templates. Copyright © 2017 Elsevier B.V. All rights reserved.

MET overexpression, gene amplification and relevant clinicopathological features in gastric adenocarcinoma.

Science.gov (United States)

Zhang, Jing; Guo, Lei; Liu, Xiuyun; Li, Wenbin; Ying, Jianming

2017-02-07

This study was conducted to investigate the expression of MET in Chinese gastric adenocarcinoma cohort, the correlation between MET overexpression and clinical pathological features, HER2 expression and MET gene amplification. A total of 816 gastric adenocarcinoma patients were included and MET and HER2 immunohistochemical (IHC) staining were performed. IHC and dual-color silver in situ hybridization analysis were performed in the tissue microarrays, constructed from the 240 patients who were randomly selected. MET overexpression (IHC 3+) was observed in 6.0% (49/816) of the cohort. MET overexpression rate was higher in patients with poor prognostic factors, such as clinical stages III/IV (p =0.012) and pathologic stages T3/T4 (p =0.027). The HER2 overexpression (IHC 3+) rate was 8.8% (72/816) and MET overexpression rate was higher in HER2 positive patients (9.7%, 7/72). A high concordance rate (94.6%) between MET overexpression and gene amplification was demonstrated. Therefore, MET overexpression could serve as a prognostic biomarker and a potential therapeutic target for gastric cancer.

Bread crumb classification using fractal and multifractal features

OpenAIRE

Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos

2017-01-01

Adequate image descriptors are fundamental in image classification and object recognition. Main requirements for image features are robustness and low dimensionality which would lead to low classification errors in a variety of situations and with a reasonable computational cost. In this context, the identification of materials poses a significant challenge, since typical (geometric and/or differential) feature extraction methods are not robust enough. Texture features based on Fourier or wav...

The LAILAPS Search Engine: Relevance Ranking in Life Science Databases

Directory of Open Access Journals (Sweden)

Lange Matthias

2010-06-01

Full Text Available Search engines and retrieval systems are popular tools at a life science desktop. The manual inspection of hundreds of database entries, that reflect a life science concept or fact, is a time intensive daily work. Hereby, not the number of query results matters, but the relevance does. In this paper, we present the LAILAPS search engine for life science databases. The concept is to combine a novel feature model for relevance ranking, a machine learning approach to model user relevance profiles, ranking improvement by user feedback tracking and an intuitive and slim web user interface, that estimates relevance rank by tracking user interactions. Queries are formulated as simple keyword lists and will be expanded by synonyms. Supporting a flexible text index and a simple data import format, LAILAPS can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases.

Feature singletons attract spatial attention independently of feature priming.

Science.gov (United States)

Yashar, Amit; White, Alex L; Fang, Wanghaoming; Carrasco, Marisa

2017-08-01

People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial.

Neutronic design for a 100MWth Small modular natural circulation lead or lead-alloy cooled fast reactors core

International Nuclear Information System (INIS)

Chen, C.; Chen, H.; Zhang, H.; Chen, Z.; Zeng, Q.

2015-01-01

Lead or lead-alloy cooled fast reactor with good fuel proliferation and nuclear waste transmutation capability, as well as high security and economy, is a great potential for the development of fourth-generation nuclear energy systems. Small natural circulation reactor is an important technical route lead cooled fast reactors industrial applications, which has been chosen as one of the three reference technical for solution lead or lead-alloy cooled fast reactors by GIF lead-cooled fast reactor steering committee. The School of Nuclear Science and Technology of USTC proposed a small 100MW th natural circulation lead cooled fast reactor concept called SNCLFR-100 based realistic technology. This article describes the SNCLFR-100 reactor of the overall technical program, core physics calculation and analysis. The results show that: SNCLFR-100 with good neutronic and safety performance and relevant design parameters meet the security requirements with feasibility. (author)

Testing the idea of privileged awareness of self-relevant information.

Science.gov (United States)

Stein, Timo; Siebold, Alisha; van Zoest, Wieske

2016-03-01

Self-relevant information is prioritized in processing. Some have suggested the mechanism driving this advantage is akin to the automatic prioritization of physically salient stimuli in information processing (Humphreys & Sui, 2015). Here we investigate whether self-relevant information is prioritized for awareness under continuous flash suppression (CFS), as has been found for physical salience. Gabor patches with different orientations were first associated with the labels You or Other. Participants were more accurate in matching the self-relevant association, replicating previous findings of self-prioritization. However, breakthrough into awareness from CFS did not differ between self- and other-associated Gabors. These findings demonstrate that self-relevant information has no privileged access to awareness. Rather than modulating the initial visual processes that precede and lead to awareness, the advantage of self-relevant information may better be characterized as prioritization at later processing stages. (c) 2016 APA, all rights reserved).

Feature Optimization for Long-Range Visual Homing in Changing Environments

Directory of Open Access Journals (Sweden)

Qidan Zhu

2014-02-01

Full Text Available This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

Permutation importance: a corrected feature importance measure.

Science.gov (United States)

Altmann, André; Toloşi, Laura; Sander, Oliver; Lengauer, Thomas

2010-05-15

In life sciences, interpretability of machine learning models is as important as their prediction accuracy. Linear models are probably the most frequently used methods for assessing feature relevance, despite their relative inflexibility. However, in the past years effective estimators of feature relevance have been derived for highly complex or non-parametric models such as support vector machines and RandomForest (RF) models. Recently, it has been observed that RF models are biased in such a way that categorical variables with a large number of categories are preferred. In this work, we introduce a heuristic for normalizing feature importance measures that can correct the feature importance bias. The method is based on repeated permutations of the outcome vector for estimating the distribution of measured importance for each variable in a non-informative setting. The P-value of the observed importance provides a corrected measure of feature importance. We apply our method to simulated data and demonstrate that (i) non-informative predictors do not receive significant P-values, (ii) informative variables can successfully be recovered among non-informative variables and (iii) P-values computed with permutation importance (PIMP) are very helpful for deciding the significance of variables, and therefore improve model interpretability. Furthermore, PIMP was used to correct RF-based importance measures for two real-world case studies. We propose an improved RF model that uses the significant variables with respect to the PIMP measure and show that its prediction accuracy is superior to that of other existing models. R code for the method presented in this article is available at http://www.mpi-inf.mpg.de/ approximately altmann/download/PIMP.R CONTACT: altmann@mpi-inf.mpg.de, laura.tolosi@mpi-inf.mpg.de Supplementary data are available at Bioinformatics online.

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

Science.gov (United States)

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.

Deaths related to lead poisoning in the United States, 1979-1998

International Nuclear Information System (INIS)

Kaufmann, R.B.; Staes, Catherine J.; Matte, Thomas D.

2003-01-01

This study was conducted to describe trends in US lead poisoning-relate deaths between 1979 and 1998. The predictive value of relevant ICD-9 codes was also evaluated. Multiple cause-of-death files were searched for record containing relevant ICD-9 codes, and underlying causes and demographic characteristics were assessed. For 1979-1988, death certificates were reviewed; lead source information was abstracted and accuracy of coding was determined. An estimated 200 lead poisoning-related deaths occurred from 1979 to 1998. Most were among males (74%), Blacks (67%), adults of age ≥45 years (76%), and Southerners (70%). The death rate was significantly lower in more recent years. An alcohol-related code was a contributing cause for 28% of adults. Only three of nine ICD-9 codes for lead poisoning were highl predictive of lead poisoning-related deaths. In conclusion, lead poisoning-related death rates have dropped dramatically since earlier decades and are continuing to decline. However, the findings imply that moonshine ingestion remains a source of high-dose lead exposure in adults

Lead-Time Models Should Not Be Used to Estimate Overdiagnosis in Cancer Screening

DEFF Research Database (Denmark)

Zahl, Per-Henrik; Jørgensen, Karsten Juhl; Gøtzsche, Peter C

2014-01-01

screening--the excess-incidence approach and the lead-time approach--that rely on two different lead-time definitions. Overdiagnosis when screening with mammography has varied from 0 to 75 %. We have explained that these differences are mainly caused by using different definitions and methods......Lead-time can mean two different things: Clinical lead-time is the lead-time for clinically relevant tumors; that is, those that are not overdiagnosed. Model-based lead-time is a theoretical construct where the time when the tumor would have caused symptoms is not limited by the person's death....... It is the average time at which the diagnosis is brought forward for both clinically relevant and overdiagnosed cancers. When screening for breast cancer, clinical lead-time is about 1 year, while model-based lead-time varies from 2 to 7 years. There are two different methods to calculate overdiagnosis in cancer...

Lack of parvalbumin in mice leads to behavioral deficits relevant to all human autism core symptoms and related neural morphofunctional abnormalities.

Science.gov (United States)

Wöhr, M; Orduz, D; Gregory, P; Moreno, H; Khan, U; Vörckel, K J; Wolfer, D P; Welzl, H; Gall, D; Schiffmann, S N; Schwaller, B

2015-03-10

Gene mutations and gene copy number variants are associated with autism spectrum disorders (ASDs). Affected gene products are often part of signaling networks implicated in synapse formation and/or function leading to alterations in the excitation/inhibition (E/I) balance. Although the network of parvalbumin (PV)-expressing interneurons has gained particular attention in ASD, little is known on PV's putative role with respect to ASD. Genetic mouse models represent powerful translational tools for studying the role of genetic and neurobiological factors underlying ASD. Here, we report that PV knockout mice (PV(-/-)) display behavioral phenotypes with relevance to all three core symptoms present in human ASD patients: abnormal reciprocal social interactions, impairments in communication and repetitive and stereotyped patterns of behavior. PV-depleted mice also showed several signs of ASD-associated comorbidities, such as reduced pain sensitivity and startle responses yet increased seizure susceptibility, whereas no evidence for behavioral phenotypes with relevance to anxiety, depression and schizophrenia was obtained. Reduced social interactions and communication were also observed in heterozygous (PV(+/-)) mice characterized by lower PV expression levels, indicating that merely a decrease in PV levels might be sufficient to elicit core ASD-like deficits. Structural magnetic resonance imaging measurements in PV(-/-) and PV(+/-) mice further revealed ASD-associated developmental neuroanatomical changes, including transient cortical hypertrophy and cerebellar hypoplasia. Electrophysiological experiments finally demonstrated that the E/I balance in these mice is altered by modification of both inhibitory and excitatory synaptic transmission. On the basis of the reported changes in PV expression patterns in several, mostly genetic rodent models of ASD, we propose that in these models downregulation of PV might represent one of the points of convergence, thus providing a

Seeing without knowing: task relevance dissociates between visual awareness and recognition.

Science.gov (United States)

Eitam, Baruch; Shoval, Roy; Yeshurun, Yaffa

2015-03-01

We demonstrate that task relevance dissociates between visual awareness and knowledge activation to create a state of seeing without knowing-visual awareness of familiar stimuli without recognizing them. We rely on the fact that in order to experience a Kanizsa illusion, participants must be aware of its inducers. While people can indicate the orientation of the illusory rectangle with great ease (signifying that they have consciously experienced the illusion's inducers), almost 30% of them could not report the inducers' color. Thus, people can see, in the sense of phenomenally experiencing, but not know, in the sense of recognizing what the object is or activating appropriate knowledge about it. Experiment 2 tests whether relevance-based selection operates within objects and shows that, contrary to the pattern of results found with features of different objects in our previous studies and replicated in Experiment 1, selection does not occur when both relevant and irrelevant features belong to the same object. We discuss these findings in relation to the existing theories of consciousness and to attention and inattentional blindness, and the role of cognitive load, object-based attention, and the use of self-reports as measures of awareness. © 2015 New York Academy of Sciences.

Celluloid angels: a research study of nurses in feature films 1900-2007.

Science.gov (United States)

Stanley, David J

2008-10-01

This paper is a report of a study examining the influence on how nursing and nurses are portrayed in feature films made between 1900 and 2007, with a nurse as their main or a principle character and a story-line related specifically to nursing. Nurses and the nursing profession are frequently portrayed negatively or stereotypically in the media, with nurses often being portrayed as feminine and caring but not as leaders or professionals capable of autonomous practice. A mixed method approach was used to examine feature films made in the Western world. Over 36,000 feature film synopses were reviewed (via CINAHL, ProQuest and relevant movie-specific literature) for the keywords 'nurse'/'nursing'. Identified films were analysed quantitatively to determine their country of production, genre, plot(s) and other relevant data, and qualitatively to identify the emergence of themes related to the image of nurses/nursing in films. For the period from 1900 to 2007, 280 relevant feature films were identified. Most films were made in the United States of America or United Kingdom, although in recent years films have been increasingly produced in other countries. Early films portrayed nurses as self-sacrificial heroines, sex objects and romantics. More recent films increasingly portray them as strong and self-confident, professionals. Nurse-related films offer a unique insight into the image of nurses and how they have been portrayed. Nurses need to be aware of the impact the film industry has on how nurses and nursing are perceived and represented in feature films.

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

Science.gov (United States)

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

2017-09-01

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

Environmental mixtures of nanomaterials and chemicals: The Trojan-horse phenomenon and its relevance for ecotoxicity.

Science.gov (United States)

Naasz, Steffi; Altenburger, Rolf; Kühnel, Dana

2018-04-22

The usage of engineered nanomaterials (NM) offers many novel products and applications with advanced features, but at the same time raises concerns with regard to potential adverse biological effects. Upon release and emission, NM may interact with chemicals in the environment, potentially leading to a co-exposure of organisms and the occurrence of mixture effects. A prominent idea is that NM may act as carriers of chemicals, facilitating and enhancing the entry of substances into cells or organisms, subsequently leading to an increased toxicity. In the literature, the term 'Trojan-horse effect' describes this hypothesis. The relevance of this mechanism for organisms is, however, unclear as yet. Here, a review has been performed to provide a more systematic picture on existing evidence. It includes 151 experimental studies investigating the exposure of various NM and chemical mixtures in ecotoxicological in vitro and in vivo model systems. The papers retrieved comprised studies investigating (i) uptake, (ii) toxicity and (iii) investigations considering both, changes in substance uptake and toxicity upon joint exposure of a chemical with an NM. A closer inspection of the studies demonstrated that the existing evidence for interference of NM-chemical mixture exposure with uptake and toxicity points into different directions compared to the original Trojan-horse hypothesis. We could discriminate at least 7 different categories to capture the evidence ranging from no changes in uptake and toxicity to an increase in uptake and toxicity upon mixture exposure. Concluding recommendations for the consideration of relevant processes are given, including a proposal for a nomenclature to describe NM-chemical mixture interactions in consistent terms. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

[Relevant public health enteropathogens].

Science.gov (United States)

Riveros, Maribel; Ochoa, Theresa J

2015-01-01

Diarrhea remains the third leading cause of death in children under five years, despite recent advances in the management and prevention of this disease. It is caused by multiple pathogens, however, the prevalence of each varies by age group, geographical area and the scenario where cases (community vs hospital) are recorded. The most relevant pathogens in public health are those associated with the highest burden of disease, severity, complications and mortality. In our country, norovirus, Campylobacter and diarrheagenic E. coli are the most prevalent pathogens at the community level in children. In this paper we review the local epidemiology and potential areas of development in five selected pathogens: rotavirus, norovirus, Shiga toxin-producing E. coli (STEC), Shigella and Salmonella. Of these, rotavirus is the most important in the pediatric population and the main agent responsible for child mortality from diarrhea. The introduction of rotavirus vaccination in Peru will have a significant impact on disease burden and mortality from diarrhea. However, surveillance studies are needed to determine the impact of vaccination and changes in the epidemiology of diarrhea in Peru following the introduction of new vaccines, as well as antibiotic resistance surveillance of clinical relevant bacteria.

Framework for the Integration of Mobile Device Features in PLM

OpenAIRE

Hopf, Jens Michael

2016-01-01

Currently, companies have covered their business processes with stationary workstations while mobile business applications have limited relevance. Companies can cover their overall business processes more time-efficiently and cost-effectively when they integrate mobile users in workflows using mobile device features. The objective is a framework that can be used to model and control business applications for PLM processes using mobile device features to allow a totally new user experience.

Case Studies of Leading Edge Small Urban High Schools. Relevance Strategic Designs: 4. Boston Arts Academy

Science.gov (United States)

Shields, Regis Anne; Ireland, Nicole; City, Elizabeth; Derderian, Julie; Miles, Karen Hawley

2008-01-01

This report is one of nine detailed case studies of small urban high schools that served as the foundation for the Education Resource Strategies (ERS) report "Strategic Designs: Lessons from Leading Edge Small Urban High Schools." These nine schools were dubbed "Leading Edge Schools" because they stand apart from other high…

Case Studies of Leading Edge Small Urban High Schools. Relevance Strategic Designs: 6. Perspectives Charter School

Science.gov (United States)

Shields, Regis Anne; Ireland, Nicole; City, Elizabeth; Derderian, Julie; Miles, Karen Hawley

2008-01-01

This report is one of nine detailed case studies of small urban high schools that served as the foundation for the Education Resource Strategies (ERS) report "Strategic Designs: Lessons from Leading Edge Small Urban High Schools." These nine schools were dubbed "Leading Edge Schools" because they stand apart from other high…

Case Studies of Leading Edge Small Urban High Schools. Relevance Strategic Designs: 7. TechBoston Academy

Science.gov (United States)

Shields, Regis Anne; Ireland, Nicole; City, Elizabeth; Derderian, Julie; Miles, Karen Hawley

2008-01-01

This report is one of nine detailed case studies of small urban high schools that served as the foundation for the Education Resource Strategies (ERS) report "Strategic Designs: Lessons from Leading Edge Small Urban High Schools." These nine schools were dubbed "Leading Edge Schools" because they stand apart from other high…

Dynamic binding of visual features by neuronal/stimulus synchrony.

Science.gov (United States)

Iwabuchi, A

1998-05-01

When people see a visual scene, certain parts of the visual scene are treated as belonging together and we regard them as a perceptual unit, which is called a "figure". People focus on figures, and the remaining parts of the scene are disregarded as "ground". In Gestalt psychology this process is called "figure-ground segregation". According to current perceptual psychology, a figure is formed by binding various visual features in a scene, and developments in neuroscience have revealed that there are many feature-encoding neurons, which respond to such features specifically. It is not known, however, how the brain binds different features of an object into a coherent visual object representation. Recently, the theory of binding by neuronal synchrony, which argues that feature binding is dynamically mediated by neuronal synchrony of feature-encoding neurons, has been proposed. This review article portrays the problem of figure-ground segregation and features binding, summarizes neurophysiological and psychophysical experiments and theory relevant to feature binding by neuronal/stimulus synchrony, and suggests possible directions for future research on this topic.

Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism.

Directory of Open Access Journals (Sweden)

Bineng Zhong

Full Text Available To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object, while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object. Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.

Feature selection in classification of eye movements using electrooculography for activity recognition.

Science.gov (United States)

Mala, S; Latha, K

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.

Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms

Directory of Open Access Journals (Sweden)

Shengyun Liang

2015-11-01

Full Text Available The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF data, which was quantified by sample entropy, was collected by foot force sensors. Thirty eight subjects (23 fallers and 15 non-fallers participated in functional movement tests, including walking and sit-to-stand (STS. A feature selection algorithm was used to select relevant features to classify the elderly into two groups: at risk and not at risk of falling down, for three KNN-based classifiers: local mean-based k-nearest neighbor (LMKNN, pseudo nearest neighbor (PNN, local mean pseudo nearest neighbor (LMPNN classification. We compared classification performances, and achieved the best results with LMPNN, with sensitivity, specificity and accuracy all 100%. Moreover, a subset of GRFs was significantly different between the two groups via Wilcoxon rank sum test, which is compatible with the classification results. This method could potentially be used by non-experts to monitor balance and the risk of falling down in the elderly population.

Discriminative semi-supervised feature selection via manifold regularization.

Science.gov (United States)

Xu, Zenglin; King, Irwin; Lyu, Michael Rung-Tsong; Jin, Rong

2010-07-01

Feature selection has attracted a huge amount of interest in both research and application communities of data mining. We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number of labeled samples are usually insufficient for identifying the relevant features, the critical problem arising from semi-supervised feature selection is how to take advantage of the information underneath the unlabeled data. To address this problem, we propose a novel discriminative semi-supervised feature selection method based on the idea of manifold regularization. The proposed approach selects features through maximizing the classification margin between different classes and simultaneously exploiting the geometry of the probability distribution that generates both labeled and unlabeled data. In comparison with previous semi-supervised feature selection algorithms, our proposed semi-supervised feature selection method is an embedded feature selection method and is able to find more discriminative features. We formulate the proposed feature selection method into a convex-concave optimization problem, where the saddle point corresponds to the optimal solution. To find the optimal solution, the level method, a fairly recent optimization method, is employed. We also present a theoretic proof of the convergence rate for the application of the level method to our problem. Empirical evaluation on several benchmark data sets demonstrates the effectiveness of the proposed semi-supervised feature selection method.

The pricing relevance of insider information; Die Preiserheblichkeit von Insiderinformationen

Energy Technology Data Exchange (ETDEWEB)

Kruse, Dominik

2011-07-01

The publication attempts to describe the so far discussion concerning the feature of pricing relevance and to develop it further with the aid of new research approaches. First, a theoretical outline is presented of the elementary regulation problem of insider trading, its historical development, and the regulation goals of the WpHG. This is followed by an analysis of the concrete specifications of the law. In view of the exemplarity of US law, a country with long experience in regulation of the capital market, the materiality doctrine of US insider law is gone into in some detail. The goals and development of the doctrine are reviewed in the light of court rulings. The third part outlines the requirements of German law in order to forecast the pricing relevance of insider information, while the final part presents a critical review of the current regulations on pricing relevance. (orig./RHM)

Enriching science, practice, and policy relevant to school psychology around the globe.

Science.gov (United States)

Jimerson, Shane R

2016-03-01

This editorial provides a brief synthesis of the past, present, and future of School Psychology Quarterly, highlighting important contributions as an international resource to enrich, invigorate, enhance, and advance science, practice, and policy relevant to school psychology around the globe. Information herein highlights (a) the value of high quality and timely reviews, (b) publishing manuscripts that address a breadth of important topics relevant to school psychology, and (c) the structure and contributions of the special topic sections featured in School Psychology Quarterly. (c) 2016 APA, all rights reserved).

Neutronic design for a 100MW{sub th} Small modular natural circulation lead or lead-alloy cooled fast reactors core

Energy Technology Data Exchange (ETDEWEB)

Chen, C.; Chen, H.; Zhang, H.; Chen, Z.; Zeng, Q., E-mail: shchshch@ustc.edu.cn, E-mail: hlchen1@ustc.edu.cn, E-mail: kulah@mail.ustc.edu.cn, E-mail: zchen214@mail.ustc.edu.cn, E-mail: zengqin@ustc.edu.cn [Univ. of Science and Technology of China, School of Nuclear Science and Technology, Hefei, Anhui (China)

2015-07-01

Lead or lead-alloy cooled fast reactor with good fuel proliferation and nuclear waste transmutation capability, as well as high security and economy, is a great potential for the development of fourth-generation nuclear energy systems. Small natural circulation reactor is an important technical route lead cooled fast reactors industrial applications, which has been chosen as one of the three reference technical for solution lead or lead-alloy cooled fast reactors by GIF lead-cooled fast reactor steering committee. The School of Nuclear Science and Technology of USTC proposed a small 100MW{sub th} natural circulation lead cooled fast reactor concept called SNCLFR-100 based realistic technology. This article describes the SNCLFR-100 reactor of the overall technical program, core physics calculation and analysis. The results show that: SNCLFR-100 with good neutronic and safety performance and relevant design parameters meet the security requirements with feasibility. (author)

Reconciling the Rigor-Relevance Dilemma in Intellectual Capital Research

Science.gov (United States)

Andriessen, Daniel

2004-01-01

This paper raises the issue of research methodology for intellectual capital and other types of management research by focusing on the dilemma of rigour versus relevance. The more traditional explanatory approach to research often leads to rigorous results that are not of much help to solve practical problems. This paper describes an alternative…

The relevance and legibility of radio/TV weather reports to the Austrian public

Science.gov (United States)

Keul, A. G.; Holzer, A. M.

2013-03-01

The communicative quality of media weather reports, especially warnings, can be evaluated by user research. It is an interdisciplinary field, still uncoordinated after 35 years. The authors suggest to shift from a cognitive learning model to news processing, qualitative discourse and usability models as the media audience is in an edutainment situation where it acts highly selective. A series of field surveys 2008-2011 tested the relevance and legibility of Austrian radio and television weather reports on fair weather and in warning situations. 247 laypeople heard/saw original, mostly up-to-date radio/TV weather reports and recalled personally relevant data. Also, a questionnaire on weather knowledge was answered by 237 Austrians. Several research hypotheses were tested. The main results were (a) a relatively high level of meteorological knowledge of the general population, with interest and participation of German-speaking migrants, (b) a pluralistic media usage with TV, radio and internet as the leading media, (c) higher interest and attention (also for local weather) after warnings, but a risk of more false recalls after long warnings, (d) more recall problems with radio messages and a wish that the weather elements should always appear in the same order to faciliate processing for the audience. In their narrow time windows, radio/TV weather reports should concentrate on main features (synoptic situation, tomorrow's temperature and precipitation, possible warnings), keep a verbal “speed limit” and restrict show elements to serve the active, selective, multioptional, multicultural audience.

Imaging features of thalassemia

Energy Technology Data Exchange (ETDEWEB)

Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B. [Dept. of Radiology, Istanbul Univ. (Turkey); Dincol, G. [Dept. of Internal Medicine, Istanbul Univ. (Turkey)

1999-07-01

Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of {beta}-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

Imaging features of thalassemia

International Nuclear Information System (INIS)

Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B.; Dincol, G.

1999-01-01

Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of β-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

Mining Specific and General Features in Both Positive and Negative Relevance Feedback. QUT E-Discovery Lab at the TREC󈧍 Relevance Feedback Track

Science.gov (United States)

2009-11-01

relevance feedback algo- rithm. Four methods, εMap [1], MapA , P10A, and StatAP [2], were used in the track to measure the performance of Phase 2 runs...εMap and StatAP were applied to the runs us- ing the testing set of only ClueWeb09 Category-B, whereas MapA and P10A were applied to those using the...whole ClueWeb09 English set. Because our experiments were based on only ClueWeb09 Category-B, measuring our per- formance by MapA and P10A might not

Prediction of protein modification sites of pyrrolidone carboxylic acid using mRMR feature selection and analysis.

Directory of Open Access Journals (Sweden)

Lu-Lu Zheng

Full Text Available Pyrrolidone carboxylic acid (PCA is formed during a common post-translational modification (PTM of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR and incremental feature selection (IFS. We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations.

Feature Selection for Audio Surveillance in Urban Environment

Directory of Open Access Journals (Sweden)

KIKTOVA Eva

2014-05-01

Full Text Available This paper presents the work leading to the acoustic event detection system, which is designed to recognize two types of acoustic events (shot and breaking glass in urban environment. For this purpose, a huge front-end processing was performed for the effective parametric representation of an input sound. MFCC features and features computed during their extraction (MELSPEC and FBANK, then MPEG-7 audio descriptors and other temporal and spectral characteristics were extracted. High dimensional feature sets were created and in the next phase reduced by the mutual information based selection algorithms. Hidden Markov Model based classifier was applied and evaluated by the Viterbi decoding algorithm. Thus very effective feature sets were identified and also the less important features were found.

Prominent feature extraction for review analysis: an empirical study

Science.gov (United States)

Agarwal, Basant; Mittal, Namita

2016-05-01

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

CT Features of pseudo tumoral bronchopulmonary tuberculosis

International Nuclear Information System (INIS)

Zidi, A.; Hantoux, S.; Mestiri, I.; Ben Miled-Mrad, K.

2006-01-01

Pulmonary tuberculosis may at times simulate lung carcinoma on bronchoscopic examination or imaging studies. Diagnosis can be delayed and lead to surgical resection. Based on review of 25 cases, the different CT features are reviewed. (author)

Transforming Big Data into cancer-relevant insight: An initial, multi-tier approach to assess reproducibility and relevance* | Office of Cancer Genomics

Science.gov (United States)

The Cancer Target Discovery and Development (CTD^2) Network was established to accelerate the transformation of "Big Data" into novel pharmacological targets, lead compounds, and biomarkers for rapid translation into improved patient outcomes. It rapidly became clear in this collaborative network that a key central issue was to define what constitutes sufficient computational or experimental evidence to support a biologically or clinically relevant finding.

Recently confirmed apoptosis-inducing lead compounds isolated from marine sponge of potential relevance in cancer treatment

KAUST Repository

Essack, Magbubah; Bajic, Vladimir B.; Archer, John A.C.

2011-01-01

Despite intense efforts to develop non-cytotoxic anticancer treatments, effective agents are still not available. Therefore, novel apoptosis-inducing drug leads that may be developed into effective targeted cancer therapies are of interest to the cancer research community. Targeted cancer therapies affect specific aberrant apoptotic pathways that characterize different cancer types and, for this reason, it is a more desirable type of therapy than chemotherapy or radiotherapy, as it is less harmful to normal cells. In this regard, marine sponge derived metabolites that induce apoptosis continue to be a promising source of new drug leads for cancer treatments. A PubMed query from 01/01/2005 to 31/01/2011 combined with hand-curation of the retrieved articles allowed for the identification of 39 recently confirmed apoptosis-inducing anticancer lead compounds isolated from the marine sponge that are selectively discussed in this review. 2011 by the authors.

Recently confirmed apoptosis-inducing lead compounds isolated from marine sponge of potential relevance in cancer treatment

KAUST Repository

Essack, Magbubah

2011-09-20

Despite intense efforts to develop non-cytotoxic anticancer treatments, effective agents are still not available. Therefore, novel apoptosis-inducing drug leads that may be developed into effective targeted cancer therapies are of interest to the cancer research community. Targeted cancer therapies affect specific aberrant apoptotic pathways that characterize different cancer types and, for this reason, it is a more desirable type of therapy than chemotherapy or radiotherapy, as it is less harmful to normal cells. In this regard, marine sponge derived metabolites that induce apoptosis continue to be a promising source of new drug leads for cancer treatments. A PubMed query from 01/01/2005 to 31/01/2011 combined with hand-curation of the retrieved articles allowed for the identification of 39 recently confirmed apoptosis-inducing anticancer lead compounds isolated from the marine sponge that are selectively discussed in this review. 2011 by the authors.

