Which features are important for effectiveness of sport- and health-related apps?

NARCIS (Netherlands)

Joan Dallinga; Marije Baart de la Faille-Deutekom; Mark Janssen; Steven Vos

2017-01-01

In this presentation we presented the results of expert meetings. The aim was to identify which features in sport- and health-related apps contribute to effectiveness of apps. A nominal group technique was used.

An expert botanical feature extraction technique based on phenetic features for identifying plant species.

Directory of Open Access Journals (Sweden)

Hoshang Kolivand

Full Text Available In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost.

An expert botanical feature extraction technique based on phenetic features for identifying plant species

Science.gov (United States)

Fern, Bong Mei; Rahim, Mohd Shafry Mohd; Sulong, Ghazali; Baker, Thar; Tully, David

2018-01-01

In this paper, we present a new method to recognise the leaf type and identify plant species using phenetic parts of the leaf; lobes, apex and base detection. Most of the research in this area focuses on the popular features such as the shape, colour, vein, and texture, which consumes large amounts of computational processing and are not efficient, especially in the Acer database with a high complexity structure of the leaves. This paper is focused on phenetic parts of the leaf which increases accuracy. Detecting the local maxima and local minima are done based on Centroid Contour Distance for Every Boundary Point, using north and south region to recognise the apex and base. Digital morphology is used to measure the leaf shape and the leaf margin. Centroid Contour Gradient is presented to extract the curvature of leaf apex and base. We analyse 32 leaf images of tropical plants and evaluated with two different datasets, Flavia, and Acer. The best accuracy obtained is 94.76% and 82.6% respectively. Experimental results show the effectiveness of the proposed technique without considering the commonly used features with high computational cost. PMID:29420568

Identifying prognostic features by bottom-up approach and correlating to drug repositioning.

Directory of Open Access Journals (Sweden)

Wei Li

Full Text Available Traditionally top-down method was used to identify prognostic features in cancer research. That is to say, differentially expressed genes usually in cancer versus normal were identified to see if they possess survival prediction power. The problem is that prognostic features identified from one set of patient samples can rarely be transferred to other datasets. We apply bottom-up approach in this study: survival correlated or clinical stage correlated genes were selected first and prioritized by their network topology additionally, then a small set of features can be used as a prognostic signature.Gene expression profiles of a cohort of 221 hepatocellular carcinoma (HCC patients were used as a training set, 'bottom-up' approach was applied to discover gene-expression signatures associated with survival in both tumor and adjacent non-tumor tissues, and compared with 'top-down' approach. The results were validated in a second cohort of 82 patients which was used as a testing set.Two sets of gene signatures separately identified in tumor and adjacent non-tumor tissues by bottom-up approach were developed in the training cohort. These two signatures were associated with overall survival times of HCC patients and the robustness of each was validated in the testing set, and each predictive performance was better than gene expression signatures reported previously. Moreover, genes in these two prognosis signature gave some indications for drug-repositioning on HCC. Some approved drugs targeting these markers have the alternative indications on hepatocellular carcinoma.Using the bottom-up approach, we have developed two prognostic gene signatures with a limited number of genes that associated with overall survival times of patients with HCC. Furthermore, prognostic markers in these two signatures have the potential to be therapeutic targets.

A Cross-Sectional Investigation of the Importance of Park Features for Promoting Regular Physical Activity in Parks.

Science.gov (United States)

Costigan, Sarah A; Veitch, Jenny; Crawford, David; Carver, Alison; Timperio, Anna

2017-11-02

Parks in the US and Australia are generally underutilised, and park visitors typically engage in low levels of physical activity (PA). Better understanding park features that may encourage visitors to be active is important. This study examined the perceived importance of park features for encouraging park-based PA and examined differences by sex, age, parental-status and participation in PA. Cross-sectional surveys were completed by local residents ( n = 2775) living near two parks (2013/2015). Demographic variables, park visitation and leisure-time PA were self-reported, respondents rated the importance of 20 park features for encouraging park-based PA in the next fortnight. Chi-square tests of independence examined differences in importance of park features for PA among sub-groups of local residents (sex, age, parental-status, PA). Park features ranked most important for park-based PA were: well maintained (96.2%), feel safe (95.4%), relaxing atmosphere (91.2%), easy to get to (91.7%), and shady trees (90.3%). All subgroups ranked 'well maintained' as most important. Natural and built environment features of parks are important for promoting adults' park-based PA, and should be considered in park (re)design.

PROBLEMATIC FEATURES OF THE POLITICAL DECISION MAKERS

OpenAIRE

Aleksey Sergeevih Voynov

2014-01-01

Purpose: identify the most important features in the process of making political decisions that affect the effectiveness of problem-solving situationsScientific novelty: as a result of the analysis identified the problematic features of major importance for the efficiency of the development and adoption of the most rational solution to a problem situation.Results: the analysis of the most significant features affecting the quality of decisions among them the interest of the person making deci...

Important features of Sustainable Aggregate Resource Management

Science.gov (United States)

Solar, Slavko V.; Shields, Deborah J.; Langer, William H.

2004-01-01

Every society, whether developed, developing or in a phase of renewal following governmental change, requires stable, adequate and secure supplies of natural resources. In the latter case, there could be significant need for construction materials for rebuilding infrastructure, industrial capacity, and housing. It is essential that these large-volume materials be provided in a rational manner that maximizes their societal contribution and minimizes environmental impacts. We describe an approach to resource management based on the principles of sustainable developed. Sustainable Aggregate Resource Management offers a way of addressing the conflicting needs and interests of environmental, economic, and social systems. Sustainability is an ethics based concept that utilizes science and democratic processes to reach acceptable agreements and tradeoffs among interests, while acknowledging the fundamental importance of the environment and social goods. We discuss the features of sustainable aggregate resource management.

Important Features of Sustainable Aggregate Resource Management

Directory of Open Access Journals (Sweden)

Slavko V. Šolar

2004-06-01

Full Text Available Every society, whether developed, developing or in a phase of renewal following governmental change, requires stable, adequate and secure supplies of natural resources. In the latter case, there could be significant need for construction materials for rebuilding infrastructure, industrial capacity, and housing. It is essential that these large-volume materials be provided in a rational manner that maximizes their societal contribution and minimizes environmental impacts. We describe an approach to resource management based on the principles of sustainable development. Sustainable Aggregate Resource Management offers a way of addressing the conflicting needs and interests of environmental, economic, and social systems. Sustainability is an ethics based concept that utilizes science and democratic processes to reach acceptable agreements and tradeoffs among interests, while acknowledging the fundamental importance of the environment and social goods. We discuss the features of sustainable aggregate resource management.

Robust modal curvature features for identifying multiple damage in beams

Science.gov (United States)

Ostachowicz, Wiesław; Xu, Wei; Bai, Runbo; Radzieński, Maciej; Cao, Maosen

2014-03-01

Curvature mode shape is an effective feature for damage detection in beams. However, it is susceptible to measurement noise, easily impairing its advantage of sensitivity to damage. To deal with this deficiency, this study formulates an improved curvature mode shape for multiple damage detection in beams based on integrating a wavelet transform (WT) and a Teager energy operator (TEO). The improved curvature mode shape, termed the WT - TEO curvature mode shape, has inherent capabilities of immunity to noise and sensitivity to damage. The proposed method is experimentally validated by identifying multiple cracks in cantilever steel beams with the mode shapes acquired using a scanning laser vibrometer. The results demonstrate that the improved curvature mode shape can identify multiple damage accurately and reliably, and it is fairly robust to measurement noise.

Sequencing of bovine herpesvirus 4 v.test strain reveals important genome features

Directory of Open Access Journals (Sweden)

Gillet Laurent

2011-08-01

Full Text Available Abstract Background Bovine herpesvirus 4 (BoHV-4 is a useful model for the human pathogenic gammaherpesviruses Epstein-Barr virus and Kaposi's Sarcoma-associated Herpesvirus. Although genome manipulations of this virus have been greatly facilitated by the cloning of the BoHV-4 V.test strain as a Bacterial Artificial Chromosome (BAC, the lack of a complete genome sequence for this strain limits its experimental use. Methods In this study, we have determined the complete sequence of BoHV-4 V.test strain by a pyrosequencing approach. Results The long unique coding region (LUR consists of 108,241 bp encoding at least 79 open reading frames and is flanked by several polyrepetitive DNA units (prDNA. As previously suggested, we showed that the prDNA unit located at the left prDNA-LUR junction (prDNA-G differs from the other prDNA units (prDNA-inner. Namely, the prDNA-G unit lacks the conserved pac-2 cleavage and packaging signal in its right terminal region. Based on the mechanisms of cleavage and packaging of herpesvirus genomes, this feature implies that only genomes bearing left and right end prDNA units are encapsulated into virions. Conclusions In this study, we have determined the complete genome sequence of the BAC-cloned BoHV-4 V.test strain and identified genome organization features that could be important in other herpesviruses.

Automated local bright feature image analysis of nuclear proteindistribution identifies changes in tissue phenotype

Energy Technology Data Exchange (ETDEWEB)

Knowles, David; Sudar, Damir; Bator, Carol; Bissell, Mina

2006-02-01

The organization of nuclear proteins is linked to cell and tissue phenotypes. When cells arrest proliferation, undergo apoptosis, or differentiate, the distribution of nuclear proteins changes. Conversely, forced alteration of the distribution of nuclear proteins modifies cell phenotype. Immunostaining and fluorescence microscopy have been critical for such findings. However, there is an increasing need for quantitative analysis of nuclear protein distribution to decipher epigenetic relationships between nuclear structure and cell phenotype, and to unravel the mechanisms linking nuclear structure and function. We have developed imaging methods to quantify the distribution of fluorescently-stained nuclear protein NuMA in different mammary phenotypes obtained using three-dimensional cell culture. Automated image segmentation of DAPI-stained nuclei was generated to isolate thousands of nuclei from three-dimensional confocal images. Prominent features of fluorescently-stained NuMA were detected using a novel local bright feature analysis technique, and their normalized spatial density calculated as a function of the distance from the nuclear perimeter to its center. The results revealed marked changes in the distribution of the density of NuMA bright features as non-neoplastic cells underwent phenotypically normal acinar morphogenesis. In contrast, we did not detect any reorganization of NuMA during the formation of tumor nodules by malignant cells. Importantly, the analysis also discriminated proliferating non-neoplastic cells from proliferating malignant cells, suggesting that these imaging methods are capable of identifying alterations linked not only to the proliferation status but also to the malignant character of cells. We believe that this quantitative analysis will have additional applications for classifying normal and pathological tissues.

PACS administrators' and radiologists' perspective on the importance of features for PACS selection.

Science.gov (United States)

Joshi, Vivek; Narra, Vamsi R; Joshi, Kailash; Lee, Kyootai; Melson, David

2014-08-01

Picture archiving and communication systems (PACS) play a critical role in radiology. This paper presents the criteria important to PACS administrators for selecting a PACS. A set of criteria are identified and organized into an integrative hierarchical framework. Survey responses from 48 administrators are used to identify the relative weights of these criteria through an analytical hierarchy process. The five main dimensions for PACS selection in order of importance are system continuity and functionality, system performance and architecture, user interface for workflow management, user interface for image manipulation, and display quality. Among the subdimensions, the highest weights were assessed for security, backup, and continuity; tools for continuous performance monitoring; support for multispecialty images; and voice recognition/transcription. PACS administrators' preferences were generally in line with that of previously reported results for radiologists. Both groups assigned the highest priority to ensuring business continuity and preventing loss of data through features such as security, backup, downtime prevention, and tools for continuous PACS performance monitoring. PACS administrators' next high priorities were support for multispecialty images, image retrieval speeds from short-term and long-term storage, real-time monitoring, and architectural issues of compatibility and integration with other products. Thus, next to ensuring business continuity, administrators' focus was on issues that impact their ability to deliver services and support. On the other hand, radiologists gave high priorities to voice recognition, transcription, and reporting; structured reporting; and convenience and responsiveness in manipulation of images. Thus, radiologists' focus appears to be on issues that may impact their productivity, effort, and accuracy.

Application of the RES methodology for identifying features, events and processes (FEPs) for near-field analysis of copper-steel canister

International Nuclear Information System (INIS)

Vieno, T.; Hautojaervi, A.; Raiko, H.; Ahonen, L.; Salo, J.P.

1994-12-01

Rock Engineering Systems (RES) is an approach to discover the important characteristics and interactions of a complex problem. Recently RES has been applied to identify features, events and processes (FEPs) for performance analysis of nuclear waste repositories. The RES methodology was applied to identify FEPs for the near-field analysis of the copper-steel canister for spent fuel disposal. The aims of the exercise were to learn and test the RES methodology and, secondly, to find out how much the results differ when RES is applied by two different groups on the same problem. A similar exercise was previously carried out by a SKB group. A total of 90 potentially significant FEPs were identified. The exercise showed that the RES methodology is a practicable tool to get a comprehensive and transparent picture of a complex problem. The approach is easy to learn and use. It reveals the important characteristics and interactions and organizes them in a format easy to understand. (9 refs., 5 figs., 3 tabs.)

Identifying the important factors in simulation models with many factors

NARCIS (Netherlands)

Bettonvil, B.; Kleijnen, J.P.C.

1994-01-01

Simulation models may have many parameters and input variables (together called factors), while only a few factors are really important (parsimony principle). For such models this paper presents an effective and efficient screening technique to identify and estimate those important factors. The

Varied Rates of Implementation of Patient-Centered Medical Home Features and Residents' Perceptions of Their Importance Based on Practice Experience.

Science.gov (United States)

Eiff, M Patrice; Green, Larry A; Jones, Geoff; Devlaeminck, Alex Verdieck; Waller, Elaine; Dexter, Eve; Marino, Miguel; Carney, Patricia A

2017-03-01

Little is known about how the patient-centered medical home (PCMH) is being implemented in residency practices. We describe both the trends in implementation of PCMH features and the influence that working with PCMH features has on resident attitudes toward their importance in 14 family medicine residencies associated with the P4 Project. We assessed 24 residency continuity clinics annually between 2007-2011 on presence or absence of PCMH features. Annual resident surveys (n=690) assessed perceptions of importance of PCMH features using a 4-point scale (not at all important to very important). We used generalized estimating equations logistic regression to assess trends and ordinal-response proportional odds regression models to determine if resident ratings of importance were associated with working with those features during training. Implementation of electronic health record (EHR) features increased significantly from 2007-2011, such as email communication with patients (33% to 67%), preventive services registries (23% to 64%), chronic disease registries (63% to 82%), and population-based quality assurance (46% to 79%). Team-based care was the only process of care feature to change significantly (54% to 93%). Residents with any exposure to EHR-based features had higher odds of rating the features more important compared to those with no exposure. We observed consistently lower odds of the resident rating process of care features as more important with any exposure compared to no exposure. Residencies engaged in educational transformation were more successful in implementing EHR-based PCMH features, and exposure during training appears to positively influence resident ratings of importance, while exposure to process of care features are slower to implement with less influence on importance ratings.

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

Science.gov (United States)

Vrkljan, Brenda H; Anaby, Dana

2011-02-01

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

Comparative analyses of Legionella species identifies genetic features of strains causing Legionnaires' disease.

Science.gov (United States)

Gomez-Valero, Laura; Rusniok, Christophe; Rolando, Monica; Neou, Mario; Dervins-Ravault, Delphine; Demirtas, Jasmin; Rouy, Zoe; Moore, Robert J; Chen, Honglei; Petty, Nicola K; Jarraud, Sophie; Etienne, Jerome; Steinert, Michael; Heuner, Klaus; Gribaldo, Simonetta; Médigue, Claudine; Glöckner, Gernot; Hartland, Elizabeth L; Buchrieser, Carmen

2014-01-01

The genus Legionella comprises over 60 species. However, L. pneumophila and L. longbeachae alone cause over 95% of Legionnaires’ disease. To identify the genetic bases underlying the different capacities to cause disease we sequenced and compared the genomes of L. micdadei, L. hackeliae and L. fallonii (LLAP10), which are all rarely isolated from humans. We show that these Legionella species possess different virulence capacities in amoeba and macrophages, correlating with their occurrence in humans. Our comparative analysis of 11 Legionella genomes belonging to five species reveals highly heterogeneous genome content with over 60% representing species-specific genes; these comprise a complete prophage in L. micdadei, the first ever identified in a Legionella genome. Mobile elements are abundant in Legionella genomes; many encode type IV secretion systems for conjugative transfer, pointing to their importance for adaptation of the genus. The Dot/Icm secretion system is conserved, although the core set of substrates is small, as only 24 out of over 300 described Dot/Icm effector genes are present in all Legionella species. We also identified new eukaryotic motifs including thaumatin, synaptobrevin or clathrin/coatomer adaptine like domains. Legionella genomes are highly dynamic due to a large mobilome mainly comprising type IV secretion systems, while a minority of core substrates is shared among the diverse species. Eukaryotic like proteins and motifs remain a hallmark of the genus Legionella. Key factors such as proteins involved in oxygen binding, iron storage, host membrane transport and certain Dot/Icm substrates are specific features of disease-related strains.

The value of anthropometric indices for identifying women with features of metabolic syndrome

Science.gov (United States)

BMI is a widely used anthropometric measure for identifying CVD and metabolic syndrome (MetS) risk. Two new anthropometric indices are A Body Shape Index (ABSI) and Body Roundness Index (BRI) that may provide better correlations to features of MetS. Methods: Subject data were obtained from 91 over...

Role of Importance and Distinctiveness of Semantic Features in People with Aphasia: A Replication Study

Science.gov (United States)

Mason-Baughman, Mary Beth; Wallace, Sarah E.

2014-01-01

Previous studies suggest that people with aphasia have incomplete lexical-semantic representations with decreased low-importance distinctive (LID) feature knowledge. In addition, decreased LID feature knowledge correlates with ability to discriminate among semantically related words. The current study seeks to replicate and extend previous…

Automated local bright feature image analysis of nuclear protein distribution identifies changes in tissue phenotype

International Nuclear Information System (INIS)

Knowles, David; Sudar, Damir; Bator, Carol; Bissell, Mina

2006-01-01

The organization of nuclear proteins is linked to cell and tissue phenotypes. When cells arrest proliferation, undergo apoptosis, or differentiate, the distribution of nuclear proteins changes. Conversely, forced alteration of the distribution of nuclear proteins modifies cell phenotype. Immunostaining and fluorescence microscopy have been critical for such findings. However, there is an increasing need for quantitative analysis of nuclear protein distribution to decipher epigenetic relationships between nuclear structure and cell phenotype, and to unravel the mechanisms linking nuclear structure and function. We have developed imaging methods to quantify the distribution of fluorescently-stained nuclear protein NuMA in different mammary phenotypes obtained using three-dimensional cell culture. Automated image segmentation of DAPI-stained nuclei was generated to isolate thousands of nuclei from three-dimensional confocal images. Prominent features of fluorescently-stained NuMA were detected using a novel local bright feature analysis technique, and their normalized spatial density calculated as a function of the distance from the nuclear perimeter to its center. The results revealed marked changes in the distribution of the density of NuMA bright features as non-neoplastic cells underwent phenotypically normal acinar morphogenesis. In contrast, we did not detect any reorganization of NuMA during the formation of tumor nodules by malignant cells. Importantly, the analysis also discriminated proliferating non-neoplastic cells from proliferating malignant cells, suggesting that these imaging methods are capable of identifying alterations linked not only to the proliferation status but also to the malignant character of cells. We believe that this quantitative analysis will have additional applications for classifying normal and pathological tissues

Familiarity and Within-Person Facial Variability: The Importance of the Internal and External Features.

Science.gov (United States)

Kramer, Robin S S; Manesi, Zoi; Towler, Alice; Reynolds, Michael G; Burton, A Mike

2018-01-01

As faces become familiar, we come to rely more on their internal features for recognition and matching tasks. Here, we assess whether this same pattern is also observed for a card sorting task. Participants sorted photos showing either the full face, only the internal features, or only the external features into multiple piles, one pile per identity. In Experiments 1 and 2, we showed the standard advantage for familiar faces-sorting was more accurate and showed very few errors in comparison with unfamiliar faces. However, for both familiar and unfamiliar faces, sorting was less accurate for external features and equivalent for internal and full faces. In Experiment 3, we asked whether external features can ever be used to make an accurate sort. Using familiar faces and instructions on the number of identities present, we nevertheless found worse performance for the external in comparison with the internal features, suggesting that less identity information was available in the former. Taken together, we show that full faces and internal features are similarly informative with regard to identity. In comparison, external features contain less identity information and produce worse card sorting performance. This research extends current thinking on the shift in focus, both in attention and importance, toward the internal features and away from the external features as familiarity with a face increases.

System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

Science.gov (United States)

Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

2014-06-17

A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

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

Science.gov (United States)

Vidyasagar, Mathukumalli

2015-01-01

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

System and method employing a minimum distance and a load feature database to identify electric load types of different electric loads

Science.gov (United States)

Lu, Bin; Yang, Yi; Sharma, Santosh K; Zambare, Prachi; Madane, Mayura A

2014-12-23

A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.

A Permutation Importance-Based Feature Selection Method for Short-Term Electricity Load Forecasting Using Random Forest

Directory of Open Access Journals (Sweden)

Nantian Huang

2016-09-01

Full Text Available The prediction accuracy of short-term load forecast (STLF depends on prediction model choice and feature selection result. In this paper, a novel random forest (RF-based feature selection method for STLF is proposed. First, 243 related features were extracted from historical load data and the time information of prediction points to form the original feature set. Subsequently, the original feature set was used to train an RF as the original model. After the training process, the prediction error of the original model on the test set was recorded and the permutation importance (PI value of each feature was obtained. Then, an improved sequential backward search method was used to select the optimal forecasting feature subset based on the PI value of each feature. Finally, the optimal forecasting feature subset was used to train a new RF model as the final prediction model. Experiments showed that the prediction accuracy of RF trained by the optimal forecasting feature subset was higher than that of the original model and comparative models based on support vector regression and artificial neural network.

Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

Directory of Open Access Journals (Sweden)

Jaesung Lee

2016-11-01

Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

Textural features for radar image analysis

Science.gov (United States)

Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

1981-01-01

Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

Identifying relevant feature-action associations for grasping unmodelled objects

DEFF Research Database (Denmark)

Thomsen, Mikkel Tang; Kraft, Dirk; Krüger, Norbert

2015-01-01

content. The method is provided with a large and structured set of visual features, motivated by the visual hierarchy in primates and finds relevant feature action associations automatically. We apply our method in a simulated environment on three different object sets for the case of grasp affordance...... learning. For box objects, we achieve a 0.90 success probability, 0.80 for round objects and up to 0.75 for open objects, when presented with novel objects. In this work, we in particular demonstrate the effect of choosing appropriate feature representations. We demonstrate a significant performance...

Identifying important nodes by adaptive LeaderRank

Science.gov (United States)

Xu, Shuang; Wang, Pei

2017-03-01

Spreading process is a common phenomenon in complex networks. Identifying important nodes in complex networks is of great significance in real-world applications. Based on the spreading process on networks, a lot of measures have been proposed to evaluate the importance of nodes. However, most of the existing measures are appropriate to static networks, which are fragile to topological perturbations. Many real-world complex networks are dynamic rather than static, meaning that the nodes and edges of such networks may change with time, which challenge numerous existing centrality measures. Based on a new weighted mechanism and the newly proposed H-index and LeaderRank (LR), this paper introduces a variant of the LR measure, called adaptive LeaderRank (ALR), which is a new member of the LR-family. Simulations on six real-world networks reveal that the new measure can well balance between prediction accuracy and robustness. More interestingly, the new measure can better adapt to the adjustment or local perturbations of network topologies, as compared with the existing measures. By discussing the detailed properties of the measures from the LR-family, we illustrate that the ALR has its competitive advantages over the other measures. The proposed algorithm enriches the measures to understand complex networks, and may have potential applications in social networks and biological systems.

A delphi exercise to identify characteristic features of gout - opinions from patients and physicians, the first stage in developing new classification criteria.

Science.gov (United States)

Prowse, Rebecca L; Dalbeth, Nicola; Kavanaugh, Arthur; Adebajo, Adewale O; Gaffo, Angelo L; Terkeltaub, Robert; Mandell, Brian F; Suryana, Bagus P P; Goldenstein-Schainberg, Claudia; Diaz-Torne, Cèsar; Khanna, Dinesh; Lioté, Frederic; Mccarthy, Geraldine; Kerr, Gail S; Yamanaka, Hisashi; Janssens, Hein; Baraf, Herbert F; Chen, Jiunn-Horng; Vazquez-Mellado, Janitzia; Harrold, Leslie R; Stamp, Lisa K; Van De Laar, Mart A; Janssen, Matthijs; Doherty, Michael; Boers, Maarten; Edwards, N Lawrence; Gow, Peter; Chapman, Peter; Khanna, Puja; Helliwell, Philip S; Grainger, Rebecca; Schumacher, H Ralph; Neogi, Tuhina; Jansen, Tim L; Louthrenoo, Worawit; Sivera, Francisca; Taylor, William J; Alten, Rieke

2013-04-01

To identify a comprehensive list of features that might discriminate between gout and other rheumatic musculoskeletal conditions, to be used subsequently for a case-control study to develop and test new classification criteria for gout. Two Delphi exercises were conducted using Web-based questionnaires: one with physicians from several countries who had an interest in gout and one with patients from New Zealand who had gout. Physicians rated a list of potentially discriminating features that were identified by literature review and expert opinion, and patients rated a list of features that they generated themselves. Agreement was defined by the RAND/UCLA disagreement index. Forty-four experienced physicians and 9 patients responded to all iterations. For physicians, 71 items were identified by literature review and 15 more were suggested by physicians. The physician survey showed agreement for 26 discriminatory features and 15 as not discriminatory. The patients identified 46 features of gout, for which there was agreement on 25 items as being discriminatory and 7 items as not discriminatory. Patients and physicians agreed upon several key features of gout. Physicians emphasized objective findings, imaging, and patterns of symptoms, whereas patients emphasized severity, functional results, and idiographic perception of symptoms.

Genes Important for Schizosaccharomyces pombe Meiosis Identified Through a Functional Genomics Screen

Science.gov (United States)

Blyth, Julie; Makrantoni, Vasso; Barton, Rachael E.; Spanos, Christos; Rappsilber, Juri; Marston, Adele L.

2018-01-01

Meiosis is a specialized cell division that generates gametes, such as eggs and sperm. Errors in meiosis result in miscarriages and are the leading cause of birth defects; however, the molecular origins of these defects remain unknown. Studies in model organisms are beginning to identify the genes and pathways important for meiosis, but the parts list is still poorly defined. Here we present a comprehensive catalog of genes important for meiosis in the fission yeast, Schizosaccharomyces pombe. Our genome-wide functional screen surveyed all nonessential genes for roles in chromosome segregation and spore formation. Novel genes important at distinct stages of the meiotic chromosome segregation and differentiation program were identified. Preliminary characterization implicated three of these genes in centrosome/spindle pole body, centromere, and cohesion function. Our findings represent a near-complete parts list of genes important for meiosis in fission yeast, providing a valuable resource to advance our molecular understanding of meiosis. PMID:29259000

SoftSearch: integration of multiple sequence features to identify breakpoints of structural variations.