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory

Directory of Open Access Journals (Sweden)

Sachiko eTakahama

2014-06-01

Full Text Available Information on an object’s features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC, hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS, DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010 demonstrated that the superior parietal lobule (SPL cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding.

Identifying noncoding risk variants using disease-relevant gene regulatory networks.

Science.gov (United States)

Gao, Long; Uzun, Yasin; Gao, Peng; He, Bing; Ma, Xiaoke; Wang, Jiahui; Han, Shizhong; Tan, Kai

2018-02-16

Identifying noncoding risk variants remains a challenging task. Because noncoding variants exert their effects in the context of a gene regulatory network (GRN), we hypothesize that explicit use of disease-relevant GRNs can significantly improve the inference accuracy of noncoding risk variants. We describe Annotation of Regulatory Variants using Integrated Networks (ARVIN), a general computational framework for predicting causal noncoding variants. It employs a set of novel regulatory network-based features, combined with sequence-based features to infer noncoding risk variants. Using known causal variants in gene promoters and enhancers in a number of diseases, we show ARVIN outperforms state-of-the-art methods that use sequence-based features alone. Additional experimental validation using reporter assay further demonstrates the accuracy of ARVIN. Application of ARVIN to seven autoimmune diseases provides a holistic view of the gene subnetwork perturbed by the combinatorial action of the entire set of risk noncoding mutations.

Lead contamination of small mammals from abandoned metalliferous mines

Energy Technology Data Exchange (ETDEWEB)

Roberts, R D [Liverpool Univ.; Johnson, M S; Hutton, M

1978-01-01

Spoil tips associated with abandoned non-ferrous mines contain anomalously high levels of heavy metals compared with other contaminated environments. Little attention has been given to the impact of such contaminated environments on terrestrial ecosystems. In this study, lead in soil, vegetation, ground-living invertebrates and indigenous small mammal populations are reported for two derelict mines in Wales. Small mammal body and tissue lead concentrations were markedly elevated compared with control populations and with published data for other lead-contaminated areas. Oedema, intranuclear inclusion bodies and mitochondrial abnormalities--symptoms of clinical plumbism--were identified in kidney tissue in populations with highest tissue lead concentrations. The results and their relevance to other lead-contaminated areas, including roadside verges, are discussed.

Celluloid devils: a research study of male nurses in feature films.

Science.gov (United States)

Stanley, David

2012-11-01

To report a study of how male nurses are portrayed in feature films. It was hypothesized that male nurses are frequently portrayed negatively or stereotypically in the film media, potentially having a negative impact on male nurse recruitment and the public's perception of male nurses. An interpretive, qualitative methodology guided by insights into hegemonic masculinity and structured around a set of collective case studies (films) was used to examine the portrayal of male nurses in feature films made in the Western world from 1900 to 2007. Over 36,000 feature film synopses were reviewed (via CINAHL, ProQuest and relevant movie-specific literature) for the keyword 'nurse' and 'nursing' with an additional search for films from 1900 to 2010 for the word 'male nurse'. Identified films were labelled as 'cases' and analysed collectively to determine key attributes related to men in nursing and explore them for the emergence of concepts and themes related to the image of male nurses in films. A total of 13 relevant cases (feature films) were identified with 12 being made in the USA. Most films portrayed male nurses negatively and in ways opposed to hegemonic masculinity, as effeminate, homosexual, homicidal, corrupt or incompetent. Few film images of male nurses show them in traditional masculine roles or as clinically competent or self-confident professionals.   Feature films predominantly portray male nurses negatively. Given the popularity of feature films, there may be negative effects on recruitment and on the public's perception of male nurses. © 2012 Blackwell Publishing Ltd.

Currency features for visually impaired people

Science.gov (United States)

Hyland, Sandra L.; Legge, Gordon E.; Shannon, Robert R.; Baer, Norbert S.

1996-03-01

The estimated 3.7 million Americans with low vision experience a uniquely difficult task in identifying the denominations of U.S. banknotes because the notes are remarkably uniform in size, color, and general design. The National Research Council's Committee on Currency Features Usable by the Visually Impaired assessed features that could be used by people who are visually disabled to distinguish currency from other documents and to denominate and authenticate banknotes using available technology. Variation of length and height, introduction of large numerals on a uniform, high-contrast background, use of different colors for each of the six denominations printed, and the introduction of overt denomination codes that could lead to development of effective, low-cost devices for examining banknotes were all deemed features available now. Issues affecting performance, including the science of visual and tactile perception, were addressed for these features, as well as for those features requiring additional research and development. In this group the committee included durable tactile features such as those printed with transparent ink, and the production of currency with holes to indicate denomination. Among long-range approaches considered were the development of technologically advanced devices and smart money.

Using the Characteristics of Documents, Users and Tasks to Predict the Situational Relevance of Health Web Documents

Directory of Open Access Journals (Sweden)

Melinda Oroszlányová

2017-09-01

Full Text Available Relevance is usually estimated by search engines using document content, disregarding the user behind the search and the characteristics of the task. In this work, we look at relevance as framed in a situational context, calling it situational relevance, and analyze whether it is possible to predict it using documents, users and tasks characteristics. Using an existing dataset composed of health web documents, relevance judgments for information needs, user and task characteristics, we build a multivariate prediction model for situational relevance. Our model has an accuracy of 77.17%. Our findings provide insights into features that could improve the estimation of relevance by search engines, helping to conciliate the systemic and situational views of relevance. In a near future we will work on the automatic assessment of document, user and task characteristics.

Synthesis, crystal structures and properties of lead phosphite compounds

International Nuclear Information System (INIS)

Song, Jun-Ling; Hu, Chun-Li; Xu, Xiang; Kong, Fang; Mao, Jiang-Gao

2015-01-01

Here, we report the preparation and characterization of two lead(II) phosphites, namely, Pb_2(HPO_3)_2 and Pb_2(HPO_3)(NO_3)_2 through hydrothermal reaction or simple solution synthesis, respectively. A new lead phosphite, namely, Pb_2(HPO_3)_2, crystallizes in the noncentrosymmetric space group Cmc2_1 (no. 36), which features 3D framework formed by the interconnection of 2D layer of lead(II) phosphites and 1D chain of [Pb(HPO_3)_5]_∞. The nonlinear optical properties of Pb_2(HPO_3)(NO_3)_2 have been studied for the first time. The synergistic effect of the stereo-active lone-pairs on Pb"2"+ cations and π-conjugated NO_3 units in Pb_2(HPO_3)(NO_3)_2 produces a moderate second harmonic generation (SHG) response of ∼1.8×KDP (KH_2PO_4), which is phase matchable (type I). IR, UV–vis spectra and thermogravimetric analysis (TGA) for the two compounds were also measured. - Graphical abstract: Two lead phosphites Pb_2(HPO_3)_2 and Pb_2(HPO_3)(NO_3)_2 are studied. A new lead phosphite Pb_2(HPO_3)_2 features a unique 3D framework structure and Pb_2(HPO_3)(NO_3)_2 shows a moderate SHG response of ∼1.8×KDP (KH_2PO_4). - Highlights: • A new lead phosphite, Pb_2(HPO_3)_2 is reported. • Pb_2(HPO_3)_2 features a unique 3D framework structure. • NLO property of Pb_2(HPO_3)(NO_3)_2 is investigated. • Pb_2(HPO_3)(NO_3)_2 produces a moderate SHG response of ∼1.8×KDP (KH_2PO_4).

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

Science.gov (United States)

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

2017-09-22

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

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods

Directory of Open Access Journals (Sweden)

Kaiyang Qu

2017-09-01

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

Deep learning relevance

DEFF Research Database (Denmark)

Lioma, Christina; Larsen, Birger; Petersen, Casper

2016-01-01

train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

Science.gov (United States)

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Case Studies of Leading Edge Small Urban High Schools. Relevance Strategic Designs: 8. High Tech High School

Science.gov (United States)

Shields, Regis Anne; Ireland, Nicole; City, Elizabeth; Derderian, Julie; Miles, Karen Hawley

2008-01-01

This report is one of nine detailed case studies of small urban high schools that served as the foundation for the Education Resource Strategies (ERS) report "Strategic Designs: Lessons from Leading Edge Small Urban High Schools." These nine schools were dubbed "Leading Edge Schools" because they stand apart from other high…

LANGUAGE EXPERIENCE SHAPES PROCESSING OF PITCH RELEVANT INFORMATION IN THE HUMAN BRAINSTEM AND AUDITORY CORTEX: ELECTROPHYSIOLOGICAL EVIDENCE.

Science.gov (United States)

Krishnan, Ananthanarayan; Gandour, Jackson T

2014-12-01

Pitch is a robust perceptual attribute that plays an important role in speech, language, and music. As such, it provides an analytic window to evaluate how neural activity relevant to pitch undergo transformation from early sensory to later cognitive stages of processing in a well coordinated hierarchical network that is subject to experience-dependent plasticity. We review recent evidence of language experience-dependent effects in pitch processing based on comparisons of native vs. nonnative speakers of a tonal language from electrophysiological recordings in the auditory brainstem and auditory cortex. We present evidence that shows enhanced representation of linguistically-relevant pitch dimensions or features at both the brainstem and cortical levels with a stimulus-dependent preferential activation of the right hemisphere in native speakers of a tone language. We argue that neural representation of pitch-relevant information in the brainstem and early sensory level processing in the auditory cortex is shaped by the perceptual salience of domain-specific features. While both stages of processing are shaped by language experience, neural representations are transformed and fundamentally different at each biological level of abstraction. The representation of pitch relevant information in the brainstem is more fine-grained spectrotemporally as it reflects sustained neural phase-locking to pitch relevant periodicities contained in the stimulus. In contrast, the cortical pitch relevant neural activity reflects primarily a series of transient temporal neural events synchronized to certain temporal attributes of the pitch contour. We argue that experience-dependent enhancement of pitch representation for Chinese listeners most likely reflects an interaction between higher-level cognitive processes and early sensory-level processing to improve representations of behaviorally-relevant features that contribute optimally to perception. It is our view that long

Behind every innovative solution lies an obscure feature

Directory of Open Access Journals (Sweden)

Lee Spector (Fellow ISGEC

2012-06-01

Full Text Available The Obscure Features Hypothesis (OFH for innovation states that a two-step process undergirds almost all innovative solutions: (1 notice an infrequently observed or new (i.e., obscure feature of the problem and (2 construct an interaction involving the obscure feature that produces the desired effects to solve the problem. The OFH leads to a systematic derivation of innovation-enhancing techniques by engaging in two tasks. First, we developed a 32-category system of the types of features possessable by a physical object or material. This Feature Type Taxonomy (FTT provides a panoramic view of the space of features and assists in searches for the obscure ones. Second, we are articulating the many cognitive reasons that obscure features are overlooked and are developing countering techniques for each known reason. We present the implications and techniques of the OFH, as well as indicate how software can assist innovators in the effective use of these innovation-enhancing techniques.

Extraction of auditory features and elicitation of attributes for the assessment of multichannel reproduced sound

DEFF Research Database (Denmark)

Choisel, Sylvain; Wickelmaier, Florian Maria

2006-01-01

), subjects were asked to directly assign verbal labels to the features when encountering them, and to subsequently rate the sounds on the scales thus obtained. The second method required the subjects to consistently use the perceptually relevant features in triadic comparisons, without having to assign them...

Searchers' relevance judgments and criteria in evaluating Web pages in a learning style perspective

DEFF Research Database (Denmark)

Papaeconomou, Chariste; Zijlema, Annemarie F.; Ingwersen, Peter

2008-01-01

The paper presents the results of a case study of searcher's relevance criteria used for assessments of Web pages in a perspective of learning style. 15 test persons participated in the experiments based on two simulated work tasks that provided cover stories to trigger their information needs. Two...... learning styles were examined: Global and Sequential learners. The study applied eye-tracking for the observation of relevance hot spots on Web pages, learning style index analysis and post-search interviews to gain more in-depth information on relevance behavior. Findings reveal that with respect to use......, they are statistically insignificant. When interviewed in retrospective the resulting profiles tend to become even similar across learning styles but a shift occurs from instant assessments with content features of web pages replacing topicality judgments as predominant relevance criteria....

Transcriptomic and genomic features of invasive lobular breast cancer.

Science.gov (United States)

Desmedt, Christine; Zoppoli, Gabriele; Sotiriou, Christos; Salgado, Roberto

2017-06-01

Accounting for 10-15% of all breast neoplasms, invasive lobular breast cancer (ILC) is the second most common histological subtype of breast cancer after invasive ductal breast cancer (IDC). Understanding ILC biology, which differs from IDC in terms of clinical presentation, treatment response, relapse timing and patterns, is essential in order to adopt novel, disease-specific management strategies. While the contribution of the histological subtypes to tumour biology has been poorly investigated and acknowledged in the past, recently several major, independent efforts have led to the assembly and molecular characterization of well-annotated ILC case sets. In this review, we provide a critical overview of the literature exploring ILC, through comprehensive and multiomic methods. The first part specifically focuses on ILC transcriptomic features by reviewing the intrinsic molecular subtypes, the application of gene expression scores for the prediction of recurrence, and the identification of gene expression subtypes. The second part describes the main research efforts that lead to the identification of the genomic landscape of ILC, with a special focus to findings that differentiate ILC from IDC and carry potential clinical relevance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessing environmental features related to mental health: a reliability study of visual streetscape images.

Science.gov (United States)

Wu, Yu-Tzu; Nash, Paul; Barnes, Linda E; Minett, Thais; Matthews, Fiona E; Jones, Andy; Brayne, Carol

2014-10-22

An association between depressive symptoms and features of built environment has been reported in the literature. A remaining research challenge is the development of methods to efficiently capture pertinent environmental features in relevant study settings. Visual streetscape images have been used to replace traditional physical audits and directly observe the built environment of communities. The aim of this work is to examine the inter-method reliability of the two audit methods for assessing community environments with a specific focus on physical features related to mental health. Forty-eight postcodes in urban and rural areas of Cambridgeshire, England were randomly selected from an alphabetical list of streets hosted on a UK property website. The assessment was conducted in July and August 2012 by both physical and visual image audits based on the items in Residential Environment Assessment Tool (REAT), an observational instrument targeting the micro-scale environmental features related to mental health in UK postcodes. The assessor used the images of Google Street View and virtually "walked through" the streets to conduct the property and street level assessments. Gwet's AC1 coefficients and Bland-Altman plots were used to compare the concordance of two audits. The results of conducting the REAT by visual image audits generally correspond to direct observations. More variations were found in property level items regarding physical incivilities, with broad limits of agreement which importantly lead to most of the variation in the overall REAT score. Postcodes in urban areas had lower consistency between the two methods than rural areas. Google Street View has the potential to assess environmental features related to mental health with fair reliability and provide a less resource intense method of assessing community environments than physical audits.

Effects on topic familiarity on online search behaviour and use of relevance criteria

DEFF Research Database (Denmark)

Wen, Lei; Ruthven, Ian; Borlund, Pia

2006-01-01

This paper presents an experimental study on the effect of topic familiarity on the assessment behaviour of online searchers. In particular we investigate the effect of topic familiarity on the resources and relevance criteria used by searchers. Our results indicate that searching on an unfamiliar...... topic leads to use of more generic and fewer specialised resources and that searchers employ different relevance criteria when searching on less familiar topics....

QCD next-to-leading-order predictions matched to parton showers for vector-like quark models.

Science.gov (United States)

Fuks, Benjamin; Shao, Hua-Sheng

2017-01-01

Vector-like quarks are featured by a wealth of beyond the Standard Model theories and are consequently an important goal of many LHC searches for new physics. Those searches, as well as most related phenomenological studies, however, rely on predictions evaluated at the leading-order accuracy in QCD and consider well-defined simplified benchmark scenarios. Adopting an effective bottom-up approach, we compute next-to-leading-order predictions for vector-like-quark pair production and single production in association with jets, with a weak or with a Higgs boson in a general new physics setup. We additionally compute vector-like-quark contributions to the production of a pair of Standard Model bosons at the same level of accuracy. For all processes under consideration, we focus both on total cross sections and on differential distributions, most these calculations being performed for the first time in our field. As a result, our work paves the way to precise extraction of experimental limits on vector-like quarks thanks to an accurate control of the shapes of the relevant observables and emphasise the extra handles that could be provided by novel vector-like-quark probes never envisaged so far.

Altering the trajectory of early postnatal cortical development can lead to structural and behavioural features of autism

Directory of Open Access Journals (Sweden)

Chomiak Taylor

2010-08-01

Full Text Available Abstract Background Autism is a behaviourally defined neurodevelopmental disorder with unknown etiology. Recent studies in autistic children consistently point to neuropathological and functional abnormalities in the temporal association cortex (TeA and its associated structures. It has been proposed that the trajectory of postnatal development in these regions may undergo accelerated maturational alterations that predominantly affect sensory recognition and social interaction. Indeed, the temporal association regions that are important for sensory recognition and social interaction are one of the last regions to mature suggesting a potential vulnerability to early maturation. However, direct evaluation of the emerging hypothesis that an altered time course of early postnatal development can lead to an ASD phenotype remains lacking. Results We used electrophysiological, histological, and behavioural techniques to investigate if the known neuronal maturational promoter valproate, similar to that in culture systems, can influence the normal developmental trajectory of TeA in vivo. Brain sections obtained from postnatal rat pups treated with VPA in vivo revealed that almost 40% of cortical cells in TeA prematurely exhibited adult-like intrinsic electrophysiological properties and that this was often associated with gross cortical hypertrophy and a reduced predisposition for social play behaviour. Conclusions The co-manifestation of these functional, structural and behavioural features suggests that alteration of the developmental time course in certain high-order cortical networks may play an important role in the neurophysiological basis of autism.

Light field morphing using 2D features.

Science.gov (United States)

Wang, Lifeng; Lin, Stephen; Lee, Seungyong; Guo, Baining; Shum, Heung-Yeung

2005-01-01

We present a 2D feature-based technique for morphing 3D objects represented by light fields. Existing light field morphing methods require the user to specify corresponding 3D feature elements to guide morph computation. Since slight errors in 3D specification can lead to significant morphing artifacts, we propose a scheme based on 2D feature elements that is less sensitive to imprecise marking of features. First, 2D features are specified by the user in a number of key views in the source and target light fields. Then the two light fields are warped view by view as guided by the corresponding 2D features. Finally, the two warped light fields are blended together to yield the desired light field morph. Two key issues in light field morphing are feature specification and warping of light field rays. For feature specification, we introduce a user interface for delineating 2D features in key views of a light field, which are automatically interpolated to other views. For ray warping, we describe a 2D technique that accounts for visibility changes and present a comparison to the ideal morphing of light fields. Light field morphing based on 2D features makes it simple to incorporate previous image morphing techniques such as nonuniform blending, as well as to morph between an image and a light field.

Optical Studies on Sol-Gel Derived Lead Chloride Crystals

OpenAIRE

Rejeena, I; Lillibai, B; Nithyaja, B; Nampoori, P.N V; Radhakrishnan, P

2013-01-01

Optical characterization of lead chloride crystals prepared by sol-gel method is reported. The relevant sol-gel technique is used for the preparation of PbCl2 samples with five different types. In this paper, we report the absorption and fluorescence behaviour of pure, UV& IR irradiated and electric & magnetic field applied lead chloride crystal samples in solution phase at two different concentrations. Optical bandgap and emission studies of these crystals are also done.

Introduction: Features of environmental sustainability in agriculture

DEFF Research Database (Denmark)

Dalgaard, Tommy; Ferrari, S; Rambonilaza, M

2006-01-01

This introductive paper aims to address the features of environmental sustainability in agriculture. Recent developments of the concept, which are discussed here, emphasise its multi-faceted nature and lead to various definitions as well as to different implications for policy measures in society...

Urban gardens: lead exposure, recontamination mechanisms, and implications for remediation design.

Science.gov (United States)

Clark, Heather F; Hausladen, Debra M; Brabander, Daniel J

2008-07-01

Environmental lead contamination is prevalent in urban areas where soil represents a significant sink and pathway of exposure. This study characterizes the speciation of lead that is relevant to local recontamination and to human exposure in the backyard gardens of Roxbury and Dorchester, MA, USA. One hundred forty-one backyard gardens were tested by X-ray fluorescence, and 81% of gardens have lead levels above the US EPA action limit of 400 microg/g. Raised gardening beds are the in situ exposure reduction method used in the communities to promote urban gardening. Raised beds were tested for lead and the results showed that the lead concentration increased from an initial range of 150+/-40 microg/g to an average of 336 microg/g over 4 years. The percent distribution of lead in the fine grain soil (lead, and the trace metal signature of the fine grain soil in both gardens and raised gardening beds is characteristic of lead-based paint. This study demonstrates that raised beds are a limited exposure reduction method and require maintenance to achieve exposure reduction goals. An exposure model was developed based on a suite of parameters that combine relevant values from the literature with site-specific quantification of exposure pathways. This model suggests that consumption of homegrown produce accounts for only 3% of children's daily exposure of lead while ingestion of fine grained soil (lead remediation on a yard-by-yard scale requires constant maintenance and that remediation may need to occur on a neighborhood-wide scale.

Subsurface Behavior of Plutonium and Americium at Non-Hanford Sites and Relevance to Hanford

Energy Technology Data Exchange (ETDEWEB)

Cantrell, Kirk J.; Riley, Robert G.

2008-02-01

Seven sites where Pu release to the environment has raised significant environmental concerns have been reviewed. A summary of the most significant hydrologic and geochemical features, contaminant release events and transport processes relevant to Pu migration at the seven sites is presented.

Relevant Sex Appeals in Advertising: Gender and Commitment Context Differences.

Science.gov (United States)

Lanseng, Even J

2016-01-01

This research investigates differences in men's and women's attitudes toward ads featuring product-relevant sex appeals. It is found that women, but not men, were more negative toward an ad featuring an attractive opposite-sex model when their commitment thoughts were heightened. Women were also more negative toward an ad with an attractive same-sex model in the presence of commitment thoughts, but only when they scored high on sociosexuality. Men appeared unaffected, regardless of their level of sociosexuality. Commitment thoughts were manipulated by two types of prime, a parenting prime (study1) and a romantic prime (study 2). Results are explained by differences in how men and women react to sexual material and by differences in men's and women's evolved mating preferences.

Extraction of auditory features and elicitation of attributes for the assessment of multi-channel reproduced sound

DEFF Research Database (Denmark)

Choisel, Sylvain; Wickelmaier, Florian Maria

2005-01-01

), subjects were asked to directly assign verbal labels to the features when encountering them and to subsequently rate the sounds on the scales thus obtained. The second method requires the subjects to consistently identify the perceptually relevant features before assigning them a verbal label. Under...

Extraction of auditory features and elicitation of attributes for the assessment of multi-channel reproduced sound

DEFF Research Database (Denmark)

Choisel, Sylvain; Wickelmaier, Florian

2005-01-01

), subjects were asked to directly assign verbal labels to the features when encountering them, and to subsequently rate the sounds on the scales thus obtained. The second method requires the subjects to consistently identify the perceptually relevant features before assigning them a verbal label. Under...

Clinical Features and Pattern of Presentation of Breast Diseases in ...

African Journals Online (AJOL)

Objective: To characterize the clinical features and pattern of presentation of breast diseases as observed in our practice. Materials and Methods: A prospective study of 121 consecutive patients with breast complaints presenting in our Surgical Outpatient Clinics. The relevant data were collected by two surgeons using the ...

Assessing the relevance of ecotoxicological studies for regulatory decision making.

Science.gov (United States)

Rudén, Christina; Adams, Julie; Ågerstrand, Marlene; Brock, Theo Cm; Poulsen, Veronique; Schlekat, Christian E; Wheeler, James R; Henry, Tala R

2017-07-01

Regulatory policies in many parts of the world recognize either the utility of or the mandate that all available studies be considered in environmental or ecological hazard and risk assessment (ERA) of chemicals, including studies from the peer-reviewed literature. Consequently, a vast array of different studies and data types need to be considered. The first steps in the evaluation process involve determining whether the study is relevant to the ERA and sufficiently reliable. Relevance evaluation is typically performed using existing guidance but involves application of "expert judgment" by risk assessors. In the present paper, we review published guidance for relevance evaluation and, on the basis of the practical experience within the group of authors, we identify additional aspects and further develop already proposed aspects that should be considered when conducting a relevance assessment for ecotoxicological studies. From a regulatory point of view, the overarching key aspect of relevance concerns the ability to directly or indirectly use the study in ERA with the purpose of addressing specific protection goals and ultimately regulatory decision making. Because ERA schemes are based on the appropriate linking of exposure and effect estimates, important features of ecotoxicological studies relate to exposure relevance and biological relevance. Exposure relevance addresses the representativeness of the test substance, environmental exposure media, and exposure regime. Biological relevance deals with the environmental significance of the test organism and the endpoints selected, the ecological realism of the test conditions simulated in the study, as well as a mechanistic link of treatment-related effects for endpoints to the protection goal identified in the ERA. In addition, uncertainties associated with relevance should be considered in the assessment. A systematic and transparent assessment of relevance is needed for regulatory decision making. The relevance

A Method to Measure the Bracelet Based on Feature Energy

Science.gov (United States)

Liu, Hongmin; Li, Lu; Wang, Zhiheng; Huo, Zhanqiang

2017-12-01

To measure the bracelet automatically, a novel method based on feature energy is proposed. Firstly, the morphological method is utilized to preprocess the image, and the contour consisting of a concentric circle is extracted. Then, a feature energy function, which is relevant to the distances from one pixel to the edge points, is defined taking into account the geometric properties of the concentric circle. The input image is subsequently transformed to the feature energy distribution map (FEDM) by computing the feature energy of each pixel. The center of the concentric circle is thus located by detecting the maximum on the FEDM; meanwhile, the radii of the concentric circle are determined according to the feature energy function of the center pixel. Finally, with the use of a calibration template, the internal diameter and thickness of the bracelet are measured. The experimental results show that the proposed method can measure the true sizes of the bracelet accurately with the simplicity, directness and robustness compared to the existing methods.

Audiovisual laughter detection based on temporal features

NARCIS (Netherlands)

Petridis, Stavros; Nijholt, Antinus; Nijholt, A.; Pantic, M.; Pantic, Maja; Poel, Mannes; Poel, M.; Hondorp, G.H.W.

2008-01-01

Previous research on automatic laughter detection has mainly been focused on audio-based detection. In this study we present an audiovisual approach to distinguishing laughter from speech based on temporal features and we show that the integration of audio and visual information leads to improved

Stable lead isotopes and lake sediments. A useful combination for the study of atmospheric lead pollution history

Energy Technology Data Exchange (ETDEWEB)

Renberg, I.; Braennvall, M.-L.; Bindler, R. [Department of Ecology and Environmental Science, Umea University, SE-901 87 Umea (Sweden); Emteryd, O. [Department of Forest Ecology, Swedish University of Agricultural Sciences, SE-901 83 Umea (Sweden)

2002-06-20

Analysis of stable lead isotopes and lead concentrations in lake-sediment deposits, not least in varved (annually-laminated) sediments, is a useful method to study lead pollution history. This paper presents details from a study of 31 lakes in Sweden. Using a strong acid digestion of sediment samples and ICP-MS analyses, we have found that Swedish lake sediments have a high natural (pre-pollution) 206[Pb]/207[Pb] ratio (mean 1.52{+-}0.18, range 1.28-2.01, n=31 lakes). In contrast, atmospheric lead pollution derived from metal smelting processes, coal burning and from alkyl-lead added to petrol has a lower ratio (<1.2). Consequently, when pollution lead deposition began approximately 3500 years ago, the lead isotope ratio of the sediments started to decline, and in modern sediments it is typically <1.2. Using the isotope and concentration values and a mixing model, the relative contribution of pollution and natural lead in sediment samples can be calculated. The pollution lead records of the Swedish lake sediments show a consistent picture of the atmospheric lead pollution history. Some noticeable features are the Roman peak, the large and permanent Medieval increase, peaks at approximately 1200 and 1530 ad, the rapid increase after World War II, the peak in the 1970s, and the large modern decline.

Comparative Study on Feature Selection and Fusion Schemes for Emotion Recognition from Speech

Directory of Open Access Journals (Sweden)

Santiago Planet

2012-09-01

Full Text Available The automatic analysis of speech to detect affective states may improve the way users interact with electronic devices. However, the analysis only at the acoustic level could be not enough to determine the emotion of a user in a realistic scenario. In this paper we analyzed the spontaneous speech recordings of the FAU Aibo Corpus at the acoustic and linguistic levels to extract two sets of features. The acoustic set was reduced by a greedy procedure selecting the most relevant features to optimize the learning stage. We compared two versions of this greedy selection algorithm by performing the search of the relevant features forwards and backwards. We experimented with three classification approaches: Naïve-Bayes, a support vector machine and a logistic model tree, and two fusion schemes: decision-level fusion, merging the hard-decisions of the acoustic and linguistic classifiers by means of a decision tree; and feature-level fusion, concatenating both sets of features before the learning stage. Despite the low performance achieved by the linguistic data, a dramatic improvement was achieved after its combination with the acoustic information, improving the results achieved by this second modality on its own. The results achieved by the classifiers using the parameters merged at feature level outperformed the classification results of the decision-level fusion scheme, despite the simplicity of the scheme. Moreover, the extremely reduced set of acoustic features obtained by the greedy forward search selection algorithm improved the results provided by the full set.

Perceptual and categorical decision making: goal-relevant representation of two domains at different levels of abstraction.

Science.gov (United States)

Shankar, Swetha; Kayser, Andrew S

2017-06-01

To date it has been unclear whether perceptual decision making and rule-based categorization reflect activation of similar cognitive processes and brain regions. On one hand, both map potentially ambiguous stimuli to a smaller set of motor responses. On the other hand, decisions about perceptual salience typically concern concrete sensory representations derived from a noisy stimulus, while categorization is typically conceptualized as an abstract decision about membership in a potentially arbitrary set. Previous work has primarily examined these types of decisions in isolation. Here we independently varied salience in both the perceptual and categorical domains in a random dot-motion framework by manipulating dot-motion coherence and motion direction relative to a category boundary, respectively. Behavioral and modeling results suggest that categorical (more abstract) information, which is more relevant to subjects' decisions, is weighted more strongly than perceptual (more concrete) information, although they also have significant interactive effects on choice. Within the brain, BOLD activity within frontal regions strongly differentiated categorical salience and weakly differentiated perceptual salience; however, the interaction between these two factors activated similar frontoparietal brain networks. Notably, explicitly evaluating feature interactions revealed a frontal-parietal dissociation: parietal activity varied strongly with both features, but frontal activity varied with the combined strength of the information that defined the motor response. Together, these data demonstrate that frontal regions are driven by decision-relevant features and argue that perceptual decisions and rule-based categorization reflect similar cognitive processes and activate similar brain networks to the extent that they define decision-relevant stimulus-response mappings. NEW & NOTEWORTHY Here we study the behavioral and neural dynamics of perceptual categorization when

A Variance Minimization Criterion to Feature Selection Using Laplacian Regularization.

Science.gov (United States)

He, Xiaofei; Ji, Ming; Zhang, Chiyuan; Bao, Hujun

2011-10-01

In many information processing tasks, one is often confronted with very high-dimensional data. Feature selection techniques are designed to find the meaningful feature subset of the original features which can facilitate clustering, classification, and retrieval. In this paper, we consider the feature selection problem in unsupervised learning scenarios, which is particularly difficult due to the absence of class labels that would guide the search for relevant information. Based on Laplacian regularized least squares, which finds a smooth function on the data manifold and minimizes the empirical loss, we propose two novel feature selection algorithms which aim to minimize the expected prediction error of the regularized regression model. Specifically, we select those features such that the size of the parameter covariance matrix of the regularized regression model is minimized. Motivated from experimental design, we use trace and determinant operators to measure the size of the covariance matrix. Efficient computational schemes are also introduced to solve the corresponding optimization problems. Extensive experimental results over various real-life data sets have demonstrated the superiority of the proposed algorithms.

Search asymmetry: a diagnostic for preattentive processing of separable features.

Science.gov (United States)

Treisman, A; Souther, J

1985-09-01

The search rate for a target among distractors may vary dramatically depending on which stimulus plays the role of target and which that of distractors. For example, the time required to find a circle distinguished by an intersecting line is independent of the number of regular circles in the display, whereas the time to find a regular circle among circles with lines increases linearly with the number of distractors. The pattern of performance suggests parallel processing when the target has a unique distinguishing feature and serial self-terminating search when the target is distinguished only by the absence of a feature that is present in all the distractors. The results are consistent with feature-integration theory (Treisman & Gelade, 1980), which predicts that a single feature should be detected by the mere presence of activity in the relevant feature map, whereas tasks that require subjects to locate multiple instances of a feature demand focused attention. Search asymmetries may therefore offer a new diagnostic to identify the primitive features of early vision. Several candidate features are examined in this article: Colors, line ends or terminators, and closure (in the sense of a partly or wholly enclosed area) appear to be functional features; connectedness, intactness (absence of an intersecting line), and acute angles do not.

Optical and luminescent properties of the lead and barium molybdates

Energy Technology Data Exchange (ETDEWEB)

Spassky, D.A. E-mail: dima@opts.phys.msu.ru; Ivanov, S.N.; Kolobanov, V.N.; Mikhailin, V.V.; Zemskov, V.N.; Zadneprovski, B.I.; Potkin, L.I

2004-12-01

Time-resolved luminescence as well as excitation and reflectivity spectra of the oriented lead and barium molybdate single crystals were studied using synchrotron radiation. Features in reflectivity spectra in the fundamental absorption region were analyzed. The contribution of electronic states of lead cation to the formation of the bandgap in PbMoO{sub 4} is supposed. The role of lead states in the intrinsic luminescence of PbMoO{sub 4} is discussed.

Forgotten Features of Head Zones and Their Relation to Diagnostically Relevant Acupuncture Points

Directory of Open Access Journals (Sweden)

Florian Beissner

2011-01-01

Full Text Available In the 1890s Sir Henry Head discovered certain areas of the skin that develop tenderness (allodynia in the course of visceral disease. These areas were later termed “Head zones”. In addition, he also emphasized the existence of specific points within these zones, that he called “maximum points”, a finding that seems to be almost forgotten today. We hypothesized that two important groups of acupuncture points, the diagnostically relevant Mu and Shu points, spatially and functionally coincide with these maximum points to a large extent. A comparison of Head's papers with the Huang Di Neijing (Yellow Thearch's Inner Classic and the Zhen Jiu Jia Yi Jing (Systematic Classic of Acupuncture and Moxibustion, two of the oldest still extant Chinese sources on acupuncture, revealed astonishing parallels between the two concepts regarding both point locations and functional aspects. These findings suggest that the Chinese discovery of viscerocutaneous reflexes preceded the discovery in the West by more than 2000 years. Furthermore, the fact that Chinese medicine uses Mu and Shu points not only diagnostically but also therapeutically may give us new insights into the underlying mechanisms of acupuncture.

A SURVEY OF URBAN PEOPLE AWARENESS ABOUT NEW INDIAN CURRENCY SECURITY FEATURES AFTER DEMONETIZATION

OpenAIRE

Mr. Rajeev & Mr. Dhirender

2017-01-01

Use of currency notes is increasing year by year and so does risk of its holders.It has become need of hour for every country to make its currency difficult to counterfeit.Security features and security printing are the only solution for this problem.Security features not only prevent duplicacyof notes but also save the poor citizens from possible financial loss.This survey work was carried out to understand the awareness level about security features in new currency notes because relevancy o...

Retrospective cues based on object features improve visual working memory performance in older adults.

Science.gov (United States)

Gilchrist, Amanda L; Duarte, Audrey; Verhaeghen, Paul

2016-01-01

Research with younger adults has shown that retrospective cues can be used to orient top-down attention toward relevant items in working memory. We examined whether older adults could take advantage of these cues to improve memory performance. Younger and older adults were presented with visual arrays of five colored shapes; during maintenance, participants were presented either with an informative cue based on an object feature (here, object shape or color) that would be probed, or with an uninformative, neutral cue. Although older adults were less accurate overall, both age groups benefited from the presentation of an informative, feature-based cue relative to a neutral cue. Surprisingly, we also observed differences in the effectiveness of shape versus color cues and their effects upon post-cue memory load. These results suggest that older adults can use top-down attention to remove irrelevant items from visual working memory, provided that task-relevant features function as cues.

Spatiotemporal Features for Asynchronous Event-based Data

Directory of Open Access Journals (Sweden)

Xavier eLagorce

2015-02-01

Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

Discovery and fusion of salient multimodal features toward news story segmentation

Science.gov (United States)

Hsu, Winston; Chang, Shih-Fu; Huang, Chih-Wei; Kennedy, Lyndon; Lin, Ching-Yung; Iyengar, Giridharan

2003-12-01

In this paper, we present our new results in news video story segmentation and classification in the context of TRECVID video retrieval benchmarking event 2003. We applied and extended the Maximum Entropy statistical model to effectively fuse diverse features from multiple levels and modalities, including visual, audio, and text. We have included various features such as motion, face, music/speech types, prosody, and high-level text segmentation information. The statistical fusion model is used to automatically discover relevant features contributing to the detection of story boundaries. One novel aspect of our method is the use of a feature wrapper to address different types of features -- asynchronous, discrete, continuous and delta ones. We also developed several novel features related to prosody. Using the large news video set from the TRECVID 2003 benchmark, we demonstrate satisfactory performance (F1 measures up to 0.76 in ABC news and 0.73 in CNN news), present how these multi-level multi-modal features construct the probabilistic framework, and more importantly observe an interesting opportunity for further improvement.

Natural convection in enclosures containing lead-bismuth and lead

International Nuclear Information System (INIS)

Dzodzo, M.; Cuckovic-Dzodzo, D.

2001-01-01

The design of liquid metal reactors such as Encapsulated Nuclear Heat Source (ENHS) which are based predominantly on the flow generated by natural convection effects demands knowledge of velocity and temperature fields, distribution of the local Nusselt numbers and values of the average Nusselt numbers for small coolant velocity regimes. Laminar natural convection in rectangular enclosures with different aspect ratios, containing lead-bismuth and lead is studied numerically in this paper. The numerical model takes into account variable properties of the liquid metals. The developed correlation for average Nusselt numbers is presented. It is concluded that average Nusselt numbers are lower than in 'normal' fluids (air, water and glycerol) for the same values of Rayleigh numbers. However, the heat flux, which can be achieved, is greater due to the high thermal conductivity of liquid metals. Some specific features of the flow fields generated by natural convection in liquid metals are presented. Their consequences on the design of heat exchangers for liquid metals are discussed. An application of the obtained results to the design of a new type of steam generator, which integrates the intermediate heat exchanger and secondary pool functions of the ENHS reactor, is presented. (authors)

Understanding Legacy Features with Featureous

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...

Mammographic and sonographic features of fat necrosis of the breast

International Nuclear Information System (INIS)

Upadhyaya, Vidya S; Uppoor, Raghuraj; Shetty, Lathika

2013-01-01

Imaging features of fat necrosis vary depending on its stage of evolution and can mimic malignancy in late stages. Imaging may suffice to differentiate fat necrosis in the early stages from malignancy and thus avoid unnecessary biopsy. In this pictorial essay, we present combination of benign features in mammography and/or ultrasonography (USG) that can lead to imaging diagnosis of fat necrosis. The follow-up imaging features of fat necrosis which mirror its pathophysiological evolution have also been demonstrated. To summarize, in the appropriate clinical setting, no mammographic features suspicious for malignancy should be present. When the typical mammographic features are not present, USG can aid with the diagnosis and follow up USG can confirm it

Mass lead intoxication from informal used lead-acid battery recycling in dakar, senegal.

Science.gov (United States)

Haefliger, Pascal; Mathieu-Nolf, Monique; Lociciro, Stephanie; Ndiaye, Cheikh; Coly, Malang; Diouf, Amadou; Faye, Absa Lam; Sow, Aminata; Tempowski, Joanna; Pronczuk, Jenny; Filipe Junior, Antonio Pedro; Bertollini, Roberto; Neira, Maria

2009-10-01

Between November 2007 and March 2008, 18 children died from a rapidly progressive central nervous system disease of unexplained origin in a community involved in the recycling of used lead-acid batteries (ULAB) in the suburbs of Dakar, Senegal. We investigated the cause of these deaths. Because autopsies were not possible, the investigation centered on clinical and laboratory assessments performed on 32 siblings of deceased children and 23 mothers and on 18 children and 8 adults living in the same area, complemented by environmental health investigations. All 81 individuals investigated were poisoned with lead, some of them severely. The blood lead level of the 50 children tested ranged from 39.8 to 613.9 microg/dL with a mean of 129.5 microg/dL. Seventeen children showed severe neurologic features of toxicity. Homes and soil in surrounding areas were heavily contaminated with lead (indoors, up to 14,000 mg/kg; outdoors, up to 302,000 mg/kg) as a result of informal ULAB recycling. Our investigations revealed a mass lead intoxication that occurred through inhalation and ingestion of soil and dust heavily contaminated with lead as a result of informal and unsafe ULAB recycling. Circumstantial evidence suggested that most or all of the 18 deaths were due to encephalopathy resulting from severe lead intoxication. Findings also suggest that most habitants of the contaminated area, estimated at 950, are also likely to be poisoned. This highlights the severe health risks posed by informal ULAB recycling, in particular in developing countries, and emphasizes the need to strengthen national and international efforts to address this global public health problem.

An Empirical Study of Wrappers for Feature Subset Selection based on a Parallel Genetic Algorithm: The Multi-Wrapper Model

KAUST Repository

Soufan, Othman

2012-01-01

proper criterion seeks to find the best subset of features describing data (relevance) and achieving better performance (optimality). Wrapper approaches are feature selection methods which are wrapped around a classification algorithm and use a

Citations and references as keys to relevance ranking in interactive IR

DEFF Research Database (Denmark)

Ingwersen, Peter

2012-01-01

According to the principle of Polyrepresentation (Ingwersen & Järvelin, 2005; Ingwersen, 2012) bibliographic references in scientific documents as well as citations to documents have the potential of serving as useful features for re-ranking of retrieved documents. References (and thus citations...... been demonstrated to improve retrieval performance (Skov et al. 2008), whereas the number of citations has not provided similar improvements. The presentation will discuss the following phenomena and characteristics of references and citations as means for relevance re-ranking: 1) Are academic...... references (and thus citations) associated with relevance? 2) What are their potentials for IR? 3) What are their limitations? The presentation will propose a range of potentials and provide an initial research design. Selected cases are exemplified from the Web of Science database....

MetaFIND: A feature analysis tool for metabolomics data

Directory of Open Access Journals (Sweden)

Cunningham Pádraig

2008-11-01

Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

Relevant sex appeals in advertising: Gender and commitment context differences

Directory of Open Access Journals (Sweden)

Even J. Lanseng

2016-09-01

Full Text Available This research investigates differences in men’s and women’s attitudes toward ads featuring product-relevant sex appeals. It is found that women, but not men, were more negative toward an ad featuring an attractive opposite-sex model when their commitment thoughts were heightened. Women were also more negative toward an ad with an attractive same-sex model in the presence of commitment thoughts, but only when they scored high on sociosexuality. Men appeared unaffected, regardless of their level of sociosexuality. Commitment thoughts were manipulated by two types of prime, a parenting prime (study1 and a romantic prime (study 2.Results are explained by differences in how men and women react to sexual material and by differences in men’s and women’s evolved mating preferences.

High Performance Lead--free Piezoelectric Materials

OpenAIRE

Gupta, Shashaank

2013-01-01

Piezoelectric materials find applications in number of devices requiring inter-conversion of mechanical and electrical energy.  These devices include different types of sensors, actuators and energy harvesting devices. A number of lead-based perovskite compositions (PZT, PMN-PT, PZN-PT etc.) have dominated the field in last few decades owing to their giant piezoresponse and convenient application relevant tunability. With increasing environmental concerns, in the last one decade, focus has be...

Disclosure of Non-Financial Information: Relevant to Financial Analysts?

OpenAIRE

ORENS, Raf; LYBAERT, Nadine

2013-01-01

The decline in the relevance of financial statement information to value firms leads to calls from organizational stakeholders to convey non-financial information in order to be able to judge firms' financial performance and value. This literature review aims to report extant literature findings on the use of corporate non-financial information by sell-side financial analysts, the information intermediaries between corporate management and investors. Prior studies highlight that financial ana...

Hybridization between multi-objective genetic algorithm and support vector machine for feature selection in walker-assisted gait.

Science.gov (United States)

Martins, Maria; Costa, Lino; Frizera, Anselmo; Ceres, Ramón; Santos, Cristina

2014-03-01

Walker devices are often prescribed incorrectly to patients, leading to the increase of dissatisfaction and occurrence of several problems, such as, discomfort and pain. Thus, it is necessary to objectively evaluate the effects that assisted gait can have on the gait patterns of walker users, comparatively to a non-assisted gait. A gait analysis, focusing on spatiotemporal and kinematics parameters, will be issued for this purpose. However, gait analysis yields redundant information that often is difficult to interpret. This study addresses the problem of selecting the most relevant gait features required to differentiate between assisted and non-assisted gait. For that purpose, it is presented an efficient approach that combines evolutionary techniques, based on genetic algorithms, and support vector machine algorithms, to discriminate differences between assisted and non-assisted gait with a walker with forearm supports. For comparison purposes, other classification algorithms are verified. Results with healthy subjects show that the main differences are characterized by balance and joints excursion in the sagittal plane. These results, confirmed by clinical evidence, allow concluding that this technique is an efficient feature selection approach. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

An analysis of feature relevance in the classification of astronomical transients with machine learning methods

Science.gov (United States)

D'Isanto, A.; Cavuoti, S.; Brescia, M.; Donalek, C.; Longo, G.; Riccio, G.; Djorgovski, S. G.

2016-04-01

The exploitation of present and future synoptic (multiband and multi-epoch) surveys requires an extensive use of automatic methods for data processing and data interpretation. In this work, using data extracted from the Catalina Real Time Transient Survey (CRTS), we investigate the classification performance of some well tested methods: Random Forest, MultiLayer Perceptron with Quasi Newton Algorithm and K-Nearest Neighbours, paying special attention to the feature selection phase. In order to do so, several classification experiments were performed. Namely: identification of cataclysmic variables, separation between galactic and extragalactic objects and identification of supernovae.

Holographic QCD beyond the leading order

International Nuclear Information System (INIS)

Kim, Youngman; Ko, P.; Wu, Xiao-Hong

2008-01-01

We consider a holographic QCD model for light mesons beyond the leading order in the context of 5-dim gauged linear sigma model on the interval in the AdS 5 space. We include two dimension-6 operators in addition to the canonical bulk kinetic terms, and study chiral dynamics of π, ρ, a 1 and some of their KK modes. As novel features of dim-6 operators, we get non-vanishing Br(a 1 → πγ), the electromagnetic form factor and the charge radius of a charged pion, which improve the leading order results significantly and agree well with the experimental results.

Letter to editor: Blood pressure, hypertension and lead exposure.

Science.gov (United States)

Yang, Wen-Yi; Staessen, Jan A

2018-02-19

A significant association of office diastolic blood pressure with low-level blood lead exposure was reported in a Brazilian adult population. However, caution should be taken to interpret these results. The multivariable-adjusted association with blood pressure was positive for diastolic blood pressure, but inverse for systolic blood pressure. The association sizes were infinitesimal without clinical relevance. The outcome measures, i.e. blood pressure and the prevalence of hypertension were analysed across categories of the blood lead distribution - not in relation to blood lead as continuous variable. Blood pressure was the average of two oscillometric office readings, whereas ambulatory monitoring is the state-of-the-art.

Cherubism: Clinicoradiographic Features and Treatment

Directory of Open Access Journals (Sweden)

Luiz Antonio Guimarães Cabral

2010-04-01

Full Text Available Objectives: Cherubism is a congenital childhood disease of autosomal dominant inheritance. This disease is characterized by painless bilateral enlargement of the jaws, in which bone is replaced with fibrous tissue. The condition has sui generis clinical, radiographic and histological features, of which the clinician should be aware for a better differential diagnosis in the presence of a fibro-osseous lesion affecting the bones of the maxillomandibular complex. The purpose of present paper was to review the literature and to report the most important aspects of cherubism in order to facilitate the study of this disease.Material and Methods: Literature was reviewed about cherubism, emphasizing the relevant clinicoradiographic features and treatment. Literature was selected through a search of PubMed and Scielo electronic databases. The keywords used for search were adolescent, cherubism, cherubism/physiopathology, cherubism/treatment, cherubism/radiography. A manual search of the reference lists of the identified articles and the authors’ article files and recent reviews was conducted to identify additional publications. Those studies that described new features about cherubism were included in this review.Results: In total 44 literature sources were obtained and reviewed. Studies that described new features about cherubism physiopathology, diagnostics and treatment were reviewed.Conclusions: Despite the exceptions, cherubism is a clinically well-characterized disease. In cases of a suspicion of cherubism, radiographic examination is essential since the clinical presentation, the location and distribution of the lesions may define the diagnosis. Histopathological examination is complementary. Nowadays, genetic tests should be used for final diagnosis of cherubism.

Test beam results from a scintillating fibers-lead calorimeter

International Nuclear Information System (INIS)

Caria, M.

1991-01-01

The SpaCal collaboration has built prototypes of lead-scintillating fibers calorimter. The aim is to check predicted performances. Here are briefly mentioned results obtained from prototypes tests in beam of e, π, μ at CERN. Layers 2m long of extruded lead, were equipped with 1mm fibers in an hexagonal geometry. The ratio of scintillator to lead was 1/4. Results are presented on the most appealing features of such a calorimeter: energy resolution, homogeneity, containment and compensation. It is shown, that excellent energy resolution togehter with compensation has been achieved. (orig.)

Selective weighting of action-related feature dimensions in visual working memory.

Science.gov (United States)

Heuer, Anna; Schubö, Anna

2017-08-01

Planning an action primes feature dimensions that are relevant for that particular action, increasing the impact of these dimensions on perceptual processing. Here, we investigated whether action planning also affects the short-term maintenance of visual information. In a combined memory and movement task, participants were to memorize items defined by size or color while preparing either a grasping or a pointing movement. Whereas size is a relevant feature dimension for grasping, color can be used to localize the goal object and guide a pointing movement. The results showed that memory for items defined by size was better during the preparation of a grasping movement than during the preparation of a pointing movement. Conversely, memory for color tended to be better when a pointing movement rather than a grasping movement was being planned. This pattern was not only observed when the memory task was embedded within the preparation period of the movement, but also when the movement to be performed was only indicated during the retention interval of the memory task. These findings reveal that a weighting of information in visual working memory according to action relevance can even be implemented at the representational level during maintenance, demonstrating that our actions continue to influence visual processing beyond the perceptual stage.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

Science.gov (United States)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Optical high-performance computing: introduction to the JOSA A and Applied Optics feature.

Science.gov (United States)

Caulfield, H John; Dolev, Shlomi; Green, William M J

2009-08-01

The feature issues in both Applied Optics and the Journal of the Optical Society of America A focus on topics of immediate relevance to the community working in the area of optical high-performance computing.

Relevant Market in Commercial Aviation of the European Union

Directory of Open Access Journals (Sweden)

Jakub Kociubiński

2011-06-01

Full Text Available The purpose of this paper is to provide a brief overview of the issue of definition of relevant market in civil aviation within the European Union. The liberalization of the market since the early 1990s has led to a rapid increase in the number of airlines operating in the EU. The increase in the competitiveness of the market has brought many positive changes for passengers, such as lower fares and a better network of connections. At the same time it has created a risk that the airlines, in order to gain a competitive edge, would infringe the rules of competition. This is especially important in the context of the phenomenon that is the development of the airline alliances, which could lead to an abuse of a dominant position. A clear definition of the relevant market is a first step in an assessment of whether such an abuse occurred. This paper focus on the elements that Internal Market regulator, the European Commission, takes into consideration when defining relevant market in the airline industry.

Integration of heterogeneous features for remote sensing scene classification

Science.gov (United States)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Relevance of NET first wall concept for DEMO DN

International Nuclear Information System (INIS)

Kiltie, J.S.

1987-01-01

Design studies for the Next European Torus (NET) have produced a design concept for the first wall. This concept features poloidal water cooling, double contained in a welded steel structure which is protected by radiatively cooled tiles. In this appendix the relevance of this concept to a DEMO is examined with particular emphasis given to the ability of the cooling tube arrangement to remove the heat. A suggested modification to the arrangement of coolant tubes is suggested so that the design can operate at the higher loadings of a DEMO. (author)

Differential lead retention in zircons: implications for nuclear waste containment.

Science.gov (United States)

Gentry, R V; Sworski, T J; McKown, H S; Smith, D H; Eby, R E; Christie, W H

1982-04-16

An innovative ultrasensitive technique was used for lead isotopic analysis of individual zircons extracted from granite core samples at depths of 960, 2170, 2900, 3930, and 4310 meters. The results show that lead, a relatively mobile element compared to the nuclear waste-related actinides uranium and thorium, has been highly retained at elevated temperatures (105 degrees to 313 degrees C) under conditions relevant to the burial of synthetic rock waste containers in deep granite holes.

Multijet final states: exact results and the leading pole approximation

International Nuclear Information System (INIS)

Ellis, R.K.; Owens, J.F.

1984-09-01

Exact results for the process gg → ggg are compared with those obtained using the leading pole approximation. Regions of phase space where the approximation breaks down are discussed. A specific example relevant for background estimates to W boson production is presented. It is concluded that in this instance the leading pole approximation may underestimate the standard QCD background by more than a factor of two in certain kinematic regions of physical interest

The winner takes it all: Event-related brain potentials reveal enhanced motivated attention toward athletes' nonverbal signals of leading.

Science.gov (United States)

Furley, Philip; Schnuerch, Robert; Gibbons, Henning

2017-08-01

Observers of sports can reliably estimate who is leading or trailing based on nonverbal cues. Most likely, this is due to an adaptive mechanism of detecting motivationally relevant signals such as high status, superiority, and dominance. We reasoned that the relevance of leading athletes should lead to a sustained attentional prioritization. To test this idea, we recorded electroencephalography while 45 participants saw brief stills of athletes and estimated whether they were leading or trailing. Based on these recordings, we assessed event-related potentials and focused on the late positive complex (LPC), a well-established signature of controlled attention to motivationally relevant visual stimuli. Confirming our expectation, we found that LPC amplitude was significantly enhanced for leading as compared to trailing athletes. Moreover, this modulation was significantly related to behavioral performance on the score-estimation task. The present data suggest that subtle cues related to athletic supremacy are reliably differentiated in the human brain, involving a strong attentional orienting toward leading athletes. This mechanism might be part of an adaptive cognitive strategy that guides human social behavior.

Feature generation and representations for protein-protein interaction classification.

Science.gov (United States)

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.

Task relevance differentially shapes ventral visual stream sensitivity to visible and invisible faces

DEFF Research Database (Denmark)

Kouider, Sid; Barbot, Antoine; Madsen, Kristoffer Hougaard

2016-01-01

requires dissociating it from the top-down influences underlying conscious recognition. Here, using visual masking to abolish perceptual consciousness in humans, we report that functional magnetic resonance imaging (fMRI) responses to invisible faces in the fusiform gyrus are enhanced when they are task...... relevance crucially shapes the sensitivity of fusiform regions to face stimuli, leading from enhancement to suppression of neural activity when the top-down influences accruing from conscious recognition are prevented.......Top-down modulations of the visual cortex can be driven by task relevance. Yet, several accounts propose that the perceptual inferences underlying conscious recognition involve similar top-down modulations of sensory responses. Studying the pure impact of task relevance on sensory responses...

Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

Science.gov (United States)

Kim, Jonghwa; André, Elisabeth

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

Urban gardens: Lead exposure, recontamination mechanisms, and implications for remediation design

International Nuclear Information System (INIS)

Clark, Heather F.; Hausladen, Debra M.; Brabander, Daniel J.

2008-01-01

Environmental lead contamination is prevalent in urban areas where soil represents a significant sink and pathway of exposure. This study characterizes the speciation of lead that is relevant to local recontamination and to human exposure in the backyard gardens of Roxbury and Dorchester, MA, USA. One hundred forty-one backyard gardens were tested by X-ray fluorescence, and 81% of gardens have lead levels above the US EPA action limit of 400 μg/g. Raised gardening beds are the in situ exposure reduction method used in the communities to promote urban gardening. Raised beds were tested for lead and the results showed that the lead concentration increased from an initial range of 150±40 μg/g to an average of 336 μg/g over 4 years. The percent distribution of lead in the fine grain soil (<100 μm) and the trace metal signature of the raised beds support the conclusion that the mechanism of recontamination is wind-transported particles. Scanning electron microscopy and sequential extraction were used to characterize the speciation of lead, and the trace metal signature of the fine grain soil in both gardens and raised gardening beds is characteristic of lead-based paint. This study demonstrates that raised beds are a limited exposure reduction method and require maintenance to achieve exposure reduction goals. An exposure model was developed based on a suite of parameters that combine relevant values from the literature with site-specific quantification of exposure pathways. This model suggests that consumption of homegrown produce accounts for only 3% of children's daily exposure of lead while ingestion of fine grained soil (<100 μm) accounts for 82% of the daily exposure. This study indicates that urban lead remediation on a yard-by-yard scale requires constant maintenance and that remediation may need to occur on a neighborhood-wide scale

A novel method for the fabrication of freestanding PZT features on substrates

NARCIS (Netherlands)

van Bennekom, Joost G.; van Bennekom, J.G.; Winnubst, Aloysius J.A.; Nijdam, W.; Wessling, Matthias; Lammertink, Rob G.H.

2009-01-01

A simple and cheap micromoulding fabrication route was developed to prepare freestanding piezo active features. Dimensions as small as 200 μm by 200 μm and 40 μm high were successfully fabricated via a replication technique. The lead zirconate titanate features were thoroughly characterized using

Generic emergence of classical features in quantum Darwinism

Science.gov (United States)

Brandão, Fernando G. S. L.; Piani, Marco; Horodecki, Paweł

2015-08-01

Quantum Darwinism posits that only specific information about a quantum system that is redundantly proliferated to many parts of its environment becomes accessible and objective, leading to the emergence of classical reality. However, it is not clear under what conditions this mechanism holds true. Here we prove that the emergence of classical features along the lines of quantum Darwinism is a general feature of any quantum dynamics: observers who acquire information indirectly through the environment have effective access at most to classical information about one and the same measurement of the quantum system. Our analysis does not rely on a strict conceptual splitting between a system-of-interest and its environment, and allows one to interpret any system as part of the environment of any other system. Finally, our approach leads to a full operational characterization of quantum discord in terms of local redistribution of correlations.

Setting and changing feature priorities in visual short-term memory.

Science.gov (United States)

Kalogeropoulou, Zampeta; Jagadeesh, Akshay V; Ohl, Sven; Rolfs, Martin

2017-04-01

Many everyday tasks require prioritizing some visual features over competing ones, both during the selection from the rich sensory input and while maintaining information in visual short-term memory (VSTM). Here, we show that observers can change priorities in VSTM when, initially, they attended to a different feature. Observers reported from memory the orientation of one of two spatially interspersed groups of black and white gratings. Using colored pre-cues (presented before stimulus onset) and retro-cues (presented after stimulus offset) predicting the to-be-reported group, we manipulated observers' feature priorities independently during stimulus encoding and maintenance, respectively. Valid pre-cues reliably increased observers' performance (reduced guessing, increased report precision) as compared to neutral ones; invalid pre-cues had the opposite effect. Valid retro-cues also consistently improved performance (by reducing random guesses), even if the unexpected group suddenly became relevant (invalid-valid condition). Thus, feature-based attention can reshape priorities in VSTM protecting information that would otherwise be forgotten.