Directory of Open Access Journals (Sweden)

Steven N Hart

Full Text Available BACKGROUND: Structural variation (SV represents a significant, yet poorly understood contribution to an individual's genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints. RESULTS: We developed and validated SoftSearch using real and synthetic datasets. SoftSearch's key features are 1 not requiring secondary (or exhaustive primary alignment, 2 portability into established sequencing workflows, and 3 is applicable to any DNA-sequencing experiment (e.g. whole genome, exome, custom capture, etc.. SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call. CONCLUSIONS: We show that SoftSearch can identify more true SVs by combining multiple sequence features. SoftSearch was able to call clinically relevant SVs in the BRCA2 gene not reported by other tools while offering significantly improved overall performance.

Identifying Trajectories of Borderline Personality Features in Adolescence: Antecedent and Interactive Risk Factors.

Science.gov (United States)

Haltigan, John D; Vaillancourt, Tracy

2016-03-01

To examine trajectories of adolescent borderline personality (BP) features in a normative-risk cohort (n = 566) of Canadian children assessed at ages 13, 14, 15, and 16 and childhood predictors of trajectory group membership assessed at ages 8, 10, 11, and 12. Data were drawn from the McMaster Teen Study, an on-going study examining relations among bullying, mental health, and academic achievement. Participants and their parents completed a battery of mental health and peer relations questionnaires at each wave of the study. Academic competence was assessed at age 8 (Grade 3). Latent class growth analysis, analysis of variance, and logistic regression were used to analyze the data. Three distinct BP features trajectory groups were identified: elevated or rising, intermediate or stable, and low or stable. Parent- and child-reported mental health symptoms, peer relations risk factors, and intra-individual risk factors were significant predictors of elevated or rising and intermediate or stable trajectory groups. Child-reported attention-deficit hyperactivity disorder (ADHD) and somatization symptoms uniquely predicted elevated or rising trajectory group membership, whereas parent-reported anxiety and child-reported ADHD symptoms uniquely predicted intermediate or stable trajectory group membership. Child-reported somatization symptoms was the only predictor to differentiate the intermediate or stable and elevated or rising trajectory groups (OR 1.15, 95% CI 1.04 to 1.28). Associations between child-reported reactive temperament and elevated BP features trajectory group membership were 10.23 times higher among children who were bullied, supporting a diathesis-stress pathway in the development of BP features for these youth. Findings demonstrate the heterogeneous course of BP features in early adolescence and shed light on the potential prodromal course of later borderline personality disorder. © The Author(s) 2015.

Methodology for identifying boundaries of systems important to safety in CANDU nuclear power plants

International Nuclear Information System (INIS)

Therrien, S.; Komljenovic, D.; Therrien, P.; Ruest, C.; Prevost, P.; Vaillancourt, R.

2007-01-01

This paper presents a methodology developed to identify the boundaries of the systems important to safety (SIS) at the Gentilly-2 Nuclear Power Plant (NPP), Hydro-Quebec. The SIS boundaries identification considers nuclear safety only. Components that are not identified as important to safety are systematically identified as related to safety. A global assessment process such as WANO/INPO AP-913 'Equipment Reliability Process' will be needed to implement adequate changes in the management rules of those components. The paper depicts results in applying the methodology to the Shutdown Systems 1 and 2 (SDS 1, 2), and to the Emergency Core Cooling System (ECCS). This validation process enabled fine tuning the methodology, performing a better estimate of the effort required to evaluate a system, and identifying components important to safety of these systems. (author)

The Problem of Informational Object Identification in Case of the Considerable Quantity of Identifying Features

Directory of Open Access Journals (Sweden)

S. D. Kulik

2010-03-01

Full Text Available The modification of the algorithm of identification of the informational object, used for identification of the hand-written texts performer in an automated workplace of the forensic expert, is presented. As modification, it is offered to use a method of association rules discovery for definition of statistically dependent sets of feature of hand-written capital letters of the Russian language. The algorithm is approved on set of 691 samples of hand-written documents for which about 2000 identifying feature are defined. The modification of the identification algorithm allows to lower level of errors and to raise quality of accepted decisions for information security.

[Importance of the hyperuricaemia, gout and gender nosological features in the activity of general practitioner - family doctor].

Science.gov (United States)

Rudichenko, V M

2012-01-01

In this article there were analyzed gender data about features of hyperuricaemia and gout: women are much older at the onset of gout arthritis (one of main reasons, probably, makes menopause by itself), have more associated comorbid deseases as hypertension and kidney failure and drinks less alcoholic beverages. It was noticed, that typical localisation of the lesion on the first toe is less often in women, and women are more inclined to use diuretics among medical drugs. Abovementioned clinical features are of some importance for the broad activity of general practitioners - family doctors. Gender features of polyarthicular gout are not uniformed. Scientific researches confirmed possibility of the genetic basis of the uric acid metabolism, which influences some fenotypical features of the organism. Several genes are known for their influence on serum uric acid: PDZK1, GCKR, SLC2A9, ABCG2, LRRC16A, SLC17A3, SLC16A9 and SLC22A12. However, conclusions of the research works confirm the necessity of scientific clarification of the importance of different factors of gender differences.

Estimation of minimum sample size for identification of the most important features: a case study providing a qualitative B2B sales data set

OpenAIRE

Marko Bohanec; Mirjana Kljajić Borštnar; Marko Robnik-Šikonja

2017-01-01

An important task in machine learning is to reduce data set dimensionality, which in turn contributes to reducing computational load and data collection costs, while improving human understanding and interpretation of models. We introduce an operational guideline for determining the minimum number of instances sufficient to identify correct ranks of features with the highest impact. We conduct tests based on qualitative B2B sales forecasting data. The results show that a relatively small inst...

Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.

Science.gov (United States)

Tuo, Youlin; An, Ning; Zhang, Ming

2018-03-01

The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of PSVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an independent dataset (35 metastatic samples and 143 non‑metastatic samples) revealed an accuracy of 94.38% and AUROC of 0.958. Cell cycle associated functions and pathways were the most significant terms of the 30 feature genes. A SVM classifier was constructed to assess the possibility of breast cancer metastasis, which presented high accuracy in several

kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

Science.gov (United States)

Fletez-Brant, Christopher; Lee, Dongwon; McCallion, Andrew S.; Beer, Michael A.

2013-01-01

Massively parallel sequencing technologies have made the generation of genomic data sets a routine component of many biological investigations. For example, Chromatin immunoprecipitation followed by sequence assays detect genomic regions bound (directly or indirectly) by specific factors, and DNase-seq identifies regions of open chromatin. A major bottleneck in the interpretation of these data is the identification of the underlying DNA sequence code that defines, and ultimately facilitates prediction of, these transcription factor (TF) bound or open chromatin regions. We have recently developed a novel computational methodology, which uses a support vector machine (SVM) with kmer sequence features (kmer-SVM) to identify predictive combinations of short transcription factor-binding sites, which determine the tissue specificity of these genomic assays (Lee, Karchin and Beer, Discriminative prediction of mammalian enhancers from DNA sequence. Genome Res. 2011; 21:2167–80). This regulatory information can (i) give confidence in genomic experiments by recovering previously known binding sites, and (ii) reveal novel sequence features for subsequent experimental testing of cooperative mechanisms. Here, we describe the development and implementation of a web server to allow the broader research community to independently apply our kmer-SVM to analyze and interpret their genomic datasets. We analyze five recently published data sets and demonstrate how this tool identifies accessory factors and repressive sequence elements. kmer-SVM is available at http://kmersvm.beerlab.org. PMID:23771147

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.

Data-Wave-Based Features Extraction and Its Application in Symbol Identifier Recognition and Positioning Suitable for Multi-Robot Systems

Directory of Open Access Journals (Sweden)

Xilong Liu

2012-12-01

Full Text Available In this paper, feature extraction based on data-wave is proposed. The concept of data-wave is introduced to describe the rising and falling trends of the data over the long-term which are detected based on ripple and wave filters. Supported by data-wave, a novel symbol identifier with significant structure features is designed and these features are extracted by constructing pixel chains. On this basis, the corresponding recognition and positioning approach is presented. The effectiveness of the proposed approach is verified by experiments.

Mammographic feature enhancement by multiscale analysis

International Nuclear Information System (INIS)

Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.

1994-01-01

This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients

Important conventional island design features: generators

International Nuclear Information System (INIS)

Fritsch, Th.

1985-01-01

To-day, maximum reactor capacity is setting a provisional limit to the MW race. The latest nuclear generators in manufacturing are rated 1530 MW - 1710 MVA and are doubtless the most powerful ones in the world. The target to be aimed at in designing large turbogenerators may be defined by the following points: 1) meeting the rated load conditions without overpassing maximum admissible temperatures in any part of the machine; 2) keeping losses as small as possible; 3) keeping overall size small enough to allow rail transportation from the works to the site; 4) choosing well experienced solutions in order to set a highly reliable machine with maximum maintenance. In this report the main features of nuclear generators in the 1000-2000 MVA range are described. (Auth.)

Individual discriminative face recognition models based on subsets of features

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder; Gomez, David Delgado; Ersbøll, Bjarne Kjær

2007-01-01

The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection is used to identify meaningful and important features in face recognition. Modelling the characteristics which distinguish one...... person from another using only subsets of features will both decrease the computational cost and increase the generalization capacity of the face recognition algorithm. Moreover, identifying which are the features that better discriminate between persons will also provide a deeper understanding...... of the face recognition problem. The elastic net model is able to select a subset of features with low computational effort compared to other state-of-the-art feature selection methods. Furthermore, the fact that the number of features usually is larger than the number of images in the data base makes feature...

PROBLEMATIC FEATURES OF THE POLITICAL DECISION MAKERS

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Aleksey Sergeevih Voynov

2014-11-01

Full Text Available Purpose: identify the most important features in the process of making political decisions that affect the effectiveness of problem-solving situationsScientific novelty: as a result of the analysis identified the problematic features of major importance for the efficiency of the development and adoption of the most rational solution to a problem situation.Results: the analysis of the most significant features affecting the quality of decisions among them the interest of the person making decisions in the search for causes of the problem situation; decisions from the influence of the immediate environment; populism in decision making, creating a visibility problem-solving; decision making based on personal emotional factor face decision-makers; the perception of the population face decision-makers in relation to the current problem situation and possible ways of its resolution.Defined facts influencing the process of political decision-making such as: corruption, the struggle for influence on the process of political decision-making, lack of qualified specialists, staff shortage, including arose as the result of substitution of notions of "succession" to "nepotism".

Radiometric monitoring of contaminated scrap metals imported in Italy. Technical and regulatory features

International Nuclear Information System (INIS)

Dobici, F.; Piermattei, S.; Susanna, A.

1996-01-01

During these last ten years there have been occasional reports of mishaps from trafficking of contaminated scraps or containing radioactive sources. Recently an increase of events indicated that the problem becomes more important as to generate possible consequences, from a radiation protection standpoint, for workers and general public. Following the detection of contaminated metal scraps in some recycling industries and in some consignments entering the Italian borders, the competent Authorities laid down rules to put the matter under control. In this paper technical and regulatory features are discussed. (author)

Accurately Identifying New QoS Violation Driven by High-Distributed Low-Rate Denial of Service Attacks Based on Multiple Observed Features

Directory of Open Access Journals (Sweden)

Jian Kang

2015-01-01

Full Text Available We propose using multiple observed features of network traffic to identify new high-distributed low-rate quality of services (QoS violation so that detection accuracy may be further improved. For the multiple observed features, we choose F feature in TCP packet header as a microscopic feature and, P feature and D feature of network traffic as macroscopic features. Based on these features, we establish multistream fused hidden Markov model (MF-HMM to detect stealthy low-rate denial of service (LDoS attacks hidden in legitimate network background traffic. In addition, the threshold value is dynamically adjusted by using Kaufman algorithm. Our experiments show that the additive effect of combining multiple features effectively reduces the false-positive rate. The average detection rate of MF-HMM results in a significant 23.39% and 44.64% improvement over typical power spectrum density (PSD algorithm and nonparametric cumulative sum (CUSUM algorithm.

Human body as a set of biometric features identified by means of optoelectronics

Science.gov (United States)

Podbielska, Halina; Bauer, Joanna

2005-09-01

Human body posses many unique, singular features that are impossible to copy or forge. Nowadays, to establish and to ensure the public security requires specially designed devices and systems. Biometrics is a field of science and technology, exploiting human body characteristics for people recognition. It identifies the most characteristic and unique ones in order to design and construct systems capable to recognize people. In this paper some overview is given, presenting the achievements in biometrics. The verification and identification process is explained, along with the way of evaluation of biometric recognition systems. The most frequently human biometrics used in practice are shortly presented, including fingerprints, facial imaging (including thermal characteristic), hand geometry and iris patterns.

Identifying important motivational factors for professionals in Greek hospitals

Science.gov (United States)

Kontodimopoulos, Nick; Paleologou, Victoria; Niakas, Dimitris

2009-01-01

Background The purpose of this study was to identify important motivational factors according to the views of health-care professionals in Greek hospitals and particularly to determine if these might differ in the public and private sectors. Methods A previously developed -and validated- instrument addressing four work-related motivators (job attributes, remuneration, co-workers and achievements) was used. Three categories of health care professionals, doctors (N = 354), nurses (N = 581) and office workers (N = 418), working in public and private hospitals, participated and motivation was compared across socio-demographic and occupational variables. Results The range of reported motivational factors was mixed and Maslow's conclusions that lower level motivational factors must be met before ascending to the next level were not confirmed. The highest ranked motivator for the entire sample, and by professional subgroup, was achievements (P motivators were similar, and only one significant difference was observed, namely between doctors and nurses in respect to co-workers (P motivated by all factors significantly more than their public-hospital counterparts. Conclusion The results are in agreement with the literature which focuses attention to management approaches employing both monetary and non-monetary incentives to motivate health care workers. This study showed that intrinsic factors are particularly important and should become a target for effective employee motivation. PMID:19754968

Crowding with conjunctions of simple features.

Science.gov (United States)

Põder, Endel; Wagemans, Johan

2007-11-20

Several recent studies have related crowding with the feature integration stage in visual processing. In order to understand the mechanisms involved in this stage, it is important to use stimuli that have several features to integrate, and these features should be clearly defined and measurable. In this study, Gabor patches were used as target and distractor stimuli. The stimuli differed in three dimensions: spatial frequency, orientation, and color. A group of 3, 5, or 7 objects was presented briefly at 4 deg eccentricity of the visual field. The observers' task was to identify the object located in the center of the group. A strong effect of the number of distractors was observed, consistent with various spatial pooling models. The analysis of incorrect responses revealed that these were a mix of feature errors and mislocalizations of the target object. Feature errors were not purely random, but biased by the features of distractors. We propose a simple feature integration model that predicts most of the observed regularities.

Identifying persistent and characteristic features in firearm tool marks on cartridge cases

Science.gov (United States)

Ott, Daniel; Soons, Johannes; Thompson, Robert; Song, John

2017-12-01

Recent concerns about subjectivity in forensic firearm identification have motivated the development of algorithms to compare firearm tool marks that are imparted on ammunition and to generate quantitative measures of similarity. In this paper, we describe an algorithm that identifies impressed tool marks on a cartridge case that are both consistent between firings and contribute strongly to a surface similarity metric. The result is a representation of the tool mark topography that emphasizes both significant and persistent features across firings. This characteristic surface map is useful for understanding the variability and persistence of the tool marks created by a firearm and can provide improved discrimination between the comparison scores of samples fired from the same firearm and the scores of samples fired from different firearms. The algorithm also provides a convenient method for visualizing areas of similarity that may be useful in providing quantitative support for visual comparisons by trained examiners.

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

NARCIS (Netherlands)

Malta, Tathiane M.; Sokolov, Artem; Gentles, Andrew J.; Burzykowski, Tomasz; Poisson, Laila; Weinstein, John N.; Kamińska, Bożena; Huelsken, Joerg; Omberg, Larsson; Gevaert, Olivier; Colaprico, Antonio; Czerwińska, Patrycja; Mazurek, Sylwia; Mishra, Lopa; Heyn, Holger; Krasnitz, Alex; Godwin, Andrew K.; Lazar, Alexander J.; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Gonzalez, Ana Maria Angulo; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Pinero, Edna M.Mora; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Stuart, Joshua M.; Hoadley, Katherine A.; Laird, Peter W.; Noushmehr, Houtan; Wiznerowicz, Maciej

2018-01-01

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR)

Study of a methodology of identifying important research problems by the PIRT process

International Nuclear Information System (INIS)

Aoki, Takayuki; Takagi, Toshiyuki; Urayama, Ryoichi; Komura, Ichiro; Furukawa, Takashi; Yusa, Noritaka

2014-01-01

In this paper, we propose a new methodology of identifying important research problems to be solved to improve the performance of some specific scientific technologies by the phenomena identification and ranking table (PIRT) process which has been used as a methodology for demonstrating the validity of the best estimate simulation codes in US Nuclear Regulatory Commission (USNRC) licensing of nuclear power plants. The new methodology makes it possible to identify important factors affecting the performance of the technologies from the viewpoint of the figure of merit and problems associated with them while it keeps the fundamental concepts of the original PIRT process. Also in this paper, we demonstrate the effectiveness of the new methodology by applying it to a task of extracting research problems for improving an inspection accuracy of ultrasonic testing or eddy current testing in the inspection of objects having cracks due to fatigue or stress corrosion cracking. (author)

Study of a methodology of identifying important research problems by the PIRT process

International Nuclear Information System (INIS)

Aoki, Takayuki; Takagi, Toshiyuki; Urayama, Ryoichi; Komura, Ichiro; Furukawa, Takashi; Yusa, Noritaka

2013-01-01

In this paper, we propose a new methodology of identifying important research problems to be solved to improve the performance of some specific scientific technologies by the phenomena identification and ranking table (PIRT) process, which has been used as a methodology for demonstrating the validity of the best estimate simulation codes in USNRC licensing of nuclear power plants. It keeps the fundamental concepts of the original PIRT process but makes it possible to identify important factors affecting the performance of the technologies from the viewpoint of the figure of merit and problems associated with them, which need to be solved to improve the performance. Also in this paper, we demonstrate the effectiveness of the developed method by showing a specific example of the application to physical events or phenomena in objects having fatigue or SCC crack(s) under ultrasonic testing and eddy current testing. (author)

Assessment of severe accident prevention and mitigation features: PWR, large dry containment design

International Nuclear Information System (INIS)

Perkins, K.R.; Hsu, C.J.; Lehner, J.R.; Luckas, W.J.; Cho, N.; Fitzpatrick, R.G.; Pratt, W.T.; Eltawila, F.; Maly, J.A.

1988-07-01

Plant features and operator actions which have been found to be important in either preventing or mitigating severe accidents in PWRs with large dry containments have been identified. These features and actions were developed from insights derived from reviews of risk assessments performed specifically for the Zion plant and from assessments of other relevant studies. Accident sequences that dominate the core-damage frequency and those accident sequences that are of potentially high consequence were identified. Vulnerabilities of the large dry containment to severe accident containment loads were also identified. In addition, those features of a PWR with a large dry containment, which are important for preventing core damage and are available for mitigating fission-product release to the environment were identified. The report is issued to provide focus to the analyst examining an individual plant. The report calls attention to plant features and operator actions and provides a list of deterministic tributes for assessing those features and actions found to be helpful in reducing the overall risk for Zion and other PWRs with large dry containments. Thus, the guidance is offered as a resource in examining the subject plant to determine if the same, or similar, plant features and operator actions will be of value in reducing overall plant risk. This report is intended to serve solely as guidance

Assessment of severe accident prevention and mitigation features: PWR, ice-condenser containment design

International Nuclear Information System (INIS)

Hsu, C.J.; Perkins, K.R.; Luckas, W.J.; Fitzpatrick, R.G.; Cho, N.; Lehner, J.R.; Pratt, W.T.; Eltawila, F.; Maly, J.A.

1988-07-01

Plant features and operator actions which have been found to be important in either preventing and mitigating severe accidents in PWRs with ice-condenser containments have been identified. Thus features and actions were developed from insights derived from reviews of risk assessments performed specifically for the Sequoyah plant and from assessments of other relevant studies. Accident sequences that dominate the core-damage frequency and those accident sequences that are of potentially high consequence were identified. Vulnerabilities of the ice-condenser containment to sever accident containment loads were also identified. In addition, those features of a PWR with an ice-condenser containment, which are important for preventing core damage and are available for mitigating fission-product release to the environment were identified. This report is issued to provide focus to an analyst examining an individual plant. The report calls attention to plant features and operator actions and provides a list of deterministic attributes for assessing those features and actions found to be helpful in reducing the overall risk for Sequoyah and other PWRs with ice-condenser containments. Thus, the guidance is offered as a resource in examining the subject plant to determine if the same, or similar, plant features and operator actions will be of value in reducing overall plant risk. This report is intended to serve solely as guidance. 14 tabs

Nonlinear features identified by Volterra series for damage detection in a buckled beam

Directory of Open Access Journals (Sweden)

Shiki S. B.

2014-01-01

Full Text Available The present paper proposes a new index for damage detection based on nonlinear features extracted from prediction errors computed by multiple convolutions using the discrete-time Volterra series. A reference Volterra model is identified with data in the healthy condition and used for monitoring the system operating with linear or nonlinear behavior. When the system has some structural change, possibly associated with damage, the index metrics computed could give an alert to separate the linear and nonlinear contributions, besides provide a diagnostic about the structural state. To show the applicability of the method, an experimental test is performed using nonlinear vibration signals measured in a clamped buckled beam subject to different levels of force applied and with simulated damages through discontinuities inserted in the beam surface.

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

Energy Technology Data Exchange (ETDEWEB)

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.

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.

Politeness as a feature: so important and so rare

Directory of Open Access Journals (Sweden)

Corbett, Greville G.

2012-01-01

Full Text Available Politeness has a major place in many languages, and is remarkably pervasive in some. Yet we rarely find respect as a morphosyntactic feature, alongside gender, person, number and case. I document this imbalance, and then ask why this is what we find.

Discovery and analysis of topographic features using learning algorithms: A seamount case study

NARCIS (Netherlands)

Valentine, A.P.; Kalnins, L.M.; Trampert, J.

2013-01-01

Identifying and cataloging occurrences of particular topographic features are important but time-consuming tasks. Typically, automation is challenging, as simple models do not fully describe the complexities of natural features. We propose a new approach, where a particular class of neural network

Measures of risk importance and their applications

International Nuclear Information System (INIS)

Vesely, W.E.; Davis, T.C.; Denning, R.S.; Saltos, N.

1983-07-01

This work is part of a project being conducted for the Division of Risk Analysis (DRA) of the Nuclear Regulatory Commission (NRC). The objectives of the project are to evaluate the importances of containment, the different safety functions, and other various contributers as assessed in probabilistic risk analyses and to identify generic conclusions regarding the importances. Effective display of the importances is an important part of these objectives. To address these objectives, measures of risk importance need to be first identified and then they need to be evaluated for the different risk analyses which have been performed. This report describes the risk importance measures that were defined and were applied to the risk analyses which were performed as part of the Reactor Safety Study Methodology Applications Program (RSSMAP). The risk importance measures defined in this report measure the importance of features not only with regard to risk reduction but also with regard to reliability assurance, or risk maintenance. The goal of this report is not to identify new mathematical formulas for risk importance but to show how importance measures can be interpreted and can be applied

Combining Methods to Describe Important Marine Habitats for Top Predators: Application to Identify Biological Hotspots in Tropical Waters.

Science.gov (United States)

Thiers, Laurie; Louzao, Maite; Ridoux, Vincent; Le Corre, Matthieu; Jaquemet, Sébastien; Weimerskirch, Henri

2014-01-01

In tropical waters resources are usually scarce and patchy, and predatory species generally show specific adaptations for foraging. Tropical seabirds often forage in association with sub-surface predators that create feeding opportunities by bringing prey close to the surface, and the birds often aggregate in large multispecific flocks. Here we hypothesize that frigatebirds, a tropical seabird adapted to foraging with low energetic costs, could be a good predictor of the distribution of their associated predatory species, including other seabirds (e.g. boobies, terns) and subsurface predators (e.g., dolphins, tunas). To test this hypothesis, we compared distribution patterns of marine predators in the Mozambique Channel based on a long-term dataset of both vessel- and aerial surveys, as well as tracking data of frigatebirds. By developing species distribution models (SDMs), we identified key marine areas for tropical predators in relation to contemporaneous oceanographic features to investigate multi-species spatial overlap areas and identify predator hotspots in the Mozambique Channel. SDMs reasonably matched observed patterns and both static (e.g. bathymetry) and dynamic (e.g. Chlorophyll a concentration and sea surface temperature) factors were important explaining predator distribution patterns. We found that the distribution of frigatebirds included the distributions of the associated species. The central part of the channel appeared to be the best habitat for the four groups of species considered in this study (frigatebirds, brown terns, boobies and sub-surface predators).

Combining Methods to Describe Important Marine Habitats for Top Predators: Application to Identify Biological Hotspots in Tropical Waters.

Directory of Open Access Journals (Sweden)

Laurie Thiers

Full Text Available In tropical waters resources are usually scarce and patchy, and predatory species generally show specific adaptations for foraging. Tropical seabirds often forage in association with sub-surface predators that create feeding opportunities by bringing prey close to the surface, and the birds often aggregate in large multispecific flocks. Here we hypothesize that frigatebirds, a tropical seabird adapted to foraging with low energetic costs, could be a good predictor of the distribution of their associated predatory species, including other seabirds (e.g. boobies, terns and subsurface predators (e.g., dolphins, tunas. To test this hypothesis, we compared distribution patterns of marine predators in the Mozambique Channel based on a long-term dataset of both vessel- and aerial surveys, as well as tracking data of frigatebirds. By developing species distribution models (SDMs, we identified key marine areas for tropical predators in relation to contemporaneous oceanographic features to investigate multi-species spatial overlap areas and identify predator hotspots in the Mozambique Channel. SDMs reasonably matched observed patterns and both static (e.g. bathymetry and dynamic (e.g. Chlorophyll a concentration and sea surface temperature factors were important explaining predator distribution patterns. We found that the distribution of frigatebirds included the distributions of the associated species. The central part of the channel appeared to be the best habitat for the four groups of species considered in this study (frigatebirds, brown terns, boobies and sub-surface predators.

Integrated genomics identifies five medulloblastoma subtypes with distinct genetic profiles, pathway signatures and clinicopathological features.

Directory of Open Access Journals (Sweden)

Marcel Kool

Full Text Available BACKGROUND: Medulloblastoma is the most common malignant brain tumor in children. Despite recent improvements in cure rates, prediction of disease outcome remains a major challenge and survivors suffer from serious therapy-related side-effects. Recent data showed that patients with WNT-activated tumors have a favorable prognosis, suggesting that these patients could be treated less intensively, thereby reducing the side-effects. This illustrates the potential benefits of a robust classification of medulloblastoma patients and a detailed knowledge of associated biological mechanisms. METHODS AND FINDINGS: To get a better insight into the molecular biology of medulloblastoma we established mRNA expression profiles of 62 medulloblastomas and analyzed 52 of them also by comparative genomic hybridization (CGH arrays. Five molecular subtypes were identified, characterized by WNT signaling (A; 9 cases, SHH signaling (B; 15 cases, expression of neuronal differentiation genes (C and D; 16 and 11 cases, respectively or photoreceptor genes (D and E; both 11 cases. Mutations in beta-catenin were identified in all 9 type A tumors, but not in any other tumor. PTCH1 mutations were exclusively identified in type B tumors. CGH analysis identified several fully or partly subtype-specific chromosomal aberrations. Monosomy of chromosome 6 occurred only in type A tumors, loss of 9q mostly occurred in type B tumors, whereas chromosome 17 aberrations, most common in medulloblastoma, were strongly associated with type C or D tumors. Loss of the inactivated X-chromosome was highly specific for female cases of type C, D and E tumors. Gene expression levels faithfully reflected the chromosomal copy number changes. Clinicopathological features significantly different between the 5 subtypes included metastatic disease and age at diagnosis and histology. Metastatic disease at diagnosis was significantly associated with subtypes C and D and most strongly with subtype E

Tensor decomposition-based unsupervised feature extraction identifies candidate genes that induce post-traumatic stress disorder-mediated heart diseases.

Science.gov (United States)

Taguchi, Y-H

2017-12-21

Although post-traumatic stress disorder (PTSD) is primarily a mental disorder, it can cause additional symptoms that do not seem to be directly related to the central nervous system, which PTSD is assumed to directly affect. PTSD-mediated heart diseases are some of such secondary disorders. In spite of the significant correlations between PTSD and heart diseases, spatial separation between the heart and brain (where PTSD is primarily active) prevents researchers from elucidating the mechanisms that bridge the two disorders. Our purpose was to identify genes linking PTSD and heart diseases. In this study, gene expression profiles of various murine tissues observed under various types of stress or without stress were analyzed in an integrated manner using tensor decomposition (TD). Based upon the obtained features, ∼ 400 genes were identified as candidate genes that may mediate heart diseases associated with PTSD. Various gene enrichment analyses supported biological reliability of the identified genes. Ten genes encoding protein-, DNA-, or mRNA-interacting proteins-ILF2, ILF3, ESR1, ESR2, RAD21, HTT, ATF2, NR3C1, TP53, and TP63-were found to be likely to regulate expression of most of these ∼ 400 genes and therefore are candidate primary genes that cause PTSD-mediated heart diseases. Approximately 400 genes in the heart were also found to be strongly affected by various drugs whose known adverse effects are related to heart diseases and/or fear memory conditioning; these data support the reliability of our findings. TD-based unsupervised feature extraction turned out to be a useful method for gene selection and successfully identified possible genes causing PTSD-mediated heart diseases.

Assessment of severe accident prevention and mitigation features: BWR, Mark II containment design

International Nuclear Information System (INIS)

Lehner, J.R.; Hsu, C.J.; Eltawila, F.; Perkins, K.R.; Luckas, W.J.; Fitzpatrick, R.G.; Pratt, W.T.

1988-07-01

Plant features and operator actions, which have been found to be important in either preventing or mitigating severe accidents in BWRs with Mark II containments (BWR Mark II's) have been identified. These features and actions were developed from insights derived from reviews of in-depth risk assessments performed specifically for the Limerick and Shoreham plants and from other relevant studies. Accident sequences that dominate the core-damage frequency and those accident sequences that are of potentially high consequence were identified. Vulnerabilities of the BWR Mark II to severe-accident containment loads were also noted. In addition, those features of a BWR Mark II, which are important for preventing core damage and are available for mitigating fission-product release to the environment were also identified. This report is issued to provide focus to an analyst examining an individual plant. This report calls attention to plant features and operator actions and provides a list of deterministic attributes for assessing those features and actions found to be helpful in reducing the overall risk for Mark II plants. Thus, the guidance is offered as a resource in examining the subject plant to determine if the same, or similar, plant features and operator actions will be of value in reducing overall plant risk. This report is intended to serve solely as guidance

Use of DNA sequences to identify forensically important fly species and their distribution in the coastal region of Central California.

Science.gov (United States)

Nakano, Angie; Honda, Jeff

2015-08-01

Forensic entomology has gained prominence in recent years, as improvements in DNA technology and molecular methods have allowed insect and other arthropod evidence to become increasingly useful in criminal and civil investigations. However, comprehensive faunal inventories are still needed, including cataloging local DNA sequences for forensically significant Diptera. This multi-year fly-trapping study was built upon and expanded a previous survey of these flies in Santa Clara County, including the addition of genetic barcoding data from collected species of flies. Flies from the families Calliphoridae, Sarcophagidae, and Muscidae were trapped in meat-baited traps set in a variety of locations throughout the county. Flies were identified using morphological features and confirmed by molecular analysis. A total of 16 calliphorid species, 11 sarcophagid species, and four muscid species were collected and differentiated. This study found more species of flies than previous area surveys and established new county records for two calliphorid species: Cynomya cadaverina and Chrysomya rufifacies. Differences were found in fly fauna in different areas of the county, indicating the importance of microclimates in the distribution of these flies. Molecular analysis supported the use of DNA barcoding as an effective method of identifying cryptic fly species. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Modeling vehicle emissions in different types of Chinese cities: Importance of vehicle fleet and local features

International Nuclear Information System (INIS)

Huo Hong; Zhang Qiang; He Kebin; Yao Zhiliang; Wang Xintong; Zheng Bo; Streets, David G.; Wang Qidong; Ding Yan

2011-01-01

We propose a method to simulate vehicle emissions in Chinese cities of different sizes and development stages. Twenty two cities are examined in this study. The target year is 2007. Among the cities, the vehicle emission factors were remarkably different (the highest is 50-90% higher than the lowest) owing to their distinct local features and vehicle technology levels, and the major contributors to total vehicle emissions were also different. A substantial increase in vehicle emissions is foreseeable unless stronger measures are implemented because the benefit of current policies can be quickly offset by the vehicle growth. Major efforts should be focused on all cities, especially developing cities where the requirements are lenient. This work aims a better understanding of vehicle emissions in all types of Chinese cities. The proposed method could benefit national emission inventory studies in improving accuracy and help in designing national and local policies for vehicle emission control. - Highlights: → We examine vehicle emissions in 22 Chinese cities of different types and locations. → Vehicle emission factors of the cities differ by 50-90% due to distinct local features. → Each vehicle type contributes differently to total emissions among the cities. → A substantial increase in vehicle emissions in most Chinese cities is foreseeable. → City-specific fleet and local features are important in research and policy making. - Vehicle emission characteristics of Chinese cities are remarkably different, and local features need to be taken into account in vehicle emission studies and control strategy.

Adaptive Colour Feature Identification in Image for Object Tracking

Directory of Open Access Journals (Sweden)

Feng Su

2012-01-01

Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

Blood Falls: A novel management approach for a subglacial feature of outstanding scientific importance

Science.gov (United States)

Carr, J. R.; Penhale, P. A.; Dahood, A.; Biletnikoff, N.; Harris, C. M.

2012-04-01

Blood Falls is a subglacial feature located in the ablation zone of the Taylor Glacier, Taylor Valley, McMurdo Dry Valleys, Antarctica. Blood Falls has a unique physical configuration, microbial ecology and geochemistry and consists of a subglacial brine reservoir and an iron-rich, saline surface discharge at the Taylor Glacier terminus. The feature provides a rare opportunity to sample properties of a subglacial reservoir and its ecosystem without the need for direct contact and is a key site for exobiological studies. The Blood Falls subglacial feature is globally unique and of outstanding scientific importance. As such, it warrants special protection from potential damage by drilling and/or surface activities. Moreover, currently subglacial environments are not represented in the Antarctic protected area network. To address these points, the United States National Science Foundation is working with the scientific community to develop at Blood Falls the first subglacial protected area in Antarctica. The protected area aims to maintain the integrity of the Blood Falls system, whilst allowing continued access for scientific and management purposes. Novel management approaches are being designed to protect the values of the site in three dimensions. Specific guidelines on activities conducted within the area, most notably drilling and coring, are being defined in a management plan. This new approach incorporates uncertainties in the location of the Blood Falls brine reservoir and the connectivity of the subglacial hydrological system of the Taylor Glacier. The management approaches employed at Blood Falls draw on the experience of the subglacial research community and potentially offer an effective framework for the protection of other subglacial environments.

Identify the Important Decision Factors of Online Shopping Adoption in Indonesia

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Lailatul HIJRAH

2017-12-01

Full Text Available The objective of this study is to identify factors encouraging a consumer to engage in online shopping activities. The expected contribution of this study is for online entrepreneurs, in order to develop the most suitable business strategy, so that it will be clearly identified and sorted out which factors are the most important and the main motivation of Indonesian consumers to shop via online by using responses from respondents who usually shop online and offline in 3 cities in Indonesia, Jakarta, Surabaya and Samarinda. The research instruments were developed by conducting FGDs on relevant groups, either academics, online shopping activists, suppliers and courier businessmen in Jakarta, Surabaya and Samarinda Cities in effort to extract any information that encourages consumers to online shopping. After conducting FGD, the researcher produced 48 items proposed for factor analysis and after extracted to form eleven constructs, some items were removed because they had less loading factors. The eleven constructs or dimensions are trust, risk, consumer factors, website factors, price, service quality, convenience, subjective norm, product guarantee, variety of products and lifestyle. The implications of this study provide valuable insights about consumer decisions to online shopping or not online shopping.

The Importance of identifiers: IWGSC Meeting 20170720

OpenAIRE

Haak, Laurel

2017-01-01

Presentation by Laure Haak at the 20 July 2017 meeting of the IWGSC, about use of identifiers in connecting researchers, funding, facilities, and publications. Description of approach and initial results of User Facilities and Publications Working Group, and applications for Scientific Collections.

The Role of Attention for Context-Context Binding of Intrinsic and Extrinsic Features

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Boywitt, C. Dennis; Meiser, Thorsten

2012-01-01

There is converging evidence that the feeling of conscious recollection is usually accompanied by the bound retrieval of context features of the encoding episode (e.g., Meiser, Sattler, & Weiber, 2008). Recently, however, important limiting conditions have been identified for the binding between context features in memory. For example, focusing on…

Serotonin-immunoreactivity in the ventral nerve cord of Pycnogonida--support for individually identifiable neurons as ancestral feature of the arthropod nervous system.

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Brenneis, Georg; Scholtz, Gerhard

2015-07-10

The arthropod ventral nerve cord features a comparably low number of serotonin-immunoreactive neurons, occurring in segmentally repeated arrays. In different crustaceans and hexapods, these neurons have been individually identified and even inter-specifically homologized, based on their soma positions and neurite morphologies. Stereotypic sets of serotonin-immunoreactive neurons are also present in myriapods, whereas in the investigated chelicerates segmental neuron clusters with higher and variable cell numbers have been reported. This led to the suggestion that individually identifiable serotonin-immunoreactive neurons are an apomorphic feature of the Mandibulata. To test the validity of this neurophylogenetic hypothesis, we studied serotonin-immunoreactivity in three species of Pycnogonida (sea spiders). This group of marine arthropods is nowadays most plausibly resolved as sister group to all other extant chelicerates, rendering its investigation crucial for a reliable reconstruction of arthropod nervous system evolution. In all three investigated pycnogonids, the ventral walking leg ganglia contain different types of serotonin-immunoreactive neurons, the somata of which occurring mostly singly or in pairs within the ganglionic cortex. Several of these neurons are readily and consistently identifiable due to their stereotypic soma position and characteristic neurite morphology. They can be clearly homologized across different ganglia and different specimens as well as across the three species. Based on these homologous neurons, we reconstruct for their last common ancestor (presumably the pycnogonid stem species) a minimal repertoire of at least seven identified serotonin-immunoreactive neurons per hemiganglion. Beyond that, each studied species features specific pattern variations, which include also some neurons that were not reliably labeled in all specimens. Our results unequivocally demonstrate the presence of individually identifiable serotonin

Cherubism: Clinicoradiographic Features and Treatment

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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.

Prediction of interface residue based on the features of residue interaction network.

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Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Diagnostic importance of clinical and radiologic features of the Multiple Cemento-osseous dysplasia

International Nuclear Information System (INIS)

Han, M. R.; Kim, Y. H.; Kang, B. C.

1998-01-01

This case was diagnosed as multiple cementoosseous dysplasia on the basis of clinical and radiological features but was diagnosed as ossifying fibroma on the basis of histopathological feature. The histopathologic features of the multiple cementoosseous dysplasia and cementoossifying fibroma have common features of cementum, fibrous network and bone. Multiple cementoosseous dysplasia is reactive lesion and shows restricted lesion size, occurred on anterior and posterior tooth of the mandible and needs no treatment except periodic follow up. But Cementoossifying fibroma is the true neoplasm and grows continuously and needs surgical removal. The final diagnosis of the multiple cementoosseous dysplasia requires good correlation of the clinical histopathological, and radiological features.

How important is vehicle safety for older consumers in the vehicle purchase process?

Science.gov (United States)

Koppel, Sjaan; Clark, Belinda; Hoareau, Effie; Charlton, Judith L; Newstead, Stuart V

2013-01-01

This study aimed to investigate the importance of vehicle safety to older consumers in the vehicle purchase process. Older (n = 102), middle-aged (n = 791), and younger (n = 109) participants throughout the eastern Australian states of Victoria, New South Wales, and Queensland who had recently purchased a new or used vehicle completed an online questionnaire about their vehicle purchase process. When asked to list the 3 most important considerations in the vehicle purchase process (in an open-ended format), older consumers were mostly likely to list price as their most important consideration (43%). Similarly, when presented with a list of vehicle factors (such as price, design, Australasian New Car Assessment Program [ANCAP] rating), older consumers were most likely to identify price as the most important vehicle factor (36%). When presented with a list of vehicle features (such as automatic transmission, braking, air bags), older consumers in the current study were most likely to identify an antilock braking system (41%) as the most important vehicle feature, and 50 percent of older consumers identified a safety-related vehicle feature as the highest priority vehicle feature (50%). When asked to list up to 3 factors that make a vehicle safe, older consumers in the current study were most likely to list braking systems (35%), air bags (22%), and the driver's behavior or skill (11%). When asked about the influence of safety in the new vehicle purchase process, one third of older consumers reported that all new vehicles are safe (33%) and almost half of the older consumers rated their vehicle as safer than average (49%). A logistic regression model was developed to predict the profile of older consumers more likely to assign a higher priority to safety features in the vehicle purchasing process. The model predicted that the importance of safety-related features was influenced by several variables, including older consumers' beliefs that they could protect themselves

Cyberprints: Identifying Cyber Attackers by Feature Analysis

Science.gov (United States)

Blakely, Benjamin A.

2012-01-01

The problem of attributing cyber attacks is one of increasing importance. Without a solid method of demonstrating the origin of a cyber attack, any attempts to deter would-be cyber attackers are wasted. Existing methods of attribution make unfounded assumptions about the environment in which they will operate: omniscience (the ability to gather,…

Print advertisements for Alzheimer's disease drugs: informational and transformational features.

Science.gov (United States)

Gooblar, Jonathan; Carpenter, Brian D

2013-06-01

We examined print advertisements for Alzheimer's disease drugs published in journals and magazines between January 2008 and February 2012, using an informational versus transformational theoretical framework to identify objective and persuasive features. In 29 unique advertisements, we used qualitative methods to code and interpret identifying information, charts, benefit and side effect language, and persuasive appeals embedded in graphics and narratives. Most elements contained a mixture of informational and transformational features. Charts were used infrequently, but when they did appear the accompanying text often exaggerated the data. Benefit statements covered an array of symptoms, drug properties, and caregiver issues. Side effect statements often used positive persuasive appeals. Graphics and narrative features emphasized positive emotions and outcomes. We found subtle and sophisticated attempts both to educate and to persuade readers. It is important for consumers and prescribing physicians to read print advertisements critically so that they can make informed treatment choices.

TCGA study identifies genomic features of cervical cancer

Science.gov (United States)

Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified novel genomic and molecular characteristics of cervical cancer that will aid in subclassification of the disease and may help target therapies that are most appropriate for each patient.

Categorical templates are more useful when features are consistent: Evidence from eye movements during search for societally important vehicles.

Science.gov (United States)

Hout, Michael C; Robbins, Arryn; Godwin, Hayward J; Fitzsimmons, Gemma; Scarince, Collin

2017-08-01

Unlike in laboratory visual search tasks-wherein participants are typically presented with a pictorial representation of the item they are asked to seek out-in real-world searches, the observer rarely has veridical knowledge of the visual features that define their target. During categorical search, observers look for any instance of a categorically defined target (e.g., helping a family member look for their mobile phone). In these circumstances, people may not have information about noncritical features (e.g., the phone's color), and must instead create a broad mental representation using the features that define (or are typical of) the category of objects they are seeking out (e.g., modern phones are typically rectangular and thin). In the current investigation (Experiment 1), using a categorical visual search task, we add to the body of evidence suggesting that categorical templates are effective enough to conduct efficient visual searches. When color information was available (Experiment 1a), attentional guidance, attention restriction, and object identification were enhanced when participants looked for categories with consistent features (e.g., ambulances) relative to categories with more variable features (e.g., sedans). When color information was removed (Experiment 1b), attention benefits disappeared, but object recognition was still better for feature-consistent target categories. In Experiment 2, we empirically validated the relative homogeneity of our societally important vehicle stimuli. Taken together, our results are in line with a category-consistent view of categorical target templates (Yu, Maxfield, & Zelinsky in, Psychological Science, 2016. doi: 10.1177/0956797616640237 ), and suggest that when features of a category are consistent and predictable, searchers can create mental representations that allow for the efficient guidance and restriction of attention as well as swift object identification.

Atmospheric-water absorption features near 2.2 micrometers and their importance in high spectral resolution remote sensing

Science.gov (United States)

Kruse, F. A.; Clark, R. N.

1986-01-01

Selective absorption of electromagnetic radiation by atmospheric gases and water vapor is an accepted fact in terrestrial remote sensing. Until recently, only a general knowledge of atmospheric effects was required for analysis of remote sensing data; however, with the advent of high spectral resolution imaging devices, detailed knowledge of atmospheric absorption bands has become increasingly important for accurate analysis. Detailed study of high spectral resolution aircraft data at the U.S. Geological Survey has disclosed narrow absorption features centered at approximately 2.17 and 2.20 micrometers not caused by surface mineralogy. Published atmospheric transmission spectra and atmospheric spectra derived using the LOWTRAN-5 computer model indicate that these absorption features are probably water vapor. Spectral modeling indicates that the effects of atmospheric absorption in this region are most pronounced in spectrally flat materials with only weak absorption bands. Without correction and detailed knowledge of the atmospheric effects, accurate mapping of surface mineralogy (particularly at low mineral concentrations) is not possible.

Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.

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Taosheng Xu

Full Text Available Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms. Therefore, there are great opportunities for developing methods that can utilise network information in identifying cancer subtypes.In this paper, we propose a method, weighted similarity network fusion (WSNF, to utilise the information in the complex miRNA-TF-mRNA regulatory network in identifying cancer subtypes. We firstly build the regulatory network where the nodes represent the features, i.e. the microRNAs (miRNAs, transcription factors (TFs and messenger RNAs (mRNAs and the edges indicate the interactions between the features. The interactions are retrieved from various interatomic databases. We then use the network information and the expression data of the miRNAs, TFs and mRNAs to calculate the weight of the features, representing the level of importance of the features. The feature weight is then integrated into a network fusion approach to cluster the samples (patients and thus to identify cancer subtypes. We applied our method to the TCGA breast invasive carcinoma (BRCA and glioblastoma multiforme (GBM datasets. The experimental results show that WSNF performs better than the other commonly used computational methods, and the information from miRNA-TF-mRNA regulatory network contributes to the performance improvement. The WSNF method successfully identified five breast cancer subtypes and three GBM subtypes which show significantly different survival patterns. We observed that the expression patterns of the features in some mi

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.

Perceived Importance of Wellness Features at a Cancer Center: Patient and Staff Perspectives.

Science.gov (United States)

Tinner, Michelle; Crovella, Paul; Rosenbaum, Paula F

2018-01-01

Determine the relative impact of 11 building wellness features on preference and on the ability to deliver/receive quality care for two groups: patients and caregivers. The impact of building features that promote wellness is of increasing interest to the building owners, designers, and occupants. This study performed a postoccupancy evaluation of two user groups at a healthcare facility with specific wellness features. Seventy-six staff and 62 patients of a cancer center were polled separately to determine their preferences in 11 categories. Results showed that all wellness features were viewed favorably by the two groups, with natural lighting, views of nature, and thermal comfort as top categories for both. The t-test comparisons were performed, and significant differences ( p < .05) between the two groups were found for three of the features (views of nature, art and murals, and indoor plants). Discussion of these differences and the interaction of competing design goals (thermal comfort, views of nature, natural light, and desire for privacy) are included. Designers and owners will want to consider the preferred use of roof gardens, art and murals, and indoor plants for patient spaces, where their relative value is greater. Access to private and quiet spaces is the top need for caregivers. Ease of movement, thermal comfort, and natural light were top needs for patients.

RETAIL BANKING BUSINESS: CURRENT STATE ANDSPECIFIC FEATURES

Directory of Open Access Journals (Sweden)

Гузель Рефкадовна Фаизова

2013-04-01

Full Text Available The role and importance of the retail banking business in the banking sector continueto grow. The current state of the retail banking business is considered and specific features of this area in the face of growing demand for banking products and services by the public and interest from lending institutions are identified by the article.Purpose: Research of current state of retail banking business and detection specific features of this area.Methodology: In the process of analysis and researchof the question the methods of economical and statistical analysis, methods of comparison and generalizationwereused.Results: The conclusion is that interest in the retail banking business continues to grow.There were revealed the role and the importance of standardized service processes and standardized products and services delivering as one of the main line of development in the segment of retail business.DOI: http://dx.doi.org/10.12731/2218-7405-2013-3-2

NRC Information No. 90-01: Importance of proper response to self-identified violations by licensees

International Nuclear Information System (INIS)

Cunningham, R.E.

1992-01-01

NRC expects a high standard of compliance by its licensees and requires that licensees provide NRC accurate and complete information and that required records will also be complete and accurate in all material respects. Licensees should be aware of the importance placed by NRC on licensee programs for self detection, correction and reporting of violations or errors related to regulatory requirements. The General Statement of Policy and Procedures for NRC Enforcement Actions in Appendix C to 10 CFR Part 2 underscores the importance of licensees responding promptly and properly to self-identified violations in two ways. It is suggested that when a licensee identifies a violation involving an NRC-required record, the licensee should make a dated notation indicating identification, either on the record itself or other appropriate documentation retrievable for NRC review. The record with the self-identified violation noted should not be altered in any way to mask the correction. The licensee should determine the cause of the violation, correct the root cause of the violation, and document such findings in an appropriate manner. Licensees should also assure that if a report of the violation is required, the report is submitted to NRC in a timely manner. These actions will be considered by NRC in making any enforcement decision, and generally lead to lesser or no civil penalty

Examining the design features of a communication-rich, problem-centred mathematics professional development

Science.gov (United States)

de Araujo, Zandra; Orrill, Chandra Hawley; Jacobson, Erik

2018-04-01

While there is considerable scholarship describing principles for effective professional development, there have been few attempts to examine these principles in practice. In this paper, we identify and examine the particular design features of a mathematics professional development experience provided for middle grades teachers over 14 weeks. The professional development was grounded in a set of mathematical tasks that each had one right answer, but multiple solution paths. The facilitator engaged participants in problem solving and encouraged participants to work collaboratively to explore different solution paths. Through analysis of this collaborative learning environment, we identified five design features for supporting teacher learning of important mathematics and pedagogy in a problem-solving setting. We discuss these design features in depth and illustrate them by presenting an elaborated example from the professional development. This study extends the existing guidance for the design of professional development by examining and operationalizing the relationships among research-based features of effective professional development and the enacted features of a particular design.

Analytical Features: A Knowledge-Based Approach to Audio Feature Generation

Directory of Open Access Journals (Sweden)

Pachet François

2009-01-01

Full Text Available We present a feature generation system designed to create audio features for supervised classification tasks. The main contribution to feature generation studies is the notion of analytical features (AFs, a construct designed to support the representation of knowledge about audio signal processing. We describe the most important aspects of AFs, in particular their dimensional type system, on which are based pattern-based random generators, heuristics, and rewriting rules. We show how AFs generalize or improve previous approaches used in feature generation. We report on several projects using AFs for difficult audio classification tasks, demonstrating their advantage over standard audio features. More generally, we propose analytical features as a paradigm to bring raw signals into the world of symbolic computation.

Common Features in Electronic Structure of the Oxypnictide Superconductors from Photoemission Spectroscopy

International Nuclear Information System (INIS)

Xiao-Wen, Jia; Hai-Yun, Liu; Wen-Tao, Zhang; Lin, Zhao; Jian-Qiao, Meng; Guo-Dong, Liu; Xiao-Li, Dong; Zhi-An, Ren; Wei, Yi; Guang-Can, Che; Zhong-Xian, Zhao; Gang, Wu; Rong-Hua, Liu; Xian-Hui, Chen; Gen-Fu, Chen; Nan-Lin, Wang; Yong, Zhu; Xiao-Yang, Wang; Gui-Ling, Wang; Yong, Zhou

2008-01-01

High resolution photoemission measurements are carried out on non-superconducting LaFeAsO parent compound and various superconducting RFeAs(O 1-x F x ) (R=La, Ce and Pr) compounds. It is found that the parent LaFeAsO compound shows a metallic character. By extensive measurements, several common features are identified in the electronic structure of these Fe-based compounds: (1) 0.2 eV feature in the valence band, (2) a universal 13-16 meV feature, (3) near Ef spectral weight suppression with decreasing temperature. These universal features can provide important information about band structure, superconducting gap and pseudogap in these Fe-based materials

Proposal of Non-Contact Type Interface of Command Input Using Lip Motion Features

Science.gov (United States)

Sato, Yoshiyuki; Kageyama, Yoichi; Nishida, Makoto

Lip motion features are of practical use in identifying individuals. It is therefore important to develop non-contact type interface. For the interface using lip motion features, individual differences such as accents and dialects in commands should be accepted. In this paper, we propose a method to identify commands by analyzing three kinds of lip motion features. They are lip width, lip length, and ratio of width and length. The analysis is made on the basis of these features' relative values obtained from the primary and object frame. The proposed method has three steps. First, we extracted the lip motion features on the basis of both positions and shapes of lip in each frame of facial images. Second, standard patterns were created from features of six utterances per command. The standard pattern is able to reduce the relative difference in the lip motion features. Third, similarities among commands were computed by Dynamic-Programming (DP) matching. And then, the command with the largest similarity was selected as the target one. Our experimental results suggest that proposed method is useful to construct the non-contact type interface of command input using lip motion features.