MORAL VALUES AND PSYCHOLOGICAL WELFARE OF PEOPLE LEADING A WAVE LIFESTYLE

Directory of Open Access Journals (Sweden)

Assel Alimakhanovna Issakhanova

2017-06-01

Full Text Available Purpose. The moral values of the modern personality are manifested through its value orientations. Vagrancy in the modern world has acquired a large-scale character. More and more people are beginning to lead a vagrancy lifestyle, moving away from social reality, not coping with the onslaught of globalization and economic instability. The problem of vagrancy is considered by many authors, but this does not become less relevant. This article examines the psychological self-awareness of the well-being of the personalities of people leading a stray lifestyle through self-assessment of moral indicators, as well as the relationship between psychological well-being and the morality of the individual. Most relevant, the problem of value orientation becomes in adulthood. It is in adulthood that most of the tramps begin to lead a wandering lifestyle. In this connection, the value orientations of people leading the vagrancy lifestyle change, making adjustments to the behavioral element of the personality and changing the sense of psychological well-being. Methodology. In the process of research, psychological methods and a survey were used to identify the problems faced by people leading a vagrancy lifestyle. Results. People without a fixed place of residence are a problem not only of a social nature but also of a psychological one leading to the degradation of the individual and society as a whole in all its areas of social interaction.

Binding of intrinsic and extrinsic features in working memory.

Science.gov (United States)

Ecker, Ullrich K H; Maybery, Murray; Zimmer, Hubert D

2013-02-01

There is ongoing debate concerning the mechanisms of feature binding in working memory. In particular, there is controversy regarding the extent to which these binding processes are automatic. The present article demonstrates that binding mechanisms differ depending on whether the to-be-integrated features are perceived as forming a coherent object. We presented a series of experiments that investigated the binding of color and shape, whereby color was either an intrinsic feature of the shape or an extrinsic feature of the shape's background. Results show that intrinsic color affected shape recognition, even when it was incidentally studied and irrelevant for the recognition task. In contrast, extrinsic color did not affect shape recognition, even when the association of color and shape was encoded and retrievable on demand. This strongly suggests that binding of intrinsic intra-item information but not extrinsic contextual information is obligatory in visual working memory. We highlight links to perception as well as implicit and explicit long-term memory, which suggest that the intrinsic-extrinsic dimension is a principle relevant to multiple domains of human cognition. 2013 APA, all rights reserved

Molecular Mechanisms of Glutamine Synthetase Mutations that Lead to Clinically Relevant Pathologies.

Directory of Open Access Journals (Sweden)

Benedikt Frieg

2016-02-01

Full Text Available Glutamine synthetase (GS catalyzes ATP-dependent ligation of ammonia and glutamate to glutamine. Two mutations of human GS (R324C and R341C were connected to congenital glutamine deficiency with severe brain malformations resulting in neonatal death. Another GS mutation (R324S was identified in a neurologically compromised patient. However, the molecular mechanisms underlying the impairment of GS activity by these mutations have remained elusive. Molecular dynamics simulations, free energy calculations, and rigidity analyses suggest that all three mutations influence the first step of GS catalytic cycle. The R324S and R324C mutations deteriorate GS catalytic activity due to loss of direct interactions with ATP. As to R324S, indirect, water-mediated interactions reduce this effect, which may explain the suggested higher GS residual activity. The R341C mutation weakens ATP binding by destabilizing the interacting residue R340 in the apo state of GS. Additionally, the mutation is predicted to result in a significant destabilization of helix H8, which should negatively affect glutamate binding. This prediction was tested in HEK293 cells overexpressing GS by dot-blot analysis: Structural stability of H8 was impaired through mutation of amino acids interacting with R341, as indicated by a loss of masking of an epitope in the glutamate binding pocket for a monoclonal anti-GS antibody by L-methionine-S-sulfoximine; in contrast, cells transfected with wild type GS showed the masking. Our analyses reveal complex molecular effects underlying impaired GS catalytic activity in three clinically relevant mutants. Our findings could stimulate the development of ATP binding-enhancing molecules by which the R324S mutant can be repaired extrinsically.

Feature hashing for fast image retrieval

Science.gov (United States)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

The Implementation of Cosine Similarity to Calculate Text Relevance between Two Documents

Science.gov (United States)

Gunawan, D.; Sembiring, C. A.; Budiman, M. A.

2018-03-01

Rapidly increasing number of web pages or documents leads to topic specific filtering in order to find web pages or documents efficiently. This is a preliminary research that uses cosine similarity to implement text relevance in order to find topic specific document. This research is divided into three parts. The first part is text-preprocessing. In this part, the punctuation in a document will be removed, then convert the document to lower case, implement stop word removal and then extracting the root word by using Porter Stemming algorithm. The second part is keywords weighting. Keyword weighting will be used by the next part, the text relevance calculation. Text relevance calculation will result the value between 0 and 1. The closer value to 1, then both documents are more related, vice versa.

Autonomia e relevância dos regimes The autonomy and relevance of regimes

Directory of Open Access Journals (Sweden)

Gustavo Seignemartin de Carvalho

2005-12-01

of norms and rules that create patterns of behavior and allow the convergence of the expectations of their participants in specific issue areas, in order to solve coordination problems that could lead to non-pareto-efficient outcomes. Considering that such definitions based merely on the "efficiency" of regimes do not seem to be sufficient to explain their effectiveness, the present article proposes a different definition for regimes: political arrangements that allow a redistribution of the gains of cooperation among the participants in certain issue areas, within an interdependence context. Regimes would thus be effective due to their autonomy and relevance - that is, due to their objective existence autonomously from their participants and their influence on the participants' behavior and expectations in ways that cannot be reduced to the individual action of any of them. This article begins with a brief discussion about terminological problems related to regime studies and with a definition of the concepts of autonomy and relevance. Then it classifies the authors that take part in this debate according to two distinct perspectives, one that denies (non-autonomists and the other that attributes (autonomists autonomy and relevance to regimes, briefly analyzing the authors and traditions that are more significant for this debate, focusing on autonomist authors and on arguments that back the hypothesis here presented. Finally, the article proposes an analytic decomposition of regimes into four main elements that give them autonomy and relevance: normativity, actors, specificity of the issue area and complex interdependence as context.

What is a Leading Case in EU law? An empirical analysis

DEFF Research Database (Denmark)

Sadl, Urska; Panagis, Yannis

2015-01-01

Lawyers generally explain legal development by looking at explicit amendments to statutory law and modifications in judicial practice. As far as the latter are concerned, leading cases occupy a special place. This article empirically studies the process in which certain cases become leading cases....... Our analysis focuses on Les Verts, a case of considerable fame in EU law, closely scrutinising whether it contains inherent leading case material. We show how the legal relevance of a case can become “embedded” in a long process of reinterpretation by legal actors, and we demonstrate that the actual...

Deep Feature Consistent Variational Autoencoder

OpenAIRE

Hou, Xianxu; Shen, Linlin; Sun, Ke; Qiu, Guoping

2016-01-01

We present a novel method for constructing Variational Autoencoder (VAE). Instead of using pixel-by-pixel loss, we enforce deep feature consistency between the input and the output of a VAE, which ensures the VAE's output to preserve the spatial correlation characteristics of the input, thus leading the output to have a more natural visual appearance and better perceptual quality. Based on recent deep learning works such as style transfer, we employ a pre-trained deep convolutional neural net...

Structural health monitoring feature design by genetic programming

International Nuclear Information System (INIS)

Harvey, Dustin Y; Todd, Michael D

2014-01-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems. (paper)

Lead Your Boss The Subtle Art of Managing Up

CERN Document Server

Baldoni, John

2009-01-01

Every manager on the move wants to have influence at the top in order to get his or her ideas heard and ultimately acted upon. In Lead Your Boss, recognized leadership guru John Baldoni gives managers new—as well as tried-and-true— methods for influencing both their bosses and their peers, and giving senior leaders reasons to follow their lead. Featuring instructive stories based on real-life experiences from leaders at all levels, Lead Your Boss reveals proven strategies for: • Developing spheres of influence • Handling tough issues • Asserting oneself diplomatically • Putting the team first

MANAGERS AND THEIR STYLE OF LEADING

Directory of Open Access Journals (Sweden)

Vlad FLOREA

2013-06-01

Full Text Available As main model for a manager, the German managers come from all walks of life, are graduates of higher technically and economically education, paying special attention to the individual qualities of leadership and to community professional competence to professionalism and to experience. In this paper we describe managers’ style of leading. A key feature of the Euroentrepeneur and Euromanager activity is achieving a sixth feature (creating outposts in major economic centers of Europe that is not addressing to traditional management techniques, but making use of specific techniques. The main conclusion reveals that the consolidation of European single market will grow the European management model rapidly, with its economic, social and cultural traits that will confer distinction from the North American and Japanese management.

Prediction of human protein function from post-translational modifications and localization features

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Gupta, Ramneek; Blom, Nikolaj

2002-01-01

a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects......We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from...

Reduced risk-taking behavior as a trait feature of anxiety

NARCIS (Netherlands)

Giorgetta, C.; Grecucci, A.; Zuanon, S.; Perini, L; Balestrieri, M.; Bonini, N.; Sanfey, A.G.; Brambilla, P.

2012-01-01

Affect can have a significant influence on decision-making processes and subsequent choice. One particularly relevant type of negative affect is anxiety, which serves to enhance responses to threatening stimuli or situations. In its exaggerated form, it can lead to psychiatric disorders, with

Integration of internal and external facial features in 8- to 10-year-old children and adults.

Science.gov (United States)

Meinhardt-Injac, Bozana; Persike, Malte; Meinhardt, Günter

2014-06-01

Investigation of whole-part and composite effects in 4- to 6-year-old children gave rise to claims that face perception is fully mature within the first decade of life (Crookes & McKone, 2009). However, only internal features were tested, and the role of external features was not addressed, although external features are highly relevant for holistic face perception (Sinha & Poggio, 1996; Axelrod & Yovel, 2010, 2011). In this study, 8- to 10-year-old children and adults performed a same-different matching task with faces and watches. In this task participants attended to either internal or external features. Holistic face perception was tested using a congruency paradigm, in which face and non-face stimuli either agreed or disagreed in both features (congruent contexts) or just in the attended ones (incongruent contexts). In both age groups, pronounced context congruency and inversion effects were found for faces, but not for watches. These findings indicate holistic feature integration for faces. While inversion effects were highly similar in both age groups, context congruency effects were stronger for children. Moreover, children's face matching performance was generally better when attending to external compared to internal features. Adults tended to perform better when attending to internal features. Our results indicate that both adults and 8- to 10-year-old children integrate external and internal facial features into holistic face representations. However, in children's face representations external features are much more relevant. These findings suggest that face perception is holistic but still not adult-like at the end of the first decade of life. Copyright © 2014 Elsevier B.V. All rights reserved.

Extracting the relevant delays in time series modelling

DEFF Research Database (Denmark)

Goutte, Cyril

1997-01-01

selection, and more precisely stepwise forward selection. The method is compared to other forward selection schemes, as well as to a nonparametric tests aimed at estimating the embedding dimension of time series. The final application extends these results to the efficient estimation of FIR filters on some......In this contribution, we suggest a convenient way to use generalisation error to extract the relevant delays from a time-varying process, i.e. the delays that lead to the best prediction performance. We design a generalisation-based algorithm that takes its inspiration from traditional variable...

The role of audience participation and task relevance on change detection during a card trick

Directory of Open Access Journals (Sweden)

Tim J Smith

2015-02-01

Full Text Available Magicians utilize many techniques for misdirecting audience attention away from the secret sleight of a trick. One technique is to ask an audience member to participate in a trick either physically by asking them to choose a card or cognitively by having them keep track of a card. While such audience participation is an established part of most magic the cognitive mechanisms by which it operates are unknown. Failure to detect changes to objects while passively viewing magic tricks has been shown to be conditional on the changing feature being irrelevant to the current task. How change blindness operates during interactive tasks is unclear but preliminary evidence suggests that relevance of the changing feature may also play a role (Triesch, Ballard, Hayhoe & Sullivan, 2003. The present study created a simple on-line card trick inspired by Triesch and colleagues’ (2003 that allowed playing cards to be instantaneously replaced without distraction or occlusion as participants were either actively sorting the cards (active condition or watching another person perform the task (passive conditions. Participants were given one of three sets of instructions. The relevance of the card color to the task increased across the three instructions. During half of the trials a card changed color (but retained its number as it was moving to the stack. Participants were instructed to immediately report such changes. Analysis of the probability of reporting a change revealed that actively performing the sorting task led to more missed changes than passively watching the same task but only when the changing feature was irrelevant to the sorting task. If the feature was relevant during either the pick-up or put-down action change detection was as good as during the passive block. These results confirm the ability of audience participation to create subtle dynamics of attention and perception during a magic trick and hide otherwise striking changes at the center of

The role of audience participation and task relevance on change detection during a card trick.

Science.gov (United States)

Smith, Tim J

2015-01-01

Magicians utilize many techniques for misdirecting audience attention away from the secret sleight of a trick. One technique is to ask an audience member to participate in a trick either physically by asking them to choose a card or cognitively by having them keep track of a card. While such audience participation is an established part of most magic the cognitive mechanisms by which it operates are unknown. Failure to detect changes to objects while passively viewing magic tricks has been shown to be conditional on the changing feature being irrelevant to the current task. How change blindness operates during interactive tasks is unclear but preliminary evidence suggests that relevance of the changing feature may also play a role (Triesch et al., 2003). The present study created a simple on-line card trick inspired by Triesch et al.'s (2003) that allowed playing cards to be instantaneously replaced without distraction or occlusion as participants were either actively sorting the cards (Doing condition) or watching another person perform the task (Watching conditions). Participants were given one of three sets of instructions. The relevance of the card color to the task increased across the three instructions. During half of the trials a card changed color (but retained its number) as it was moving to the stack. Participants were instructed to immediately report such changes. Analysis of the probability of reporting a change revealed that actively performing the sorting task led to more missed changes than passively watching the same task but only when the changing feature was irrelevant to the sorting task. If the feature was relevant during either the pick-up or put-down action change detection was as good as during the watching block. These results confirm the ability of audience participation to create subtle dynamics of attention and perception during a magic trick and hide otherwise striking changes at the center of attention.

The amazing world of smashed protons and lead ions

CERN Multimedia

Antonella Del Rosso

2013-01-01

When a single proton (p) is smashed against a lead ion (Pb), unexpected events may occur: in the most violent p-Pb collisions, correlations of particles exhibit similar features as in lead-lead collisions where quark-gluon plasma is formed. This and other amazing results were presented by the ALICE experiment at the SQM2013 conference held in Birmingham from 21 to 27 July.   Event display from the proton-lead run, in January 2013. This event was generated by the High Level Trigger (HLT) of the ALICE experiment. “Jet quenching” is one of the most powerful signatures of quark-gluon plasma (QGP) formed in high-energy lead-lead collisions. QGP is expected to exist only in specific conditions involving extremely hot temperatures and a very high particle concentration. These conditions are not expected to apply in the case of less “dense” particle collisions such as proton-lead collisions. “When we observe the results of these collisions in ALICE, ...

3-D FEATURE-BASED MATCHING BY RSTG APPROACH

Directory of Open Access Journals (Sweden)

J.-J. Jaw

2012-07-01

Full Text Available 3-D feature matching is the essential kernel in a fully automated feature-based LiDAR point cloud registration. After feasible procedures of feature acquisition, connecting corresponding features in different data frames is imperative to be solved. The objective addressed in this paper is developing an approach coined RSTG to retrieve corresponding counterparts of unsorted multiple 3-D features extracted from sets of LiDAR point clouds. RSTG stands for the four major processes, "Rotation alignment"; "Scale estimation"; "Translation alignment" and "Geometric check," strategically formulated towards finding out matching solution with high efficiency and leading to accomplishing the 3-D similarity transformation among all sets. The workable types of features to RSTG comprise points, lines, planes and clustered point groups. Each type of features can be employed exclusively or combined with others, if sufficiently supplied, throughout the matching scheme. The paper gives a detailed description of the matching methodology and discusses on the matching effects based on the statistical assessment which revealed that the RSTG approach reached an average matching rate of success up to 93% with around 6.6% of statistical type 1 error. Notably, statistical type 2 error, the critical indicator of matching reliability, was kept 0% throughout all the experiments.

Progress in engineering high strain lead-free piezoelectric ceramics

International Nuclear Information System (INIS)

Leontsev, Serhiy O; Eitel, Richard E

2010-01-01

Environmental concerns are strongly driving the need to replace the lead-based piezoelectric materials currently employed as multilayer actuators. The current review describes both compositional and structural engineering approaches to achieve enhanced piezoelectric properties in lead-free materials. The review of the compositional engineering approach focuses on compositional tuning of the properties and phase behavior in three promising families of lead-free perovskite ferroelectrics: the titanate, alkaline niobate and bismuth perovskites and their solid solutions. The 'structural engineering' approaches focus instead on optimization of microstructural features including grain size, grain orientation or texture, ferroelectric domain size and electrical bias field as potential paths to induce large piezoelectric properties in lead-free piezoceramics. It is suggested that a combination of both compositional and novel structural engineering approaches will be required in order to realize viable lead-free alternatives to current lead-based materials for piezoelectric actuator applications. (topical review)

Progress in engineering high strain lead-free piezoelectric ceramics

Science.gov (United States)

Leontsev, Serhiy O; Eitel, Richard E

2010-01-01

Environmental concerns are strongly driving the need to replace the lead-based piezoelectric materials currently employed as multilayer actuators. The current review describes both compositional and structural engineering approaches to achieve enhanced piezoelectric properties in lead-free materials. The review of the compositional engineering approach focuses on compositional tuning of the properties and phase behavior in three promising families of lead-free perovskite ferroelectrics: the titanate, alkaline niobate and bismuth perovskites and their solid solutions. The ‘structural engineering’ approaches focus instead on optimization of microstructural features including grain size, grain orientation or texture, ferroelectric domain size and electrical bias field as potential paths to induce large piezoelectric properties in lead-free piezoceramics. It is suggested that a combination of both compositional and novel structural engineering approaches will be required in order to realize viable lead-free alternatives to current lead-based materials for piezoelectric actuator applications. PMID:27877343

Lead isotope approach to the understanding of early Japanese bronze culture

International Nuclear Information System (INIS)

Mabuchi, H.; Hirao, Y.

1985-01-01

For several years, the authors have used lead isotope analysis to investigate extensively the provenance of ancient bronze or copper artifacts which had been excavated mainly from Japanese archaeological sites. The results have been published item by item in several relevant Japanese journals. This review is intended to give an account which will review the whole work relating early Japanese bronze culture to Chinese and Korean cultures through lead isotope study. (author)

The fate of task-irrelevant visual motion: perceptual load versus feature-based attention.

Science.gov (United States)

Taya, Shuichiro; Adams, Wendy J; Graf, Erich W; Lavie, Nilli

2009-11-18

We tested contrasting predictions derived from perceptual load theory and from recent feature-based selection accounts. Observers viewed moving, colored stimuli and performed low or high load tasks associated with one stimulus feature, either color or motion. The resultant motion aftereffect (MAE) was used to evaluate attentional allocation. We found that task-irrelevant visual features received less attention than co-localized task-relevant features of the same objects. Moreover, when color and motion features were co-localized yet perceived to belong to two distinct surfaces, feature-based selection was further increased at the expense of object-based co-selection. Load theory predicts that the MAE for task-irrelevant motion would be reduced with a higher load color task. However, this was not seen for co-localized features; perceptual load only modulated the MAE for task-irrelevant motion when this was spatially separated from the attended color location. Our results suggest that perceptual load effects are mediated by spatial selection and do not generalize to the feature domain. Feature-based selection operates to suppress processing of task-irrelevant, co-localized features, irrespective of perceptual load.

More target features in visual working memory leads to poorer search guidance: evidence from contralateral delay activity.

Science.gov (United States)

Schmidt, Joseph; MacNamara, Annmarie; Proudfit, Greg Hajcak; Zelinsky, Gregory J

2014-03-05

The visual-search literature has assumed that the top-down target representation used to guide search resides in visual working memory (VWM). We directly tested this assumption using contralateral delay activity (CDA) to estimate the VWM load imposed by the target representation. In Experiment 1, observers previewed four photorealistic objects and were cued to remember the two objects appearing to the left or right of central fixation; Experiment 2 was identical except that observers previewed two photorealistic objects and were cued to remember one. CDA was measured during a delay following preview offset but before onset of a four-object search array. One of the targets was always present, and observers were asked to make an eye movement to it and press a button. We found lower magnitude CDA on trials when the initial search saccade was directed to the target (strong guidance) compared to when it was not (weak guidance). This difference also tended to be larger shortly before search-display onset and was largely unaffected by VWM item-capacity limits or number of previews. Moreover, the difference between mean strong- and weak-guidance CDA was proportional to the increase in search time between mean strong-and weak-guidance trials (as measured by time-to-target and reaction-time difference scores). Contrary to most search models, our data suggest that trials resulting in the maintenance of more target features results in poor search guidance to a target. We interpret these counterintuitive findings as evidence for strong search guidance using a small set of highly discriminative target features that remain after pruning from a larger set of features, with the load imposed on VWM varying with this feature-consolidation process.

Case study of the gradient features of in situ concrete

Directory of Open Access Journals (Sweden)

Pengkun Hou

2014-01-01

Full Text Available The recognition of gradient features of the properties of in situ concrete is important for the interpretation/prediction of service life. In this work, the gradient features: water absorption, porosity, mineralogy, morphology and micromechanical properties were studied on two in situ road concretes (15 and 5 years old, respectively by weighing, MIP, XRD, IR, SEM/EDS and micro-indentation techniques. Results showed that a coarsening trend of the pores of the concrete leads to a gradual increase of liquid transport property from inside to outside. Although the carbonation of the exposed surface results in a compact microstructure of the paste, its combined action with calcium-leaching leads to a comparable porosity of different concrete layers. Moreover, the combining factors result in three morphological features, i.e. a porous and granular exposed-layer, a fibrous and porous subexposed-layer and a compact inner-layer. Micro-indentation test results showed that a hard layer that moves inward with aging exists due to the alterations of the mineralogy, the pore and the gel structure.

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

Science.gov (United States)

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.

Improving permafrost distribution modelling using feature selection algorithms

Science.gov (United States)

Deluigi, Nicola; Lambiel, Christophe; Kanevski, Mikhail

2016-04-01

The availability of an increasing number of spatial data on the occurrence of mountain permafrost allows the employment of machine learning (ML) classification algorithms for modelling the distribution of the phenomenon. One of the major problems when dealing with high-dimensional dataset is the number of input features (variables) involved. Application of ML classification algorithms to this large number of variables leads to the risk of overfitting, with the consequence of a poor generalization/prediction. For this reason, applying feature selection (FS) techniques helps simplifying the amount of factors required and improves the knowledge on adopted features and their relation with the studied phenomenon. Moreover, taking away irrelevant or redundant variables from the dataset effectively improves the quality of the ML prediction. This research deals with a comparative analysis of permafrost distribution models supported by FS variable importance assessment. The input dataset (dimension = 20-25, 10 m spatial resolution) was constructed using landcover maps, climate data and DEM derived variables (altitude, aspect, slope, terrain curvature, solar radiation, etc.). It was completed with permafrost evidences (geophysical and thermal data and rock glacier inventories) that serve as training permafrost data. Used FS algorithms informed about variables that appeared less statistically important for permafrost presence/absence. Three different algorithms were compared: Information Gain (IG), Correlation-based Feature Selection (CFS) and Random Forest (RF). IG is a filter technique that evaluates the worth of a predictor by measuring the information gain with respect to the permafrost presence/absence. Conversely, CFS is a wrapper technique that evaluates the worth of a subset of predictors by considering the individual predictive ability of each variable along with the degree of redundancy between them. Finally, RF is a ML algorithm that performs FS as part of its

Nonthermal plasmas around black holes, relevant collective modes, new configurations, and magnetic field amplification

Energy Technology Data Exchange (ETDEWEB)

Coppi, B., E-mail: coppi@mit.edu [Massachusetts Institute of Technology (United States)

2017-03-15

The radiation emission from Shining Black Holes is most frequently observed to have nonthermal features. It is therefore appropriate to consider relevant collective processes in plasmas surrounding black holes that contain high energy particles with nonthermal distributions in momentum space. A fluid description with significant temperature anisotropies is the simplest relevant approach. These anisotropies are shown to have a critical influence on: (a) the existence and characteristics of stationary plasma and field ring configurations, (b) the excitation of “thermo-gravitational modes” driven by temperature anisotropies and gradients that involve gravity and rotation, (c) the generation of magnetic fields over macroscopic scale distances, and (d) the transport of angular momentum.

Structural features that predict real-value fluctuations of globular proteins.

Science.gov (United States)

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

Compressive behavior of pervious concretes and a quantification of the influence of random pore structure features

International Nuclear Information System (INIS)

Deo, Omkar; Neithalath, Narayanan

2010-01-01

Research highlights: → Identified the relevant pore structure features of pervious concretes, provided methodologies to extract those, and quantified the influence of these features on compressive response. → A model for stress-strain relationship of pervious concretes, and relationship between model parameters and parameters of the stress-strain relationship developed. → Statistical model for compressive strength as a function of pore structure features; and a stochastic model for the sensitivity of pore structure features in strength prediction. - Abstract: Properties of a random porous material such as pervious concrete are strongly dependent on its pore structure features, porosity being an important one among them. This study deals with developing an understanding of the material structure-compressive response relationships in pervious concretes. Several pervious concrete mixtures with different pore structure features are proportioned and subjected to static compression tests. The pore structure features such as pore area fractions, pore sizes, mean free spacing of the pores, specific surface area, and the three-dimensional pore distribution density are extracted using image analysis methods. The compressive stress-strain response of pervious concretes, a model to predict the stress-strain response, and its relationship to several of the pore structure features are outlined. Larger aggregate sizes and increase in paste volume fractions are observed to result in increased compressive strengths. The compressive response is found to be influenced by the pore sizes, their distributions and spacing. A statistical model is used to relate the compressive strength to the relevant pore structure features, which is then used as a base model in a Monte-Carlo simulation to evaluate the sensitivity of the predicted compressive strength to the model terms.

Feature-Based Statistical Analysis of Combustion Simulation Data

Energy Technology Data Exchange (ETDEWEB)

Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

2011-11-18

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion

Evaluation of pattern recognition and feature extraction methods in ADHD prediction.

Directory of Open Access Journals (Sweden)

Joao Ricardo Sato

2012-09-01

Full Text Available Attention-Deficit/Hyperactivity Disorder is a neurodevelopmental disorder, being one of the most prevalent psychiatric disorders in childhood. The neural substrates associated with this condition, both from structural and functional perspectives, are not yet well established . Recent studies have highlighted the relevance of neuroimaging not only to provide a more solid understanding about the disorder but also for possible clinical support. The ADHD-200 Consortium organized the ADHD-200 global competition making publicly available, hundreds of structural magnetic resonance imaging (MRI and functional MRI (fMRI datasets of both ADHD patients and typically developing controls for research use. In the current study, we evaluate the predictive power of a set of three different feature extraction methods and 10 different pattern recognition methods. The features tested were regional homogeneity (ReHo, amplitude of low frequency fluctuations (ALFF and independent components analysis maps (RSN. Our findings suggest that the combination ALFF+ReHo maps contain relevant information to discriminate ADHD patients from typically developing controls, but with limited accuracy. All classifiers provided almost the same performance in this case. In addition, the combination ALFF+ReHo+RSN was relevant in combined vs inattentive ADHD classification, achieving a score accuracy of 67%. In this latter case, the performances of the classifiers were not equivalent and L2-regularized logistic regression (both in primal and dual space provided the most accurate predictions. The analysis of brain regions containing most discriminative information suggested that in both classifications (ADHD vs typically developing controls and combined vs inattentive, the relevant information is not confined only to a small set of regions but it is spatially distributed across the whole brain.

Case Studies of Leading Edge Small Urban High Schools. Relevance Strategic Designs: 5. Life Academy of Health and Bioscience

Science.gov (United States)

Shields, Regis Anne; Ireland, Nicole; City, Elizabeth; Derderian, Julie; Miles, Karen Hawley

2008-01-01

This report is one of nine detailed case studies of small urban high schools that served as the foundation for the Education Resource Strategies (ERS) report "Strategic Designs: Lessons from Leading Edge Small Urban High Schools." These nine schools were dubbed "Leading Edge Schools" because they stand apart from other high…

SOCIAL EXPERIENTIAL FEATURES OF CHILDREN SWIMMERS AND THEIR SUCCESS IN SPORT

Directory of Open Access Journals (Sweden)

Vojinović Jugoslav

2009-11-01

Full Text Available The aim of this research was to perceive a mutual connection of social - experien- tial features of children swimmers on one hand, and their success in sport on the other hand. According to the available methods and possibilities of their application, for this research the most relevant is empirical – unexperimental method or Survey method. An access in the obtained results shows that higher education of parents leads to less suc- cess of children in swimming. One more interesting social psychological category is a connection of parents’ pleasure and sports success. Here is also a connection negative – bigger parents’ pleasure leads more rare to sports success than less parents’ satisfac- tion (33,3 % versus 48,5 % . Probably it is being discussed about children swimmers of those parents who have more striking ambitions when the sports success of their children is concerned. Namely, their children are successful but they would like that they are mo- re successful. The reason for that attitude of those parents probably lies in the fact that all those things that they didn’t achieve in sport in their youth, they want to achieve and compensate through their children. Or vice versa, parents who are more prominently satisfied with the behaviour of their children do not have such great expectations when the success of their children in swimming is concerned. They are cheerful because their children do some sport and because they are not exposed to all those well-known temp- tations of young people today.