On the importance of identifying, characterizing, and predicting fundamental phenomena towards microbial electrochemistry applications.

Science.gov (United States)

Torres, César Iván

2014-06-01

The development of microbial electrochemistry research toward technological applications has increased significantly in the past years, leading to many process configurations. This short review focuses on the need to identify and characterize the fundamental phenomena that control the performance of microbial electrochemical cells (MXCs). Specifically, it discusses the importance of recent efforts to discover and characterize novel microorganisms for MXC applications, as well as recent developments to understand transport limitations in MXCs. As we increase our understanding of how MXCs operate, it is imperative to continue modeling efforts in order to effectively predict their performance, design efficient MXC technologies, and implement them commercially. Thus, the success of MXC technologies largely depends on the path of identifying, understanding, and predicting fundamental phenomena that determine MXC performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Hypothesis testing for differentially correlated features.

Science.gov (United States)

Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

2016-10-01

In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Use of amplified fragment length polymorphism analysis to identify medically important Candida spp., including C-dubliniensis

NARCIS (Netherlands)

Borst, A; Theelen, B; Reinders, E; Boekhout, T; Fluit, AC; Savelkoul, PHM

Non-Candida albicans Candida species are increasingly being isolated. These species show differences in levels of resistance to antimycotic agents and mortality. Therefore, it is important to be able to correctly identify the causative organism to the species level. Identification of C. dubliniensis

Use of amplified fragment length polymorphism analysis to identify medically important Candida spp., including C. dubliniensis.

NARCIS (Netherlands)

Borst, A; Theelen, B; Reinders, E; Boekhout, T; Fluit, AC; Savelkoul, P.H.M.

2003-01-01

Non-Candida albicans Candida species are increasingly being isolated. These species show differences in levels of resistance to antimycotic agents and mortality. Therefore, it is important to be able to correctly identify the causative organism to the species level. Identification of C. dubliniensis

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

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Christine E. Kistler

2017-06-01

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

Evaluations and utilizations of risk importances

International Nuclear Information System (INIS)

Vesely, W.E.; Davis, T.C.

1985-08-01

This report presents approaches for utilizing Probabilistic Risk Analyses (PRA's) to determine risk importances. Risk importances are determined for design features, plant operations, and other factors that can affect risk. PRA's can be used to identify the importances of risk contributors or proposed changes to designs or operations. The objective of this report is to serve as a handbook and guide in evaluating and applying risk importances. The utilization of both qualitative risk importances and quantitative risk importances is described in this report. Qualitative risk importances are based on the logic models in the PRA, while quantitative risk importances are based on the quantitative results of the PRA. Both types of importances are among the most robust and meaningful information a PRA can provide. A wide variety of risk importance evaluations are described including evaluations of the importances of design changes, testing, maintenance, degrading environments, and aging. Specific utilizations are described in inspection and in reliability assurance programs, however the general approaches have widespread applicability. The role of personal computers and decision support programs in applying risk importance evaluations is also described

Comprehensive metabolomics identified lipid peroxidation as a prominent feature in human plasma of patients with coronary heart diseases

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Jianhong Lu

2017-08-01

Full Text Available Coronary heart disease (CHD is a complex human disease associated with inflammation and oxidative stress. The underlying mechanisms and diagnostic biomarkers for the different types of CHD remain poorly defined. Metabolomics has been increasingly recognized as an enabling technique with the potential to identify key metabolomic features in an attempt to understand the pathophysiology and differentiate different stages of CHD. We performed comprehensive metabolomic analysis in human plasma from 28 human subjects with stable angina (SA, myocardial infarction (MI, and healthy control (HC. Subsequent analysis demonstrated a uniquely altered metabolic profile in these CHD: a total of 18, 37 and 36 differential metabolites were identified to distinguish SA from HC, MI from SA, and MI from HC groups respectively. Among these metabolites, glycerophospholipid (GPL metabolism emerged as the most significantly disturbed pathway. Next, we used a targeted metabolomic approach to systematically analyze GPL, oxidized phospholipid (oxPL, and downstream metabolites derived from polyunsaturated fatty acids (PUFAs, such as arachidonic acid and linoleic acid. Surprisingly, lipids associated with lipid peroxidation (LPO pathways including oxidized PL and isoprostanes, isomers of prostaglandins, were significantly elevated in plasma of MI patients comparing to HC and SA, consistent with the notion that oxidative stress-induced LPO is a prominent feature in CHD. Our studies using the state-of-the-art metabolomics help to understand the underlying biological mechanisms involved in the pathogenesis of CHD; LPO metabolites may serve as potential biomarkers to differentiation MI from SA and HC. Keywords: Metabolomics, Lipid peroxidation, Lipidomics, Myocardial infarction, Isoprostanes, Coronary heart disease (CHD

A Novel Technique for Identifying Patients with ICU Needs Using Hemodynamic Features

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A. Jalali

2012-01-01

Full Text Available Identification of patients requiring intensive care is a critical issue in clinical treatment. The objective of this study is to develop a novel methodology using hemodynamic features for distinguishing such patients requiring intensive care from a group of healthy subjects. In this study, based on the hemodynamic features, subjects are divided into three groups: healthy, risky and patient. For each of the healthy and patient subjects, the evaluated features are based on the analysis of existing differences between hemodynamic variables: Blood Pressure and Heart Rate. Further, four criteria from the hemodynamic variables are introduced: circle criterion, estimation error criterion, Poincare plot deviation, and autonomic response delay criterion. For each of these criteria, three fuzzy membership functions are defined to distinguish patients from healthy subjects. Furthermore, based on the evaluated criteria, a scoring method is developed. In this scoring method membership degree of each subject is evaluated for the three classifying groups. Then, for each subject, the cumulative sum of membership degree of all four criteria is calculated. Finally, a given subject is classified with the group which has the largest cumulative sum. In summary, the scoring method results in 86% sensitivity, 94.8% positive predictive accuracy and 82.2% total accuracy.

Featured Image: Identifying a Glowing Shell

Science.gov (United States)

Kohler, Susanna

2018-05-01

New nebulae are being discovered and classified every day and this false-color image reveals one of the more recent objects of interest. This nebula, IPHASX J210204.7+471015, was recently imaged by the Andalucia Faint Object Spectrograph and Camera mounted on the 2.5-m Nordic Optical Telescope in La Palma, Spain. J210204 was initially identified as a possible planetary nebula a remnant left behind at the end of a red giants lifetime. Based on the above imaging, however, a team of authors led by Martn Guerrero (Institute of Astrophysics of Andalusia, Spain) is arguing that this shell of glowing gas was instead expelled around a classical nova. In a classical nova eruption, a white dwarf and its binary companion come very close together, and mass transfers to form a thin atmosphere of hydrogen around the white dwarf. When this hydrogen suddenly ignites in runaway fusion, this outer atmosphere can be expelled, forming a short-lived nova remnant which is what Guerrero and collaborators think were seeing with J210204. If so, this nebula can reveal information about the novathat caused it. To find out more about what the authors learned from this nebula, check out the paper below.CitationMartn A. Guerrero et al 2018 ApJ 857 80. doi:10.3847/1538-4357/aab669

Familiarity and within-person facial variability: the importance of the internal and external features

OpenAIRE

Kramer, R. S. S.; Manesi, Z.; Towler, A.; Reynolds, M. G.; Burton, A. M.

2018-01-01

As faces become familiar, we come to rely more on their internal features for recognition and matching tasks. Here, we assess whether this same pattern is also observed for a card sorting task. Participants sorted photos showing either the full face, only the internal features, or only the external features into multiple piles, one pile per identity. In Experiments 1 and 2, we showed the standard advantage for familiar faces—sorting was more accurate and showed very few errors in comparison w...

Reducing uncertainty at minimal cost: a method to identify important input parameters and prioritize data collection

NARCIS (Netherlands)

Uwizeye, U.A.; Groen, E.A.; Gerber, P.J.; Schulte, Rogier P.O.; Boer, de I.J.M.

2016-01-01

The study aims to illustrate a method to identify important input parameters that explain most of the output variance ofenvironmental assessment models. The method is tested for the computation of life-cycle nitrogen (N) use efficiencyindicators among mixed dairy production systems in Rwanda. We

Classification of radiolarian images with hand-crafted and deep features

Science.gov (United States)

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

2017-12-01

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

PCR-RFLP Method to Identify Salmonid Species of Economic Importance

Directory of Open Access Journals (Sweden)

Andreea Dudu

2011-05-01

Full Text Available The identification of different fish species by molecular methods has become necessary to avoid both the incorrect labelling of individuals involved in repopulation programmes and the commercial frauds on the fish market. Different fish species of great economical importance, like the salmonids, which are very much requested for their meat, can be identified using molecular techniques such as PCR-RFLP. The method is based on the amplification of a target region from the genome by PCR reaction followed by endonucleases digestion to detect the polymorphism of restriction fragments. In our study we analysed the following salmonid species from Romania: Salmo trutta fario, Salmo labrax, Salvelinus fontinalis, Onchorhynchus mykiss, Thymallus thymallus and Hucho hucho. In order to discriminate between the analysed species we amplified a fragment of mitochondrial genome comprising tRNAGlu/ cytochrome b/ tRNAThr/ tRNAPro/ D-loop/ tRNAPhe, followed by digestion with a specific restriction enzyme. The direct digestion of unpurified PCR products generated species-specific restriction patterns and proved to be a simple, reliable, inexpensive and fast method. Thus, it may be successfully utilized in specialized laboratories for the correct identification of the fish species for multiple purposes, including the traceability of fish food products.

A comparative analysis of DNA barcode microarray feature size

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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.

Finding Important Terms for Patients in Their Electronic Health Records: A Learning-to-Rank Approach Using Expert Annotations

Science.gov (United States)

Zheng, Jiaping; Yu, Hong

2016-01-01

Background Many health organizations allow patients to access their own electronic health record (EHR) notes through online patient portals as a way to enhance patient-centered care. However, EHR notes are typically long and contain abundant medical jargon that can be difficult for patients to understand. In addition, many medical terms in patients’ notes are not directly related to their health care needs. One way to help patients better comprehend their own notes is to reduce information overload and help them focus on medical terms that matter most to them. Interventions can then be developed by giving them targeted education to improve their EHR comprehension and the quality of care. Objective We aimed to develop a supervised natural language processing (NLP) system called Finding impOrtant medical Concepts most Useful to patientS (FOCUS) that automatically identifies and ranks medical terms in EHR notes based on their importance to the patients. Methods First, we built an expert-annotated corpus. For each EHR note, 2 physicians independently identified medical terms important to the patient. Using the physicians’ agreement as the gold standard, we developed and evaluated FOCUS. FOCUS first identifies candidate terms from each EHR note using MetaMap and then ranks the terms using a support vector machine-based learn-to-rank algorithm. We explored rich learning features, including distributed word representation, Unified Medical Language System semantic type, topic features, and features derived from consumer health vocabulary. We compared FOCUS with 2 strong baseline NLP systems. Results Physicians annotated 90 EHR notes and identified a mean of 9 (SD 5) important terms per note. The Cohen’s kappa annotation agreement was .51. The 10-fold cross-validation results show that FOCUS achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.940 for ranking candidate terms from EHR notes to identify important terms. When including term

Histological image classification using biologically interpretable shape-based features

International Nuclear Information System (INIS)

Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

2013-01-01

Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

Print Advertisements for Alzheimer’s Disease Drugs: Informational and Transformational Features

Science.gov (United States)

Gooblar, Jonathan; Carpenter, Brian D.

2014-01-01

Purpose We examined print advertisements for Alzheimer’s disease drugs published in journals and magazines between January 2008 and February 2012, using an informational versus transformational theoretical framework to identify objective and persuasive features. Methods In 29 unique advertisements, we used qualitative methods to code and interpret identifying information, charts, benefit and side effect language, and persuasive appeals embedded in graphics and narratives. Results Most elements contained a mixture of informational and transformational features. Charts were used infrequently, but when they did appear the accompanying text often exaggerated the data. Benefit statements covered an array of symptoms, drug properties, and caregiver issues. Side effect statements often used positive persuasive appeals. Graphics and narrative features emphasized positive emotions and outcomes. Implications We found subtle and sophisticated attempts both to educate and to persuade readers. It is important for consumers and prescribing physicians to read print advertisements critically so that they can make informed treatment choices. PMID:23687184

Comparison of Cytotoxic Activity in Leukemic Lineages Reveals Important Features of β-Hairpin Antimicrobial Peptides.

Science.gov (United States)

Buri, Marcus V; Torquato, Heron F Vieira; Barros, Carlos Castilho; Ide, Jaime S; Miranda, Antonio; Paredes-Gamero, Edgar J

2017-07-01

Several reports described different modes of cell death triggered by antimicrobial peptides (AMPs) due to direct effects on membrane disruption, and more recently by apoptosis and necrosis-like patterns. Cytotoxic curves of four β-hairpin AMPs (gomesin, protegrin, tachyplesin, and polyphemusin) were obtained from several human leukemic lineages and normal monocytes and Two cell lines were then selected based on their cytotoxic sensitivity. One was sensitive to AMPs (K562) and the other resistant (KG-1) and their effect compared between these lineages. Thus, these lineages were chosen to further investigate biological features related with their cytotoxicities to AMPs. Stimulation with AMPs produced cell death, with activation of caspase-3, in K562 lineage. Increase on the fluidity of plasmatic membrane by reducing cholesterol potentiated cytotoxicity of AMPs in both lineages. Quantification of internal and external gomesin binding to the cellular membrane of both K562 and KG-1 cells showed that more peptide is accumulated inside of K562 cells. Additionally, evaluation of multi-drug resistant pumps activity showed that KG-1 has more activity than K562 lineage. A comparison of intrinsic gene patterns showed great differences between K562 and KG-1, but stimulation with gomesin promoted few changes in gene expression patterns. Differences in internalization process through the plasma membrane, multidrug resistance pumps activity, and gene expression pattern are important features to AMPs regulated cell death. J. Cell. Biochem. 118: 1764-1773, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Quantitative Analysis of the Association Angle between T-cell Receptor Vα/Vβ Domains Reveals Important Features for Epitope Recognition.

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Thomas Hoffmann

2015-07-01

Full Text Available T-cell receptors (TCR play an important role in the adaptive immune system as they recognize pathogen- or cancer-based epitopes and thus initiate the cell-mediated immune response. Therefore there exists a growing interest in the optimization of TCRs for medical purposes like adoptive T-cell therapy. However, the molecular mechanisms behind T-cell signaling are still predominantly unknown. For small sets of TCRs it was observed that the angle between their Vα- and Vβ-domains, which bind the epitope, can vary and might be important for epitope recognition. Here we present a comprehensive, quantitative study of the variation in the Vα/Vβ interdomain-angle and its influence on epitope recognition, performing a systematic bioinformatics analysis based on a representative set of experimental TCR structures. For this purpose we developed a new, cuboid-based superpositioning method, which allows a unique, quantitative analysis of the Vα/Vβ-angles. Angle-based clustering led to six significantly different clusters. Analysis of these clusters revealed the unexpected result that the angle is predominantly influenced by the TCR-clonotype, whereas the bound epitope has only a minor influence. Furthermore we could identify a previously unknown center of rotation (CoR, which is shared by all TCRs. All TCR geometries can be obtained by rotation around this center, rendering it a new, common TCR feature with the potential of improving the accuracy of TCR structure prediction considerably. The importance of Vα/Vβ rotation for signaling was confirmed as we observed larger variances in the Vα/Vβ-angles in unbound TCRs compared to epitope-bound TCRs. Our results strongly support a two-step mechanism for TCR-epitope: First, preformation of a flexible TCR geometry in the unbound state and second, locking of the Vα/Vβ-angle in a TCR-type specific geometry upon epitope-MHC association, the latter being driven by rotation around the unique center of rotation.

Clinically Important Features of Porphyrin and Heme Metabolism and the Porphyrias

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Siddesh Besur

2014-11-01

Full Text Available Heme, like chlorophyll, is a primordial molecule and is one of the fundamental pigments of life. Disorders of normal heme synthesis may cause human diseases, including certain anemias (X-linked sideroblastic anemias and porphyrias. Porphyrias are classified as hepatic and erythropoietic porphyrias based on the organ system in which heme precursors (5-aminolevulinic acid (ALA, porphobilinogen and porphyrins are chiefly overproduced. The hepatic porphyrias are further subdivided into acute porphyrias and chronic hepatic porphyrias. The acute porphyrias include acute intermittent, hereditary copro-, variegate and ALA dehydratase deficiency porphyria. Chronic hepatic porphyrias include porphyria cutanea tarda and hepatoerythropoietic porphyria. The erythropoietic porphyrias include congenital erythropoietic porphyria (Gűnther’s disease and erythropoietic protoporphyria. In this review, we summarize the key features of normal heme synthesis and its differing regulation in liver versus bone marrow. In both organs, principal regulation is exerted at the level of the first and rate-controlling enzyme, but by different molecules (heme in the liver and iron in the bone marrow. We also describe salient clinical, laboratory and genetic features of the eight types of porphyria.

The Non-motor Features of Essential Tremor: A Primary Disease Feature or Just a Secondary Phenomenon?

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Ketan Jhunjhunwala

2014-08-01

Full Text Available Essential tremor (ET is a pathologically heterogeneous neurodegenerative disorder with both motor and increasingly recognized non-motor features. It is debated whether the non-motor manifestations in ET result from widespread neurodegeneration or are merely secondary to impaired motor functions and decreased quality of life due to tremor. It is important to review these features to determine how to best treat the non-motor symptoms of patients and to understand the basic pathophysiology of the disease and develop appropriate pharmacotherapies. In this review, retrospective and prospective clinical studies were critically analyzed to identify possible correlations between the severities of non-motor features and tremor. We speculated that if such a correlation existed, the non-motor features were likely to be secondary to tremor. According to the current literature, the deficits in executive function, attention, concentration, and memory often observed in ET are likely to be a primary manifestation of the disease. It has also been documented that patients with ET often exhibit characteristic personality traits. However, it remains to be determined whether the other non-motor features often seen in ET, such as anxiety, depression, and sleep disturbances are primary or secondary to motor manifestations of ET and subsequent poor quality of life. Finally, there is evidence that patients with ET can also have impaired color vision, disturbances of olfaction, and hearing impairments, though there are few studies in these areas. Further investigations of large cohorts of patients with ET are required to understand the prevalence, nature, and true significance of the non-motor features in ET.

A pair of seamount chains in the Central Indian Basin, identified from multibeam mapping

Digital Repository Service at National Institute of Oceanography (India)

Kodagali, V.N.

Seamounts are major physiographic features on the ocean floor. Their study is important to the understanding of the tectonic history of the seafloor. Over 150 seamounts were identified during the multibeam (Hydrosweep system) mapping of the Central...

Language Features and Culture Features on Short Message

Institute of Scientific and Technical Information of China (English)

王佳

2013-01-01

Mobile phone is regarded as“the fifth media”after newspaper,radio,TV and the Internet.The mobile phone short message further highlights the importance of written signs in communication.“The thumb revolution”is eagerly anticipating one kind of trend by the hand replace of mouth,sound substitute for the quiet around us. My paper will analyze the language features and the culture features of mobile phone short messages which are written in Chinese and English.

Stylistic Features of Comment in Arabic Blogosphere

Directory of Open Access Journals (Sweden)

Gabdulzyamil G. Zaynullin

2017-11-01

Full Text Available One of the most important issues in the study of the functioning of the Internet language is the definition of the features of each Internet genre presented in online communication, taking into account the linguocultural features of the language in question. This paper studies the genre of the Internet comments of the Arabic-speaking blogosphere and reveals its stylistic features. The most common goal of the comment is gratitude, followed by praise. We created a corpus of comments from blogs of various subjects, and then conducted the tagging, having identified the group to which we attributed a comment, depending on the subject and the communicative goal. With the help of the Lexico 3 software, the most frequent lexical units were identified, the lexical features of the comments were described, the main one being the widespread use of religionyms, and the relationship between the blog subject and the stylistic characteristics of communication was revealed. The article traces the correlation between the literary and colloquial functional style in the comments, and also draws a conclusion that the comments are of a conversational, informal character. The main devices of expressiveness that are characteristic for both network and pre-network communication were revealed, and the tendency of the analysts to observe in the comments a stable three-part composition (greeting, message, final formula. The influence of traditional Arabic rhetoric, as well as the epistolary genre, was preserved. The results of the paper can be used when studying other genres of Internet communication in Arabic and in comparative studies to create the linguistic software.

Search features of digital libraries

Directory of Open Access Journals (Sweden)

Alastair G. Smith

2000-01-01

Full Text Available Traditional on-line search services such as Dialog, DataStar and Lexis provide a wide range of search features (boolean and proximity operators, truncation, etc. This paper discusses the use of these features for effective searching, and argues that these features are required, regardless of advances in search engine technology. The literature on on-line searching is reviewed, identifying features that searchers find desirable for effective searching. A selective survey of current digital libraries available on the Web was undertaken, identifying which search features are present. The survey indicates that current digital libraries do not implement a wide range of search features. For instance: under half of the examples included controlled vocabulary, under half had proximity searching, only one enabled browsing of term indexes, and none of the digital libraries enable searchers to refine an initial search. Suggestions are made for enhancing the search effectiveness of digital libraries, for instance by: providing a full range of search operators, enabling browsing of search terms, enhancement of records with controlled vocabulary, enabling the refining of initial searches, etc.

The importance of service-users' perspectives: A systematic review of qualitative evidence reveals overlooked critical features of weight management programmes.

Science.gov (United States)

Sutcliffe, Katy; Melendez-Torres, G J; Burchett, Helen E D; Richardson, Michelle; Rees, Rebecca; Thomas, James

2018-03-14

Extensive research effort shows that weight management programmes (WMPs) targeting both diet and exercise are broadly effective. However, the critical features of WMPs remain unclear. To develop a deeper understanding of WMPs critical features, we undertook a systematic review of qualitative evidence. We sought to understand from a service-user perspective how programmes are experienced, and may be effective, on the ground. We identified qualitative studies from existing reviews and updated the searches of one review. We included UK studies capturing the views of adult WMP users. Thematic analysis was used inductively to code and synthesize the evidence. Service users were emphatic that supportive relationships, with service providers or WMP peers, are the most critical aspect of WMPs. Supportive relationships were described as providing an extrinsic motivator or "hook" which helped to overcome barriers such as scepticism about dietary advice or a lack confidence to engage in physical activity. The evidence revealed that service-users' understandings of the critical features of WMPs differ from the focus of health promotion guidance or descriptions of evaluated programmes which largely emphasize educational or goal setting aspects of WMPs. Existing programme guidance may not therefore fully address the needs of service users. The study illustrates that the perspectives of service users can reveal unanticipated intervention mechanisms or underemphasized critical features and underscores the value of a holistic understanding about "what happens" in complex psychosocial interventions such as WMPs. © 2017 The Authors Health Expectations published by John Wiley & Sons Ltd.

Using the Developmental Gene Bicoid to Identify Species of Forensically Important Blowflies (Diptera: Calliphoridae

Directory of Open Access Journals (Sweden)

Seong Hwan Park

2013-01-01

Full Text Available Identifying species of insects used to estimate postmortem interval (PMI is a major subject in forensic entomology. Because forensic insect specimens are morphologically uniform and are obtained at various developmental stages, DNA markers are greatly needed. To develop new autosomal DNA markers to identify species, partial genomic sequences of the bicoid (bcd genes, containing the homeobox and its flanking sequences, from 12 blowfly species (Aldrichina grahami, Calliphora vicina, Calliphora lata, Triceratopyga calliphoroides, Chrysomya megacephala, Chrysomya pinguis, Phormia regina, Lucilia ampullacea, Lucilia caesar, Lucilia illustris, Hemipyrellia ligurriens and Lucilia sericata; Calliphoridae: Diptera were determined and analyzed. This study first sequenced the ten blowfly species other than C. vicina and L. sericata. Based on the bcd sequences of these 12 blowfly species, a phylogenetic tree was constructed that discriminates the subfamilies of Calliphoridae (Luciliinae, Chrysomyinae, and Calliphorinae and most blowfly species. Even partial genomic sequences of about 500 bp can distinguish most blowfly species. The short intron 2 and coding sequences downstream of the bcd homeobox in exon 3 could be utilized to develop DNA markers for forensic applications. These gene sequences are important in the evolution of insect developmental biology and are potentially useful for identifying insect species in forensic science.

Using the Developmental Gene Bicoid to Identify Species of Forensically Important Blowflies (Diptera: Calliphoridae)

Science.gov (United States)

Park, Seong Hwan; Park, Chung Hyun; Zhang, Yong; Piao, Huguo; Chung, Ukhee; Kim, Seong Yoon; Ko, Kwang Soo; Yi, Cheong-Ho; Jo, Tae-Ho; Hwang, Juck-Joon

2013-01-01

Identifying species of insects used to estimate postmortem interval (PMI) is a major subject in forensic entomology. Because forensic insect specimens are morphologically uniform and are obtained at various developmental stages, DNA markers are greatly needed. To develop new autosomal DNA markers to identify species, partial genomic sequences of the bicoid (bcd) genes, containing the homeobox and its flanking sequences, from 12 blowfly species (Aldrichina grahami, Calliphora vicina, Calliphora lata, Triceratopyga calliphoroides, Chrysomya megacephala, Chrysomya pinguis, Phormia regina, Lucilia ampullacea, Lucilia caesar, Lucilia illustris, Hemipyrellia ligurriens and Lucilia sericata; Calliphoridae: Diptera) were determined and analyzed. This study first sequenced the ten blowfly species other than C. vicina and L. sericata. Based on the bcd sequences of these 12 blowfly species, a phylogenetic tree was constructed that discriminates the subfamilies of Calliphoridae (Luciliinae, Chrysomyinae, and Calliphorinae) and most blowfly species. Even partial genomic sequences of about 500 bp can distinguish most blowfly species. The short intron 2 and coding sequences downstream of the bcd homeobox in exon 3 could be utilized to develop DNA markers for forensic applications. These gene sequences are important in the evolution of insect developmental biology and are potentially useful for identifying insect species in forensic science. PMID:23586044

Acoustic features of objects matched by an echolocating bottlenose dolphin.

Science.gov (United States)

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

2006-03-01

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

MRI features associated with acute appendicitis

NARCIS (Netherlands)

Leeuwenburgh, Marjolein M. N.; Jensch, Sebastiaan; Gratama, Jan W. C.; Spilt, Aart; Wiarda, Bart M.; van Es, H. Wouter; Cobben, Lodewijk P. J.; Bossuyt, Patrick M. M.; Boermeester, Marja A.; Stoker, Jaap; Bouma, Wim H.; Houdijk, Alexander P. J.; Richir, Milan C.; Stockmann, Hein B. A. C.; Wiezer, Marinus J.; Verhagen, Thijs

2014-01-01

To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith,

Genomic, Epigenomic, and Transcriptomic Profiling towards Identifying Omics Features and Specific Biomarkers That Distinguish Uterine Leiomyosarcoma and Leiomyoma at Molecular Levels

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Tomoko Miyata

2015-01-01

Full Text Available Uterine leiomyosarcoma (LMS is the worst malignancy among the gynecologic cancers. Uterine leiomyoma (LM, a benign tumor of myometrial origin, is the most common among women of childbearing age. Because of their similar symptoms, it is difficult to preoperatively distinguish the two conditions only by ultrasound and pelvic MRI. While histopathological diagnosis is currently the main approach used to distinguish them postoperatively, unusual histologic variants of LM tend to be misdiagnosed as LMS. Therefore, development of molecular diagnosis as an alternative or confirmatory means will help to diagnose LMS more accurately. We adopted omics-based technologies to identify genome-wide features to distinguish LMS from LM and revealed that copy number, gene expression, and DNA methylation profiles successfully distinguished these tumors. LMS was found to possess features typically observed in malignant solid tumors, such as extensive chromosomal abnormalities, overexpression of cell cycle-related genes, hypomethylation spreading through large genomic regions, and frequent hypermethylation at the polycomb group target genes and protocadherin genes. We also identified candidate expression and DNA methylation markers, which will facilitate establishing postoperative molecular diagnostic tests based on conventional quantitative assays. Our results demonstrate the feasibility of establishing such tests and the possibility of developing preoperative and noninvasive methods.

Gene expression profiling identifies inflammation and angiogenesis as distinguishing features of canine hemangiosarcoma

International Nuclear Information System (INIS)

Tamburini, Beth A; Cutter, Gary R; Wojcieszyn, John W; Bellgrau, Donald; Gemmill, Robert M; Hunter, Lawrence E; Modiano, Jaime F; Phang, Tzu L; Fosmire, Susan P; Scott, Milcah C; Trapp, Susan C; Duckett, Megan M; Robinson, Sally R; Slansky, Jill E; Sharkey, Leslie C

2010-01-01

The etiology of hemangiosarcoma remains incompletely understood. Its common occurrence in dogs suggests predisposing factors favor its development in this species. These factors could represent a constellation of heritable characteristics that promote transformation events and/or facilitate the establishment of a microenvironment that is conducive for survival of malignant blood vessel-forming cells. The hypothesis for this study was that characteristic molecular features distinguish hemangiosarcoma from non-malignant endothelial cells, and that such features are informative for the etiology of this disease. We first investigated mutations of VHL and Ras family genes that might drive hemangiosarcoma by sequencing tumor DNA and mRNA (cDNA). Protein expression was examined using immunostaining. Next, we evaluated genome-wide gene expression profiling using the Affymetrix Canine 2.0 platform as a global approach to test the hypothesis. Data were evaluated using routine bioinformatics and validation was done using quantitative real time RT-PCR. Each of 10 tumor and four non-tumor samples analyzed had wild type sequences for these genes. At the genome wide level, hemangiosarcoma cells clustered separately from non-malignant endothelial cells based on a robust signature that included genes involved in inflammation, angiogenesis, adhesion, invasion, metabolism, cell cycle, signaling, and patterning. This signature did not simply reflect a cancer-associated angiogenic phenotype, as it also distinguished hemangiosarcoma from non-endothelial, moderately to highly angiogenic bone marrow-derived tumors (lymphoma, leukemia, osteosarcoma). The data show that inflammation and angiogenesis are important processes in the pathogenesis of vascular tumors, but a definitive ontogeny of the cells that give rise to these tumors remains to be established. The data do not yet distinguish whether functional or ontogenetic plasticity creates this phenotype, although they suggest that cells

Gene expression profiling identifies inflammation and angiogenesis as distinguishing features of canine hemangiosarcoma

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Slansky Jill E

2010-11-01

Full Text Available Abstract Background The etiology of hemangiosarcoma remains incompletely understood. Its common occurrence in dogs suggests predisposing factors favor its development in this species. These factors could represent a constellation of heritable characteristics that promote transformation events and/or facilitate the establishment of a microenvironment that is conducive for survival of malignant blood vessel-forming cells. The hypothesis for this study was that characteristic molecular features distinguish hemangiosarcoma from non-malignant endothelial cells, and that such features are informative for the etiology of this disease. Methods We first investigated mutations of VHL and Ras family genes that might drive hemangiosarcoma by sequencing tumor DNA and mRNA (cDNA. Protein expression was examined using immunostaining. Next, we evaluated genome-wide gene expression profiling using the Affymetrix Canine 2.0 platform as a global approach to test the hypothesis. Data were evaluated using routine bioinformatics and validation was done using quantitative real time RT-PCR. Results Each of 10 tumor and four non-tumor samples analyzed had wild type sequences for these genes. At the genome wide level, hemangiosarcoma cells clustered separately from non-malignant endothelial cells based on a robust signature that included genes involved in inflammation, angiogenesis, adhesion, invasion, metabolism, cell cycle, signaling, and patterning. This signature did not simply reflect a cancer-associated angiogenic phenotype, as it also distinguished hemangiosarcoma from non-endothelial, moderately to highly angiogenic bone marrow-derived tumors (lymphoma, leukemia, osteosarcoma. Conclusions The data show that inflammation and angiogenesis are important processes in the pathogenesis of vascular tumors, but a definitive ontogeny of the cells that give rise to these tumors remains to be established. The data do not yet distinguish whether functional or ontogenetic

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

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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.

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.

Quantitative imaging features: extension of the oncology medical image database

Science.gov (United States)

Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

2015-03-01

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

Identifying important parameters for a continuous bioscouring process

NARCIS (Netherlands)

Lenting, H.B.M.; Lenting, H.B.M.; Zwier, E.; Nierstrasz, Vincent

2002-01-01

Compared to a bioscouring process in the batch mode, a continuously operating process requires relatively short processing steps. This study focusses on minimizing the required enzymatic incubation time. It is clear that the presence of a sufficient level of surfactant is of major importance in

Selecting protein families for environmental features based on manifold regularization.

Science.gov (United States)

Jiang, Xingpeng; Xu, Weiwei; Park, E K; Li, Guangrong

2014-06-01

Recently, statistics and machine learning have been developed to identify functional or taxonomic features of environmental features or physiological status. Important proteins (or other functional and taxonomic entities) to environmental features can be potentially used as biosensors. A major challenge is how the distribution of protein and gene functions embodies the adaption of microbial communities across environments and host habitats. In this paper, we propose a novel regularization method for linear regression to adapt the challenge. The approach is inspired by local linear embedding (LLE) and we call it a manifold-constrained regularization for linear regression (McRe). The novel regularization procedure also has potential to be used in solving other linear systems. We demonstrate the efficiency and the performance of the approach in both simulation and real data.

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

Science.gov (United States)

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

2018-03-01

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

The hierarchy-by-interval approach to identifying important models that need improvement in severe-accident simulation codes

International Nuclear Information System (INIS)

Heames, T.J.; Khatib-Rahbar, M.; Kelly, J.E.

1995-01-01

The hierarchy-by-interval (HBI) methodology was developed to determine an appropriate phenomena identification and ranking table for an independent peer review of severe-accident computer codes. The methodology is described, and the results of a specific code review are presented. Use of this systematic and structured approach ensures that important code models that need improvement are identified and prioritized, which allows code sponsors to more effectively direct limited resources in future code development. In addition, critical phenomenological areas that need more fundamental work, such as experimentation, are identified

TBX1 mutation identified by exome sequencing in a Japanese family with 22q11.2 deletion syndrome-like craniofacial features and hypocalcemia.

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Tsutomu Ogata

Full Text Available BACKGROUND: Although TBX1 mutations have been identified in patients with 22q11.2 deletion syndrome (22q11.2DS-like phenotypes including characteristic craniofacial features, cardiovascular anomalies, hypoparathyroidism, and thymic hypoplasia, the frequency of TBX1 mutations remains rare in deletion-negative patients. Thus, it would be reasonable to perform a comprehensive genetic analysis in deletion-negative patients with 22q11.2DS-like phenotypes. METHODOLOGY/PRINCIPAL FINDINGS: We studied three subjects with craniofacial features and hypocalcemia (group 1, two subjects with craniofacial features alone (group 2, and three subjects with normal phenotype within a single Japanese family. Fluorescence in situ hybridization analysis excluded chromosome 22q11.2 deletion, and genomewide array comparative genomic hybridization analysis revealed no copy number change specific to group 1 or groups 1+2. However, exome sequencing identified a heterozygous TBX1 frameshift mutation (c.1253delA, p.Y418fsX459 specific to groups 1+2, as well as six missense variants and two in-frame microdeletions specific to groups 1+2 and two missense variants specific to group 1. The TBX1 mutation resided at exon 9C and was predicted to produce a non-functional truncated protein missing the nuclear localization signal and most of the transactivation domain. CONCLUSIONS/SIGNIFICANCE: Clinical features in groups 1+2 are well explained by the TBX1 mutation, while the clinical effects of the remaining variants are largely unknown. Thus, the results exemplify the usefulness of exome sequencing in the identification of disease-causing mutations in familial disorders. Furthermore, the results, in conjunction with the previous data, imply that TBX1 isoform C is the biologically essential variant and that TBX1 mutations are associated with a wide phenotypic spectrum, including most of 22q11.2DS phenotypes.

Writer identification using curvature-free features

NARCIS (Netherlands)

He, Sheng; Schomaker, Lambertus

2017-01-01

Feature engineering takes a very important role in writer identification which has been widely studied in the literature. Previous works have shown that the joint feature distribution of two properties can improve the performance. The joint feature distribution makes feature relationships explicit

Identifying the distinct features of geometric structures for hole trapping to generate radicals on rutile TiO₂(110) in photooxidation using density functional theory calculations with hybrid functional.

Science.gov (United States)

Wang, Dong; Wang, Haifeng; Hu, P

2015-01-21

Using density functional theory calculations with HSE 06 functional, we obtained the structures of spin-polarized radicals on rutile TiO2(110), which is crucial to understand the photooxidation at the atomic level, and further calculate the thermodynamic stabilities of these radicals. By analyzing the results, we identify the structural features for hole trapping in the system, and reveal the mutual effects among the geometric structures, the energy levels of trapped hole states and their hole trapping capacities. Furthermore, the results from HSE 06 functional are compared to those from DFT + U and the stability trend of radicals against the number of slabs is tested. The effect of trapped holes on two important steps of the oxygen evolution reaction, i.e. water dissociation and the oxygen removal, is investigated and discussed.

Statistical analyses of scatterplots to identify important factors in large-scale simulations, 2: robustness of techniques

International Nuclear Information System (INIS)

Kleijnen, J.P.C.; Helton, J.C.

1999-01-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (i) Type I errors are unavoidable, (ii) Type II errors can occur when inappropriate analysis procedures are used, (iii) physical explanations should always be sought for why statistical procedures identify variables as being important, and (iv) the identification of important variables tends to be stable for independent Latin hypercube samples

Biologically important conformational features of DNA as interpreted by quantum mechanics and molecular mechanics computations of its simple fragments.

Science.gov (United States)

Poltev, V; Anisimov, V M; Dominguez, V; Gonzalez, E; Deriabina, A; Garcia, D; Rivas, F; Polteva, N A

2018-02-01

Deciphering the mechanism of functioning of DNA as the carrier of genetic information requires identifying inherent factors determining its structure and function. Following this path, our previous DFT studies attributed the origin of unique conformational characteristics of right-handed Watson-Crick duplexes (WCDs) to the conformational profile of deoxydinucleoside monophosphates (dDMPs) serving as the minimal repeating units of DNA strand. According to those findings, the directionality of the sugar-phosphate chain and the characteristic ranges of dihedral angles of energy minima combined with the geometric differences between purines and pyrimidines determine the dependence on base sequence of the three-dimensional (3D) structure of WCDs. This work extends our computational study to complementary deoxydinucleotide-monophosphates (cdDMPs) of non-standard conformation, including those of Z-family, Hoogsteen duplexes, parallel-stranded structures, and duplexes with mispaired bases. For most of these systems, except Z-conformation, computations closely reproduce experimental data within the tolerance of characteristic limits of dihedral parameters for each conformation family. Computation of cdDMPs with Z-conformation reveals that their experimental structures do not correspond to the internal energy minimum. This finding establishes the leading role of external factors in formation of the Z-conformation. Energy minima of cdDMPs of non-Watson-Crick duplexes demonstrate different sequence-dependence features than those known for WCDs. The obtained results provide evidence that the biologically important regularities of 3D structure distinguish WCDs from duplexes having non-Watson-Crick nucleotide pairing.

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

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Mourad, Raphaël; Cuvier, Olivier

2016-05-01

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

[Imported malaria and HIV infection in Madrid. Clinical and epidemiological features].

Science.gov (United States)

Ramírez-Olivencia, G; Herrero, M D; Subirats, M; de Juanes, J R; Peña, J M; Puente, S

2012-01-01

Few data are available in Spain data on human immunodeficiency virus (HIV) patients coinfected with malaria. This study has aimed to determine the epidemiological and clinical characteristics of imported malaria in patients coinfected with HIV. A case-series retrospective study was performed using the patient's medical records. The study population consisted on patients diagnosed with malaria attended in our center from january 1, 2002 to december 31, 2007. A total of 484 episodes of malaria, 398 of which were included in this study, were identified. Co-infection with HIV was described in 32 cases. All of them occurred in individuals presumably with some degree of semi-immunity. In the coinfected group, there were 13 cases (40.6%) asymptomatic, whereas this event occurred in 99 cases of patients not coinfected (37.2%) (P=0.707). The greater presence of anemia in co-infected patients (62.5% vs 32.3% in non-coinfected [P=0.001]) stands out. In present study, the clinical presentation forms were similar, regardless of the presence or absence of HIV infection. Although the study population does not reflect all possible scenarios of malaria and HIV coinfection, our results indicate the reality of patients attended in the Autonomous Community of Madrid. Copyright © 2011 Elsevier España, S.L. All rights reserved.

Features influencing Islamic websites use: A Muslim user perspective

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Mansur Aliyu

2013-06-01

Full Text Available Muslim scholars and organisations use the Internet through various websites to spread Islam globally. The presence of many websites providing Islamic contents online makes it necessary to examine their Islamic features and the factors that influence Muslims to use Islamic websites. This paper empirically investigates the Islamic features that influence the use of Islamic websites by Muslim users. The identified Islamic factors were grouped under five factors: beliefs, ethics, services, symbols, and values. A survey of 246 Muslim Islamic website users was conducted between November and December  2012 at the International Islamic University Malaysia (IIUM. The study develops and tests a path measurement model to confirm the psychometric properties of the five identified factors. The study found that Islamic features significantly influence Muslims to use Islamic websites. The measurement model and empirical results provide valuable indicators for the direction of future research and also suggest guidelines for developing Islamic websites that will easily influence many Internet users to visit them in order to learn about Islamic teachings and practices. The findings are also of considerable importance as they contribute to the present body of knowledge on Islamic websites’ evaluation and for practice in designing and developing quality Islamic websites.

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

Science.gov (United States)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

Comparing experts and novices in Martian surface feature change detection and identification

Science.gov (United States)

Wardlaw, Jessica; Sprinks, James; Houghton, Robert; Muller, Jan-Peter; Sidiropoulos, Panagiotis; Bamford, Steven; Marsh, Stuart

2018-02-01

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided ;expert; data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who

Idiosyncratic Features of the Contemporary Regional Economic Architecture in Asia

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Dilip K. Das

2012-06-01

Full Text Available The objective of this article is to examine the characteristic features of contemporary policy-led regionalism in Asia. It identifies the positive and negative features associated with the free trade agreements that have proliferated in Asia during the first decade of the 21st century. There has been a marked transformation in Asia's regional architecture in a short span of a decade-and-a-half. The mode and conduct of multilateral trade has been signifThe objective of this article is to examine the characteristic features of contemporary policy-led regionalism in Asia. It identifies the positive and negative features associated with the free trade agreements that have proliferated in Asia during the first decade of the 21st century. There has been a marked transformation in Asia's regional architecture in a short span of a decade-and-a-half. The mode and conduct of multilateral trade has been significantly transformed during recent years and Asia could not possibly remain immune to this transformation. The importance of regionalism in multilateral trade has increased steadily. In addition, the trade-investment-services nexus has developed and grown increasingly important. As business firms now manufacture parts of their products across the border, bilateral trade agreements (BTAs, regional trade agreements (RTAs and free trade agreements (FTAs of the contemporary period need to take into account the new kind of trade barriers that have been created due to the changing mode of trade. The contemporary regional agreements need to be designed to facilitate the new modes of conducting business and trade. It was understood rather late in Asia that the 'WTO-Plus' FTAs are more functional and result-oriented than their predecessors.

Astronomy and big data a data clustering approach to identifying uncertain galaxy morphology

CERN Document Server

Edwards, Kieran Jay

2014-01-01

With the onset of massive cosmological data collection through media such as the Sloan Digital Sky Survey (SDSS), galaxy classification has been accomplished for the most part with the help of citizen science communities like Galaxy Zoo. Seeking the wisdom of the crowd for such Big Data processing has proved extremely beneficial. However, an analysis of one of the Galaxy Zoo morphological classification data sets has shown that a significant majority of all classified galaxies are labelled as “Uncertain”. This book reports on how to use data mining, more specifically clustering, to identify galaxies that the public has shown some degree of uncertainty for as to whether they belong to one morphology type or another. The book shows the importance of transitions between different data mining techniques in an insightful workflow. It demonstrates that Clustering enables to identify discriminating features in the analysed data sets, adopting a novel feature selection algorithms called Incremental Feature Select...

Multimodal emotional state recognition using sequence-dependent deep hierarchical features.

Science.gov (United States)

Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan

2015-12-01

Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Rare features associated with Mobius syndrome: Report of two cases

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Rumela Ghosh

2017-03-01

Full Text Available Mobius syndrome is a rare congenital disorder with the preliminary diagnostic criteria of congenital facial and abducent nerve palsy. Involvement of other cranial nerves, too, is common. Prevalence rate of this syndrome is approximately 1 in 100,000 neonates. It is of unknown etiology with sporadic occurrence. However, data regarding the occurrence rate in India is limited. Features such as orofacial malformations, limb defects, and musculoskeletal, behavioral, and cognitive abnormalities might be associated. A thorough evaluation to identify the condition and establishing an adequate treatment plan is of utmost important in this condition. We are reporting clinical and radiographic features of Mobius syndrome in two cases along with unusual findings of limb and neck deformity.

Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection.

Science.gov (United States)

Kipli, Kuryati; Kouzani, Abbas Z

2015-07-01

Accurate detection of depression at an individual level using structural magnetic resonance imaging (sMRI) remains a challenge. Brain volumetric changes at a structural level appear to have importance in depression biomarkers studies. An automated algorithm is developed to select brain sMRI volumetric features for the detection of depression. A feature selection (FS) algorithm called degree of contribution (DoC) is developed for selection of sMRI volumetric features. This algorithm uses an ensemble approach to determine the degree of contribution in detection of major depressive disorder. The DoC is the score of feature importance used for feature ranking. The algorithm involves four stages: feature ranking, subset generation, subset evaluation, and DoC analysis. The performance of DoC is evaluated on the Duke University Multi-site Imaging Research in the Analysis of Depression sMRI dataset. The dataset consists of 115 brain sMRI scans of 88 healthy controls and 27 depressed subjects. Forty-four sMRI volumetric features are used in the evaluation. The DoC score of forty-four features was determined as the accuracy threshold (Acc_Thresh) was varied. The DoC performance was compared with that of four existing FS algorithms. At all defined Acc_Threshs, DoC outperformed the four examined FS algorithms for the average classification score and the maximum classification score. DoC has a good ability to generate reduced-size subsets of important features that could yield high classification accuracy. Based on the DoC score, the most discriminant volumetric features are those from the left-brain region.

Individual differences in using geometric and featural cues to maintain spatial orientation: cue quantity and cue ambiguity are more important than cue type.

Science.gov (United States)

Kelly, Jonathan W; McNamara, Timothy P; Bodenheimer, Bobby; Carr, Thomas H; Rieser, John J

2009-02-01

Two experiments explored the role of environmental cues in maintaining spatial orientation (sense of self-location and direction) during locomotion. Of particular interest was the importance of geometric cues (provided by environmental surfaces) and featural cues (nongeometric properties provided by striped walls) in maintaining spatial orientation. Participants performed a spatial updating task within virtual environments containing geometric or featural cues that were ambiguous or unambiguous indicators of self-location and direction. Cue type (geometric or featural) did not affect performance, but the number and ambiguity of environmental cues did. Gender differences, interpreted as a proxy for individual differences in spatial ability and/or experience, highlight the interaction between cue quantity and ambiguity. When environmental cues were ambiguous, men stayed oriented with either one or two cues, whereas women stayed oriented only with two. When environmental cues were unambiguous, women stayed oriented with one cue.

Estimating Human Physical States from Chronological Gait Features Acquired with RFID Technology

Directory of Open Access Journals (Sweden)

Yoshihiro UEMURA

2015-11-01

Full Text Available This paper proposes a method to estimate the state of the user to provide proactive hospitality from features of their gait pattern acquired with a Radio Frequency Identifier (RFID system. This method uses RFID readers on each shoe, as well as RFID tags installed on the floor. The ID of each tag is organized as a map, to show the precise position of the user. The reader and tags communicate while the user is walking. We extract feature components which represents gait patterns. Two-way ANOVA test and correlation analysis are conducted to find significant features. We classify the state of the user from these components with the Naȉve Bayes, the Support Vector Machine, and the Random Forest. Compared with each combination of the analysis and the machine learning method, the most efficient way is found to identify the state of the user. The experimental results show that different state of users can be classified appropriately. Finally, variable importance and the feasibility of proposed method are discussed to show potential implications of the proposed approach.

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...

Mining genome sequencing data to identify the genomic features linked to breast cancer histopathology

Science.gov (United States)

Ping, Zheng; Siegal, Gene P.; Almeida, Jonas S.; Schnitt, Stuart J.; Shen, Dejun

2014-01-01

Background: Genetics and genomics have radically altered our understanding of breast cancer progression. However, the genomic basis of various histopathologic features of breast cancer is not yet well-defined. Materials and Methods: The Cancer Genome Atlas (TCGA) is an international database containing a large collection of human cancer genome sequencing data. cBioPortal is a web tool developed for mining these sequencing data. We performed mining of TCGA sequencing data in an attempt to characterize the genomic features correlated with breast cancer histopathology. We first assessed the quality of the TCGA data using a group of genes with known alterations in various cancers. Both genome-wide gene mutation and copy number changes as well as a group of genes with a high frequency of genetic changes were then correlated with various histopathologic features of invasive breast cancer. Results: Validation of TCGA data using a group of genes with known alterations in breast cancer suggests that the TCGA has accurately documented the genomic abnormalities of multiple malignancies. Further analysis of TCGA breast cancer sequencing data shows that accumulation of specific genomic defects is associated with higher tumor grade, larger tumor size and receptor negativity. Distinct groups of genomic changes were found to be associated with the different grades of invasive ductal carcinoma. The mutator role of the TP53 gene was validated by genomic sequencing data of invasive breast cancer and TP53 mutation was found to play a critical role in defining high tumor grade. Conclusions: Data mining of the TCGA genome sequencing data is an innovative and reliable method to help characterize the genomic abnormalities associated with histopathologic features of invasive breast cancer. PMID:24672738

Mining genome sequencing data to identify the genomic features linked to breast cancer histopathology

Directory of Open Access Journals (Sweden)

Zheng Ping

2014-01-01

Full Text Available Background: Genetics and genomics have radically altered our understanding of breast cancer progression. However, the genomic basis of various histopathologic features of breast cancer is not yet well-defined. Materials and Methods: The Cancer Genome Atlas (TCGA is an international database containing a large collection of human cancer genome sequencing data. cBioPortal is a web tool developed for mining these sequencing data. We performed mining of TCGA sequencing data in an attempt to characterize the genomic features correlated with breast cancer histopathology. We first assessed the quality of the TCGA data using a group of genes with known alterations in various cancers. Both genome-wide gene mutation and copy number changes as well as a group of genes with a high frequency of genetic changes were then correlated with various histopathologic features of invasive breast cancer. Results: Validation of TCGA data using a group of genes with known alterations in breast cancer suggests that the TCGA has accurately documented the genomic abnormalities of multiple malignancies. Further analysis of TCGA breast cancer sequencing data shows that accumulation of specific genomic defects is associated with higher tumor grade, larger tumor size and receptor negativity. Distinct groups of genomic changes were found to be associated with the different grades of invasive ductal carcinoma. The mutator role of the TP53 gene was validated by genomic sequencing data of invasive breast cancer and TP53 mutation was found to play a critical role in defining high tumor grade. Conclusions: Data mining of the TCGA genome sequencing data is an innovative and reliable method to help characterize the genomic abnormalities associated with histopathologic features of invasive breast cancer.

Identification of four class emotion from Indonesian spoken language using acoustic and lexical features

Science.gov (United States)

Kasyidi, Fatan; Puji Lestari, Dessi

2018-03-01

One of the important aspects in human to human communication is to understand emotion of each party. Recently, interactions between human and computer continues to develop, especially affective interaction where emotion recognition is one of its important components. This paper presents our extended works on emotion recognition of Indonesian spoken language to identify four main class of emotions: Happy, Sad, Angry, and Contentment using combination of acoustic/prosodic features and lexical features. We construct emotion speech corpus from Indonesia television talk show where the situations are as close as possible to the natural situation. After constructing the emotion speech corpus, the acoustic/prosodic and lexical features are extracted to train the emotion model. We employ some machine learning algorithms such as Support Vector Machine (SVM), Naive Bayes, and Random Forest to get the best model. The experiment result of testing data shows that the best model has an F-measure score of 0.447 by using only the acoustic/prosodic feature and F-measure score of 0.488 by using both acoustic/prosodic and lexical features to recognize four class emotion using the SVM RBF Kernel.

Predicting protein amidation sites by orchestrating amino acid sequence features

Science.gov (United States)

Zhao, Shuqiu; Yu, Hua; Gong, Xiujun

2017-08-01

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

A Comparison of the Identifying Features of Imitated Handwriting and Elderly Handwriting

OpenAIRE

Jing Wang

2017-01-01

Imitated handwriting and elderly handwriting are two manifestation patterns of altered handwriting. Several similarities in features can be found in both, such as gentle movement and curved jitter. In practice, it is very easy to confuse the two patterns, leading to wrong decisions and difficulties in document examination. The key to solving these problems is to recognize the similarities and differences between imitated handwriting and elderly handwriting. This paper comprises four parts. Th...