Decoding stimulus features in primate somatosensory cortex during perceptual categorization

Science.gov (United States)

Alvarez, Manuel; Zainos, Antonio; Romo, Ranulfo

2015-01-01

Neurons of the primary somatosensory cortex (S1) respond as functions of frequency or amplitude of a vibrotactile stimulus. However, whether S1 neurons encode both frequency and amplitude of the vibrotactile stimulus or whether each sensory feature is encoded by separate populations of S1 neurons is not known, To further address these questions, we recorded S1 neurons while trained monkeys categorized only one sensory feature of the vibrotactile stimulus: frequency, amplitude, or duration. The results suggest a hierarchical encoding scheme in S1: from neurons that encode all sensory features of the vibrotactile stimulus to neurons that encode only one sensory feature. We hypothesize that the dynamic representation of each sensory feature in S1 might serve for further downstream processing that leads to the monkey’s psychophysical behavior observed in these tasks. PMID:25825711

Charge migration induced by attosecond pulses in bio-relevant molecules

International Nuclear Information System (INIS)

Calegari, Francesca; Castrovilli, Mattea C; Nisoli, Mauro; Trabattoni, Andrea; Palacios, Alicia; Ayuso, David; Martín, Fernando; Greenwood, Jason B; Decleva, Piero

2016-01-01

After sudden ionization of a large molecule, the positive charge can migrate throughout the system on a sub-femtosecond time scale, purely guided by electronic coherences. The possibility to actively explore the role of the electron dynamics in the photo-chemistry of bio-relevant molecules is of fundamental interest for understanding, and perhaps ultimately controlling, the processes leading to damage, mutation and, more generally, to the alteration of the biological functions of the macromolecule. Attosecond laser sources can provide the extreme time resolution required to follow this ultrafast charge flow. In this review we will present recent advances in attosecond molecular science: after a brief description of the results obtained for small molecules, recent experimental and theoretical findings on charge migration in bio-relevant molecules will be discussed. (topical review)

Large-scale lithography for sub-500nm features

International Nuclear Information System (INIS)

Pelzer, R L; Steininger, T; Belier, Benoit; Julie, Gwenaelle

2006-01-01

The interest in micro- and nanotechnologies has grown rapidly in the last years. The applications are versatile and different techniques found its way into several research domains as optics, electronics, magnetism, fluidics, etc. In all of these fields integration of more and more functions on steadily decreasing device dimensions lead to an increase in structural density and feature size. Expensive and slow processes utilizing projection steppers or e-beam direct writer equipment are used to fabricate nm features today. A high throughput and cost effective method adapted on a standard mask aligner will be demonstrated, making features of below 300nm available on wafer-level. We will demonstrate results of 4 different resists exposed on a DUV proximity aligner and plasma etched for optical and biological applications in the sub-300nm range

Large-scale lithography for sub-500nm features

Energy Technology Data Exchange (ETDEWEB)

Pelzer, R L [Technology group, EV Group, DI Erich Thallner Str. 1, A-4780 Schaerding (Austria); Steininger, T [Technology group, EV Group, DI Erich Thallner Str. 1, A-4780 Schaerding (Austria); Belier, Benoit [CNRS, Institut d' Electronique Fondamentale, Universite Paris-Sud Bat 220, F- 91405 Orsay Cedex (France); Julie, Gwenaelle [CNRS, Institut d' Electronique Fondamentale, Universite Paris-Sud Bat 220, F- 91405 Orsay Cedex (France)

2006-04-01

The interest in micro- and nanotechnologies has grown rapidly in the last years. The applications are versatile and different techniques found its way into several research domains as optics, electronics, magnetism, fluidics, etc. In all of these fields integration of more and more functions on steadily decreasing device dimensions lead to an increase in structural density and feature size. Expensive and slow processes utilizing projection steppers or e-beam direct writer equipment are used to fabricate nm features today. A high throughput and cost effective method adapted on a standard mask aligner will be demonstrated, making features of below 300nm available on wafer-level. We will demonstrate results of 4 different resists exposed on a DUV proximity aligner and plasma etched for optical and biological applications in the sub-300nm range.

A comparative analysis of DNA barcode microarray feature size

Directory of Open Access Journals (Sweden)

Smith Andrew M

2009-10-01

Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

The importance of hydration thermodynamics in fragment-to-lead optimization.

Science.gov (United States)

Ichihara, Osamu; Shimada, Yuzo; Yoshidome, Daisuke

2014-12-01

Using a computational approach to assess changes in solvation thermodynamics upon ligand binding, we investigated the effects of water molecules on the binding energetics of over 20 fragment hits and their corresponding optimized lead compounds. Binding activity and X-ray crystallographic data of published fragment-to-lead optimization studies from various therapeutically relevant targets were studied. The analysis reveals a distinct difference between the thermodynamic profile of water molecules displaced by fragment hits and those displaced by the corresponding optimized lead compounds. Specifically, fragment hits tend to displace water molecules with notably unfavorable excess entropies-configurationally constrained water molecules-relative to those displaced by the newly added moieties of the lead compound during the course of fragment-to-lead optimization. Herein we describe the details of this analysis with the goal of providing practical guidelines for exploiting thermodynamic signatures of binding site water molecules in the context of fragment-to-lead optimization. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Charm quark contribution to K+ ---> pi+ nu anti-nu at next-to-next-to-leading order

Energy Technology Data Exchange (ETDEWEB)

Buras, Andrzej J.; /Munich, Tech. U.; Gorbahn, Martin; /Durham U., IPPP /Karlsruhe U., TTP; Haisch, Ulrich; /Fermilab /Zurich U.; Nierste, Ulrich; /Karlsruhe U., TTP

2006-03-01

The authors calculate the complete next-to-next-to-leading order QCD corrections to the charm contribution of the rare decay K{sup +} {yields} {pi}{sup +}{nu}{bar {nu}}. They encounter several new features, which were absent in lower orders. They discuss them in detail and present the results for the two-loop matching conditions of the Wilson coefficients, the three-loop anomalous dimensions, and the two-loop matrix elements of the relevant operators that enter the next-to-next-to-leading order renormalization group analysis of the Z-penguin and the electroweak box contribution. The inclusion of the next-to-next-to-leading order QCD corrections leads to a significant reduction of the theoretical uncertainty from {+-} 9.8% down to {+-} 2.4% in the relevant parameter P{sub c}(X), implying the leftover scale uncertainties in {Beta}(K{sup +} {yields} {pi}{sup +}{nu}{bar {nu}}) and in the determination of |V{sub td}|, sin 2{beta}, and {gamma} from the K {yields} {pi}{nu}{bar {nu}} system to be {+-} 1.3%, {+-} 1.0%, {+-} 0.006, and {+-} 1.2{sup o}, respectively. For the charm quark {ovr MS} mass m{sub c}(m{sub c}) = (1.30 {+-} 0.05) GeV and |V{sub us}| = 0.2248 the next-to-leading order value P{sub c}(X) = 0.37 {+-} 0.06 is modified to P{sub c}(X) = 0.38 {+-} 0.04 at the next-to-next-to-leading order level with the latter error fully dominated by the uncertainty in m{sub c}(m{sub c}). They present tables for P{sub c}(X) as a function of m{sub c}(m{sub c}) and {alpha}{sub s}(M{sub z}) and a very accurate analytic formula that summarizes these two dependences as well as the dominant theoretical uncertainties. Adding the recently calculated long-distance contributions they find {Beta}(K{sup +} {yields} {pi}{sup +}{nu}{bar {nu}}) = (8.0 {+-} 1.1) x 10{sup -11} with the present uncertainties in m{sub c}(m{sub c}) and the Cabibbo-Kobayashi-Maskawa elements being the dominant individual sources in the quoted error. They also emphasize that improved calculations of the long

Development of response inhibition in the context of relevant versus irrelevant emotions

Directory of Open Access Journals (Sweden)

Margot A Schel

2013-07-01

Full Text Available The present study examined the influence of relevant and irrelevant emotions on response inhibition from childhood to early adulthood. Ninety-four participants between 6 and 25 years of age performed two go/nogo tasks with emotional faces (neutral, happy, and fearful as stimuli. In one go/nogo task emotion formed a relevant dimension of the task and in the other go/nogo task emotion was irrelevant and participants had to respond to the color of the faces instead. A special feature of the latter task, in which emotion was irrelevant, was the inclusion of free choice trials, in which participants could freely decide between acting and inhibiting. Results showed a linear increase in response inhibition performance with increasing age both in relevant and irrelevant affective contexts. Relevant emotions had a pronounced influence on performance across age, whereas irrelevant emotions did not. Overall, participants made more false alarms on trials with fearful faces than happy faces, and happy faces were associated with better performance on go trials (higher percentage correct and faster RTs than fearful faces. The latter effect was stronger for young children in terms of accuracy. Finally, during the free choice trials participants did not base their decisions on affective context, confirming that irrelevant emotions do not have a strong impact on inhibition. Together, these findings suggest that across development relevant affective context has a larger influence on response inhibition than irrelevant affective context. When emotions are relevant, a context of positive emotions is associated with better performance compared to a context with negative emotions, especially in young children.

New Hybrid Features Selection Method: A Case Study on Websites Phishing

Directory of Open Access Journals (Sweden)

Khairan D. Rajab

2017-01-01

Full Text Available Phishing is one of the serious web threats that involves mimicking authenticated websites to deceive users in order to obtain their financial information. Phishing has caused financial damage to the different online stakeholders. It is massive in the magnitude of hundreds of millions; hence it is essential to minimize this risk. Classifying websites into “phishy” and legitimate types is a primary task in data mining that security experts and decision makers are hoping to improve particularly with respect to the detection rate and reliability of the results. One way to ensure the reliability of the results and to enhance performance is to identify a set of related features early on so the data dimensionality reduces and irrelevant features are discarded. To increase reliability of preprocessing, this article proposes a new feature selection method that combines the scores of multiple known methods to minimize discrepancies in feature selection results. The proposed method has been applied to the problem of website phishing classification to show its pros and cons in identifying relevant features. Results against a security dataset reveal that the proposed preprocessing method was able to derive new features datasets which when mined generate high competitive classifiers with reference to detection rate when compared to results obtained from other features selection methods.

Feature Selection and Kernel Learning for Local Learning-Based Clustering.

Science.gov (United States)

Zeng, Hong; Cheung, Yiu-ming

2011-08-01

The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.

Nongaussian Features from Inflationary Particle Production

International Nuclear Information System (INIS)

Barnaby, Neil

2010-01-01

The inflaton field can be expected to couple to a number of additional fields whose energy density does not play any significant role in driving inflation. Such couplings may lead to isolated bursts of particle production during inflation, for example via parametric resonance or a phase transition, and leave observable imprints in the cosmological fluctuations. I illustrate this effect for a simple prototype interaction g 2 (φ - φ 0 ) 2 χ between the inflaton, φ, and iso-inflaton, χ. Using both classical lattice simulations and analytical quantum field theory computations, I show that this mechanism generates localized bump-like features in the power spectrum and also a completely new type of nongaussianity. Observations are consistent with relatively large features of this type and the nongaussianity from particle production may be observable in future missions.

Understanding Protein-Protein Interactions Using Local Structural Features

DEFF Research Database (Denmark)

Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier

2013-01-01

Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation...... to score the likelihood of the interaction between two proteins and to develop a method for the prediction of PPIs. We have tested our method on several sets with unbalanced ratios of interactions and non-interactions to simulate real conditions, obtaining accuracies higher than 25% in the most unfavorable...

A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

Directory of Open Access Journals (Sweden)

Hossien Pourghassem

2011-04-01

Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

User perspectives on relevance criteria

DEFF Research Database (Denmark)

Maglaughlin, Kelly L.; Sonnenwald, Diane H.

2002-01-01

, partially relevant, or not relevant to their information need; and explained their decisions in an interview. Analysis revealed 29 criteria, discussed positively and negatively, that were used by the participants when selecting passages that contributed or detracted from a document's relevance......This study investigates the use of criteria to assess relevant, partially relevant, and not-relevant documents. Study participants identified passages within 20 document representations that they used to make relevance judgments; judged each document representation as a whole to be relevant...... matter, thought catalyst), full text (e.g., audience, novelty, type, possible content, utility), journal/publisher (e.g., novelty, main focus, perceived quality), and personal (e.g., competition, time requirements). Results further indicate that multiple criteria are used when making relevant, partially...

Terms, definitions and measurements to describe sonographic features of myometrium and uterine masses

DEFF Research Database (Denmark)

Van den Bosch, Thierry; Dueholm, Margit; Leone, FP

2015-01-01

imaging. The terms and definitions described may form the basis for prospective studies to predict the risk of different myometrial pathologies, based on their ultrasound appearance, and thus should be relevant for the clinician in daily practice and for clinical research. The sonographic features and use......The MUSA (Morphological Uterus Sonographic Assessment) statement is a consensus statement on terms, definitions and measurements that may be used to describe and report the sonographic features of the myometrium using gray-scale sonography, color/power Doppler and three-dimensional ultrasound...

Association between MRI structural features and cognitive measures in pediatric multiple sclerosis

Science.gov (United States)

Amoroso, N.; Bellotti, R.; Fanizzi, A.; Lombardi, A.; Monaco, A.; Liguori, M.; Margari, L.; Simone, M.; Viterbo, R. G.; Tangaro, S.

2017-09-01

Multiple sclerosis (MS) is an inflammatory and demyelinating disease associated with neurodegenerative processes that lead to brain structural changes. The disease affects mostly young adults, but 3-5% of cases has a pediatric onset (POMS). Magnetic Resonance Imaging (MRI) is generally used for diagnosis and follow-up in MS patients, however the most common MRI measures (e.g. new or enlarging T2-weighted lesions, T1-weighted gadolinium- enhancing lesions) have often failed as surrogate markers of MS disability and progression. MS is clinically heterogenous with symptoms that can include both physical changes (such as visual loss or walking difficulties) and cognitive impairment. 30-50% of POMS experience prominent cognitive dysfunction. In order to investigate the association between cognitive measures and brain morphometry, in this work we present a fully automated pipeline for processing and analyzing MRI brain scans. Relevant anatomical structures are segmented with FreeSurfer; besides, statistical features are computed. Thus, we describe the data referred to 12 patients with early POMS (mean age at MRI: 15.5 +/- 2.7 years) with a set of 181 structural features. The major cognitive abilities measured are verbal and visuo-spatial learning, expressive language and complex attention. Data was collected at the Department of Basic Sciences, Neurosciences and Sense Organs, University of Bari, and exploring different abilities like the verbal and visuo-spatial learning, expressive language and complex attention. Different regression models and parameter configurations are explored to assess the robustness of the results, in particular Generalized Linear Models, Bayes Regression, Random Forests, Support Vector Regression and Artificial Neural Networks are discussed.

Abdominal tuberculosis: Imaging features

International Nuclear Information System (INIS)

Pereira, Jose M.; Madureira, Antonio J.; Vieira, Alberto; Ramos, Isabel

2005-01-01

Radiological findings of abdominal tuberculosis can mimic those of many different diseases. A high level of suspicion is required, especially in high-risk population. In this article, we will describe barium studies, ultrasound (US) and computed tomography (CT) findings of abdominal tuberculosis (TB), with emphasis in the latest. We will illustrate CT findings that can help in the diagnosis of abdominal tuberculosis and describe imaging features that differentiate it from other inflammatory and neoplastic diseases, particularly lymphoma and Crohn's disease. As tuberculosis can affect any organ in the abdomen, emphasis is placed to ileocecal involvement, lymphadenopathy, peritonitis and solid organ disease (liver, spleen and pancreas). A positive culture or hystologic analysis of biopsy is still required in many patients for definitive diagnosis. Learning objectives:1.To review the relevant pathophysiology of abdominal tuberculosis. 2.Illustrate CT findings that can help in the diagnosis

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results

NARCIS (Netherlands)

Nketiah, G.; Elschot, M.; Kim, E.; Teruel, J.R.; Scheenen, T.W.J.; Bathen, T.F.; Selnaes, K.M.

2017-01-01

PURPOSE: To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. MATERIALS AND METHODS:

Recognizing the radiographic features of some common bovine foot problems

International Nuclear Information System (INIS)

Ebeid, M.; Steiner, A.

1996-01-01

Radiographs of an injured or infected bovine foot can be tricky to interpret - the anatomy is complex, and the signs may be subtle. This guide leads you through the classic radiographic features of several common foot conditions

Cognitive impairment and dementia in Parkinson’s disease: clinical features, diagnosis, and management

Directory of Open Access Journals (Sweden)

Joana eMeireles

2012-05-01

Full Text Available Parkinson’s disease (PD is a common, disabling, neurodegenerative disorder. In addition to classical motor symptoms, nonmotor features are now widely accepted as part of the clinical picture, and cognitive decline is a very important aspect of the disease, as it brings an additional significant burden for the patient and caregivers. The diagnosis of cognitive decline in PD, namely mild cognitive impairment and dementia, can be extremely challenging, remaining largely based on clinical and cognitive assessments. Diagnostic criteria and methods for PD dementia and mild cognitive impairment have been recently issued by expert work groups. This manuscript has synthesized relevant data in order to obtain a pragmatic and updated review regarding cognitive decline in PD, from milder stages to dementia. This text will summarize clinical features, diagnostic methodology, and therapeutic issues of clinical decline in Parkinson’s disease. Relevant clinical genetic issues, including recent advances, will also be approached.

Central nervous system infectious diseases mimicking multiple sclerosis: recognizing distinguishable features using MRI

Directory of Open Access Journals (Sweden)

Antonio Jose da Rocha

2013-09-01

Full Text Available The current diagnostic criteria for multiple sclerosis (MS confirm the relevant role of magnetic resonance imaging (MRI, supporting the possibility of characterizing the dissemination in space (DIS and the dissemination in time (DIT in a single scan. To maintain the specificity of these criteria, it is necessary to determine whether T2/FLAIR visible lesions and the gadolinium enhancement can be attributed to diseases that mimic MS. Several diseases are included in the MS differential diagnosis list, including diseases with exacerbation, remitting periods and numerous treatable infectious diseases, which can mimic the MRI features of MS. We discuss the most relevant imaging features in several infectious diseases that resemble MS and examine the primary spatial distributions of lesions and the gadolinium enhancement patterns related to MS. Recognizing imaging "red flags" can be useful for the proper diagnostic evaluation of suspected cases of MS, facilitating the correct differential diagnosis by assessing the combined clinical, laboratory and MR imaging information.

Adaptive feature selection using v-shaped binary particle swarm optimization.

Science.gov (United States)

Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

2017-01-01

Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

Anxiety or agitation in mood disorder with mixed features: A review with a focus on validity as a dimensional criterion.

Science.gov (United States)

Shim, In Hee; Bae, Dong Sik; Bahk, Won-Myong

2016-08-01

The diagnostic validity of mixed features, excluding anxiety or psychomotor agitation in mood disorders, has not yet been fully examined. PubMed and relevant English-language literature (regardless of year) were searched. Keywords were mixed or mixed state or mixed features or mixed episode and anxious or anxiety or agitation and bipolar disorder or depressive disorder or mood disorder or affective disorder. Most studies on anxiety or psychomotor agitation have included a significant correlation relevant to the "with mixed features" specifier, although it is common in both poles of mood episodes regardless of the predominant polarity. There is some confusion between the characteristic of classical mixed states and the definition of the mixed features specifier with the newly added anxious distress specifier in DSM-5, specifically, whether to include anxiety and agitation as significant characteristics. This change is of concern because a large proportion of patients with mixed features are now unspecified, and this may influence treatment planning and prognosis. The findings of our review suggest that anxiety and psychomotor agitation can be core symptoms in mood episodes with mixed features and important clinical clues for prediction of treatment effects and disease course.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Visual search for features and conjunctions in development.

Science.gov (United States)

Lobaugh, N J; Cole, S; Rovet, J F

1998-12-01

Visual search performance was examined in three groups of children 7 to 12 years of age and in young adults. Colour and orientation feature searches and a conjunction search were conducted. Reaction time (RT) showed expected improvements in processing speed with age. Comparisons of RT's on target-present and target-absent trials were consistent with parallel search on the two feature conditions and with serial search in the conjunction condition. The RT results indicated searches for feature and conjunctions were treated similarly for children and adults. However, the youngest children missed more targets at the largest array sizes, most strikingly in conjunction search. Based on an analysis of speed/accuracy trade-offs, we suggest that low target-distractor discriminability leads to an undersampling of array elements, and is responsible for the high number of misses in the youngest children.

Mapping genomic features to functional traits through microbial whole genome sequences.

Science.gov (United States)

Zhang, Wei; Zeng, Erliang; Liu, Dan; Jones, Stuart E; Emrich, Scott

2014-01-01

Recently, the utility of trait-based approaches for microbial communities has been identified. Increasing availability of whole genome sequences provide the opportunity to explore the genetic foundations of a variety of functional traits. We proposed a machine learning framework to quantitatively link the genomic features with functional traits. Genes from bacteria genomes belonging to different functional traits were grouped to Cluster of Orthologs (COGs), and were used as features. Then, TF-IDF technique from the text mining domain was applied to transform the data to accommodate the abundance and importance of each COG. After TF-IDF processing, COGs were ranked using feature selection methods to identify their relevance to the functional trait of interest. Extensive experimental results demonstrated that functional trait related genes can be detected using our method. Further, the method has the potential to provide novel biological insights.

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

Directory of Open Access Journals (Sweden)

Andrew F Neuwald

2016-12-01

Full Text Available Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs, which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu.

Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

Science.gov (United States)

Neuwald, Andrew F; Altschul, Stephen F

2016-12-01

Over evolutionary time, members of a superfamily of homologous proteins sharing a common structural core diverge into subgroups filling various functional niches. At the sequence level, such divergence appears as correlations that arise from residue patterns distinct to each subgroup. Such a superfamily may be viewed as a population of sequences corresponding to a complex, high-dimensional probability distribution. Here we model this distribution as hierarchical interrelated hidden Markov models (hiHMMs), which describe these sequence correlations implicitly. By characterizing such correlations one may hope to obtain information regarding functionally-relevant properties that have thus far evaded detection. To do so, we infer a hiHMM distribution from sequence data using Bayes' theorem and Markov chain Monte Carlo (MCMC) sampling, which is widely recognized as the most effective approach for characterizing a complex, high dimensional distribution. Other routines then map correlated residue patterns to available structures with a view to hypothesis generation. When applied to N-acetyltransferases, this reveals sequence and structural features indicative of functionally important, yet generally unknown biochemical properties. Even for sets of proteins for which nothing is known beyond unannotated sequences and structures, this can lead to helpful insights. We describe, for example, a putative coenzyme-A-induced-fit substrate binding mechanism mediated by arginine residue switching between salt bridge and π-π stacking interactions. A suite of programs implementing this approach is available (psed.igs.umaryland.edu).

Rough-fuzzy clustering and unsupervised feature selection for wavelet based MR image segmentation.

Directory of Open Access Journals (Sweden)

Pradipta Maji

Full Text Available Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices.

Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

Science.gov (United States)

Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

2013-01-01

DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

Towards the maturity model for feature oriented domain analysis

Directory of Open Access Journals (Sweden)

Muhammad Javed

2014-09-01

Full Text Available Assessing the quality of a model has always been a challenge for researchers in academia and industry. The quality of a feature model is a prime factor because it is used in the development of products. A degraded feature model leads the development of low quality products. Few efforts have been made on improving the quality of feature models. This paper is an effort to present our ongoing work i.e. development of FODA (Feature Oriented Domain Analysis maturity model which will help to evaluate the quality of a given feature model. In this paper, we provide the quality levels along with their descriptions. The proposed model consists of four levels starting from level 0 to level 3. Design of each level is based on the severity of errors, whereas severity of errors decreases from level 0 to level 3. We elaborate each level with the help of examples. We borrowed all examples from the material published by the research community of Software Product Lines (SPL for the application of our framework.

Dysmorphic features and developmental outcome of 2-year-old children

NARCIS (Netherlands)

Seggers, Jorien; Haadsma, Maaike L.; Bos, Arend F.; Heineman, Maas Jan; Middelburg, Karin J.; van den Heuvel, Edwin R.; Hadders-Algra, Mijna

2014-01-01

The aim of this study was to assess the associations between dysmorphic features and neurological, mental, psychomotor, and behavioural development in order to improve our understanding of aetiological pathways leading to minor developmental problems. In our cross-sectional study, 272 generally

ENGINEERED BARRIER SYSTEM FEATURES, EVENTS AND PROCESSES

International Nuclear Information System (INIS)

Jaros, W.

2005-01-01

The purpose of this report is to evaluate and document the inclusion or exclusion of engineered barrier system (EBS) features, events, and processes (FEPs) with respect to models and analyses used to support the total system performance assessment for the license application (TSPA-LA). A screening decision, either Included or Excluded, is given for each FEP along with the technical basis for exclusion screening decisions. This information is required by the U.S. Nuclear Regulatory Commission (NRC) at 10 CFR 63.114 (d, e, and f) [DIRS 173273]. The FEPs addressed in this report deal with those features, events, and processes relevant to the EBS focusing mainly on those components and conditions exterior to the waste package and within the rock mass surrounding emplacement drifts. The components of the EBS are the drip shield, waste package, waste form, cladding, emplacement pallet, emplacement drift excavated opening (also referred to as drift opening in this report), and invert. FEPs specific to the waste package, cladding, and drip shield are addressed in separate FEP reports: for example, ''Screening of Features, Events, and Processes in Drip Shield and Waste Package Degradation'' (BSC 2005 [DIRS 174995]), ''Clad Degradation--FEPs Screening Arguments (BSC 2004 [DIRS 170019]), and Waste-Form Features, Events, and Processes'' (BSC 2004 [DIRS 170020]). For included FEPs, this report summarizes the implementation of the FEP in the TSPA-LA (i.e., how the FEP is included). For excluded FEPs, this analysis provides the technical basis for exclusion from TSPA-LA (i.e., why the FEP is excluded). This report also documents changes to the EBS FEPs list that have occurred since the previous versions of this report. These changes have resulted due to a reevaluation of the FEPs for TSPA-LA as identified in Section 1.2 of this report and described in more detail in Section 6.1.1. This revision addresses updates in Yucca Mountain Project (YMP) administrative procedures as they

Shape adaptive, robust iris feature extraction from noisy iris images.

Science.gov (United States)

Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

2013-10-01

In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate.

STYLISTIC FEATURES OF ADVERTISING TEXTS OF INFORMATIVE AND COMPARATIVE TYPES

Directory of Open Access Journals (Sweden)

Poddubskaya, O.N.

2016-06-01

Full Text Available The relevance of this article is related to the fact that nowadays advertising has a very strong impact both on the consumer market, political and cultural life of society, and on the language and its development as a system. Advertising has given rise to the development of a special set of stylistic features of a text, formed under the influence of reviving advertising traditions in the Russian language and under the active impact of energetic and pushy European advertising. The purpose of this study is to explore stylistic features of informative and comparative advertising texts. The object of research is Russian-language advertising in printed media and on television. In the end of the article we made conclusions about groups of language means used for different stylistic devices in informative and comparative advertising texts. Analysis of stylistic features of modern informative and comparative advertising texts can be of great interest to specialists in the field of theoretical studies of modern advertising.

The relevance of clinical and radiographic features of jaw lesions: A prospective study

Directory of Open Access Journals (Sweden)

Juliane Piragine ARAUJO

Full Text Available Abstract The study was carried out in a Brazilian population and the aim was to describe the prevalence and the clinic-radiographical features of jaw lesions. In addition, a comparison between the main diagnosis hypothesis and final diagnosis was accessed. A prospective study which evaluated all patients with jaw lesions diagnosed in an Oral Diagnosis Center, between August 2013 and October 2014. A total of 450 patients were observed for the first time, and 130 had some type of jaw lesion. The mean age of the patients was 35.2 years ± 17.86. Among these, 71 were women (54.62% and 87 were Caucasian (66.92%. The mandible was affected more frequently (71.43% than the maxilla (28.57%. Swelling and pain were the most frequent clinical signs and symptoms and were observed in 60 (42.85% and 38 (27.14% cases, respectively. The panoramic x-ray was the main radiographic exam utilized (88.57%. Radiolucent lesions accounted for 89 cases (63.57% and the unilocular form was present in 114 cases (81.43%. A total of 93 cases had histopathological analyses and the periapical cyst was the most frequent lesion. In the other 47 lesions, the diagnosis was conducted by clinical and radiographic management. Bone lesions were frequent, being noted on first visit in approximately 30% of patients; in 1/3 of the cases, the diagnoses were completed with a combination of clinical and radiographic exams.

Elucidation of the Mechanisms and Environmental Relevance of cis-Dichloroethene and Vinyl Chloride Biodegradation

Science.gov (United States)

2012-11-01

thus appears that Polaromonas sp. JS666 is a safe candidate for use in bioremediation , bioaugmentation or monitored natural attenuation. 3.1.6...of multiple chlorinated ethene sources in an industrialized area. A forensic field study using compound-specific isotope analysis." Environmental ...Degrading Bacterium, and Features of Relevance to Biotechnology .” Applied and Environmental Microbiology 74(20): 6405-6416. Maymó-Gatell, X., Y.-t

Modulation of leading edge vorticity and aerodynamic forces in flexible flapping wings.

Science.gov (United States)

Zhao, Liang; Deng, Xinyan; Sane, Sanjay P

2011-09-01

In diverse biological flight systems, the leading edge vortex has been implicated as a flow feature of key importance in the generation of flight forces. Unlike fixed wings, flapping wings can translate at higher angles of attack without stalling because their leading edge vorticity is more stable than the corresponding fixed wing case. Hence, the leading edge vorticity has often been suggested as the primary determinant of the high forces generated by flapping wings. To test this hypothesis, it is necessary to modulate the size and strength of the leading edge vorticity independently of the gross kinematics while simultaneously monitoring the forces generated by the wing. In a recent study, we observed that forces generated by wings with flexible trailing margins showed a direct dependence on the flexural stiffness of the wing. Based on that study, we hypothesized that trailing edge flexion directly influences leading edge vorticity, and thereby the magnitude of aerodynamic forces on the flexible flapping wings. To test this hypothesis, we visualized the flows on wings of varying flexural stiffness using a custom 2D digital particle image velocimetry system, while simultaneously monitoring the magnitude of the aerodynamic forces. Our data show that as flexion decreases, the magnitude of the leading edge vorticity increases and enhances aerodynamic forces, thus confirming that the leading edge vortex is indeed a key feature for aerodynamic force generation in flapping flight. The data shown here thus support the hypothesis that camber influences instantaneous aerodynamic forces through modulation of the leading edge vorticity.

Coordination chemistry of two heavy metals: I, Ligand preferences in lead(II) complexation, toward the development of therapeutic agents for lead poisoning: II, Plutonium solubility and speciation relevant to the environment

International Nuclear Information System (INIS)

Neu, M.P.