Identifying Facilitators and Barriers for Patient Safety in a Medicine Label Design System Using Patient Simulation and Interviews

DEFF Research Database (Denmark)

Dieckmann, Peter; Clemmensen, Marianne Hald; Sørensen, Trine Kart

2016-01-01

Objectives Medicine label design plays an important role in improving patient safety. This study aimed at identifying facilitators and barriers in a medicine label system to prevent medication errors in clinical use by health care professionals. Methods The study design is qualitative and explora......Objectives Medicine label design plays an important role in improving patient safety. This study aimed at identifying facilitators and barriers in a medicine label system to prevent medication errors in clinical use by health care professionals. Methods The study design is qualitative...... of the system and some inconsistencies (different meaning of colors) posed challenges, when considered with the actual application context, in which there is little time to get familiar with the design features. Conclusions For optimizing medicine labels and obtaining the full benefit of label design features...

The future of primordial features with large-scale structure surveys

International Nuclear Information System (INIS)

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

2016-01-01

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

The future of primordial features with large-scale structure surveys

Energy Technology Data Exchange (ETDEWEB)

Chen, Xingang; Namjoo, Mohammad Hossein [Institute for Theory and Computation, Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Dvorkin, Cora [Department of Physics, Harvard University, Cambridge, MA 02138 (United States); Huang, Zhiqi [School of Physics and Astronomy, Sun Yat-Sen University, 135 Xingang Xi Road, Guangzhou, 510275 (China); Verde, Licia, E-mail: xingang.chen@cfa.harvard.edu, E-mail: dvorkin@physics.harvard.edu, E-mail: huangzhq25@sysu.edu.cn, E-mail: mohammad.namjoo@cfa.harvard.edu, E-mail: liciaverde@icc.ub.edu [ICREA and ICC-UB, University of Barcelona (IEEC-UB), Marti i Franques, 1, Barcelona 08028 (Spain)

2016-11-01

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

Dependency Parsing with Transformed Feature

Directory of Open Access Journals (Sweden)

Fuxiang Wu

2017-01-01

Full Text Available Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the un-indexed strings and alleviate the feature sparse problem. The model transforms the extracted features to transformed features via applying a feature weight matrix, which consists of similarities between the feature strings. Since the matrix is usually rank-deficient because of similar feature strings, it would influence the strength of constraints. However, it is proven that the duplicate transformed features do not degrade the optimization algorithm: the margin infused relaxed algorithm. Moreover, this problem can be alleviated by reducing the number of the nearest transformed features of a feature. In addition, to further improve the parsing accuracy, a fusion parser is introduced to integrate transformed and original features. Our experiments verify that both transform-based and fusion parser improve the parsing accuracy compared to the corresponding feature-based parser.

Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest.

Science.gov (United States)

Ma, Suliang; Chen, Mingxuan; Wu, Jianwen; Wang, Yuhao; Jia, Bowen; Jiang, Yuan

2018-04-16

Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy rate (WTFER) was adopted as the input vector for the classifier model in the feature selection procedure. Then, a random forest classifier was used to diagnose the HVCB fault, assess the importance of the feature variable and optimize the feature space. Finally, the approach was verified based on actual HVCB vibration signals by considering six typical fault classes. The comparative experiment results show that the classification accuracy of the proposed method with the origin feature space reached 93.33% and reached up to 95.56% with optimized input feature vector of classifier. This indicates that feature optimization procedure is successful, and the proposed diagnosis algorithm has higher efficiency and robustness than traditional methods.

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq.

Science.gov (United States)

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2017-01-01

Flax ( Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits.

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L. Using SLAF-seq

Directory of Open Access Journals (Sweden)

Dongwei Xie

2018-01-01

Full Text Available Flax (Linum usitatissimum L. is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq was employed to perform a genome-wide association study (GWAS for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM and a mixed linear model (MLM as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits.

MRI of Creutzfeldt-Jakob disease: Imaging features and recommended MRI protocol

Energy Technology Data Exchange (ETDEWEB)

Collie, D.A.; Sellar, R.J.; Zeidler, M.; Colchester, A.C.F.; Knight, R.; Will, R.G

2001-09-01

Creutzfeldt-Jakob Disease (CJD) is a rare, progressive and invariably fatal neurodegenerative disease characterized by specific histopathological features. Of the four subtypes of CJD described, the commonest is sporadic CJD (sCJD). More recently, a new clinically distinct form of the disease affecting younger patients, known as variant CJD (vCJD), has been identified, and this has been causally linked to the bovine spongiform encephalopathy (BSE) agent in cattle. Characteristic appearances on magnetic resonance imaging (MRI) have been identified in several forms of CJD; sCJD may be associated with high signal changes in the putamen and caudate head and vCJD is usually associated with hyperintensity of the pulvinar (posterior nuclei) of the thalamus. These appearances and other imaging features are described in this article. Using appropriate clinical and radiological criteria and tailored imaging protocols, MRI plays an important part in the in vivodiagnosis of this disease. Collie, D.A. et al. (2001)

MRI of Creutzfeldt-Jakob disease: Imaging features and recommended MRI protocol

International Nuclear Information System (INIS)

Collie, D.A.; Sellar, R.J.; Zeidler, M.; Colchester, A.C.F.; Knight, R.; Will, R.G.

2001-01-01

Creutzfeldt-Jakob Disease (CJD) is a rare, progressive and invariably fatal neurodegenerative disease characterized by specific histopathological features. Of the four subtypes of CJD described, the commonest is sporadic CJD (sCJD). More recently, a new clinically distinct form of the disease affecting younger patients, known as variant CJD (vCJD), has been identified, and this has been causally linked to the bovine spongiform encephalopathy (BSE) agent in cattle. Characteristic appearances on magnetic resonance imaging (MRI) have been identified in several forms of CJD; sCJD may be associated with high signal changes in the putamen and caudate head and vCJD is usually associated with hyperintensity of the pulvinar (posterior nuclei) of the thalamus. These appearances and other imaging features are described in this article. Using appropriate clinical and radiological criteria and tailored imaging protocols, MRI plays an important part in the in vivodiagnosis of this disease. Collie, D.A. et al. (2001)

Crowd-sourced Ontology for Photoleukocoria: Identifying Common Internet Search Terms for a Potentially Important Pediatric Ophthalmic Sign.

Science.gov (United States)

Staffieri, Sandra E; Kearns, Lisa S; Sanfilippo, Paul G; Craig, Jamie E; Mackey, David A; Hewitt, Alex W

2018-02-01

Leukocoria is the most common presenting sign for pediatric eye disease including retinoblastoma and cataract, with worse outcomes if diagnosis is delayed. We investigated whether individuals could identify leukocoria in photographs (photoleukocoria) and examined their subsequent Internet search behavior. Using a web-based questionnaire, in this cross-sectional study we invited adults aged over 18 years to view two photographs of a child with photoleukocoria, and then search the Internet to determine a possible diagnosis and action plan. The most commonly used search terms and websites accessed were recorded. The questionnaire was completed by 1639 individuals. Facebook advertisement was the most effective recruitment strategy. The mean age of all respondents was 38.95 ± 14.59 years (range, 18-83), 94% were female, and 59.3% had children. An abnormality in the images presented was identified by 1613 (98.4%) participants. The most commonly used search terms were: "white," "pupil," "photo," and "eye" reaching a variety of appropriate websites or links to print or social media articles. Different words or phrases were used to describe the same observation of photoleukocoria leading to a range of websites. Variations in the description of observed signs and search words influenced the sites reached, information obtained, and subsequent help-seeking intentions. Identifying the most commonly used search terms for photoleukocoria is an important step for search engine optimization. Being directed to the most appropriate websites informing of the significance of photoleukocoria and the appropriate actions to take could improve delays in diagnosis of important pediatric eye disease such as retinoblastoma or cataract.

Microhabitat features influencing habitat use by Florida black bears

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Dana L. Karelus

2018-01-01

Full Text Available Understanding fine-scale habitat needs of species and the factors influencing heterogeneous use of habitat within home range would help identify limiting resources and inform habitat management practices. This information is especially important for large mammals living in fragmented habitats where resources may be scarcer and more patchily distributed than in contiguous habitats. Using bihourly Global Position System (GPS location data collected from 10 individuals during 2011–2014, we investigated microhabitat features of areas within home ranges that received high vs. low intensity of use by Florida black bears (Ursus americanus floridanus in north-central, Florida. We identified areas receiving high and low levels of use by bears based on their utilization distributions estimated with the dynamic Brownian bridge movement model, and performed vegetation sampling at bear locations within high- and low-use areas. Using univariate analyses and generalized linear mixed models, we found that (1 canopy cover, visual obstruction, and hardwood density were important in defining high-use sites; (2 the probability of high use was positively associated with principal components that represented habitat closer to creeks and with high canopy and shrub cover and higher hardwood densities, likely characteristic of forested wetlands; and (3 the probability of high use was, to a lesser extent, associated with principal components that represented habitat with high canopy cover, high pine density, and low visual obstruction and hardwood density; likely representing sand pine and pine plantations. Our results indicate that the high bear-use sites were in forested wetlands, where cover and food resources for bears are likely to occur in higher abundance. Habitat management plans whereby bears are a focal species should aim to increase the availability and quality of forested wetlands. Keywords: Habitat selection, Heterogeneous habitat use, Forest management

An evaluation of applicability of seismic refraction method in identifying shallow archaeological features A case study at archaeological site

Science.gov (United States)

Jahangardi, Morteza; Hafezi Moghaddas, Naser; Keivan Hosseini, Sayyed; Garazhian, Omran

2015-04-01

We applied the seismic refraction method at archaeological site, Tepe Damghani located in Sabzevar, NE of Iran, in order to determine the structures of archaeological interests. This pre-historical site has special conditions with respect to geographical location and geomorphological setting, so it is an urban archaeological site, and in recent years it has been used as an agricultural field. In spring and summer of 2012, the third season of archaeological excavation was carried out. Test trenches of excavations in this site revealed that cultural layers were often disturbed adversely due to human activities such as farming and road construction in recent years. Conditions of archaeological cultural layers in southern and eastern parts of Tepe are slightly better, for instance, in test trench 3×3 m²1S03, third test trench excavated in the southern part of Tepe, an adobe in situ architectural structure was discovered that likely belongs to cultural features of a complex with 5 graves. After conclusion of the third season of archaeological excavation, all of the test trenches were filled with the same soil of excavated test trenches. Seismic refraction method was applied with12 channels of P geophones in three lines with a geophone interval of 0.5 meter and a 1.5 meter distance between profiles on test trench 1S03. The goal of this operation was evaluation of applicability of seismic method in identification of archaeological features, especially adobe wall structures. Processing of seismic data was done with the seismic software, SiesImager. Results were presented in the form of seismic section for every profile, so that identification of adobe wall structures was achieved hardly. This could be due to that adobe wall had been built with the same materials of the natural surrounding earth. Thus, there is a low contrast and it has an inappropriate effect on seismic processing and identifying of archaeological features. Hence the result could be that application of

Cosmetics as a Feature of the Extended Human Phenotype: Modulation of the Perception of Biologically Important Facial Signals

Science.gov (United States)

Etcoff, Nancy L.; Stock, Shannon; Haley, Lauren E.; Vickery, Sarah A.; House, David M.

2011-01-01

Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural), to moderate (professional), to dramatic (glamorous). Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important signals at first

Cosmetics as a feature of the extended human phenotype: modulation of the perception of biologically important facial signals.

Directory of Open Access Journals (Sweden)

Nancy L Etcoff

Full Text Available Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural, to moderate (professional, to dramatic (glamorous. Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important

Cosmetics as a feature of the extended human phenotype: modulation of the perception of biologically important facial signals.

Science.gov (United States)

Etcoff, Nancy L; Stock, Shannon; Haley, Lauren E; Vickery, Sarah A; House, David M

2011-01-01

Research on the perception of faces has focused on the size, shape, and configuration of inherited features or the biological phenotype, and largely ignored the effects of adornment, or the extended phenotype. Research on the evolution of signaling has shown that animals frequently alter visual features, including color cues, to attract, intimidate or protect themselves from conspecifics. Humans engage in conscious manipulation of visual signals using cultural tools in real time rather than genetic changes over evolutionary time. Here, we investigate one tool, the use of color cosmetics. In two studies, we asked viewers to rate the same female faces with or without color cosmetics, and we varied the style of makeup from minimal (natural), to moderate (professional), to dramatic (glamorous). Each look provided increasing luminance contrast between the facial features and surrounding skin. Faces were shown for 250 ms or for unlimited inspection time, and subjects rated them for attractiveness, competence, likeability and trustworthiness. At 250 ms, cosmetics had significant positive effects on all outcomes. Length of inspection time did not change the effect for competence or attractiveness. However, with longer inspection time, the effect of cosmetics on likability and trust varied by specific makeup looks, indicating that cosmetics could impact automatic and deliberative judgments differently. The results suggest that cosmetics can create supernormal facial stimuli, and that one way they may do so is by exaggerating cues to sexual dimorphism. Our results provide evidence that judgments of facial trustworthiness and attractiveness are at least partially separable, that beauty has a significant positive effect on judgment of competence, a universal dimension of social cognition, but has a more nuanced effect on the other universal dimension of social warmth, and that the extended phenotype significantly influences perception of biologically important signals at first

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.

Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma.

Science.gov (United States)

Kebir, Sied; Khurshid, Zain; Gaertner, Florian C; Essler, Markus; Hattingen, Elke; Fimmers, Rolf; Scheffler, Björn; Herrlinger, Ulrich; Bundschuh, Ralph A; Glas, Martin

2017-01-31

Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror tumor uptake heterogeneity; some of them may be associated with tumor progression. Fourteen patients with HGG and suspected of PSP underwent FET-PET imaging. A set of 19 conventional and textural FET-PET features were evaluated and subjected to unsupervised consensus clustering. The final diagnosis of true progression vs. PSP was based on follow-up MRI using RANO criteria. Three robust clusters have been identified based on 10 predominantly textural FET-PET features. None of the patients with PSP fell into cluster 2, which was associated with high values for textural FET-PET markers of uptake heterogeneity. Three out of 4 patients with PSP were assigned to cluster 3 that was largely associated with low values of textural FET-PET features. By comparison, tumor-to-normal brain ratio (TNRmax) at the optimal cutoff 2.1 was less predictive of PSP (negative predictive value 57% for detecting true progression, p=0.07 vs. 75% with cluster 3, p=0.04). Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression.

Features of Inner Structure of Placer Gold of the North-Eastern Part Siberian Platform

Science.gov (United States)

Gerasimov, Boris; Zhuravlev, Anatolii; Ivanov, Alexey

2017-12-01

Mineral and raw material base of placer and ore gold is based on prognosis evaluation, which allows to define promising areas regarding gold-bearing deposit prospecting. But there are some difficulties in gold primary source predicting and prospecting at the North-east Siberian platform, because the studied area is overlapped by thick cover of the Cenozoic deposits, where traditional methods of gold deposit prospecting are ineffective. In this connection, detailed study of typomorphic features of placer gold is important, because it contains key genetic information, necessary for development of mineralogical criteria of prognosis evaluation of ore gold content. Authors studied mineralogical-geochemical features of placer gold of the Anabar placer area for 15 years, with a view to identify indicators of gold, typical for different formation types of primary sources. This article presents results of these works. In placer regions, where primary sources of gold are not identified, there is need to study typomorphic features of placer gold, because it contains important genetic information, necessary for the development of mineralogical criteria of prognosis evaluation of ore gold content. Inner structures of gold from the Anabar placer region are studied, as one of the diagnostic typomorphic criteria as described in prominent method, developed by N.V. Petrovskaya [1980]. Etching of gold was carried out using reagent: HCl + HNO3 + FeCl3 × 6H2O + CrO3 +thioureat + water. Identified inner structures wer studied in details by means of scanning electron microscope JEOL JSM-6480LV. Two types of gold are identified according to the features of inner structure of placer gold of the Anabar region. First type - medium-high karat fine, well processed gold with significantly changed inner structure. This gold is allochthonous, which was redeposited many times from ancient intermediate reservoirs to younger deposits. Second type - low-medium karat, poorly rounded gold with

Maternal employment and Mexican school-age children overweight in 2012: the importance of households features.

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Espinosa, Alejandro Martínez

2018-01-01

International evidence regarding the relationship between maternal employment and school-age children overweight and obesity shows divergent results. In Mexico, this relationship has not been confirmed by national data sets analysis. Consequently, the objective of this article was to evaluate the role of the mothers' participation in labor force related to excess body weight in Mexican school-age children (aged 5-11 years). A cross-sectional study was conducted on a sample of 17,418 individuals from the National Health and Nutrition Survey 2012, applying binomial logistic regression models. After controlling for individual, maternal and contextual features, the mothers' participation in labor force was associated with children body composition. However, when the household features (living arrangements, household ethnicity, size, food security and socioeconomic status) were incorporated, maternal employment was no longer statically significant. Household features are crucial factors for understanding the overweight and obesity prevalence levels in Mexican school-age children, despite the mother having a paid job. Copyright: © 2018 Permanyer.

Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals

Science.gov (United States)

Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin

How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data.

Directory of Open Access Journals (Sweden)

Yuttachon Promworn

Full Text Available Biochemical methods are available for enriching 5' ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5' ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance.We present Transformation of Nucleotide Enrichment Ratios (ToNER, a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5' ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5' ends than TSSAR. In general, the transcript 5' ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR.ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5'ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a

ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data.

Science.gov (United States)

Promworn, Yuttachon; Kaewprommal, Pavita; Shaw, Philip J; Intarapanich, Apichart; Tongsima, Sissades; Piriyapongsa, Jittima

2017-01-01

Biochemical methods are available for enriching 5' ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq) and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5' ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance. We present Transformation of Nucleotide Enrichment Ratios (ToNER), a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5' ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5' ends than TSSAR. In general, the transcript 5' ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR. ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5'ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a.biotec.or.th/GI/tools/toner) and Git

In vitro and in vivo studies identify important features of dengue virus pr-E protein interactions.

Directory of Open Access Journals (Sweden)

Aihua Zheng

2010-10-01

Full Text Available Flaviviruses bud into the endoplasmic reticulum and are transported through the secretory pathway, where the mildly acidic environment triggers particle rearrangement and allows furin processing of the prM protein to pr and M. The peripheral pr peptide remains bound to virus at low pH and inhibits virus-membrane interaction. Upon exocytosis, the release of pr at neutral pH completes virus maturation to an infectious particle. Together this evidence suggests that pr may shield the flavivirus fusion protein E from the low pH environment of the exocytic pathway. Here we developed an in vitro system to reconstitute the interaction of dengue virus (DENV pr with soluble truncated E proteins. At low pH recombinant pr bound to both monomeric and dimeric forms of E and blocked their membrane insertion. Exogenous pr interacted with mature infectious DENV and specifically inhibited virus fusion and infection. Alanine substitution of E H244, a highly conserved histidine residue in the pr-E interface, blocked pr-E interaction and reduced release of DENV virus-like particles. Folding, membrane insertion and trimerization of the H244A mutant E protein were preserved, and particle release could be partially rescued by neutralization of the low pH of the secretory pathway. Thus, pr acts to silence flavivirus fusion activity during virus secretion, and this function can be separated from the chaperone activity of prM. The sequence conservation of key residues involved in the flavivirus pr-E interaction suggests that this protein-protein interface may be a useful target for broad-spectrum inhibitors.

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

Science.gov (United States)

Li, Jing; Hong, Wenxue

2014-12-01

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

Imaging-Based Screen Identifies Laminin 411 as a Physiologically Relevant Niche Factor with Importance for i-Hep Applications

Directory of Open Access Journals (Sweden)

John Ong

2018-03-01

Full Text Available Summary: Use of hepatocytes derived from induced pluripotent stem cells (i-Heps is limited by their functional differences in comparison with primary cells. Extracellular niche factors likely play a critical role in bridging this gap. Using image-based characterization (high content analysis; HCA of freshly isolated hepatocytes from 17 human donors, we devised and validated an algorithm (Hepatocyte Likeness Index; HLI for comparing the hepatic properties of cells against a physiological gold standard. The HLI was then applied in a targeted screen of extracellular niche factors to identify substrates driving i-Heps closer to the standard. Laminin 411, the top hit, was validated in two additional induced pluripotent stem cell (iPSC lines, primary tissue, and an in vitro model of α1-antitrypsin deficiency. Cumulatively, these data provide a reference method to control and screen for i-Hep differentiation, identify Laminin 411 as a key niche protein, and underscore the importance of combining substrates, soluble factors, and HCA when developing iPSC applications. : Rashid and colleagues demonstrate the utility of a high-throughput imaging platform for identification of physiologically relevant extracellular niche factors to advance i-Heps closer to their primary tissue counterparts. The extracellular matrix (ECM protein screen identified Laminin 411 as an important niche factor facilitating i-Hep-based disease modeling in vitro. Keywords: iPS hepatocytes, extracellular niche, image-based screening, disease modeling, laminin

Bipolar disorder: The importance of clinical assessment in identifying prognostic factors - An Audit. Part 1: An analysis of potential prognostic factors.

Science.gov (United States)

Verdolini, Norma; Dean, Jonathon; Elisei, Sandro; Quartesan, Roberto; Zaman, Rashid; Agius, Mark

2014-11-01

Prognostic factors of bipolar disorder must be identified to assist in staging and treatment, and this may be done primarily during the initial psychiatric assessment. In fact, most of the prognostic factors, which determine disease outcome, could be detected from simple but often-unrecorded questions asked during the psychiatric clinic visit. We collected data from the clinical notes of 70 bipolar outpatients seen at the initial psychiatric assessment clinic about socio-demographic and clinical factors to determine whether various factors had relevance to prevalence, prognosis, or outcome. The sample comprised 16 bipolar I (22.9%) and 54 bipolar II (77.1%) outpatients; a psychiatric comorbidity was noted in 26 patients (37.1%). 60.9% (42 patients) reported anxiety features and 12 patients (17.6%) were noted to have obsessive-compulsive characteristics. Percentages reported in our results are of the sample for which the data was available. Anhedonia is a depressive feature that was present in most of the population where this data was available (92.2%, 59 patients) and 81.8% (54 patients) reported suicidal thoughts during a depressive episode. 74.6% (47 patients) had a family history of bipolar disorder, depression, suicide or psychosis. 27 patients (39.7%) reported current alcohol use and 14 patients (22.6%) current illicit drug use. A comparison between 10 prognostic factors found that only the correlations between current illicit drug use/previous illicit drug use (χ(2)=11.471, Palcohol use/previous alcohol use (χ(2)=31.510, Palcohol use (χ(2)=5.071, P=0.023) and previous alcohol use/family history (χ(2)=4.309, P=0.037) were almost statistically significant. 17 patients (24.3%) of the 70 bipolar patients were assigned to a care coordinator; we have evaluated the possible differences between the patients with or without a care coordinator on the basis of the presence of 10 possible prognostic factors and found no statistically significant differences between

Identification of important ''PIUS'' design considerations and accident sequences using qualitative plant assessment techniques

International Nuclear Information System (INIS)

Higgins, J.; Fullwood, R.; Kroeger, P.; Youngblood, R.

1992-01-01

The PIUS (Process Inherent Ultimate Safety) reactor is an advanced design nuclear power plant that uses passive safety features and basic physical processes to address safety concerns. Brookhaven National Laboratory (BNL) performed a detailed study of the PIUS design for the NRC using primarily qualitative engineering analysis techniques. Some quantitative methods were also employed. There are three key initial areas of analysis: FMECA, HAZOP, and deterministic analyses, which are described herein. Once these three analysis methods were completed, the important findings from each of the methods were assembled into thePIUS Interim Table (PIT). This table thus contains a first cut sort of the important design considerations and features of the PIUS reactor. The table also identifies some potential initiating events and systems used for mitigating these initiators. The next stage of the analysis was the construction of event trees for each of the identified initiators. The most significant sequences were then determined qualitatively, using, some quantitative input. Finally, overall insights on the PIUS design developed from the PIT and from the event tree analysis were developed and presented

Imaging features of foot osteoid osteoma

Energy Technology Data Exchange (ETDEWEB)

Shukla, Satyen; Clarke, Andrew W.; Saifuddin, Asif [Royal National Orthopaedic Hospital NHS Trust, Department of Radiology, Stanmore, Middlesex (United Kingdom)

2010-07-15

We performed a retrospective review of the imaging of nine patients with a diagnosis of foot osteoid osteoma (OO). Radiographs, computed tomography (CT) and magnetic resonance imaging (MRI) had been performed in all patients. Radiographic features evaluated were the identification of a nidus and cortical thickening. CT features noted were nidus location (affected bone - intramedullary, intracortical, subarticular) and nidus calcification. MRI features noted were the presence of an identifiable nidus, presence and grade of bone oedema and whether a joint effusion was identified. Of the nine patients, three were female and six male, with a mean age of 21 years (range 11-39 years). Classical symptoms of OO (night pain, relief with aspirin) were identified in five of eight (62.5%) cases (in one case, the medical records could not be retrieved). In five patients the lesion was located in the hindfoot (four calcaneus, one talus), while four were in the mid- or forefoot (two metatarsal and two phalangeal). Radiographs were normal in all patients with hindfoot OO. CT identified the nidus in all cases (89%) except one terminal phalanx lesion, while MRI demonstrated a nidus in six of nine cases (67%). The nidus was of predominantly intermediate signal intensity on T1-weighted (T1W) sequences, with intermediate to high signal intensity on T2-weighted (T2W) sequences. High-grade bone marrow oedema, limited to the affected bone and adjacent soft tissue oedema was identified in all cases. In a young patient with chronic hindfoot pain and a normal radiograph, MRI features suggestive of possible OO include extensive bone marrow oedema limited to one bone, with a possible nidus demonstrated in two-thirds of cases. The presence or absence of a nidus should be confirmed with high-resolution CT. (orig.)

Facial and Ocular Features of Marfan Syndrome

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Juan C. Leoni

2014-10-01

Full Text Available Marfan syndrome is the most common inherited disorder of connective tissue affecting multiple organ systems. Identification of the facial, ocular and skeletal features should prompt referral for aortic imaging since sudden death by aortic dissection and rupture remains a major cause of death in patients with unrecognized Marfan syndrome. Echocardiography is recommended as the initial imaging test, and once a dilated aortic root is identified magnetic resonance or computed tomography should be done to assess the entire aorta. Prophylactic aortic root replacement is safe and has been demonstrated to improve life expectancy in patients with Marfan syndrome. Medical therapy for Marfan syndrome includes the use of beta blockers in older children and adults with an enlarged aorta. Addition of angiotensin receptor antagonists has been shown to slow the progression of aortic root dilation compared to beta blockers alone. Lifelong and regular follow up in a center for specialized care is important for patients with Marfan syndrome. We present a case of a patient with clinical features of Marfan syndrome and discuss possible therapeutic interventions for her dilated aorta.

A method to identify important dynamical states in Boolean models of regulatory networks: application to regulation of stomata closure by ABA in A. thaliana.

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Bugs, Cristhian A; Librelotto, Giovani R; Mombach, José C M

2011-12-22

We introduce a method to analyze the states of regulatory Boolean models that identifies important network states and their biological influence on the global network dynamics. It consists in (1) finding the states of the network that are most frequently visited and (2) the identification of variable and frozen nodes of the network. The method, along with a simulation that includes random features, is applied to the study of stomata closure by abscisic acid (ABA) in A. thaliana proposed by Albert and coworkers. We find that for the case of study, that the dynamics of wild and mutant networks have just two states that are highly visited in their space of states and about a third of all nodes of the wild network are variable while the rest remain frozen in True or False states. This high number of frozen elements explains the low cardinality of the space of states of the wild network. Similar results are observed in the mutant networks. The application of the method allowed us to explain how wild and mutants behave dynamically in the SS and determined an essential feature of the activation of the closure node (representing stomata closure), i.e. its synchronization with the AnionEm node (representing anion efflux at the plasma membrane). The dynamics of this synchronization explains the efficiency reached by the wild and each of the mutant networks. For the biological problem analyzed, our method allows determining how wild and mutant networks differ 'phenotypically'. It shows that the different efficiencies of stomata closure reached among the simulated wild and mutant networks follow from a dynamical behavior of two nodes that are always synchronized. Additionally, we predict that the involvement of the anion efflux at the plasma membrane is crucial for the plant response to ABA. The algorithm used in the simulations is available upon request.

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

Science.gov (United States)

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

2012-10-01

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

Feature-based Ontology Mapping from an Information Receivers’ Viewpoint

DEFF Research Database (Denmark)

Glückstad, Fumiko Kano; Mørup, Morten

2012-01-01

This paper compares four algorithms for computing feature-based similarities between concepts respectively possessing a distinctive set of features. The eventual purpose of comparing these feature-based similarity algorithms is to identify a candidate term in a Target Language (TL) that can...... optimally convey the original meaning of a culturally-specific Source Language (SL) concept to a TL audience by aligning two culturally-dependent domain-specific ontologies. The results indicate that the Bayesian Model of Generalization [1] performs best, not only for identifying candidate translation terms...

Feature Set Evaluation for Offline Handwriting Recognition Systems: Application to the Recurrent Neural Network Model.

Science.gov (United States)

Chherawala, Youssouf; Roy, Partha Pratim; Cheriet, Mohamed

2016-12-01

The performance of handwriting recognition systems is dependent on the features extracted from the word image. A large body of features exists in the literature, but no method has yet been proposed to identify the most promising of these, other than a straightforward comparison based on the recognition rate. In this paper, we propose a framework for feature set evaluation based on a collaborative setting. We use a weighted vote combination of recurrent neural network (RNN) classifiers, each trained with a particular feature set. This combination is modeled in a probabilistic framework as a mixture model and two methods for weight estimation are described. The main contribution of this paper is to quantify the importance of feature sets through the combination weights, which reflect their strength and complementarity. We chose the RNN classifier because of its state-of-the-art performance. Also, we provide the first feature set benchmark for this classifier. We evaluated several feature sets on the IFN/ENIT and RIMES databases of Arabic and Latin script, respectively. The resulting combination model is competitive with state-of-the-art systems.

Systematic reviews identify important methodological flaws in stroke rehabilitation therapy primary studies: review of reviews.

Science.gov (United States)

Santaguida, Pasqualina; Oremus, Mark; Walker, Kathryn; Wishart, Laurie R; Siegel, Karen Lohmann; Raina, Parminder

2012-04-01

A "review of reviews" was undertaken to assess methodological issues in studies evaluating nondrug rehabilitation interventions in stroke patients. MEDLINE, CINAHL, PsycINFO, and the Cochrane Database of Systematic Reviews were searched from January 2000 to January 2008 within the stroke rehabilitation setting. Electronic searches were supplemented by reviews of reference lists and citations identified by experts. Eligible studies were systematic reviews; excluded citations were narrative reviews or reviews of reviews. Review characteristics and criteria for assessing methodological quality of primary studies within them were extracted. The search yielded 949 English-language citations. We included a final set of 38 systematic reviews. Cochrane reviews, which have a standardized methodology, were generally of higher methodological quality than non-Cochrane reviews. Most systematic reviews used standardized quality assessment criteria for primary studies, but not all were comprehensive. Reviews showed that primary studies had problems with randomization, allocation concealment, and blinding. Baseline comparability, adverse events, and co-intervention or contamination were not consistently assessed. Blinding of patients and providers was often not feasible and was not evaluated as a source of bias. The eligible systematic reviews identified important methodological flaws in the evaluated primary studies, suggesting the need for improvement of research methods and reporting. Copyright © 2012 Elsevier Inc. All rights reserved.

An Unrecognized Rash Progressing to Lyme Carditis: Important Features and Recommendations Regarding Lyme Disease.

Science.gov (United States)

Lee, Shawn; Singla, Montish

2016-01-01

We present a case report of 46-year-old man with no medical history, who complained of extreme fatigue, near-syncope, and palpitations. He initially presented in complete heart block. A transvenous pacemaker was placed in the emergency department, and he was started empirically on Ceftriaxone for Lyme disease. He was admitted and over the course of the next few days, his rhythm regressed to Mobitz type I first-degree atrioventricular block and then to normal sinus rhythm. This case report highlights some important features regarding Lyme carditis, a rare presentation of early disseminated Lyme disease (seen in a few weeks to months after the initial tick bite). In 25%-30% of patients, the characteristic targetoid rash may not be seen, a likely culprit of the disease not being detected early and progressing to disseminated disease. The most common cardiac complaint of Lyme disease is palpitations, occurring in 6.6% of patients, which may not accurately reflect progression into disseminated Lyme disease because it is a nonspecific finding. Conduction abnormality, occurring in 1.8% of patients, is a more specific finding of Borrelia invading cardiac tissue. Finally, this case report highlights a recommendation that patients with confirmed Lyme disease or those presenting with cardiac abnormalities or symptoms who have an atypical profile for a cardiac event should be screened with a 12-lead electrocardiogram, Lyme serology, and be considered for antibiotic therapy with the possibility of temporary pacing.

Stylistic Features of the Legal Discourse | Alabi | UJAH: Unizik ...

African Journals Online (AJOL)

Every profession, every occupation, for example architecture, journalism, medicine, sports, has its specialised language features. These features may be viewed at the phonological, semantic, syntactic, lexical and graphological levels, among others. The language features identified with certain professions are most of the ...

Mummified trophy heads from Peru: diagnostic features and medicolegal significance.

Science.gov (United States)

Verano, John W

2003-05-01

Several forms of mummified human trophy heads were produced by prehistoric and historic native groups in South America. This paper describes the diagnostic features of trophy heads produced by the Nasca culture of ancient Peru. A growing interest in these mummified heads among collectors of Pre-Columbian art and antiquities has led to their illegal exportation from Peru, in violation of national and international antiquities laws. Requests from the Peruvian government to protect its cultural patrimony led the United States in 1997 to declare these heads as items subject to U.S. import restriction, along with six other categories of human remains. Despite such restrictions, Nasca trophy heads continue to reach private collectors outside of Peru and thus may be encountered by local, state, or federal law enforcement officials unfamiliar with their characteristic features and origin. The objective of this paper is to describe the features that allow Nasca trophy heads to be identified and distinguished from other archaeological and forensic specimens that may be submitted to a forensic anthropologist for identification.

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

A HYBRID FILTER AND WRAPPER FEATURE SELECTION APPROACH FOR DETECTING CONTAMINATION IN DRINKING WATER MANAGEMENT SYSTEM

Directory of Open Access Journals (Sweden)

S. VISALAKSHI

2017-07-01

Full Text Available Feature selection is an important task in predictive models which helps to identify the irrelevant features in the high - dimensional dataset. In this case of water contamination detection dataset, the standard wrapper algorithm alone cannot be applied because of the complexity. To overcome this computational complexity problem and making it lighter, filter-wrapper based algorithm has been proposed. In this work, reducing the feature space is a significant component of water contamination. The main findings are as follows: (1 The main goal is speeding up the feature selection process, so the proposed filter - based feature pre-selection is applied and guarantees that useful data are improbable to be detached in the initial stage which discussed briefly in this paper. (2 The resulting features are again filtered by using the Genetic Algorithm coded with Support Vector Machine method, where it facilitates to nutshell the subset of features with high accuracy and decreases the expense. Experimental results show that the proposed methods trim down redundant features effectively and achieved better classification accuracy.

Sparse feature selection identifies H2A.Z as a novel, pattern-specific biomarker for asymmetrically self-renewing distributed stem cells

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Yang Hoon Huh

2015-03-01

Full Text Available There is a long-standing unmet clinical need for biomarkers with high specificity for distributed stem cells (DSCs in tissues, or for use in diagnostic and therapeutic cell preparations (e.g., bone marrow. Although DSCs are essential for tissue maintenance and repair, accurate determination of their numbers for medical applications has been problematic. Previous searches for biomarkers expressed specifically in DSCs were hampered by difficulty obtaining pure DSCs and by the challenges in mining complex molecular expression data. To identify such useful and specific DSC biomarkers, we combined a novel sparse feature selection method with combinatorial molecular expression data focused on asymmetric self-renewal, a conspicuous property of DSCs. The analysis identified reduced expression of the histone H2A variant H2A.Z as a superior molecular discriminator for DSC asymmetric self-renewal. Subsequent molecular expression studies showed H2A.Z to be a novel “pattern-specific biomarker” for asymmetrically self-renewing cells, with sufficient specificity to count asymmetrically self-renewing DSCs in vitro and potentially in situ.

Feature-Based Retinal Image Registration Using D-Saddle Feature

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Roziana Ramli

2017-01-01

Full Text Available Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%, Harris-PIIFD (4%, H-M (16%, and Saddle (16%. Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.

Radiographic features of periapical cysts and granulomas

OpenAIRE

Zain, R. B.; Roswati, N.; Ismail, K.

1989-01-01

Many studies have been reported on radiographic lesion sizes of periapical lesions. However no studies have been reported on prevalences of subjective radiographic features in these lesions except for the early assumption that a periapical cyst usually exhibit a radiopaque cortex. This study is conducted to evaluate the prevalences of several subjective radiographic features of periapical cysts and granulomas in the hope to identify features that maybe suggestive of either diagnosis. The resu...

Redd site selection and spawning habitat use by fall chinook salmon: The importance of geomorphic features in large rivers

International Nuclear Information System (INIS)

Geist, D.R.; Oregon State Univ., Corvallis, OR; Dauble, D.D.

1998-01-01

Knowledge of the three-dimensional connectivity between rivers and groundwater within the hyporheic zone can be used to improve the definition of fall chinook salmon (Oncorhynchus tshawytscha) spawning habitat. Information exists on the microhabitat characteristics that define suitable salmon spawning habitat. However, traditional spawning habitat models that use these characteristics to predict available spawning habitat are restricted because they can not account for the heterogeneous nature of rivers. The authors present a conceptual spawning habitat model for fall chinook salmon that describes how geomorphic features of river channels create hydraulic processes, including hyporheic flows, that influence where salmon spawn in unconstrained reaches of large mainstem alluvial rivers. Two case studies based on empirical data from fall chinook salmon spawning areas in the Hanford Reach of the Columbia River are presented to illustrate important aspects of the conceptual model. The authors suggest that traditional habitat models and the conceptual model be combined to predict the limits of suitable fall chinook salmon spawning habitat. This approach can incorporate quantitative measures of river channel morphology, including general descriptors of geomorphic features at different spatial scales, in order to understand the processes influencing redd site selection and spawning habitat use. This information is needed in order to protect existing salmon spawning habitat in large rivers, as well as to recover habitat already lost

News and Features Updates from USA.gov

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General Services Administration — Stay on top of important government news and information with the USA.gov Updates: News and Features RSS feed. We'll update this feed when we add news and featured...

The building blocks of a 'Liveable Neighbourhood': Identifying the key performance indicators for walking of an operational planning policy in Perth, Western Australia.

Science.gov (United States)

Hooper, Paula; Knuiman, Matthew; Foster, Sarah; Giles-Corti, Billie

2015-11-01

Planning policy makers are requesting clearer guidance on the key design features required to build neighbourhoods that promote active living. Using a backwards stepwise elimination procedure (logistic regression with generalised estimating equations adjusting for demographic characteristics, self-selection factors, stage of construction and scale of development) this study identified specific design features (n=16) from an operational planning policy ("Liveable Neighbourhoods") that showed the strongest associations with walking behaviours (measured using the Neighbourhood Physical Activity Questionnaire). The interacting effects of design features on walking behaviours were also investigated. The urban design features identified were grouped into the "building blocks of a Liveable Neighbourhood", reflecting the scale, importance and sequencing of the design and implementation phases required to create walkable, pedestrian friendly developments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Features of Interaction of Business and Government in the Form of Public-private partnership

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Oksana N. Taranenko

2016-12-01

Full Text Available Today modernization of relations between the government and the business sector is an important issue particularly relevant in the context of financial globalization in the transition to a market economy. The paper discusses the theoretical concept of public-private partnership, as a form of business organization, combining the functional features of an independent firm or companies and the government, which implementation is caused by the need to ensure the production of the most important benefits in various areas, as well as the features of the interaction of business and government. It is proposed to highlight the definition of public-private partnerships in the form of a special system of relations of economic agents, as well to determine the required features that separate this form of interaction as a partnership from other forms of interaction. Also the authors consider a system of public-private partnership in terms of coordination of joint relations between the government and business, try to identify the basic principles of interaction between the participants, identify their main advantages that each of the participants in the partnership seeks to contribute to the joint project, and identifiess areas to support sustainable development the country's economy. The paper describes the problems associated with the implementation of projects in the public-private partnership system and suggests ways to improve them, discusses the main advantages and disadvantages of such members, as the government and business.

Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

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Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong

2018-06-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen

Facial expression identification using 3D geometric features from Microsoft Kinect device

Science.gov (United States)

Han, Dongxu; Al Jawad, Naseer; Du, Hongbo

2016-05-01

Facial expression identification is an important part of face recognition and closely related to emotion detection from face images. Various solutions have been proposed in the past using different types of cameras and features. Microsoft Kinect device has been widely used for multimedia interactions. More recently, the device has been increasingly deployed for supporting scientific investigations. This paper explores the effectiveness of using the device in identifying emotional facial expressions such as surprise, smile, sad, etc. and evaluates the usefulness of 3D data points on a face mesh structure obtained from the Kinect device. We present a distance-based geometric feature component that is derived from the distances between points on the face mesh and selected reference points in a single frame. The feature components extracted across a sequence of frames starting and ending by neutral emotion represent a whole expression. The feature vector eliminates the need for complex face orientation correction, simplifying the feature extraction process and making it more efficient. We applied the kNN classifier that exploits a feature component based similarity measure following the principle of dynamic time warping to determine the closest neighbors. Preliminary tests on a small scale database of different facial expressions show promises of the newly developed features and the usefulness of the Kinect device in facial expression identification.

An Educational System to Help Students Assess Website Features and Identify High-Risk Websites

Science.gov (United States)

Kajiyama, Tomoko; Echizen, Isao

2015-01-01

Purpose: The purpose of this paper is to propose an effective educational system to help students assess Web site risk by providing an environment in which students can better understand a Web site's features and determine the risks of accessing the Web site for themselves. Design/methodology/approach: The authors have enhanced a prototype…

A bifurcation identifier for IV-OCT using orthogonal least squares and supervised machine learning.

Science.gov (United States)

Macedo, Maysa M G; Guimarães, Welingson V N; Galon, Micheli Z; Takimura, Celso K; Lemos, Pedro A; Gutierrez, Marco Antonio

2015-12-01

Intravascular optical coherence tomography (IV-OCT) is an in-vivo imaging modality based on the intravascular introduction of a catheter which provides a view of the inner wall of blood vessels with a spatial resolution of 10-20 μm. Recent studies in IV-OCT have demonstrated the importance of the bifurcation regions. Therefore, the development of an automated tool to classify hundreds of coronary OCT frames as bifurcation or nonbifurcation can be an important step to improve automated methods for atherosclerotic plaques quantification, stent analysis and co-registration between different modalities. This paper describes a fully automated method to identify IV-OCT frames in bifurcation regions. The method is divided into lumen detection; feature extraction; and classification, providing a lumen area quantification, geometrical features of the cross-sectional lumen and labeled slices. This classification method is a combination of supervised machine learning algorithms and feature selection using orthogonal least squares methods. Training and tests were performed in sets with a maximum of 1460 human coronary OCT frames. The lumen segmentation achieved a mean difference of lumen area of 0.11 mm(2) compared with manual segmentation, and the AdaBoost classifier presented the best result reaching a F-measure score of 97.5% using 104 features. Copyright © 2015 Elsevier Ltd. All rights reserved.

Importance of debriefing in high-fidelity simulations

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Igor Karnjuš

2014-04-01

Full Text Available Debriefing has been identified as one of the most important parts of a high-fidelity simulation learning process. During debriefing, the mentor invites learners to critically assess the knowledge and skills used during the execution of a scenario. Regardless of the abundance of studies that have examined simulation-based education, debriefing is still poorly defined.The present article examines the essential features of debriefing, its phases, techniques and methods with a systematic review of recent publications. It emphasizes the mentor’s role, since the effectiveness of debriefing largely depends on the mentor’s skills to conduct it. The guidelines that allow the mentor to evaluate his performance in conducting debriefing are also presented. We underline the importance of debriefing in clinical settings as part of continuous learning process. Debriefing allows the medical teams to assess their performance and develop new strategies to achieve higher competencies.Although the debriefing is the cornerstone of high-fidelity simulation learning process, it also represents an important learning strategy in the clinical setting. Many important aspects of debriefing are still poorly explored and understood, therefore this part of the learning process should be given greater attention in the future.

Premotor and non-motor features of Parkinson’s disease

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Goldman, Jennifer G.; Postuma, Ron

2014-01-01

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

Statistical Identification of Composed Visual Features Indicating High Likelihood of Grasp Success

DEFF Research Database (Denmark)

Thomsen, Mikkel Tang; Bodenhagen, Leon; Krüger, Norbert

2013-01-01

configurations of three 3D surface features that predict grasping actions with a high success probability. The strategy is based on first computing spatial relations between visual entities and secondly, exploring the cross-space of these relational feature space and grasping actions. The data foundation...... for identifying such indicative feature constellations is generated in a simulated environment wherein visual features are extracted and a large amount of grasping actions are evaluated through dynamic simulation. Based on the identified feature constellations, we validate by applying the acquired knowledge...

Sequence-based classification using discriminatory motif feature selection.

Directory of Open Access Journals (Sweden)

Hao Xiong

Full Text Available Most existing methods for sequence-based classification use exhaustive feature generation, employing, for example, all k-mer patterns. The motivation behind such (enumerative approaches is to minimize the potential for overlooking important features. However, there are shortcomings to this strategy. First, practical constraints limit the scope of exhaustive feature generation to patterns of length ≤ k, such that potentially important, longer (> k predictors are not considered. Second, features so generated exhibit strong dependencies, which can complicate understanding of derived classification rules. Third, and most importantly, numerous irrelevant features are created. These concerns can compromise prediction and interpretation. While remedies have been proposed, they tend to be problem-specific and not broadly applicable. Here, we develop a generally applicable methodology, and an attendant software pipeline, that is predicated on discriminatory motif finding. In addition to the traditional training and validation partitions, our framework entails a third level of data partitioning, a discovery partition. A discriminatory motif finder is used on sequences and associated class labels in the discovery partition to yield a (small set of features. These features are then used as inputs to a classifier in the training partition. Finally, performance assessment occurs on the validation partition. Important attributes of our approach are its modularity (any discriminatory motif finder and any classifier can be deployed and its universality (all data, including sequences that are unaligned and/or of unequal length, can be accommodated. We illustrate our approach on two nucleosome occupancy datasets and a protein solubility dataset, previously analyzed using enumerative feature generation. Our method achieves excellent performance results, with and without optimization of classifier tuning parameters. A Python pipeline implementing the approach is

Organization of co-occurring Axis II features in borderline personality disorder.

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Critchfield, Kenneth L; Clarkin, John F; Levy, Kenneth N; Kernberg, Otto F

2008-06-01

Considerable heterogeneity exists in the comorbid Axis II features that frequently accompany borderline personality disorder (BPD). These features have potential to be meaningfully organized, relate to specific BPD presentation, and have implications for treatment process and outcome. The present study explored patterns of Axis II comorbidity in order to identify subtypes of BPD. A well-defined sample of 90 patients diagnosed with BPD was recruited as part of an RCT study. Participants were administered the International Personality Disorder Examination (Loranger, 1999) to diagnose BPD and assess comorbid Axis II features. Other measures were also administered to assess aspects of current work and relationship functioning, symptomatology, and self-concept. Q-factoring was used to develop subtypes based on commonly occurring Axis II profiles, identifying three: Cluster A (elevated paranoid and schizotypal features), Cluster B (elevated narcissistic and histrionic features), and Cluster C (elevated avoidant and obsessive-compulsive features). An additional factor analysis revealed two dimensions underlying the comorbid features identifiable as: extraversion versus introversion and antagonism versus constraint. Validity of these two maps of comorbidity was explored in terms of the BPD criteria themselves, as well as on work and relationship functioning, identity diffusion, views of self and others, positive and negative affect, behavioural dyscontrol, and symptomatic distress. Clinically meaningful subtypes can be identified for BPD based on co-occurring Axis II features. Further research is needed to replicate and further establish base-rates of these subtypes as well as their differential implications for treatment.

The strategic importance of identifying knowledge-based and intangible assets for generating value, competitiveness and innovation in sub-Saharan Africa

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Nicoline Ondari-Okemwa

2011-01-01

Full Text Available This article discusses the strategic importance of identifying intangible assets for creating value and enhancing competitiveness and innovation in science and technology in a knowledge economy with particular reference to the sub- Saharan Africa region. It has always been difficult to gather the prerequisite information to manage such assets and create value from them. The paper discusses the nature of intangible assets, the characteristics of a knowledge economy and the role of knowledge workers in a knowledge economy. The paper also discusses the importance of identifying intangible assets in relation to capturing the value of such assets, the transfer of intangible assets to other owners and the challenges of managing organizational intangible assets. Objectives of the article include: underscoring the strategic importance of identifying intangible assets in sub-Saharan Africa; examining the performance of intangible assets in a knowledge economy; how intangible assets may generate competitiveness, economic growth and innovation; and assess how knowledge workers are becoming a dominant factor in the knowledge economy. An extensive literature review was employed to collect data for this article. It is concluded in the article that organizations and governments in sub-Saharan Africa should look at knowledge-based assets as strategic resources, even though the traditional accounting systems may still be having problems in determining the exact book value of such assets. It is recommended that organizations and government departments in sub-Saharan Africa should implement a system of the reporting of the value of intangible organizational assets just like the reporting of the value of tangible assets; and that organizations in sub-Saharan Africa should use knowledge to produce “smart products and services” which command premium prices.

Application and interview features used to assess applicant qualifications for residency training.

Science.gov (United States)

Butts, Allison R; Smith, Kelly M

2015-02-01

To determine what factors residency program directors (RPDs) consider and what methods they use to assess applicants. Respondents ranked the importance of 27 applicant features within domains: academics/credentials, application features/program fit, involvement, professional experience, research/ teaching experience, and postgraduate year 1 (PGY-1) residency experience. Rank was assigned in an ordinal fashion (1 = most important feature). The domains were characterized by their importance (mean % ± SD) in selecting candidates for interviews. Participants characterized their screening process according to 8 application and 6 interview features and the corresponding applicant dimensions evaluated. RPDs rated the importance of 14 methods applicants used to communicate with the program and 3 methods by which references were obtained. A Likert scale was used for rating (4 = crucial features). The approaches the program used to evaluate 12 application features or interpersonal interactions were reported. The most important application domain was application features/program fit (26.28 ± 19.11). The highest ranked application feature was program fit (2.04 ± 1.17). The applicant's cover letter, recommendation letters, curriculum vitae, and interview meal were commonly used to assess communication and interpersonal skills, knowledge base, and experience. The most important communication venue was the on-site interview (3.95 ± 0.23). Recommendations solicited by RPDs (3.42 ± 0.69) were most important. Programs formally evaluated the interview (89%) and recommendation letters (84%). Understanding the importance that RPDs place on application and interview features, as well as the process used to assess communication skills and interpersonal interactions, should allow residency candidates to become more competitive residency prospects.

Organizational contextual features that influence the implementation of evidence-based practices across healthcare settings: a systematic integrative review.