1993-11-01

The coordination chemistry and solution behavior of the toxic ions lead(II) and plutonium(IV, V, VI) have been investigated. The ligand pK a s and ligand-lead(II) stability constants of one hydroxamic acid and four thiohydroaxamic acids were determined. Solution thermodynamic results indicate that thiohydroxamic acids are more acidic and slightly better lead chelators than hydroxamates, e.g., N-methylthioaceto-hydroxamic acid, pK a = 5.94, logβ 120 = 10.92; acetohydroxamic acid, pK a = 9.34, logβ l20 = 9.52. The syntheses of lead complexes of two bulky hydroxamate ligands are presented. The X-ray crystal structures show the lead hydroxamates are di-bridged dimers with irregular five-coordinate geometry about the metal atom and a stereochemically active lone pair of electrons. Molecular orbital calculations of a lead hydroxamate and a highly symmetric pseudo octahedral lead complex were performed. The thermodynamic stability of plutonium(IV) complexes of the siderophore, desferrioxamine B (DFO), and two octadentate derivatives of DFO were investigated using competition spectrophotometric titrations. The stability constant measured for the plutonium(IV) complex of DFO-methylterephthalamide is logβ 110 = 41.7. The solubility limited speciation of 242 Pu as a function of time in near neutral carbonate solution was measured. Individual solutions of plutonium in a single oxidation state were added to individual solutions at pH = 6.0, T = 30.0, 1.93 mM dissolved carbonate, and sampled over intervals up to 150 days. Plutonium solubility was measured, and speciation was investigated using laser photoacoustic spectroscopy and chemical methods

Physical and technical aspects of lead cooled fast reactors safety

International Nuclear Information System (INIS)

Orlov, V.V.; Smirnov, V.S.; Filin, A.I.

2001-01-01

The safety analysis of lead-cooled fast reactors has been performed for the well-developed concept of BREST-OD-300 reactor. The most severe accidents have been considered. An ultimate design-basis accident has been defined as an event resulting from an external impact and involving a loss of leak-tightness of the lead circuit, loss of forced circulation of lead and loss of heat sink to the secondary circuit, failure of controls and of reactor scram with resultant insertion of total reactivity margin, etc. It was assumed in accident analysis that the protective feature available for accident mitigation was only reactivity feedback on the changes in the temperatures of the reactor core elements and coolant flow rate, and in some cases also actuation of passive protections of threshold action in response to low flow rate and high coolant temperature at the core outlet. It should be noted that the majority of the analyzed accidents could be overcame even without initiation of the above protections. It has been demonstrated that a combination of inherent properties of lead coolant, nitride fuel, physical and design features of fast reactors will ensure natural safety of BREST and are instrumental for avoiding by a deterministic approach the accidents associated with a significant release of radioactivity and requiring evacuation of people in any credible initiating event and a combination of events. (author)

European lead fast reactor (ELSY and LEADER projects)

International Nuclear Information System (INIS)

Alemberti, Alessandro; Carlsson, Johan; Malambu, Edouard; Orden, Alfredo; Cinotti, Luciano; Struwe, Dankward; Agostini, Pietro; Monti, Stefano

2010-01-01

The conceptual design of the European Lead Fast Reactor is being developed starting from September 2006, in the frame of the ELSY project. The ELSY reference design is a 600 MWe pool-type reactor cooled by pure lead. The ELSY project demonstrates the possibility of designing a competitive and safe fast critical reactor using simple engineered technical features, whilst fully complying with the Generation IV goal of sustainability and minor actinide (MA) burning capability. Sustainability was a leading criterion for option selection for core design, focusing on the demonstration of the potential to be self sustaining in plutonium and to burn its own generated MAs. To this end, different core configurations have been studied. Economics was a leading criterion for primary system design and plant layout. The use of a compact and simple primary circuit with the additional objective that all internal components be removable, are among the reactor features intended to assure competitive electric energy generation and long-term investment protection. Low capital cost and construction time are pursued through simplicity and compactness of the reactor building (reduced footprint and height). The reduced plant footprint is one of the benefits coming from the elimination of the Intermediate Cooling System, the low reactor building height is the result of the design approach which foresees the adoption of short-height components and two innovative DHR systems. Among the critical issues, the impact of the large mass of lead has been carefully analyzed; it has been demonstrated that the high density of lead can be mitigated by compact solutions and adoption of seismic isolators. Safety has been one of the major focuses all over the ELSY development. In addition to the inherent safety advantages of lead coolant (high boiling point and no exothermic reactions with air or water) a high safety grade of the overall system has been reached. In fact the overall primary system has been

A ROC-based feature selection method for computer-aided detection and diagnosis

Science.gov (United States)

Wang, Songyuan; Zhang, Guopeng; Liao, Qimei; Zhang, Junying; Jiao, Chun; Lu, Hongbing

2014-03-01

Image-based computer-aided detection and diagnosis (CAD) has been a very active research topic aiming to assist physicians to detect lesions and distinguish them from benign to malignant. However, the datasets fed into a classifier usually suffer from small number of samples, as well as significantly less samples available in one class (have a disease) than the other, resulting in the classifier's suboptimal performance. How to identifying the most characterizing features of the observed data for lesion detection is critical to improve the sensitivity and minimize false positives of a CAD system. In this study, we propose a novel feature selection method mR-FAST that combines the minimal-redundancymaximal relevance (mRMR) framework with a selection metric FAST (feature assessment by sliding thresholds) based on the area under a ROC curve (AUC) generated on optimal simple linear discriminants. With three feature datasets extracted from CAD systems for colon polyps and bladder cancer, we show that the space of candidate features selected by mR-FAST is more characterizing for lesion detection with higher AUC, enabling to find a compact subset of superior features at low cost.

Parsimonious relevance models

NARCIS (Netherlands)

Meij, E.; Weerkamp, W.; Balog, K.; de Rijke, M.; Myang, S.-H.; Oard, D.W.; Sebastiani, F.; Chua, T.-S.; Leong, M.-K.

2008-01-01

We describe a method for applying parsimonious language models to re-estimate the term probabilities assigned by relevance models. We apply our method to six topic sets from test collections in five different genres. Our parsimonious relevance models (i) improve retrieval effectiveness in terms of

Mirror neurons and their clinical relevance.

Science.gov (United States)

Rizzolatti, Giacomo; Fabbri-Destro, Maddalena; Cattaneo, Luigi

2009-01-01

One of the most exciting events in neurosciences over the past few years has been the discovery of a mechanism that unifies action perception and action execution. The essence of this 'mirror' mechanism is as follows: whenever individuals observe an action being done by someone else, a set of neurons that code for that action is activated in the observers' motor system. Since the observers are aware of the outcome of their motor acts, they also understand what the other individual is doing without the need for intermediate cognitive mediation. In this Review, after discussing the most pertinent data concerning the mirror mechanism, we examine the clinical relevance of this mechanism. We first discuss the relationship between mirror mechanism impairment and some core symptoms of autism. We then outline the theoretical principles of neurorehabilitation strategies based on the mirror mechanism. We conclude by examining the relationship between the mirror mechanism and some features of the environmental dependency syndromes.

Ensemble based system for whole-slide prostate cancer probability mapping using color texture features.

LENUS (Irish Health Repository)

DiFranco, Matthew D

2011-01-01

We present a tile-based approach for producing clinically relevant probability maps of prostatic carcinoma in histological sections from radical prostatectomy. Our methodology incorporates ensemble learning for feature selection and classification on expert-annotated images. Random forest feature selection performed over varying training sets provides a subset of generalized CIEL*a*b* co-occurrence texture features, while sample selection strategies with minimal constraints reduce training data requirements to achieve reliable results. Ensembles of classifiers are built using expert-annotated tiles from training images, and scores for the probability of cancer presence are calculated from the responses of each classifier in the ensemble. Spatial filtering of tile-based texture features prior to classification results in increased heat-map coherence as well as AUC values of 95% using ensembles of either random forests or support vector machines. Our approach is designed for adaptation to different imaging modalities, image features, and histological decision domains.

Is the fluid mosaic (and the accompanying raft hypothesis a suitable model to describe fundamental features of biological membranes? What may be missing?

Directory of Open Access Journals (Sweden)

Luis Alberto Bagatolli

2013-11-01

Full Text Available The structure, dynamics, and stability of lipid bilayers are controlled by thermodynamic forces, leading to overall tensionless membranes with a distinct lateral organization and a conspicuous lateral pressure profile. Bilayers are also subject to built-in curvature-stress instabilities that may be released locally or globally in terms of morphological changes leading to the formation of non-lamellar and curved structures. A key controller of the bilayer’s propensity to form curved structures is the average molecular shape of the different lipid molecules. Via the curvature stress, molecular shape mediates a coupling to membrane-protein function and provides a set of physical mechanisms for formation of lipid domains and laterally differentiated regions in the plane of the membrane. Unfortunately, these relevant physical features of membranes are often ignored in the most popular models for biological membranes. Results from a number of experimental and theoretical studies emphasize the significance of these fundamental physical properties and call for a refinement of the fluid mosaic model (and the accompanying raft hypothesis.

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise.

Science.gov (United States)

Ahveninen, Jyrki; Hämäläinen, Matti; Jääskeläinen, Iiro P; Ahlfors, Seppo P; Huang, Samantha; Lin, Fa-Hsuan; Raij, Tommi; Sams, Mikko; Vasios, Christos E; Belliveau, John W

2011-03-08

How can we concentrate on relevant sounds in noisy environments? A "gain model" suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A "tuning model" suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMRI) while subjects attended to tones delivered to one ear and ignored opposite-ear inputs. The attended ear was switched every 30 s to quantify how quickly the effects evolve. To produce overlapping inputs, the tones were presented alone vs. during white-noise masking notch-filtered ±1/6 octaves around the tone center frequencies. Amplitude modulation (39 vs. 41 Hz in opposite ears) was applied for "frequency tagging" of attention effects on maskers. Noise masking reduced early (50-150 ms; N1) auditory responses to unattended tones. In support of the tuning model, selective attention canceled out this attenuating effect but did not modulate the gain of 50-150 ms activity to nonmasked tones or steady-state responses to the maskers themselves. These tuning effects originated at nonprimary auditory cortices, purportedly occupied by neurons that, without attention, have wider frequency tuning than ±1/6 octaves. The attentional tuning evolved rapidly, during the first few seconds after attention switching, and correlated with behavioral discrimination performance. In conclusion, a simple gain model alone cannot explain auditory selective attention. In nonprimary auditory cortices, attention-driven short-term plasticity retunes neurons to segregate relevant sounds from noise.

Abdominal tuberculosis: Imaging features

Energy Technology Data Exchange (ETDEWEB)

Pereira, Jose M. [Department of Radiology, Hospital de S. Joao, Porto (Portugal)]. E-mail: jmpjesus@yahoo.com; Madureira, Antonio J. [Department of Radiology, Hospital de S. Joao, Porto (Portugal); Vieira, Alberto [Department of Radiology, Hospital de S. Joao, Porto (Portugal); Ramos, Isabel [Department of Radiology, Hospital de S. Joao, Porto (Portugal)

2005-08-01

Radiological findings of abdominal tuberculosis can mimic those of many different diseases. A high level of suspicion is required, especially in high-risk population. In this article, we will describe barium studies, ultrasound (US) and computed tomography (CT) findings of abdominal tuberculosis (TB), with emphasis in the latest. We will illustrate CT findings that can help in the diagnosis of abdominal tuberculosis and describe imaging features that differentiate it from other inflammatory and neoplastic diseases, particularly lymphoma and Crohn's disease. As tuberculosis can affect any organ in the abdomen, emphasis is placed to ileocecal involvement, lymphadenopathy, peritonitis and solid organ disease (liver, spleen and pancreas). A positive culture or hystologic analysis of biopsy is still required in many patients for definitive diagnosis. Learning objectives:1.To review the relevant pathophysiology of abdominal tuberculosis. 2.Illustrate CT findings that can help in the diagnosis.

High blood lead levels are associated with lead concentrations in households and day care centers attended by Brazilian preschool children.

Science.gov (United States)

da Rocha Silva, Júlia Prestes; Salles, Fernanda Junqueira; Leroux, Isabelle Nogueira; da Silva Ferreira, Ana Paula Sacone; da Silva, Agnes Soares; Assunção, Nilson Antonio; Nardocci, Adelaide Cassia; Sayuri Sato, Ana Paula; Barbosa, Fernando; Cardoso, Maria Regina Alves; Olympio, Kelly Polido Kaneshiro

2018-08-01

A previous study observed high blood lead levels (BLL) in preschool children attending 50 day care centers (DCC) in São Paulo, Brazil. To identify whether lead levels found in both homes and DCC environments are associated with high blood lead levels. Children attending 4 DCCs, quoted here as NR, VA, PS and PF, were divided into two groups according to BLL: high exposure (HE: ≥13.9 μg/dL; 97.5 percentile of the 2013 year sample) and low exposure (LE: 600 μg/g, whereas such levels were observed in 77.1% of NR playground measurements. In VA DCC, 22% and 23% of the measurements in the building and in the playgrounds had levels higher than 600 μg/g, respectively. The percentage of high lead levels in the children's houses of the LE group was 5.9% (95% CI: 4.3-7.6%) and 13.2 (95% CI: 8.3-18.0%) in the HE group. Moreover, a significant association was found between high BLLs and lead levels found both in households and DCCs (p < 0.001). Most of the high lead measurements were found in tiles and playground equipment. Lead exposure estimated from the DCCs, where children spend about 10 h/day, can be as relevant as their household exposure. Therefore, public authorities should render efforts to provide a rigorous surveillance for lead-free painting supplies and for all objects offered to children. Copyright © 2018 Elsevier Ltd. All rights reserved.

BRIEF REPORT: Beyond Clinical Experience: Features of Data Collection and Interpretation That Contribute to Diagnostic Accuracy

Science.gov (United States)

Nendaz, Mathieu R; Gut, Anne M; Perrier, Arnaud; Louis-Simonet, Martine; Blondon-Choa, Katherine; Herrmann, François R; Junod, Alain F; Vu, Nu V

2006-01-01

BACKGROUND Clinical experience, features of data collection process, or both, affect diagnostic accuracy, but their respective role is unclear. OBJECTIVE, DESIGN Prospective, observational study, to determine the respective contribution of clinical experience and data collection features to diagnostic accuracy. METHODS Six Internists, 6 second year internal medicine residents, and 6 senior medical students worked up the same 7 cases with a standardized patient. Each encounter was audiotaped and immediately assessed by the subjects who indicated the reasons underlying their data collection. We analyzed the encounters according to diagnostic accuracy, information collected, organ systems explored, diagnoses evaluated, and final decisions made, and we determined predictors of diagnostic accuracy by logistic regression models. RESULTS Several features significantly predicted diagnostic accuracy after correction for clinical experience: early exploration of correct diagnosis (odds ratio [OR] 24.35) or of relevant diagnostic hypotheses (OR 2.22) to frame clinical data collection, larger number of diagnostic hypotheses evaluated (OR 1.08), and collection of relevant clinical data (OR 1.19). CONCLUSION Some features of data collection and interpretation are related to diagnostic accuracy beyond clinical experience and should be explicitly included in clinical training and modeled by clinical teachers. Thoroughness in data collection should not be considered a privileged way to diagnostic success. PMID:17105525

Dysmorphic features and developmental outcome of 2-year-old children

NARCIS (Netherlands)

Seggers, Jorien; Haadsma, Maaike L.; Bos, Arend F.; Heineman, Maas Jan; Middelburg, Karin J.; Van den Heuvel, Edwin R.; Hadders-Algra, Mijna

2014-01-01

AimThe aim of this study was to assess the associations between dysmorphic features and neurological, mental, psychomotor, and behavioural development in order to improve our understanding of aetiological pathways leading to minor developmental problems. MethodIn our cross-sectional study, 272

Upwelling features near Sri Lanka in the Bay of Bengal

Digital Repository Service at National Institute of Oceanography (India)

ShreeRam, P.; Rao, L.V.G.

, the southwest monsoon in summer and the northeast monsoon in winter. The wind stress associated with these winds cause mass drift of oceanic waters leading to upwelling and downwelling. The upwelling features in the Bay of Bengal with a special mention about...

Features of statistical dynamics in a finite system

International Nuclear Information System (INIS)

Yan, Shiwei; Sakata, Fumihiko; Zhuo Yizhong

2002-01-01

We study features of statistical dynamics in a finite Hamilton system composed of a relevant one degree of freedom coupled to an irrelevant multidegree of freedom system through a weak interaction. Special attention is paid on how the statistical dynamics changes depending on the number of degrees of freedom in the irrelevant system. It is found that the macrolevel statistical aspects are strongly related to an appearance of the microlevel chaotic motion, and a dissipation of the relevant motion is realized passing through three distinct stages: dephasing, statistical relaxation, and equilibrium regimes. It is clarified that the dynamical description and the conventional transport approach provide us with almost the same macrolevel and microlevel mechanisms only for the system with a very large number of irrelevant degrees of freedom. It is also shown that the statistical relaxation in the finite system is an anomalous diffusion and the fluctuation effects have a finite correlation time

A New Feature Selection Algorithm Based on the Mean Impact Variance

Directory of Open Access Journals (Sweden)

Weidong Cheng

2014-01-01

Full Text Available The selection of fewer or more representative features from multidimensional features is important when the artificial neural network (ANN algorithm is used as a classifier. In this paper, a new feature selection method called the mean impact variance (MIVAR method is proposed to determine the feature that is more suitable for classification. Moreover, this method is constructed on the basis of the training process of the ANN algorithm. To verify the effectiveness of the proposed method, the MIVAR value is used to rank the multidimensional features of the bearing fault diagnosis. In detail, (1 70-dimensional all waveform features are extracted from a rolling bearing vibration signal with four different operating states, (2 the corresponding MIVAR values of all 70-dimensional features are calculated to rank all features, (3 14 groups of 10-dimensional features are separately generated according to the ranking results and the principal component analysis (PCA algorithm and a back propagation (BP network is constructed, and (4 the validity of the ranking result is proven by training this BP network with these seven groups of 10-dimensional features and by comparing the corresponding recognition rates. The results prove that the features with larger MIVAR value can lead to higher recognition rates.

Coordination chemistry of two heavy metals: I, Ligand preferences in lead(II) complexation, toward the development of therapeutic agents for lead poisoning: II, Plutonium solubility and speciation relevant to the environment

Energy Technology Data Exchange (ETDEWEB)

Neu, Mary Patricia [Univ. of California, Berkeley, CA (United States)

1993-11-01

The coordination chemistry and solution behavior of the toxic ions lead(II) and plutonium(IV, V, VI) have been investigated. The ligand pK_as and ligand-lead(II) stability constants of one hydroxamic acid and four thiohydroaxamic acids were determined. Solution thermodynamic results indicate that thiohydroxamic acids are more acidic and slightly better lead chelators than hydroxamates, e.g., N-methylthioaceto-hydroxamic acid, pK_a = 5.94, logβ₁₂₀ = 10.92; acetohydroxamic acid, pK_a = 9.34, logβ₁₂₀ = 9.52. The syntheses of lead complexes of two bulky hydroxamate ligands are presented. The X-ray crystal structures show the lead hydroxamates are di-bridged dimers with irregular five-coordinate geometry about the metal atom and a stereochemically active lone pair of electrons. Molecular orbital calculations of a lead hydroxamate and a highly symmetric pseudo octahedral lead complex were performed. The thermodynamic stability of plutonium(IV) complexes of the siderophore, desferrioxamine B (DFO), and two octadentate derivatives of DFO were investigated using competition spectrophotometric titrations. The stability constant measured for the plutonium(IV) complex of DFO-methylterephthalamide is logβ₁₂₀ = 41.7. The solubility limited speciation of ²⁴²Pu as a function of time in near neutral carbonate solution was measured. Individual solutions of plutonium in a single oxidation state were added to individual solutions at pH = 6.0, T = 30.0, 1.93 mM dissolved carbonate, and sampled over intervals up to 150 days. Plutonium solubility was measured, and speciation was investigated using laser photoacoustic spectroscopy and chemical methods.

Introduction to Special Feature on Catastrophic Thresholds, Perspectives, Definitions, and Applications

Directory of Open Access Journals (Sweden)

Robert A. Washington-Allen

2010-09-01

Full Text Available The contributions to this special feature focus on several conceptual and operational applications for understanding non-linear behavior of complex systems with various ecological criteria at unique levels of organization. The organizing theme of the feature emphasizes alternative stable states or regimes and intervening thresholds that possess great relevance to ecology and natural resource management. The authors within this special feature address the conceptual models of catastrophe theory, self-organization, cross-scale interactions and time-scale calculus; develop operational definitions and procedures for understanding the occurrence of dynamic regimes or multiple stable states and thresholds; suggest diagnostics tools for detection of states and thresholds and contribute to the development of scaling laws; and finally, demonstrate applications that promote both greater ecological understanding and management prescriptions for insect and disease outbreaks, resource island formation, and characterization of ecological resilience. This Special Feature concludes with a synthesis of the commonalities and disparities of concepts and interpretations among the contributed papers to identify issues and approaches that merit further research emphasis.

Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data

Science.gov (United States)

Gaspar-Cunha, A.; Recio, G.; Costa, L.; Estébanez, C.

2014-01-01

Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier. PMID:24707201

More than a filter: Feature-based attention regulates the distribution of visual working memory resources.

Science.gov (United States)

Dube, Blaire; Emrich, Stephen M; Al-Aidroos, Naseem

2017-10-01

Across 2 experiments we revisited the filter account of how feature-based attention regulates visual working memory (VWM). Originally drawing from discrete-capacity ("slot") models, the filter account proposes that attention operates like the "bouncer in the brain," preventing distracting information from being encoded so that VWM resources are reserved for relevant information. Given recent challenges to the assumptions of discrete-capacity models, we investigated whether feature-based attention plays a broader role in regulating memory. Both experiments used partial report tasks in which participants memorized the colors of circle and square stimuli, and we provided a feature-based goal by manipulating the likelihood that 1 shape would be probed over the other across a range of probabilities. By decomposing participants' responses using mixture and variable-precision models, we estimated the contributions of guesses, nontarget responses, and imprecise memory representations to their errors. Consistent with the filter account, participants were less likely to guess when the probed memory item matched the feature-based goal. Interestingly, this effect varied with goal strength, even across high probabilities where goal-matching information should always be prioritized, demonstrating strategic control over filter strength. Beyond this effect of attention on which stimuli were encoded, we also observed effects on how they were encoded: Estimates of both memory precision and nontarget errors varied continuously with feature-based attention. The results offer support for an extension to the filter account, where feature-based attention dynamically regulates the distribution of resources within working memory so that the most relevant items are encoded with the greatest precision. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Proatherogenic pathways leading to vascular calcification

International Nuclear Information System (INIS)

Mazzini, Michael J.; Schulze, P. Christian

2006-01-01

Cardiovascular disease is the leading cause of morbidity and mortality in the western world and atherosclerosis is the major common underlying disease. The pathogenesis of atherosclerosis involves local vascular injury, inflammation and oxidative stress as well as vascular calcification. Vascular calcification has long been regarded as a degenerative process leading to mineral deposition in the vascular wall characteristic for late stages of atherosclerosis. However, recent studies identified vascular calcification in early stages of atherosclerosis and its occurrence has been linked to clinical events in patients with cardiovascular disease. Its degree correlates with local vascular inflammation and with the overall impact and the progression of atherosclerosis. Over the last decade, diverse and highly regulated molecular signaling cascades controlling vascular calcification have been described. Local and circulating molecules such as osteopontin, osteoprogerin, leptin and matrix Gla protein were identified as critical regulators of vascular calcification. We here review the current knowledge on molecular pathways of vascular calcification and their relevance for the progression of cardiovascular disease

Sport science relevance and application: perceptions of UK coaches.

Science.gov (United States)

Martindale, Russell; Nash, Christine

2013-01-01

While sport science can have significant and positive impact on coaches and athletes, there is still a general consensus that the transfer of sport science knowledge to coaching is poor. Given this apparent dilemma, this study investigated the perceptions of sport science from coaches across four different sports (football, rugby league, curling and judo) across three different levels (elite, developmental and novice). Specifically, 58 coaches (19 football; 21 rugby league; 9 curling; 9 judo) drawn evenly from novice, developmental and elite groups agreed to take part and were interviewed. Three key features emerged from the analysis 1) Practical application and relevance 2) Integration and access, 3) Language. In short, there was significant variability in the extent to which sport science was considered relevant and to whom, although interestingly this was not strongly related to coaching level. This inconsistency of understanding was a barrier to sport science engagement in some instances, as was the challenge of operationalising information for specific contexts. Furthermore, availability of opportunities and resources were often left to chance, while overuse of jargon and inability for research and practitioners to consider sport specific needs were also considered barriers to engagement. Implications for research and practice are discussed.

THE RELEVANCE OF MANAGEMENT ACCOUNTING FOR THE HOSPITALITY INDUSTRY

Directory of Open Access Journals (Sweden)

Briciu Sorin

2012-07-01

Full Text Available In the contemporary period the tourism and hospitality industry has experienced dynamic growth despite the challenges facing not only the global crisis, but also market changes, consumer behavior and technological trends. Accounting, the language of business is required to keep up with changes made to each particular area of activity so that they can provide timely relevant information to be managed by an efficient information system. Our article focuses on presenting the importance of management accounting and cost information system in the hospitality industry, then consider identifying features of this sector and their impact on accounting. The methodology of our research falls within the economic research, being theoretical, aiming primarily to knowledge objectives and the relevance of management accounting for economic entities, and then we have the characteristics of hospitality industry and possible organizational management accounting in this sector. In our perspective cost calculation for services, packages or travel benefits must take into account the development of the accounts from Class 9, so we propose a possible method to customize them according to the Direct Costing and CVP analysis. Our research will also be explanatory descriptive, trying to answer the questions How? and Why?

Acromegaly: clinical features at diagnosis.

Science.gov (United States)

Vilar, Lucio; Vilar, Clarice Freitas; Lyra, Ruy; Lyra, Raissa; Naves, Luciana A

2017-02-01

Acromegaly is a rare and underdiagnosed disorder caused, in more than 95% of cases, by a growth hormone (GH)-secreting pituitary adenoma. The GH hypersecretion leads to overproduction of insulin-like growth factor 1 (IGF-1) which results in a multisystem disease characterized by somatic overgrowth, multiple comorbidities, physical disfigurement, and increased mortality. This article aims to review the clinical features of acromegaly at diagnosis. Acromegaly affects both males and females equally and the average age at diagnosis ranges from 40 to 50 years (up to 5% of cases acromegaly is often diagnosed five to more than ten years after its onset. The typical coarsening of facial features include furrowing of fronthead, pronounced brow protrusion, enlargement of the nose and the ears, thickening of the lips, skin wrinkles and nasolabial folds, as well as mandibular prognathism that leads to dental malocclusion and increased interdental spacing. Excessive growth of hands and feet (predominantly due to soft tissue swelling) is present in the vast majority of acromegalic patients. Gigantism accounts for up to 5% of cases and occurs when the excess of GH becomes manifest in the young, before the epiphyseal fusion. The disease also has rheumatologic, cardiovascular, respiratory, neoplastic, neurological, and metabolic manifestations which negatively impact its prognosis and patients quality of life. Less than 15% of acromegalic patients actively seek medical attention for change in appearance or enlargement of the extremities. The presentation of acromegaly is more often related to its systemic comorbidities or to local tumor effects.

[Hospital financing in 2016. Relevant changes for rheumatology].

Science.gov (United States)

Fiori, W; Bunzemeier, H; Lakomek, H-J; Buscham, K; Lehmann, H; Fuchs, A-K; Bessler, F; Roeder, N

2016-03-01

Hospital financing 2016 will be influenced by the prospects of the approaching considerable changes. It is assumed that the following years will lead to a considerable reallocation of financial resources between hospitals. While not directly targeted by new regulations, reallocations always also affect specialties like rheumatology. Compared to the alterations in the legislative framework the financial effects of the yearly adaptation of the German diagnosis-related groups system are subordinate. Only by comprehensive consideration of current and expected changes a forward-looking and sustainable strategy can be developed. The following article presents the relevant changes and discusses the consequences for hospitals specialized in rheumatology.

Impact of Non Accounting Information on The Value Relevance of Accounting Information: The Case of Jordan

Directory of Open Access Journals (Sweden)

DHIAA SHAMKI

2013-07-01

Full Text Available The paper presents empirical evidence about the impact of firm’s shareholders number as non accounting information on the value relevance of its earnings and book value of equity as accounting information for Jordanian industrial firms for the period from 1993 to 2002. Employing the return regression analysis and using shareholders number in two proxies namely local and foreign shareholders number, the findings of the study are fourfold. First, Individual earnings are value relevant while book value is irrelevant. Second, combining earnings with book value leads both of them to be irrelevant. Third, extending local shareholders number has significant impact on the value relevance of individual and combined earnings. Forth, extending foreign shareholders number has significant impact on the value relevance of individual book value and combined earnings. Since studies on the value relevance of these variables have neglected Jordan (and the Middle Eastern region, the study is the first especially in Jordan that tries to fill this gap by examiningthe impact of shareholders numbers on the value relevance of earnings and book valueto indicate firm value.

FEATURES OF USING WEBINARS FOR DEVELOPMENT OF SPIRITUAL AND MORAL VALUES IN INFORMAL ADULTS EDUCATION

Directory of Open Access Journals (Sweden)

Iryna S. Pichuhina

2014-10-01

Full Text Available The purpose of this article is to examine the features of using webinars for the development of spiritual and moral values in the non-formal adult education. Actualization of the problem of spirituality formation is associated with the modern requirements to moral features of adults arising from their special social function of influence on the formation of spiritual values of younger generation. Conducting psychological and educational on-line workshops, lectures, consultations for adults arising from problems of misunderstanding or loss of key moral features is relevant and demanded. As a form of such interaction the webinar is suggested as an ICT-tool used in non-formal adults education.

Extraction of lead and ridge characteristics from SAR images of sea ice

Science.gov (United States)

Vesecky, John F.; Smith, Martha P.; Samadani, Ramin

1990-01-01

Image-processing techniques for extracting the characteristics of lead and pressure ridge features in SAR images of sea ice are reported. The methods are applied to a SAR image of the Beaufort Sea collected from the Seasat satellite on October 3, 1978. Estimates of lead and ridge statistics are made, e.g., lead and ridge density (number of lead or ridge pixels per unit area of image) and the distribution of lead area and orientation as well as ridge length and orientation. The information derived is useful in both ice science and polar operations for such applications as albedo and heat and momentum transfer estimates, as well as ship routing and offshore engineering.

Predicting the presence and cover of management relevant invasive plant species on protected areas.

Science.gov (United States)

Iacona, Gwenllian; Price, Franklin D; Armsworth, Paul R

2016-01-15

Invasive species are a management concern on protected areas worldwide. Conservation managers need to predict infestations of invasive plants they aim to treat if they want to plan for long term management. Many studies predict the presence of invasive species, but predictions of cover are more relevant for management. Here we examined how predictors of invasive plant presence and cover differ across species that vary in their management priority. To do so, we used data on management effort and cover of invasive plant species on central Florida protected areas. Using a zero-inflated multiple regression framework, we showed that protected area features can predict the presence and cover of the focal species but the same features rarely explain both. There were several predictors of either presence or cover that were important across multiple species. Protected areas with three days of frost per year or fewer were more likely to have occurrences of four of the six focal species. When invasive plants were present, their proportional cover was greater on small preserves for all species, and varied with surrounding household density for three species. None of the predictive features were clearly related to whether species were prioritized for management or not. Our results suggest that predictors of cover and presence can differ both within and across species but do not covary with management priority. We conclude that conservation managers need to select predictors of invasion with care as species identity can determine the relationship between predictors of presence and the more management relevant predictors of cover. Copyright © 2015 Elsevier Ltd. All rights reserved.

Feature Extraction and Fusion Using Deep Convolutional Neural Networks for Face Detection

Directory of Open Access Journals (Sweden)

Xiaojun Lu

2017-01-01

Full Text Available This paper proposes a method that uses feature fusion to represent images better for face detection after feature extraction by deep convolutional neural network (DCNN. First, with Clarifai net and VGG Net-D (16 layers, we learn features from data, respectively; then we fuse features extracted from the two nets. To obtain more compact feature representation and mitigate computation complexity, we reduce the dimension of the fused features by PCA. Finally, we conduct face classification by SVM classifier for binary classification. In particular, we exploit offset max-pooling to extract features with sliding window densely, which leads to better matches of faces and detection windows; thus the detection result is more accurate. Experimental results show that our method can detect faces with severe occlusion and large variations in pose and scale. In particular, our method achieves 89.24% recall rate on FDDB and 97.19% average precision on AFW.

Uncertainty calculations for the measurement of in vivo bone lead by x-ray fluorescence

International Nuclear Information System (INIS)

O'Meara, J M; Fleming, D E B

2009-01-01

In order to quantify the bone lead concentration from an in vivo x-ray fluorescence measurement, typically two estimates of the lead concentration are determined by comparing the normalized x-ray peak amplitudes from the Kα 1 and Kβ 1 features to those of the calibration phantoms. In each case, the normalization consists of taking the ratio of the x-ray peak amplitude to the amplitude of the coherently scattered photon peak in the spectrum. These two Pb concentration estimates are then used to determine the weighted mean lead concentration of that sample. In calculating the uncertainties of these measurements, it is important to include any covariance terms where appropriate. When determining the uncertainty of the lead concentrations from each x-ray peak, the standard approach does not include covariance between the x-ray peaks and the coherently scattered feature. These spectral features originate from two distinct physical processes, and therefore no covariance between these features can exist. Through experimental and simulated data, we confirm that there is no observed covariance between the detected Pb x-ray peaks and the coherently scattered photon signal, as expected. This is in direct contrast to recent work published by Brito (2006 Phys. Med. Biol. 51 6125-39). There is, however, covariance introduced in the calculation of the weighted mean lead concentration due to the common coherent normalization. This must be accounted for in calculating the uncertainty of the weighted mean lead concentration, as is currently the case. We propose here an alternative approach to calculating the weighted mean lead concentration in such a way as to eliminate the covariance introduced by the common coherent normalization. It should be emphasized that this alternative approach will only apply in situations in which the calibration line intercept is not included in the calculation of the Pb concentration from the spectral data: when the source of the intercept is well

Pulmonary vasculitis: imaging features

International Nuclear Information System (INIS)

Seo, Joon Beom; Im, Jung Gi; Chung, Jin Wook; Goo, Jin Mo; Park, Jae Hyung; Yeon, Kyung Mo; Song, Jae Woo

1999-01-01

Vasculitis is defined as an inflammatory process involving blood vessels, and can lead to destruction of the vascular wall and ischemic damage to the organs supplied by these vessels. The lung is commonly affected. A number of attempts have been made to classify and organize pulmonary vasculitis, but because the clinical manifestations and pathologic features of the condition overlap considerably, these afforts have failed to achieve a consensus. We classified pulmonary vasculitis as belonging to either the angitiis-granulomatosis group, the diffuse pulmonary hemorrhage with capillaritis group, or 'other'. Characteristic radiographic and CT findings of the different types of pulmonary vasculitis are illustrated, with a brief discussion of the respective disease entities

Major depressive disorder with psychotic features may lead to misdiagnosis of dementia: a case report and review of the literature.

Science.gov (United States)

Wagner, Gerhardt S; McClintock, Shawn M; Rosenquist, Peter B; McCall, W Vaughn; Kahn, David A

2011-11-01

Major depressive disorder (MDD) with psychotic features is relatively frequent in patients with greater depressive symptom severity and is associated with a poorer course of illness and greater functional impairment than MDD without psychotic features. Multiple studies have found that patients with psychotic mood disorders demonstrate significantly poorer cognitive performance in a variety of areas than those with nonpsychotic mood disorders. The Mini Mental State Examination (MMSE) and the Dementia Rating Scale, Second Edition (DRS-2) are widely used to measure cognitive functions in research on MDD with psychotic features. Established total raw score cut-offs of 24 on the MMSE and 137 on the DRS-2 in published manuals suggest possible global cognitive impairment and dementia, respectively. Limited research is available on these suggested cut-offs for patients with MDD with psychotic features. We document the therapeutic benefit of electroconvulsive therapy (ECT), which is usually associated with short-term cognitive impairment, in a 68-year-old woman with psychotic depression whose MMSE and DRS-2 scores initially suggested possible global cognitive impairment and dementia. Over the course of four ECT treatments, the patient's MMSE scores progressively increased. After the second ECT treatment, the patient no longer met criteria for global cognitive impairment. With each treatment, depression severity, measured by the 24-item Hamilton Rating Scale for Depression, improved sequentially. Thus, the suggested cut-off scores for the MMSE and the DRS-2 in patients with MDD with psychotic features may in some cases produce false-positive indications of dementia.

Shape-Tailored Features and their Application to Texture Segmentation

KAUST Repository

Khan, Naeemullah

2014-04-01

Texture Segmentation is one of the most challenging areas of computer vision. One reason for this difficulty is the huge variety and variability of textures occurring in real world, making it very difficult to quantitatively study textures. One of the key tools used for texture segmentation is local invariant descriptors. Texture consists of textons, the basic building block of textures, that may vary by small nuisances like illumination variation, deformations, and noise. Local invariant descriptors are robust to these nuisances making them beneficial for texture segmentation. However, grouping dense descriptors directly for segmentation presents a problem: existing descriptors aggregate data from neighborhoods that may contain different textured regions, making descriptors from these neighborhoods difficult to group, leading to significant errors in segmentation. This work addresses this issue by proposing dense local descriptors, called Shape-Tailored Features, which are tailored to an arbitrarily shaped region, aggregating data only within the region of interest. Since the segmentation, i.e., the regions, are not known a-priori, we propose a joint problem for Shape-Tailored Features and the regions. We present a framework based on variational methods. Extensive experiments on a new large texture dataset, which we introduce, show that the joint approach with Shape-Tailored Features leads to better segmentations over the non-joint non Shape-Tailored approach, and the method out-performs existing state-of-the-art.

Somatic mutations associated with MRI-derived volumetric features in glioblastoma

Energy Technology Data Exchange (ETDEWEB)

Gutman, David A.; Dunn, William D. [Emory University School of Medicine, Departments of Neurology, Atlanta, GA (United States); Emory University School of Medicine, Biomedical Informatics, Atlanta, GA (United States); Grossmann, Patrick; Alexander, Brian M. [Harvard Medical School, Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women' s Hospital, Boston, MA (United States); Cooper, Lee A.D. [Emory University School of Medicine, Biomedical Informatics, Atlanta, GA (United States); Georgia Institute of Technology, Department of Biomedical Engineering, Atlanta, GA (United States); Holder, Chad A. [Emory University School of Medicine, Radiology and Imaging Sciences, Atlanta, GA (United States); Ligon, Keith L. [Brigham and Women' s Hospital, Harvard Medical School, Pathology, Dana-Farber Cancer Institute, Boston, MA (United States); Aerts, Hugo J.W.L. [Harvard Medical School, Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women' s Hospital, Boston, MA (United States); Brigham and Women' s Hospital, Harvard Medical School, Radiology, Dana-Farber Cancer Institute, Boston, MA (United States)

2015-12-15

MR imaging can noninvasively visualize tumor phenotype characteristics at the macroscopic level. Here, we investigated whether somatic mutations are associated with and can be predicted by MRI-derived tumor imaging features of glioblastoma (GBM). Seventy-six GBM patients were identified from The Cancer Imaging Archive for whom preoperative T1-contrast (T1C) and T2-FLAIR MR images were available. For each tumor, a set of volumetric imaging features and their ratios were measured, including necrosis, contrast enhancing, and edema volumes. Imaging genomics analysis assessed the association of these features with mutation status of nine genes frequently altered in adult GBM. Finally, area under the curve (AUC) analysis was conducted to evaluate the predictive performance of imaging features for mutational status. Our results demonstrate that MR imaging features are strongly associated with mutation status. For example, TP53-mutated tumors had significantly smaller contrast enhancing and necrosis volumes (p = 0.012 and 0.017, respectively) and RB1-mutated tumors had significantly smaller edema volumes (p = 0.015) compared to wild-type tumors. MRI volumetric features were also found to significantly predict mutational status. For example, AUC analysis results indicated that TP53, RB1, NF1, EGFR, and PDGFRA mutations could each be significantly predicted by at least one imaging feature. MRI-derived volumetric features are significantly associated with and predictive of several cancer-relevant, drug-targetable DNA mutations in glioblastoma. These results may shed insight into unique growth characteristics of individual tumors at the macroscopic level resulting from molecular events as well as increase the use of noninvasive imaging in personalized medicine. (orig.)

Somatic mutations associated with MRI-derived volumetric features in glioblastoma

International Nuclear Information System (INIS)

Gutman, David A.; Dunn, William D.; Grossmann, Patrick; Alexander, Brian M.; Cooper, Lee A.D.; Holder, Chad A.; Ligon, Keith L.; Aerts, Hugo J.W.L.

2015-01-01

MR imaging can noninvasively visualize tumor phenotype characteristics at the macroscopic level. Here, we investigated whether somatic mutations are associated with and can be predicted by MRI-derived tumor imaging features of glioblastoma (GBM). Seventy-six GBM patients were identified from The Cancer Imaging Archive for whom preoperative T1-contrast (T1C) and T2-FLAIR MR images were available. For each tumor, a set of volumetric imaging features and their ratios were measured, including necrosis, contrast enhancing, and edema volumes. Imaging genomics analysis assessed the association of these features with mutation status of nine genes frequently altered in adult GBM. Finally, area under the curve (AUC) analysis was conducted to evaluate the predictive performance of imaging features for mutational status. Our results demonstrate that MR imaging features are strongly associated with mutation status. For example, TP53-mutated tumors had significantly smaller contrast enhancing and necrosis volumes (p = 0.012 and 0.017, respectively) and RB1-mutated tumors had significantly smaller edema volumes (p = 0.015) compared to wild-type tumors. MRI volumetric features were also found to significantly predict mutational status. For example, AUC analysis results indicated that TP53, RB1, NF1, EGFR, and PDGFRA mutations could each be significantly predicted by at least one imaging feature. MRI-derived volumetric features are significantly associated with and predictive of several cancer-relevant, drug-targetable DNA mutations in glioblastoma. These results may shed insight into unique growth characteristics of individual tumors at the macroscopic level resulting from molecular events as well as increase the use of noninvasive imaging in personalized medicine. (orig.)

Tracing the breeding farm of domesticated pig using feature selection (

Directory of Open Access Journals (Sweden)

Taehyung Kwon

2017-11-01

Full Text Available Objective Increasing food safety demands in the animal product market have created a need for a system to trace the food distribution process, from the manufacturer to the retailer, and genetic traceability is an effective method to trace the origin of animal products. In this study, we successfully achieved the farm tracing of 6,018 multi-breed pigs, using single nucleotide polymorphism (SNP markers strictly selected through least absolute shrinkage and selection operator (LASSO feature selection. Methods We performed farm tracing of domesticated pig (Sus scrofa from SNP markers and selected the most relevant features for accurate prediction. Considering multi-breed composition of our data, we performed feature selection using LASSO penalization on 4,002 SNPs that are shared between breeds, which also includes 179 SNPs with small between-breed difference. The 100 highest-scored features were extracted from iterative simulations and then evaluated using machine-leaning based classifiers. Results We selected 1,341 SNPs from over 45,000 SNPs through iterative LASSO feature selection, to minimize between-breed differences. We subsequently selected 100 highest-scored SNPs from iterative scoring, and observed high statistical measures in classification of breeding farms by cross-validation only using these SNPs. Conclusion The study represents a successful application of LASSO feature selection on multi-breed pig SNP data to trace the farm information, which provides a valuable method and possibility for further researches on genetic traceability.

Finding Combination of Features from Promoter Regions for Ovarian Cancer-related Gene Group Classification

KAUST Repository

Olayan, Rawan S.

2012-01-01

In classification problems, it is always important to use the suitable combination of features that will be employed by classifiers. Generating the right combination of features usually results in good classifiers. In the situation when the problem is not well understood, data items are usually described by many features in the hope that some of these may be the relevant or most relevant ones. In this study, we focus on one such problem related to genes implicated in ovarian cancer (OC). We try to recognize two important OC-related gene groups: oncogenes, which support the development and progression of OC, and oncosuppressors, which oppose such tendencies. For this, we use the properties of promoters of these genes. We identified potential “regulatory features” that characterize OC-related oncogenes and oncosuppressors promoters. In our study, we used 211 oncogenes and 39 oncosuppressors. For these, we identified 538 characteristic sequence motifs from their promoters. Promoters are annotated by these motifs and derived feature vectors used to develop classification models. We made a comparison of a number of classification models in their ability to distinguish oncogenes from oncosuppressors. Based on 10-fold cross-validation, the resultant model was able to separate the two classes with sensitivity of 96% and specificity of 100% with the complete set of features. Moreover, we developed another recognition model where we attempted to distinguish oncogenes and oncosuppressors as one group from other OC-related genes. That model achieved accuracy of 82%. We believe that the results of this study will help in discovering other OC-related oncogenes and oncosuppressors not identified as yet.

Finding Combination of Features from Promoter Regions for Ovarian Cancer-related Gene Group Classification

KAUST Repository

Olayan, Rawan S.

2012-12-01

In classification problems, it is always important to use the suitable combination of features that will be employed by classifiers. Generating the right combination of features usually results in good classifiers. In the situation when the problem is not well understood, data items are usually described by many features in the hope that some of these may be the relevant or most relevant ones. In this study, we focus on one such problem related to genes implicated in ovarian cancer (OC). We try to recognize two important OC-related gene groups: oncogenes, which support the development and progression of OC, and oncosuppressors, which oppose such tendencies. For this, we use the properties of promoters of these genes. We identified potential “regulatory features” that characterize OC-related oncogenes and oncosuppressors promoters. In our study, we used 211 oncogenes and 39 oncosuppressors. For these, we identified 538 characteristic sequence motifs from their promoters. Promoters are annotated by these motifs and derived feature vectors used to develop classification models. We made a comparison of a number of classification models in their ability to distinguish oncogenes from oncosuppressors. Based on 10-fold cross-validation, the resultant model was able to separate the two classes with sensitivity of 96% and specificity of 100% with the complete set of features. Moreover, we developed another recognition model where we attempted to distinguish oncogenes and oncosuppressors as one group from other OC-related genes. That model achieved accuracy of 82%. We believe that the results of this study will help in discovering other OC-related oncogenes and oncosuppressors not identified as yet.

Sens et temps de la Gestalt (Gestalt theory: critical overview and contemporary relevance)

OpenAIRE

Rosenthal, Victor; Visetti, Yves-Marie

1999-01-01

Rather than mere psychological doctrine, Gestalt theory was conceived of as a general theory of form and organization deemed to lay a unified groundwork for several domains of scientific endeavor. Our aim in this article is to assess the legacy of this framework, and examine its relevance for present-day research in cognitive science. We thus survey the intellectual contexts within which Gestalt theory originated and evolved, and review some of its central features: a phenomenological approac...

Automated Diatom Classification (Part A: Handcrafted Feature Approaches

Directory of Open Access Journals (Sweden)

Gloria Bueno

2017-07-01

Full Text Available This paper deals with automatic taxa identification based on machine learning methods. The aim is therefore to automatically classify diatoms, in terms of pattern recognition terminology. Diatoms are a kind of algae microorganism with high biodiversity at the species level, which are useful for water quality assessment. The most relevant features for diatom description and classification have been selected using an extensive dataset of 80 taxa with a minimum of 100 samples/taxon augmented to 300 samples/taxon. In addition to published morphological, statistical and textural descriptors, a new textural descriptor, Local Binary Patterns (LBP, to characterize the diatom’s valves, and a log Gabor implementation not tested before for this purpose are introduced in this paper. Results show an overall accuracy of 98.11% using bagging decision trees and combinations of descriptors. Finally, some phycological features of diatoms that are still difficult to integrate in computer systems are discussed for future work.

Science youth action research: Promoting critical science literacy through relevance and agency

Science.gov (United States)

Coleman, Elizabeth R.

This three-article dissertation presents complementary perspectives on Science Youth Action Research (Sci-YAR), a K-12 curriculum designed to emphasize relevance and agency to promote youth's science learning. In Sci-YAR, youth conduct action research projects to better understand science-related issues in their lives, schools, or communities, while they simultaneously document, analyze, and reflect upon their own practices as researchers. The first article defines Sci-YAR and argues for its potential to enhance youth's participation as citizens in a democratic society. The second article details findings from a case study of youth engaged in Sci-YAR, describing how the curriculum enabled and constrained youth's identity work in service of critical science agency. The third article provides guidance to science teachers in implementing student-driven curriculum and instruction by emphasizing Sci-YAR's key features as a way to promote student agency and relevance in school science.

The endocannabinoid system and its relevance for nutrition

DEFF Research Database (Denmark)

Maccarrone, Mauro; Gasperi, Valeria; Catani, Maria Valeria

2010-01-01

Endocannabinoids bind to cannabinoid, vanilloid, and peroxisome proliferator-activated receptors. The biological actions of these polyunsaturated lipids are controlled by key agents responsible for their synthesis, transport and degradation, which together form an endocannabinoid system (ECS......). In the past few years, evidence has been accumulated for a role of the ECS in regulating food intake and energy balance, both centrally and peripherally. In addition, up-regulation of the ECS in the gastrointestinal tract has a potential impact on inflammatory bowel diseases. In this review, the main features...... of the ECS are summarized in order to put in better focus our current knowledge of the nutritional relevance of endocannabinoid signaling and of its role in obesity, cardiovascular pathologies, and gastrointestinal diseases. The central and peripheral pathways that underlie these effects are discussed...

A window-based time series feature extraction method.

Science.gov (United States)

Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

2017-10-01

This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reduced TET2 function leads to T-cell lymphoma with follicular helper T-cell-like features in mice

International Nuclear Information System (INIS)

Muto, H; Sakata-Yanagimoto, M; Nagae, G; Shiozawa, Y; Miyake, Y; Yoshida, K; Enami, T; Kamada, Y; Kato, T; Uchida, K; Nanmoku, T; Obara, N; Suzukawa, K; Sanada, M; Nakamura, N; Aburatani, H; Ogawa, S; Chiba, S

2014-01-01

TET2 (Ten Eleven Translocation 2) is a dioxygenase that converts methylcytosine (mC) to hydroxymethylcytosine (hmC). TET2 loss-of-function mutations are highly frequent in subtypes of T-cell lymphoma that harbor follicular helper T (Tfh)-cell-like features, such as angioimmunoblastic T-cell lymphoma (30–83%) or peripheral T-cell lymphoma, not otherwise specified (10–49%), as well as myeloid malignancies. Here, we show that middle-aged Tet2 knockdown (Tet2 gt/gt ) mice exhibit Tfh-like cell overproduction in the spleen compared with control mice. The Tet2 knockdown mice eventually develop T-cell lymphoma with Tfh-like features after a long latency (median 67 weeks). Transcriptome analysis revealed that these lymphoma cells had Tfh-like gene expression patterns when compared with splenic CD4-positive cells of wild-type mice. The lymphoma cells showed lower hmC densities around the transcription start site (TSS) and higher mC densities at the regions of the TSS, gene body and CpG islands. These epigenetic changes, seen in Tet2 insufficiency-triggered lymphoma, possibly contributed to predated outgrowth of Tfh-like cells and subsequent lymphomagenesis. The mouse model described here suggests that TET2 mutations play a major role in the development of T-cell lymphoma with Tfh-like features in humans

Accelerating Relevance Vector Machine for Large-Scale Data on Spark

Directory of Open Access Journals (Sweden)

Liu Fang

2017-01-01

Full Text Available Relevance vector machine (RVM is a machine learning algorithm based on a sparse Bayesian framework, which performs well when running classification and regression tasks on small-scale datasets. However, RVM also has certain drawbacks which restricts its practical applications such as (1 slow training process, (2 poor performance on training large-scale datasets. In order to solve these problem, we propose Discrete AdaBoost RVM (DAB-RVM which incorporate ensemble learning in RVM at first. This method performs well with large-scale low-dimensional datasets. However, as the number of features increases, the training time of DAB-RVM increases as well. To avoid this phenomenon, we utilize the sufficient training samples of large-scale datasets and propose all features boosting RVM (AFB-RVM, which modifies the way of obtaining weak classifiers. In our experiments we study the differences between various boosting techniques with RVM, demonstrating the performance of the proposed approaches on Spark. As a result of this paper, two proposed approaches on Spark for different types of large-scale datasets are available.

Chronic actinic dermatitis - A study of clinical features

Directory of Open Access Journals (Sweden)

Somani Vijay

2005-01-01

Full Text Available Background: Chronic actinic dermatitis (CAD, one of the immune mediated photo-dermatoses, comprises a spectrum of conditions including persistent light reactivity, photosensitive eczema and actinic reticuloid. Diagnostic criteria were laid down about 20 years back, but clinical features are the mainstay in diagnosis. In addition to extreme sensitivity to UVB, UVA and/or visible light, about three quarters of patients exhibit contact sensitivity to several allergens, which may contribute to the etiopathogenesis of CAD. This study was undertaken to examine the clinical features of CAD in India and to evaluate the relevance of patch testing and photo-aggravation testing in the diagnosis of CAD. Methods: The clinical data of nine patients with CAD were analyzed. Histopathology, patch testing and photo-aggravation testing were also performed. Results: All the patients were males. The average age of onset was 57 years. The first episode was usually noticed in the beginning of summer. Later the disease gradually tended to be perennial, without any seasonal variations. The areas affected were mainly the photo-exposed areas in all patients, and the back in three patients. Erythroderma was the presenting feature in two patients. The palms and soles were involved in five patients. Patch testing was positive in seven of nine patients. Conclusions: The diagnosis of CAD mainly depended upon the history and clinical features. The incidence of erythroderma and palmoplantar eczema was high in our series. Occupation seems to play a role in the etiopathogenesis of CAD.

Experience of 12 kA / 16 V SMPS during the HTS Current Leads Test

Science.gov (United States)

Panchal, P.; Christian, D.; Panchal, R.; Sonara, D.; Purwar, G.; Garg, A.; Nimavat, H.; Singh, G.; Patel, J.; Tanna, V.; Pradhan, S.

2017-04-01

As a part of up gradation plans in SST-1 Tokamak, one pair of 3.3 kA rated prototype hybrid current leads were developed using Di-BSCCO as High Temperature Superconductors (HTS) and the copper heat exchanger. In order to validate the manufacturing procedure prior to go for series production of such current leads, it was recommended to test these current leads using dedicated and very reliable DC switch mode power supply (SMPS). As part of test facility, 12 kA, 16 VDC programmable SMPS was successfully installed, commissioned and tested. This power supply has special features such as modularity, N+1 redundancy, very low ripple voltage, precise current measurements with Direct Current Current Transformer, CC/CV modes with auto-crossover and auto-sequence programming. As a part of acceptance of this converter, A 5.8 mΩ water-cooled resistive dummy load and PLC based SCADA system is designed, developed for commissioning of power supply. The same power supply was used for the testing of the prototype HTS current leads. The paper describes the salient features and experience of state-of-art of power supply and results obtained from this converter during the HTS current leads test.

TOPICAL REVIEW: Progress in engineering high strain lead-free piezoelectric ceramics

Science.gov (United States)

Leontsev, Serhiy O.; Eitel, Richard E.

2010-08-01

Environmental concerns are strongly driving the need to replace the lead-based piezoelectric materials currently employed as multilayer actuators. The current review describes both compositional and structural engineering approaches to achieve enhanced piezoelectric properties in lead-free materials. The review of the compositional engineering approach focuses on compositional tuning of the properties and phase behavior in three promising families of lead-free perovskite ferroelectrics: the titanate, alkaline niobate and bismuth perovskites and their solid solutions. The 'structural engineering' approaches focus instead on optimization of microstructural features including grain size, grain orientation or texture, ferroelectric domain size and electrical bias field as potential paths to induce large piezoelectric properties in lead-free piezoceramics. It is suggested that a combination of both compositional and novel structural engineering approaches will be required in order to realize viable lead-free alternatives to current lead-based materials for piezoelectric actuator applications.

Behavioral Recommendations in Health Research News as Cues to Action: Self-Relevancy and Self-Efficacy Processes.

Science.gov (United States)

Chang, Chingching

2016-08-01

This study argues that behavioral recommendations in health news function as cues to action. A proposed self-oriented model seeks to explore the impacts of behavioral recommendations in health research news as cues to action through their influences on self-relevancy and self-efficacy. A content analysis (Study 1) first establishes that health research news commonly features behavioral recommendations. A message experiment (Study 2) then explores the utility of behavioral recommendations as cues to action by demonstrating a self-relevancy effect: Health research news with, as opposed to without, behavioral recommendations increases the self-relevancy of advocated health behaviors, which then improve people's attitudes toward and intentions to adopt those behaviors. A second message experiment (Study 3) tests whether varying presentations of behavioral recommendations alter their effectiveness as cues to action and thus people's behavioral intentions through a dual effect process. In addition to the previously demonstrated self-relevancy effect, this experiment shows that concrete, as opposed to abstract, behavioral recommendations trigger a self-efficacy effect, increasing perceived self-efficacy and further improving behavioral intentions.

Semantic Labeling of User Location Context Based on Phone Usage Features

Directory of Open Access Journals (Sweden)

Helena Leppäkoski

2017-01-01

Full Text Available In mobile phones, the awareness of the user’s context allows services better tailored to the user’s needs. We propose a machine learning based method for semantic labeling that utilizes phone usage features to detect the user’s home, work, and other visited places. For place detection, we compare seven different classification methods. We organize the phone usage data based on periods of uninterrupted time that the user has been in a certain place. We consider three approaches to represent this data: visits, places, and cumulative samples. Our main contribution is semantic place labeling using a small set of privacy-preserving features and novel data representations suitable for resource constrained mobile devices. The contributions include (1 introduction of novel data representations including accumulation and averaging of the usage, (2 analysis of the effect of the data accumulation time on the accuracy of the place classification, (3 analysis of the confidence on the classification outcome, and (4 identification of the most relevant features obtained through feature selection methods. With a small set of privacy-preserving features and our data representations, we detect the user’s home and work with probability of 90% or better, and in 3-class problem the overall classification accuracy was 89% or better.

AHIMSA - Ad hoc histogram information measure sensing algorithm for feature selection in the context of histogram inspired clustering techniques

Science.gov (United States)

Dasarathy, B. V.

1976-01-01

An algorithm is proposed for dimensionality reduction in the context of clustering techniques based on histogram analysis. The approach is based on an evaluation of the hills and valleys in the unidimensional histograms along the different features and provides an economical means of assessing the significance of the features in a nonparametric unsupervised data environment. The method has relevance to remote sensing applications.

EcmPred: Prediction of extracellular matrix proteins based on random forest with maximum relevance minimum redundancy feature selection

KAUST Repository

Kandaswamy, Krishna Kumar Umar; Ganesan, Pugalenthi; Kalies, Kai Uwe; Hartmann, Enno; Martinetz, Thomas M.

2013-01-01

The extracellular matrix (ECM) is a major component of tissues of multicellular organisms. It consists of secreted macromolecules, mainly polysaccharides and glycoproteins. Malfunctions of ECM proteins lead to severe disorders such as marfan

A prototype feature system for feature retrieval using relationships

Science.gov (United States)

Choi, J.; Usery, E.L.

2009-01-01

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

An optimized lead system for long-term esophageal electrocardiography

International Nuclear Information System (INIS)

Niederhauser, T; Haeberlin, A; Vogel, R; Marisa, T; Goette, J; Jacomet, M; Mattle, D; Abächerli, R

2014-01-01

Long-term electrocardiography (ECG) featuring adequate atrial and ventricular signal quality is highly desirable. Routinely used surface leads are limited in atrial signal sensitivity and recording capability impeding complete ECG delineation, i.e. in the presence of supraventricular arrhythmias. Long-term esophageal ECG might overcome these limitations but requires a dedicated lead system and recorder design. To this end, we analysed multiple-lead esophageal ECGs with respect to signal quality by describing the ECG waves as a function of the insertion level, interelectrode distance, electrode shape and amplifier's input range. The results derived from clinical data show that two bipolar esophageal leads, an atrial lead with short (15 mm) interelectrode distance and a ventricular lead with long (80 mm) interelectrode distance provide non-inferior ventricular signal strength and superior atrial signal strength compared to standard surface lead II. High atrial signal slope in particular is observed with the atrial esophageal lead. The proposed esophageal lead system in combination with an increased recorder input range of ±20 mV minimizes signal loss due to excessive electrode motion typically observed in esophageal ECGs. The design proposal might help to standardize long-term esophageal ECG registrations and facilitate novel ECG classification systems based on the independent detection of ventricular and atrial electrical activity. (paper)

Screening children for elevated blood lead - Learnings from the literature

International Nuclear Information System (INIS)

Boreland, Frances; Lyle, David

2008-01-01

Introduction: Although it is important that children at risk of developing elevated blood lead receive regular screening, attendance at screening programs is variable. A literature review was undertaken to better understand the factors that affect carers' decisions about whether or not to take their children for blood lead screening. Method: Electronic databases (Medline, EMBASE, CINAHL, Psychinfo) were searched to identify relevant publications, supported by reviewing reference lists of identified articles and searching with internet-based search engines. Results: Thirty-four published studies dealing with blood lead screening rates were identified, of which only seven papers focused specifically on parent's attitudes to blood lead screening. The barriers to and enablers of screening for elevated blood lead levels appear to be similar to those identified for other screening programs. Discussion: It is recommended that attendance at screening be routinely monitored, and that where participation is suboptimal further research be undertaken, in close co-operation with affected communities or sub-groups, to determine how best to encourage screening and to protect children from lead. It is important to minimize stigma and to ensure, as far as possible, that practical barriers such as lack of transport do not restrict access to screening programs

Does location congruence matter? : a field study on the effects of location based advertising on perceived adintrusiveness, relevance and value

NARCIS (Netherlands)

Hühn, A.E.; Khan, J.V.; Ketelaar, P.; van t Riet, J.J.; Batalas, N.; König, R.; Rozendaal, E.; Markopoulos, P.

2017-01-01

We investigate the effect of location-congruent mobile messages on perceived intrusiveness, value, and relevance through a field experiment using the Experience Sampling Method (ESM). We developed a mobile application for undergraduate students, featuring campus news and information concerning class

Does location congruence matter? A field study on the effects of location-based advertising on perceived AD intrusiveness, relevance & value

NARCIS (Netherlands)

Hühn, A.E.; Khan, V.J.; Ketelaar, P.E.; Riet, J.P. van 't; Konig, R.P.; Rozendaal, E.; Batalas, N.; Markopoulos, P.

2017-01-01

We investigate the effect of location-congruent mobile messages on perceived intrusiveness, value, and relevance through a field experiment using the Experience Sampling Method (ESM). We developed a mobile application for undergraduate students, featuring campus news and information concerning class

Geochemical and mineralogical investigation of domestic archaeological soil features at the Tiel-Passewaaij site, The Netherlands

NARCIS (Netherlands)

Oonk, S.; Slomp, C.P.; Huisman, D.J.; Vriend, S.P.

2008-01-01

Archaeological soil features can be defined as areas of staining in ancient cultural soil horizons and are frequently used in surveys to locate sites and activity areas. Visual observation of these features, however, provides only limited information on their origin and the processes leading to

Geochemical and mineralogical investigation of domestic archaeological soil features at the Tiel-Passewaaij sit, The Netherlands

NARCIS (Netherlands)

Oonk, S.; Slomp, C.P.; Huisman, D.J.; Vriend, S.P.

2009-01-01

Archaeological soil features can be defined as areas of staining in ancient cultural soil horizons and are frequently used in surveys to locate sites and activity areas. Visual observation of these features, however, provides only limited information on their origin and the processes leading to

Geochemical and mineralogical investigation of domestic archaeological soil features at the Tiel-Passewaaij site, The Netherlands

NARCIS (Netherlands)

Oonk, S.; Slomp, C.P.; Huisman, D.J.; Vriend, S.P.

2009-01-01

Archaeological soil features can be defined as areas of staining in ancient cultural soil horizons and are frequently used in surveys to locate sites and activity areas. Visual observation of these features, however, provides only limited information on their origin and the processes leading to

The development of cones and associated features on ion bombarded copper

International Nuclear Information System (INIS)

Whitton, J.L.; Carter, G.; Nobes, M.J.; Williams, J.S.

1977-01-01

Observations of ion-bombardment-induced surface modifications on crystalline copper substrates have been made using scanning electron microscopy. The delineation and development of grain boundary edges, faceted and terraced etch pits and small-scale ripple structure, together with the formation of faceted conical features, have all been observed on low and high purity polycrystalline substrates. In general, the density of such surface morphological features, although variable from grain to grain, is higher in the proximity of grain boundaries. In particular, cones are only found within regions where other surface erosional features are present and it would appear that the development of these other features is a pre-requisite to cone generation in high-purity crystalline substrates. We suggest the operation of a defect-induced mechanism of cone formation whereby sputter elaboration of bulk defects (either pre-existing or bombardment-induced) leads to the formation and development of surface features which, in turn, may intersect and result in the generation of cones. (author)

The development of cones and associated features on ion bombarded copper

International Nuclear Information System (INIS)

Whitton, J.L.; Williams, J.S.

1977-01-01

Observations of ion-bombardment-induced surface modifications on crystalline copper substrates have been made using scanning electron microscopy. The delineation and development of grain boundary edges, faceted and terraced etch pits and small-scale ripple structure, together with the formation of faceted conical features have all been observed on low and high purity polycrystalline substrates. In general, the density of such surface morphological features, although variable from grain to grain, is higher in the proximity of grain boundaries. In particular, cones are only found within regions where other surface erosional features are present and it would appear that the development of these other surface features is a pre-requisite to cone generation in high-purity crystalline substrates. The authors suggest the operation of a defect-induced mechanism of cone formation whereby sputter elaboration of bulk defects (either preexisting or bombardment-induced) leads to the formation and development of surface features which, in turn, may intersect and result in the generation of cones. (Auth.)

Psychopathic Features Moderate the Relationship between Harsh and Inconsistent Parental Discipline and Adolescent Antisocial Behavior

Science.gov (United States)

Edens, John F.; Skopp, Nancy A.; Cahill, Melissa A.

2008-01-01

Although the quality of parenting predicts externalizing behavior problems generally, ineffective parenting may be less relevant to explaining the behavior problems of children high in callous-unemotional traits. This study tested the potential moderating role of psychopathic features among juvenile offenders (n = 76). Youths were administered the…

Joint Applied Optics and Chinese Optics Letters feature introduction: digital holography and three-dimensional imaging

OpenAIRE

Poon, Ting-Chung

2011-01-01

This feature issue serves as a pilot issue promoting the joint issue of Applied Optics and Chinese Optics Letters. It focuses upon topics of current relevance to the community working in the area of digital holography and 3-D imaging. (C) 2011 Optical Society of America

Joint Applied Optics and Chinese Optics Letters feature introduction: digital holography and three-dimensional imaging.

Science.gov (United States)

Poon, Ting-Chung

2011-12-01

This feature issue serves as a pilot issue promoting the joint issue of Applied Optics and Chinese Optics Letters. It focuses upon topics of current relevance to the community working in the area of digital holography and 3-D imaging. © 2011 Optical Society of America

ENGINEERED BARRIER SYSTEM FEATURES, EVENTS AND PROCESSES

Energy Technology Data Exchange (ETDEWEB)

Jaros, W.

2005-08-30

The purpose of this report is to evaluate and document the inclusion or exclusion of engineered barrier system (EBS) features, events, and processes (FEPs) with respect to models and analyses used to support the total system performance assessment for the license application (TSPA-LA). A screening decision, either Included or Excluded, is given for each FEP along with the technical basis for exclusion screening decisions. This information is required by the U.S. Nuclear Regulatory Commission (NRC) at 10 CFR 63.114 (d, e, and f) [DIRS 173273]. The FEPs addressed in this report deal with those features, events, and processes relevant to the EBS focusing mainly on those components and conditions exterior to the waste package and within the rock mass surrounding emplacement drifts. The components of the EBS are the drip shield, waste package, waste form, cladding, emplacement pallet, emplacement drift excavated opening (also referred to as drift opening in this report), and invert. FEPs specific to the waste package, cladding, and drip shield are addressed in separate FEP reports: for example, ''Screening of Features, Events, and Processes in Drip Shield and Waste Package Degradation'' (BSC 2005 [DIRS 174995]), ''Clad Degradation--FEPs Screening Arguments (BSC 2004 [DIRS 170019]), and Waste-Form Features, Events, and Processes'' (BSC 2004 [DIRS 170020]). For included FEPs, this report summarizes the implementation of the FEP in the TSPA-LA (i.e., how the FEP is included). For excluded FEPs, this analysis provides the technical basis for exclusion from TSPA-LA (i.e., why the FEP is excluded). This report also documents changes to the EBS FEPs list that have occurred since the previous versions of this report. These changes have resulted due to a reevaluation of the FEPs for TSPA-LA as identified in Section 1.2 of this report and described in more detail in Section 6.1.1. This revision addresses updates in Yucca Mountain Project

Multiple-Features-Based Semisupervised Clustering DDoS Detection Method

Directory of Open Access Journals (Sweden)

Yonghao Gu

2017-01-01

Full Text Available DDoS attack stream from different agent host converged at victim host will become very large, which will lead to system halt or network congestion. Therefore, it is necessary to propose an effective method to detect the DDoS attack behavior from the massive data stream. In order to solve the problem that large numbers of labeled data are not provided in supervised learning method, and the relatively low detection accuracy and convergence speed of unsupervised k-means algorithm, this paper presents a semisupervised clustering detection method using multiple features. In this detection method, we firstly select three features according to the characteristics of DDoS attacks to form detection feature vector. Then, Multiple-Features-Based Constrained-K-Means (MF-CKM algorithm is proposed based on semisupervised clustering. Finally, using MIT Laboratory Scenario (DDoS 1.0 data set, we verify that the proposed method can improve the convergence speed and accuracy of the algorithm under the condition of using a small amount of labeled data sets.

Pictorial essay of radiological features of benign intrathoracic masses

Directory of Open Access Journals (Sweden)

Syahminan Suut

2015-01-01

Full Text Available With increased exposure of patients to routine imaging, incidental benign intrathoracic masses are frequently recognized. Most have classical imaging features, which are pathognomonic for their benignity. The aim of this pictorial review is to educate the reader of radiological features of several types of intrathoracic masses. The masses are categorized based on their location/origin and are grouped into parenchymal, pleural, mediastinal, or bronchial. Thoracic wall masses that invade the thorax such as neurofibromas and lipomas are included as they may mimic intrathoracic masses. All examples are illustrated and include pulmonary hamartoma, pleural fibroma, sarcoidosis, bronchial carcinoid, and bronchoceles together with a variety of mediastinal cysts on plain radiographs, computed tomography (CT and magnetic resonance imaging (MRI. Sometimes a multimodality approach would be needed to confirm the diagnosis in atypical cases. The study would include the incorporation of radionuclide studies and relevant discussion in a multidisciplinary setting.

The functional relevance of polyploidization in the skin.

Science.gov (United States)

Trakala, Marianna; Malumbres, Marcos

2014-02-01

Cell proliferation and differentiation are tightly coupled through the regulation of the cell division cycle. To preserve specific functional properties in differentiated cells, distinct variants of the basic mitotic cell cycle are used in various mammalian tissues, leading to the formation of polyploid cells. In this issue of Experimental Dermatology, Gandarillas and Freije discuss the evidences for polyploidization in keratinocytes, a process whose physiological relevance is now becoming evident. A better evaluation of these unconventional cell cycles is required not only to improve our understanding of the development and structure of the epidermis but also for future therapies against skin diseases. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Teaching Effectiveness of a Relevant Physics Course

Science.gov (United States)

Hobson, Art

1998-04-01

If America is to achieve the science literacy that is ssential to industrialized democracy, all students must study such topics as scientific methodology, pseudoscience, critical thinking, ozone depletion, technological risk, and global warming. My large-enrollment liberal-arts physics course covers the great principles of physics along with several such philosophical and societal topics. Students find these topics relevant and fascinating, leading to strong course evaluations and large enrollments by non-scientists even in courses labeled physics. I will describe this course and present some evidence indicating that the course is effective in communicating physics and its interdisciplinary connections. A textbook, Physics: Concepts and Connections (Prentice Hall, 1995, 2nd edition to appear in June 1998), is available.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

Science.gov (United States)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

Science.gov (United States)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods. PMID:28120883

Toward the Relevance of Platelet Subpopulations for Transfusion Medicine

Directory of Open Access Journals (Sweden)

Stefan Handtke

2018-02-01

Full Text Available Circulating platelets consist of subpopulations with different age, maturation state and size. In this review, we address the association between platelet size and platelet function and summarize the current knowledge on platelet subpopulations including reticulated platelets, procoagulant platelets and platelets exposing signals to mediate their clearance. Thereby, we emphasize the impact of platelet turnover as an important condition for platelet production in vivo. Understanding of the features that characterize platelet subpopulations is very relevant for the methods of platelet concentrate production, which may enrich or deplete particular platelet subpopulations. Moreover, the concept of platelet size being associated with platelet function may be attractive for transfusion medicine as it holds the perspective to separate platelet subpopulations with specific functional capabilities.

Identifying sports videos using replay, text, and camera motion features

Science.gov (United States)

Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

1999-12-01

Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

[A "historical" case of lead poisoning via drinking water: diagnostic and therapeutic issues].

Science.gov (United States)

Testud, F; Girtanner-Brunel, L; Péaud, P Y; Serpollet, G; Duchen, C

2001-12-01

It is likely that lead poisoning via drinking water is often overlooked because of its supposed rarity and nonspecific early symptoms, which result in delayed management. One case of severe lead poisoning via drinking water is reported. The diagnosis was long missed and a particularly long chelating treatment was required. The clinical features included lead colic, a Burton's lead line, anemia, polyneuritis and arterial hypertension. Eighteen courses of calcium EDTA were required to obtain 'biological recovery'. The poisoning was linked to a very long water supply lead pipe and potomania secondary to alcohol withdrawal. This case report illustrates how difficult the early recognition of lead poisoning can be, and underlines the need to inquire about a toxic aetiology, particularly via the environment, of otherwise unexplained pathological conditions.

Features of the low-power charge controller of lead-acid current sources charged by solar batteries

International Nuclear Information System (INIS)

Tukfatullin, O.F.; Yuldoshev, I.A.; Solieva, N.A.

2008-01-01

Influence of different factors on exploitations characteristics of solar photoelectric plant is investigated by field-performance data. A construction of charge controller of the lead-acid accumulator battery charging by means of solar battery is analyzed taking into account these factors. (authors)

Feature Extraction for Track Section Status Classification Based on UGW Signals

Directory of Open Access Journals (Sweden)

Lei Yuan

2018-04-01

Full Text Available Track status classification is essential for the stability and safety of railway operations nowadays, when railway networks are becoming more and more complex and broad. In this situation, monitoring systems are already a key element in applications dedicated to evaluating the status of a certain track section, often determining whether it is free or occupied by a train. Different technologies have already been involved in the design of monitoring systems, including ultrasonic guided waves (UGW. This work proposes the use of the UGW signals captured by a track monitoring system to extract the features that are relevant for determining the corresponding track section status. For that purpose, three features of UGW signals have been considered: the root mean square value, the energy, and the main frequency components. Experimental results successfully validated how these features can be used to classify the track section status into free, occupied and broken. Furthermore, spatial and temporal dependencies among these features were analysed in order to show how they can improve the final classification performance. Finally, a preliminary high-level classification system based on deep learning networks has been envisaged for future works.

Assessment and correction of BCC_CSM's performance in capturing leading modes of summer precipitation over North Asia

KAUST Repository

Gong, Zhiqiang

2017-11-07

This article examines the ability of Beijing Climate Center Climate System Model (BCC_CSM) in demonstrating the prediction accuracy and the leading modes of the summer precipitation over North Asia (NA). A dynamic-statistic combined approach for improving the prediction accuracy and the prediction of the leading modes of the summer precipitation over NA is proposed. Our results show that the BCC_CSM can capture part of the spatial anomaly features of the first two leading modes of NA summer precipitation. Moreover, BCC_CSM regains relationships such that the first and second mode of the empirical orthogonal function (EOF1 and EOF2) of NA summer precipitation, respectively, corresponds to the development of the El Niño and La Niña conditions in the tropical East Pacific. Nevertheless, BCC_CSM exhibits limited prediction skill over most part of NA and presents a deficiency in reproducing the EOF1\\'s and EOF2\\'s spatial pattern over central NA and EOF2\\'s interannual variability. This can be attributed as the possible reasons why the model is unable to capture the correct relationships among the basic climate elements over the central NA, lacks in its ability to reproduce a consistent zonal atmospheric pattern over NA, and has bias in predicting the relevant Sea Surface Temperature (SST) modes over the tropical Pacific and Indian Ocean regions. Based on the proposed dynamic-statistic combined correction approach, compared with the leading modes of BCC_CSM\\'s original prediction, anomaly correlation coefficients of corrected EOF1/EOF2 with the tropical Indian Ocean SST are improved from 0.18/0.36 to 0.51/0.62. Hence, the proposed correction approach suggests that the BCC_CSM\\'s prediction skill for the summer precipitation prediction over NA and its ability to capture the dominant modes could be certainly improved by choosing proper historical analogue information.

Neutron Physics aspects of using lead as a coolant in Fast Reactors

International Nuclear Information System (INIS)

Kiefhaber, E.

1991-02-01

The use of lead as a coolant for fast reactors is being considered as an attractive alternative in the USSR, especially with respect to its inherent safety features. In order to come to an own assessment at KfK, some investigations have been performed concerning a comparison of the nuclear characteristics of fast reactors with lead and sodium cooling. The studies have shown, that the nuclear and thermal hydraulic design calculations do not face special problems and that the nuclear characteristics of both types of cores do not differ essentially, except for the coolant density or void effect, which is more favourable for smaller sized lead cooled cores. A proper safety assessment of lead cooled cores will however require more detailed safety studies. Crucial points of lead cooling are the strong corrosion of austenitic steels in lead and the unknown behavior of ferritic steels in lead and under irradiation

CASE REPORT CASE A super 'lead pipe' colon: radio-pathological ...

African Journals Online (AJOL)

2008-10-15

Oct 15, 2008 ... cancer in UC. Clearly, correct diagnosis is crucial. Our case not only had severe findings and a diagnosis that predated her surgery, but also had no clinical, radiological or histological features of the other alternative diagnoses. The case demonstrates an unusually severe form of 'lead pipe' colon occurring ...

Discussion on the Relevant Factors of General Surgery Incision Infection and Prevention Methods

Directory of Open Access Journals (Sweden)

Jin Baotao

2017-01-01

Full Text Available There are many reasons that can lead to incision infection of general surgical patients. The main reasons include weight, age, body albumin level, surgical time, observation ward, etc. This paper analyzes the clinic data of patients with incision infection after general surgery based on clinic practice and study on the reasons that have impact on general surgical incision infection and gives relevant prevention countermeasures.

Scaffolding Students’ Independent Decoding of Unfamiliar Text with a Prototype of an eBook-Feature

DEFF Research Database (Denmark)

Gissel, Stig Toke

2015-01-01

the relevant spelling patterns and in generalizing, in order to strengthen their decoding skills. The prototype was evaluated with Danish students in the second grade to see how and under what circumstances students can use the feature in ways that strengthen their decoding skills and support them in reading...

Identification of input variables for feature based artificial neural networks-saccade detection in EOG recordings.

Science.gov (United States)

Tigges, P; Kathmann, N; Engel, R R

1997-07-01

Though artificial neural networks (ANN) are excellent tools for pattern recognition problems when signal to noise ratio is low, the identification of decision relevant features for ANN input data is still a crucial issue. The experience of the ANN designer and the existing knowledge and understanding of the problem seem to be the only links for a specific construction. In the present study a backpropagation ANN based on modified raw data inputs showed encouraging results. Investigating the specific influences of prototypical input patterns on a specially designed ANN led to a new sparse and efficient input data presentation. This data coding obtained by a semiautomatic procedure combining existing expert knowledge and the internal representation structures of the raw data based ANN yielded a list of feature vectors, each representing the relevant information for saccade identification. The feature based ANN produced a reduction of the error rate of nearly 40% compared with the raw data ANN. An overall correct classification of 92% of so far unknown data was realized. The proposed method of extracting internal ANN knowledge for the production of a better input data representation is not restricted to EOG recordings, and could be used in various fields of signal analysis.

Persuasive Features in Web-Based Alcohol and Smoking Interventions: A Systematic Review of the Literature

Science.gov (United States)

2011-01-01

Background In the past decade, the use of technologies to persuade, motivate, and activate individuals’ health behavior change has been a quickly expanding field of research. The use of the Web for delivering interventions has been especially relevant. Current research tends to reveal little about the persuasive features and mechanisms embedded in Web-based interventions targeting health behavior change. Objectives The purpose of this systematic review was to extract and analyze persuasive system features in Web-based interventions for substance use by applying the persuasive systems design (PSD) model. In more detail, the main objective was to provide an overview of the persuasive features within current Web-based interventions for substance use. Methods We conducted electronic literature searches in various databases to identify randomized controlled trials of Web-based interventions for substance use published January 1, 2004, through December 31, 2009, in English. We extracted and analyzed persuasive system features of the included Web-based interventions using interpretive categorization. Results The primary task support components were utilized and reported relatively widely in the reviewed studies. Reduction, self-monitoring, simulation, and personalization seem to be the most used features to support accomplishing user’s primary task. This is an encouraging finding since reduction and self-monitoring can be considered key elements for supporting users to carry out their primary tasks. The utilization of tailoring was at a surprisingly low level. The lack of tailoring may imply that the interventions are targeted for too broad an audience. Leveraging reminders was the most common way to enhance the user-system dialogue. Credibility issues are crucial in website engagement as users will bind with sites they perceive credible and navigate away from those they do not find credible. Based on the textual descriptions of the interventions, we cautiously

The Soil Microbiota Harbors a Diversity of Carbapenem-Hydrolyzing β-Lactamases of Potential Clinical Relevance.

Science.gov (United States)

Gudeta, Dereje Dadi; Bortolaia, Valeria; Amos, Greg; Wellington, Elizabeth M H; Brandt, Kristian K; Poirel, Laurent; Nielsen, Jesper Boye; Westh, Henrik; Guardabassi, Luca

2016-01-01

The origin of carbapenem-hydrolyzing metallo-β-lactamases (MBLs) acquired by clinical bacteria is largely unknown. We investigated the frequency, host range, diversity, and functionality of MBLs in the soil microbiota. Twenty-five soil samples of different types and geographical origins were analyzed by antimicrobial selective culture, followed by phenotypic testing and expression of MBL-encoding genes in Escherichia coli, and whole-genome sequencing of MBL-producing strains was performed. Carbapenemase activity was detected in 29 bacterial isolates from 13 soil samples, leading to identification of seven new MBLs in presumptive Pedobacter roseus (PEDO-1), Pedobacter borealis (PEDO-2), Pedobacter kyungheensis (PEDO-3), Chryseobacterium piscium (CPS-1), Epilithonimonas tenax (ESP-1), Massilia oculi (MSI-1), and Sphingomonas sp. (SPG-1). Carbapenemase production was likely an intrinsic feature in Chryseobacterium and Epilithonimonas, as it occurred in reference strains of different species within these genera. The amino acid identity to MBLs described in clinical bacteria ranged between 40 and 69%. Remarkable features of the new MBLs included prophage integration of the encoding gene (PEDO-1), an unusual amino acid residue at a key position for MBL structure and catalysis (CPS-1), and overlap with a putative OXA β-lactamase (MSI-1). Heterologous expression of PEDO-1, CPS-1, and ESP-1in E. coli significantly increased the MICs of ampicillin, ceftazidime, cefpodoxime, cefoxitin, and meropenem. Our study shows that MBL producers are widespread in soil and include four genera that were previously not known to produce MBLs. The MBLs produced by these bacteria are distantly related to MBLs identified in clinical samples but constitute resistance determinants of clinical relevance if acquired by pathogenic bacteria. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Enhancing facial features by using clear facial features

Science.gov (United States)

Rofoo, Fanar Fareed Hanna

2017-09-01

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

Spatial features register: toward standardization of spatial features

Science.gov (United States)

Cascio, Janette

1994-01-01

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

Evil genius? How dishonesty can lead to greater creativity.

Science.gov (United States)

Gino, Francesca; Wiltermuth, Scott S

2014-04-01

We propose that dishonest and creative behavior have something in common: They both involve breaking rules. Because of this shared feature, creativity may lead to dishonesty (as shown in prior work), and dishonesty may lead to creativity (the hypothesis we tested in this research). In five experiments, participants had the opportunity to behave dishonestly by overreporting their performance on various tasks. They then completed one or more tasks designed to measure creativity. Those who cheated were subsequently more creative than noncheaters, even when we accounted for individual differences in their creative ability (Experiment 1). Using random assignment, we confirmed that acting dishonestly leads to greater creativity in subsequent tasks (Experiments 2 and 3). The link between dishonesty and creativity is explained by a heightened feeling of being unconstrained by rules, as indicated by both mediation (Experiment 4) and moderation (Experiment 5).

Osteoporosis and hydronephrosis of young lambs following the ingestion of lead

Energy Technology Data Exchange (ETDEWEB)

Clegg, F G; Rylands, J M

1966-01-01

Lead poisoning is described in young lambs which were reared near lead mining areas in North Derbyshire, England. A brief history of the poisoning of stock which has occurred in the past near lead workings is given. The clinical results and post-mortem findings are reported together with descriptions of radiographical, histological and biochemical findings. A striking feature of all post-mortem examinations was an emaciated carcase with grossly abnormal kidneys. The bones were fragile and easily broken or cut. Kidney cortex and liver lead estimations were carried out in every case. The response of affected lambs to treatment with ascorbic acid is described and the similarities of the clinical signs and the skeletal lesions to scurvy in man and the guinea pig are discussed. 31 references, 6 figures, 2 tables.

Linking structural features of protein complexes and biological function.

Science.gov (United States)

Sowmya, Gopichandran; Breen, Edmond J; Ranganathan, Shoba

2015-09-01

Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions. © 2015 The Protein Society.

Psychological features of attention in archery

Directory of Open Access Journals (Sweden)

Ekaterina Yu. Korobeynikova

2017-06-01

Full Text Available The issue of attention is one of the leading in sports psychology. Quite often, athletes’ failures in competitions are ultimately connected with the attention processes, i.e. distraction, switching or loss of concentration. Simultaneously, each particular kind of sport is distinguished by a specific competitive situation and accordingly presents a number of requirements to athletes, including attention features. Archery is no exception. Thus, in shooting sports, concentration and stability of attention are often deemed as the most significant features of attention. The paper is devoted to the study of the attention dynamic properties in archers. Attention features of athletes were assessed depending on the sports major, gender, age, experience and level of competence. 65 archers from different regions of Russia took part in the study, including 34 males and 31 females, the average age being 16.29 ± 1.74. Experience ranges from 1 year to 8 years, average experience is 4.46 ± 1.93. The research results showed that archers are characterized by high indicators of stability of attention, and also high efficiency of solving attention problems. The professional success of archery was associated with the ability to distribute attention when necessary. At the same time, there were no significant differences in the features of attention for recurved and compound archers, which indicates the uniformity of tasks related to attention in the sporting practice of archers. Summing up, it is necessary to include skills in the distribution of attention in the program of psychological training of archers.

Importance of Practical Relevance and Design Modules in Electrical Circuits Education

Directory of Open Access Journals (Sweden)

Kalpathy Sundaram

2011-05-01

Full Text Available The interactive technical electronic book, TechEBook, currently under development at the University of Central Florida (UCF, provides a useful tool for engineers and scientists through unique features compared to the most used traditional electrical circuit textbooks available in the market. TechEBook has comprised the two worlds of classical circuit books and an interactive operating platform such as iPads, laptops and desktops utilizing Java Virtual Machine operator. The TechEBook provides an interactive applets screen that holds many modules, in which each had a specific application in the self learning process. This paper describes two of the interactive techniques in the TechEBook known as, Practical Relevance Modules (PRM and Design Modules (DM. The Practical Relevance Module will assist the readers to learn electrical circuit analysis and to understand the practical application of the electrical network theory through solving real world examples and problems. The Design Module will help students design real-life problems. These modules will be displayed after each section in the TechEBook for the user to relate his/her understanding with the outside world, which introduces the term me-applying and me-designing, as a comprehensive full experience for self or individualized education. The main emphasis of this paper is the PRM while the DM will be discussed in brief. A practical example of applying the PRM and DM features is discussed as part of a basic electrical engineering course currently given at UCF and results show improved student performances in learning materials in Electrical Circuits. In the future, such modules can be redesigned to become highly interactive with illustrated animations.

Assessment of the stability of morphological ECG features and their potential for person verification/identification

Directory of Open Access Journals (Sweden)

Matveev Mikhail

2017-01-01

Full Text Available This study investigates the potential of a set of ECG morphological features for person verification/identification. The measurements are done over 145 pairs of ECG recordings from healthy subjects, acquired 5 years apart (T1, T2 = T1+5 years. Time, amplitude, area and slope descriptors of the QRS-T pattern are analysed in 4 ECG leads, forming quasi-orthogonal lead system (II&III, V1, V5. The correspondence between feature values in T1 and T2 is verified via factor analysis by principal components extraction method; correlation analysis applied over the measurements in T1 and T2; synthesis of regression equations for prediction of features’ values in T2 based on T1 measurements; and cluster analysis for assessment of the correspondence between measured and predicted feature values. Thus, 11 amplitude descriptors of the QRS complex are highlighted as stable, i.e. keeping their strong correlation (≥0.7 within a certain factor, weak correlation (<0.3 with the features from the remaining factors and presenting high correlation in the two measurement periods that is a sign for their person verification/identification potential. The observed coincidence between feature values measured in T2 and predicted via the designed regression models (r=0.93 suggests about the confidence of person identification via the proposed morphological features.

New learning resource features CERN

CERN Multimedia

Katarina Anthony

2011-01-01

A new educational website, STEM Works, has been launched this month, presenting science and technology in an industrial context for students aged 11-14. Developed with contributions from CERN, the site highlights the Laboratory as a “real-world” example of the opportunities available to science graduates. While the site was developed in Northern Ireland, STEM Works addresses issues of global relevance.   Students share their projects with Steve Myers, Richard Hanna (CCEA), and Catriona Ruane (Education Minister). STEM stands for Science, Technology, Engineering and Mathematics – the four cornerstones of the curriculum featured on the STEM Works website. It is part of a nationwide push in Northern Ireland to highlight how important STEM subjects are to both academia and industry. CERN worked closely with the Northern Ireland Council for the Curriculum, Examinations and Assessment (CCEA) to develop educational content for the site. “The CCEA STEM Works site i...