Science.gov (United States)

Li, Shelly-Anne; Jeffs, Lianne; Barwick, Melanie; Stevens, Bonnie

2018-05-05

Organizational contextual features have been recognized as important determinants for implementing evidence-based practices across healthcare settings for over a decade. However, implementation scientists have not reached consensus on which features are most important for implementing evidence-based practices. The aims of this review were to identify the most commonly reported organizational contextual features that influence the implementation of evidence-based practices across healthcare settings, and to describe how these features affect implementation. An integrative review was undertaken following literature searches in CINAHL, MEDLINE, PsycINFO, EMBASE, Web of Science, and Cochrane databases from January 2005 to June 2017. English language, peer-reviewed empirical studies exploring organizational context in at least one implementation initiative within a healthcare setting were included. Quality appraisal of the included studies was performed using the Mixed Methods Appraisal Tool. Inductive content analysis informed data extraction and reduction. The search generated 5152 citations. After removing duplicates and applying eligibility criteria, 36 journal articles were included. The majority (n = 20) of the study designs were qualitative, 11 were quantitative, and 5 used a mixed methods approach. Six main organizational contextual features (organizational culture; leadership; networks and communication; resources; evaluation, monitoring and feedback; and champions) were most commonly reported to influence implementation outcomes in the selected studies across a wide range of healthcare settings. We identified six organizational contextual features that appear to be interrelated and work synergistically to influence the implementation of evidence-based practices within an organization. Organizational contextual features did not influence implementation efforts independently from other features. Rather, features were interrelated and often influenced each

Ability of Slovakian Pupils to Identify Birds

Science.gov (United States)

Prokop, Pavol; Rodak, Rastislav

2009-01-01

A pupil's ability to identify common organisms is necessary for acquiring further knowledge of biology. We investigated how pupils were able to identify 25 bird species following their song, growth habits, or both features presented simultaneously. Just about 19% of birds were successfully identified by song, about 39% by growth habit, and 45% of…

Clinical features, proximate causes, and consequences of active convulsive epilepsy in Africa

Science.gov (United States)

Kariuki, Symon M; Matuja, William; Akpalu, Albert; Kakooza-Mwesige, Angelina; Chabi, Martin; Wagner, Ryan G; Connor, Myles; Chengo, Eddie; Ngugi, Anthony K; Odhiambo, Rachael; Bottomley, Christian; White, Steven; Sander, Josemir W; Neville, Brian G R; Newton, Charles R J C

2014-01-01

Purpose Epilepsy is common in sub-Saharan Africa (SSA), but the clinical features and consequences are poorly characterized. Most studies are hospital-based, and few studies have compared different ecological sites in SSA. We described active convulsive epilepsy (ACE) identified in cross-sectional community-based surveys in SSA, to understand the proximate causes, features, and consequences. Methods We performed a detailed clinical and neurophysiologic description of ACE cases identified from a community survey of 584,586 people using medical history, neurologic examination, and electroencephalography (EEG) data from five sites in Africa: South Africa; Tanzania; Uganda; Kenya; and Ghana. The cases were examined by clinicians to discover risk factors, clinical features, and consequences of epilepsy. We used logistic regression to determine the epilepsy factors associated with medical comorbidities. Key Findings Half (51%) of the 2,170 people with ACE were children and 69% of seizures began in childhood. Focal features (EEG, seizure types, and neurologic deficits) were present in 58% of ACE cases, and these varied significantly with site. Status epilepticus occurred in 25% of people with ACE. Only 36% received antiepileptic drugs (phenobarbital was the most common drug [95%]), and the proportion varied significantly with the site. Proximate causes of ACE were adverse perinatal events (11%) for onset of seizures before 18 years; and acute encephalopathy (10%) and head injury prior to seizure onset (3%). Important comorbidities were malnutrition (15%), cognitive impairment (23%), and neurologic deficits (15%). The consequences of ACE were burns (16%), head injuries (postseizure) (1%), lack of education (43%), and being unmarried (67%) or unemployed (57%) in adults, all significantly more common than in those without epilepsy. Significance There were significant differences in the comorbidities across sites. Focal features are common in ACE, suggesting identifiable and

Effective Feature Preprocessing for Time Series Forecasting

DEFF Research Database (Denmark)

Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

2006-01-01

Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

Computed tomographic, magnetic resonance imaging, and cross-sectional anatomic features of the manus in a normal American black bear (Ursus americanus).

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Ober, C P; Freeman, L E

2010-06-01

The purpose of this study was to provide a detailed description of cross-sectional anatomic structures of the manus of a black bear cadaver and correlate anatomic findings with corresponding features in computed tomographic (CT) and magnetic resonance (MR) images. CT, MR imaging, and transverse sectioning were performed on the thoracic limb of a cadaver female black bear which had no evidence of lameness or thoracic limb abnormality prior to death. Features in CT and MR images corresponding to clinically important anatomic structures in anatomic sections were identified. Most of the structures identified in transverse anatomic sections were also identified using CT and MR imaging. Bones, muscles and tendons were generally easily identified with both imaging modalities, although divisions between adjacent muscles were rarely visible with CT and only visible sometimes with MR imaging. Vascular structures could not be identified with either imaging modality.

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.

A feature-based approach to modeling protein-protein interaction hot spots.

Science.gov (United States)

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

A feature-based approach to modeling protein–protein interaction hot spots

Science.gov (United States)

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-01-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533

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...

Controllable edge feature sharpening for dental applications.

Science.gov (United States)

Fan, Ran; Jin, Xiaogang

2014-01-01

This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

Controllable Edge Feature Sharpening for Dental Applications

Directory of Open Access Journals (Sweden)

Ran Fan

2014-01-01

Full Text Available This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

Identifying the Minimum Model Features to Replicate Historic Morphodynamics of a Juvenile Delta

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Czapiga, M. J.; Parker, G.

2017-12-01

We introduce a quasi-2D morphodynamic delta model that improves on past models that require many simplifying assumptions, e.g. a single channel representative of a channel network, fixed channel width, and spatially uniform deposition. Our model is useful for studying long-term progradation rates of any generic micro-tidal delta system with specification of: characteristic grain size, input water and sediment discharges and basin morphology. In particular, we relax the assumption of a single, implicit channel sweeping across the delta topset in favor of an implicit channel network. This network, coupled with recent research on channel-forming Shields number, quantitative assessments of the lateral depositional length of sand (corresponding loosely to levees) and length between bifurcations create a spatial web of deposition within the receiving basin. The depositional web includes spatial boundaries for areas infilling with sands carried as bed material load, as well as those filling via passive deposition of washload mud. Our main goal is to identify the minimum features necessary to accurately model the morphodynamics of channel number, width, depth, and overall delta progradation rate in a juvenile delta. We use the Wax Lake Delta in Louisiana as a test site due to its rapid growth in the last 40 years. Field data including topset/island bathymetry, channel bathymetry, topset/island width, channel width, number of channels, and radial topset length are compiled from US Army Corps of Engineers data for 1989, 1998, and 2006. Additional data is extracted from a DEM from 2015. These data are used as benchmarks for the hindcast model runs. The morphology of Wax Lake Delta is also strongly affected by a pre-delta substrate that acts as a lower "bedrock" boundary. Therefore, we also include closures for a bedrock-alluvial transition and an excess shear rate-law incision model to estimate bedrock incision. The model's framework is generic, but inclusion of individual

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data

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Harris Lyndsay N

2006-04-01

Full Text Available Abstract Background Like microarray-based investigations, high-throughput proteomics techniques require machine learning algorithms to identify biomarkers that are informative for biological classification problems. Feature selection and classification algorithms need to be robust to noise and outliers in the data. Results We developed a recursive support vector machine (R-SVM algorithm to select important genes/biomarkers for the classification of noisy data. We compared its performance to a similar, state-of-the-art method (SVM recursive feature elimination or SVM-RFE, paying special attention to the ability of recovering the true informative genes/biomarkers and the robustness to outliers in the data. Simulation experiments show that a 5 %-~20 % improvement over SVM-RFE can be achieved regard to these properties. The SVM-based methods are also compared with a conventional univariate method and their respective strengths and weaknesses are discussed. R-SVM was applied to two sets of SELDI-TOF-MS proteomics data, one from a human breast cancer study and the other from a study on rat liver cirrhosis. Important biomarkers found by the algorithm were validated by follow-up biological experiments. Conclusion The proposed R-SVM method is suitable for analyzing noisy high-throughput proteomics and microarray data and it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features. The multivariate SVM-based method outperforms the univariate method in the classification performance, but univariate methods can reveal more of the differentially expressed features especially when there are correlations between the features.

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.

Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification

KAUST Repository

Wang, Jim Jing-Yan

2013-12-01

Automated classification of tissue types of Region of Interest (ROI) in medical images has been an important application in Computer-Aided Diagnosis (CAD). Recently, bag-of-feature methods which treat each ROI as a set of local features have shown their power in this field. Two important issues of bag-of-feature strategy for tissue classification are investigated in this paper: the visual vocabulary learning and weighting, which are always considered independently in traditional methods by neglecting the inner relationship between the visual words and their weights. To overcome this problem, we develop a novel algorithm, Joint-ViVo, which learns the vocabulary and visual word weights jointly. A unified objective function based on large margin is defined for learning of both visual vocabulary and visual word weights, and optimized alternately in the iterative algorithm. We test our algorithm on three tissue classification tasks: classifying breast tissue density in mammograms, classifying lung tissue in High-Resolution Computed Tomography (HRCT) images, and identifying brain tissue type in Magnetic Resonance Imaging (MRI). The results show that Joint-ViVo outperforms the state-of-art methods on tissue classification problems. © 2013 Elsevier Ltd.

Epileptic MEG Spike Detection Using Statistical Features and Genetic Programming with KNN

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Turky N. Alotaiby

2017-01-01

Full Text Available Epilepsy is a neurological disorder that affects millions of people worldwide. Monitoring the brain activities and identifying the seizure source which starts with spike detection are important steps for epilepsy treatment. Magnetoencephalography (MEG is an emerging epileptic diagnostic tool with high-density sensors; this makes manual analysis a challenging task due to the vast amount of MEG data. This paper explores the use of eight statistical features and genetic programing (GP with the K-nearest neighbor (KNN for interictal spike detection. The proposed method is comprised of three stages: preprocessing, genetic programming-based feature generation, and classification. The effectiveness of the proposed approach has been evaluated using real MEG data obtained from 28 epileptic patients. It has achieved a 91.75% average sensitivity and 92.99% average specificity.

Critical feature analysis of a radiotherapy machine

International Nuclear Information System (INIS)

Rae, Andrew; Jackson, Daniel; Ramanan, Prasad; Flanz, Jay; Leyman, Didier

2005-01-01

The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An 'assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code

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...

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

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Beiko Robert G

2005-02-01

Full Text Available Abstract Background The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence- and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results GANN (available at http://bioinformatics.org.au/gann is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

Detection of fraudulent emails by employing advanced feature abundance

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Sarwat Nizamani

2014-11-01

Full Text Available In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM (Nizamani et al., 2011 [1] which is authors’ previous cluster based classification model. The experiments have been performed on diverse feature sets and the different classification methods. The comparison of the results is also presented and the evaluation show that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection requires the better choice of feature set; while the choice of classification method is of less importance.

Statistical analyses of scatterplots to identify important factors in large-scale simulations, 1: Review and comparison of techniques

International Nuclear Information System (INIS)

Kleijnen, J.P.C.; Helton, J.C.

1999-01-01

Procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses are described and illustrated. These procedures attempt to detect increasingly complex patterns in scatterplots and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. A sequence of example analyses with a large model for two-phase fluid flow illustrates how the individual procedures can differ in the variables that they identify as having effects on particular model outcomes. The example analyses indicate that the use of a sequence of procedures is a good analysis strategy and provides some assurance that an important effect is not overlooked

Feature-based attentional modulation increases with stimulus separation in divided-attention tasks.

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Sally, Sharon L; Vidnyánsky, Zoltán; Papathomas, Thomas V

2009-01-01

Attention modifies our visual experience by selecting certain aspects of a scene for further processing. It is therefore important to understand factors that govern the deployment of selective attention over the visual field. Both location and feature-specific mechanisms of attention have been identified and their modulatory effects can interact at a neural level (Treue and Martinez-Trujillo, 1999). The effects of spatial parameters on feature-based attentional modulation were examined for the feature dimensions of orientation, motion and color using three divided-attention tasks. Subjects performed concurrent discriminations of two briefly presented targets (Gabor patches) to the left and right of a central fixation point at eccentricities of +/-2.5 degrees , 5 degrees , 10 degrees and 15 degrees in the horizontal plane. Gabors were size-scaled to maintain consistent single-task performance across eccentricities. For all feature dimensions, the data show a linear increase in the attentional effects with target separation. In a control experiment, Gabors were presented on an isoeccentric viewing arc at 10 degrees and 15 degrees at the closest spatial separation (+/-2.5 degrees ) of the main experiment. Under these conditions, the effects of feature-based attentional effects were largely eliminated. Our results are consistent with the hypothesis that feature-based attention prioritizes the processing of attended features. Feature-based attentional mechanisms may have helped direct the attentional focus to the appropriate target locations at greater separations, whereas similar assistance may not have been necessary at closer target spacings. The results of the present study specify conditions under which dual-task performance benefits from sharing similar target features and may therefore help elucidate the processes by which feature-based attention operates.

PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

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Jiangning Song

Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

Personality Features of Motorists

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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.

DEVELOPING AN IMAGE PROCESSING APPLICATION THAT SUPPORTS NEW FEATURES OF JPEG2000 STANDARD

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Evgin GÖÇERİ

2007-03-01

Full Text Available In recent years, developing technologies in multimedia brought the importance of image processing and compression. Images that are reduced in size using lossless and lossy compression techniques without degrading the quality of the image to an unacceptable level take up much less space in memory. This enables them to be sent and received over the Internet or mobile devices in much shorter time. The wavelet-based image compression standard JPEG2000 has been created by the Joint Photographic Experts Group (JPEG committee to superseding the former JPEG standard. Works on various additions to this standard are still under development. In this study, an Application has been developed in Visual C# 2005 which implies important image processing techniques such as edge detection and noise reduction. The important feature of this Application is to support JPEG2000 standard as well as supporting other image types, and the implementation does not only apply to two-dimensional images, but also to multi-dimensional images. Modern software development platforms that support image processing have also been compared and several features of the developed software have been identified.

Geomfinder: a multi-feature identifier of similar three-dimensional protein patterns: a ligand-independent approach.

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Núñez-Vivanco, Gabriel; Valdés-Jiménez, Alejandro; Besoaín, Felipe; Reyes-Parada, Miguel

2016-01-01

Since the structure of proteins is more conserved than the sequence, the identification of conserved three-dimensional (3D) patterns among a set of proteins, can be important for protein function prediction, protein clustering, drug discovery and the establishment of evolutionary relationships. Thus, several computational applications to identify, describe and compare 3D patterns (or motifs) have been developed. Often, these tools consider a 3D pattern as that described by the residues surrounding co-crystallized/docked ligands available from X-ray crystal structures or homology models. Nevertheless, many of the protein structures stored in public databases do not provide information about the location and characteristics of ligand binding sites and/or other important 3D patterns such as allosteric sites, enzyme-cofactor interaction motifs, etc. This makes necessary the development of new ligand-independent methods to search and compare 3D patterns in all available protein structures. Here we introduce Geomfinder, an intuitive, flexible, alignment-free and ligand-independent web server for detailed estimation of similarities between all pairs of 3D patterns detected in any two given protein structures. We used around 1100 protein structures to form pairs of proteins which were assessed with Geomfinder. In these analyses each protein was considered in only one pair (e.g. in a subset of 100 different proteins, 50 pairs of proteins can be defined). Thus: (a) Geomfinder detected identical pairs of 3D patterns in a series of monoamine oxidase-B structures, which corresponded to the effectively similar ligand binding sites at these proteins; (b) we identified structural similarities among pairs of protein structures which are targets of compounds such as acarbose, benzamidine, adenosine triphosphate and pyridoxal phosphate; these similar 3D patterns are not detected using sequence-based methods; (c) the detailed evaluation of three specific cases showed the versatility

Plaque echodensity and textural features are associated with histologic carotid plaque instability.

Science.gov (United States)

Doonan, Robert J; Gorgui, Jessica; Veinot, Jean P; Lai, Chi; Kyriacou, Efthyvoulos; Corriveau, Marc M; Steinmetz, Oren K; Daskalopoulou, Stella S

2016-09-01

Carotid plaque echodensity and texture features predict cerebrovascular symptomatology. Our purpose was to determine the association of echodensity and textural features obtained from a digital image analysis (DIA) program with histologic features of plaque instability as well as to identify the specific morphologic characteristics of unstable plaques. Patients scheduled to undergo carotid endarterectomy were recruited and underwent carotid ultrasound imaging. DIA was performed to extract echodensity and textural features using Plaque Texture Analysis software (LifeQ Medical Ltd, Nicosia, Cyprus). Carotid plaque surgical specimens were obtained and analyzed histologically. Principal component analysis (PCA) was performed to reduce imaging variables. Logistic regression models were used to determine if PCA variables and individual imaging variables predicted histologic features of plaque instability. Image analysis data from 160 patients were analyzed. Individual imaging features of plaque echolucency and homogeneity were associated with a more unstable plaque phenotype on histology. These results were independent of age, sex, and degree of carotid stenosis. PCA reduced 39 individual imaging variables to five PCA variables. PCA1 and PCA2 were significantly associated with overall plaque instability on histology (both P = .02), whereas PCA3 did not achieve statistical significance (P = .07). DIA features of carotid plaques are associated with histologic plaque instability as assessed by multiple histologic features. Importantly, unstable plaques on histology appear more echolucent and homogeneous on ultrasound imaging. These results are independent of stenosis, suggesting that image analysis may have a role in refining the selection of patients who undergo carotid endarterectomy. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

MRI features associated with acute appendicitis

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Leeuwenburgh, Marjolein M.N. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); Academic Medical Center, Department of Radiology (G1-223.1), Amsterdam (Netherlands); Jensch, Sebastiaan [Sint Lucas Andreas Hospital, Department of Radiology, Amsterdam (Netherlands); Gratama, Jan W.C. [Gelre Hospitals, Department of Radiology, Apeldoorn (Netherlands); Spilt, Aart [Kennemer Gasthuis, Department of Radiology, Haarlem (Netherlands); Wiarda, Bart M. [Alkmaar Medical Center, Department of Radiology, Alkmaar (Netherlands); Es, H.W. van [Sint Antonius Hospital, Department of Radiology, Nieuwegein (Netherlands); Cobben, Lodewijk P.J. [Haaglanden Medical Center, Department of Radiology, Leidschendam (Netherlands); Bossuyt, Patrick M.M. [University of Amsterdam, Department of Clinical Epidemiology, Academic Medical Center, Amsterdam (Netherlands); Boermeester, Marja A. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); Stoker, Jaap [University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); Collaboration: on behalf of the OPTIMAP study group

2014-01-15

To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith, peri-appendiceal fat infiltration, peri-appendiceal fluid, absence of gas in the appendix, appendiceal wall destruction, restricted diffusion of the appendiceal wall, lumen or focal fluid collections. Appendicitis was assigned as the final diagnosis in 117/223 patients. Associations between imaging features and appendicitis were evaluated with logistic regression analysis. All investigated features were significantly associated with appendicitis in univariate analysis. Combinations of two and three features were associated with a probability of appendicitis of 88 % and 92 %, respectively. In patients without any of the nine features, appendicitis was present in 2 % of cases. After multivariate analysis, only an appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall were significantly associated with appendicitis. The probability of appendicitis was 96 % in their presence and 2 % in their absence. An appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall have the strongest association with appendicitis on MRI. (orig.)

MRI features associated with acute appendicitis

International Nuclear Information System (INIS)

Leeuwenburgh, Marjolein M.N.; Jensch, Sebastiaan; Gratama, Jan W.C.; Spilt, Aart; Wiarda, Bart M.; Es, H.W. van; Cobben, Lodewijk P.J.; Bossuyt, Patrick M.M.; Boermeester, Marja A.; Stoker, Jaap

2014-01-01

To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith, peri-appendiceal fat infiltration, peri-appendiceal fluid, absence of gas in the appendix, appendiceal wall destruction, restricted diffusion of the appendiceal wall, lumen or focal fluid collections. Appendicitis was assigned as the final diagnosis in 117/223 patients. Associations between imaging features and appendicitis were evaluated with logistic regression analysis. All investigated features were significantly associated with appendicitis in univariate analysis. Combinations of two and three features were associated with a probability of appendicitis of 88 % and 92 %, respectively. In patients without any of the nine features, appendicitis was present in 2 % of cases. After multivariate analysis, only an appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall were significantly associated with appendicitis. The probability of appendicitis was 96 % in their presence and 2 % in their absence. An appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall have the strongest association with appendicitis on MRI. (orig.)

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

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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.

Combining textual and non-textual features for e-mail importance estimation

NARCIS (Netherlands)

Sappelli, M.; Verberne, S.; Kraaij, W.

2013-01-01

In this work, we present a binary classification problem in which we aim to identify those email messages that the receiver will reply to. The future goal is to develop a tool that informs a knowledge worker which emails are likely to need a reply. The Enron corpus was used to extract training

Modeling crash injury severity by road feature to improve safety.

Science.gov (United States)

Penmetsa, Praveena; Pulugurtha, Srinivas S

2018-01-02

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

Identifying selectively important amino acid positions associated with alternative habitat environments in fish mitochondrial genomes.

Science.gov (United States)

Xia, Jun Hong; Li, Hong Lian; Zhang, Yong; Meng, Zi Ning; Lin, Hao Ran

2018-05-01

Fish species inhabitating seawater (SW) or freshwater (FW) habitats have to develop genetic adaptations to alternative environment factors, especially salinity. Functional consequences of the protein variations associated with habitat environments in fish mitochondrial genomes have not yet received much attention. We analyzed 829 complete fish mitochondrial genomes and compared the amino acid differences of 13 mitochondrial protein families between FW and SW fish groups. We identified 47 specificity determining sites (SDS) that associated with FW or SW environments from 12 mitochondrial protein families. Thirty-two (68%) of the SDS sites are hydrophobic, 13 (28%) are neutral, and the remaining sites are acidic or basic. Seven of those SDS from ND1, ND2 and ND5 were scored as probably damaging to the protein structures. Furthermore, phylogenetic tree based Bayes Empirical Bayes analysis also detected 63 positive sites associated with alternative habitat environments across ten mtDNA proteins. These signatures could be important for studying mitochondrial genetic variation relevant to fish physiology and ecology.

Learning Transferable Features with Deep Adaptation Networks

OpenAIRE

Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

2015-01-01

Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

Identifying and Characterizing Important Trembling Aspen Competitors with Juvenile Lodgepole Pine in Three South-Central British Columbia Ecosystems

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Teresa A. Newsome

2012-01-01

Full Text Available Critical height ratios for predicting competition between trembling aspen and lodgepole pine were identified in six juvenile stands in three south-central British Columbia ecosystems. We used a series of regression analyses predicting pine stem diameter from the density of neighbouring aspen in successively shorter relative height classes to identify the aspen-pine height ratio that maximized R2. Critical height ratios varied widely among sites when stands were 8–12 years old but, by age 14–19, had converged at 1.25–1.5. Maximum R2 values at age 14–19 ranged from 13.4% to 69.8%, demonstrating that the importance of aspen competition varied widely across a relatively small geographic range. Logistic regression also indicated that the risk of poor pine vigour in the presence of aspen varied between sites. Generally, the degree of competition, risk to pine vigour, and size of individual aspen contributing to the models declined along a gradient of decreasing ecosystem productivity.

Triangulating Principal Effectiveness: How Perspectives of Parents, Teachers, and Assistant Principals Identify the Central Importance of Managerial Skills. Working Paper 35

Science.gov (United States)

Grissom, Jason A.; Loeb, Susanna

2009-01-01

While the importance of effective principals is undisputed, few studies have addressed what specific skills principals need to promote school success. This study draws on unique data combining survey responses from principals, assistant principals, teachers and parents with rich administrative data to identify which principal skills matter most…

Patterns of Dysmorphic Features in Schizophrenia

Science.gov (United States)

Scutt, L.E.; Chow, E.W.C.; Weksberg, R.; Honer, W.G.; Bassett, Anne S.

2011-01-01

Congenital dysmorphic features are prevalent in schizophrenia and may reflect underlying neurodevelopmental abnormalities. A cluster analysis approach delineating patterns of dysmorphic features has been used in genetics to classify individuals into more etiologically homogeneous subgroups. In the present study, this approach was applied to schizophrenia, using a sample with a suspected genetic syndrome as a testable model. Subjects (n = 159) with schizophrenia or schizoaffective disorder were ascertained from chronic patient populations (random, n=123) or referred with possible 22q11 deletion syndrome (referred, n = 36). All subjects were evaluated for presence or absence of 70 reliably assessed dysmorphic features, which were used in a three-step cluster analysis. The analysis produced four major clusters with different patterns of dysmorphic features. Significant between-cluster differences were found for rates of 37 dysmorphic features (P dysmorphic features (P = 0.0001), and validating features not used in the cluster analysis: mild mental retardation (P = 0.001) and congenital heart defects (P = 0.002). Two clusters (1 and 4) appeared to represent more developmental subgroups of schizophrenia with elevated rates of dysmorphic features and validating features. Cluster 1 (n = 27) comprised mostly referred subjects. Cluster 4 (n= 18) had a different pattern of dysmorphic features; one subject had a mosaic Turner syndrome variant. Two other clusters had lower rates and patterns of features consistent with those found in previous studies of schizophrenia. Delineating patterns of dysmorphic features may help identify subgroups that could represent neurodevelopmental forms of schizophrenia with more homogeneous origins. PMID:11803519

The Relative Importance of Family History, Gender, Mode of Onset, and Age at Onsetin Predicting Clinical Features of First-Episode Psychotic Disorders.

Science.gov (United States)

Compton, Michael T; Berez, Chantal; Walker, Elaine F

Family history of psychosis, gender, mode of onset, and age at onset are considered prognostic factors important to clinicians evaluating first-episode psychosis; yet, clinicians have little guidance as to how these four factors differentially predict early-course substance abuse, symptomatology, and functioning. We conducted a "head-to-head comparison" of these four factors regarding their associations with key clinical features at initial hospitalization. We also assessed potential interactions between gender and family history with regard to age at onset of psychosis and symptom severity. Consecutively admitted first-episode patients (n=334) were evaluated in two studies that rigorously assessed a number of early-course variables. Associations among variables of interest were examined using Pearson correlations, χ 2 tests, Student's t-tests, and 2×2 factorial analyses of variance. Substance (nicotine, alcohol, and cannabis) abuse and positive symptom severity were predicted only by male gender. Negative symptom severity and global functioning impairments were predicted by earlier age at onset of psychosis. General psychopathology symptom severity was predicted by both mode of onset and age at onset. Interaction effects were not observed with regard to gender and family history in predicting age at onset or symptom severity. The four prognostic features have differential associations with substance abuse, domains of symptom severity, and global functioning. Gender and age at onset of psychosis appear to be more predictive of clinical features at the time of initial evaluation (and thus presumably longer term outcomes) than the presence of a family history of psychosis and a more gradual mode of onset.

MIIB: A Metric to Identify Top Influential Bloggers in a Community.

Science.gov (United States)

Khan, Hikmat Ullah; Daud, Ali; Malik, Tahir Afzal

2015-01-01

Social networking has revolutionized the use of conventional web and has converted World Wide Web into the social web as users can generate their own content. This change has been possible due to social web platforms like forums, wikis, and blogs. Blogs are more commonly being used as a form of virtual communication to express an opinion about an event, product or experience and can reach a large audience. Users can influence others to buy a product, have certain political or social views, etc. Therefore, identifying the most influential bloggers has become very significant as this can help us in the fields of commerce, advertisement and product knowledge searching. Existing approaches consider some basic features, but lack to consider some other features like the importance of the blog on which the post has been created. This paper presents a new metric, MIIB (Metric for Identification of Influential Bloggers), based on various features of bloggers' productivity and popularity. Productivity refers to bloggers' blogging activity and popularity measures bloggers' influence in the blogging community. The novel module of BlogRank depicts the importance of blog sites where bloggers create their posts. The MIIB has been evaluated against the standard model and existing metrics for finding the influential bloggers using dataset from the real-world blogosphere. The obtained results confirm that the MIIB is able to find the most influential bloggers in a more effective manner.

MIIB: A Metric to Identify Top Influential Bloggers in a Community.

Directory of Open Access Journals (Sweden)

Hikmat Ullah Khan

Full Text Available Social networking has revolutionized the use of conventional web and has converted World Wide Web into the social web as users can generate their own content. This change has been possible due to social web platforms like forums, wikis, and blogs. Blogs are more commonly being used as a form of virtual communication to express an opinion about an event, product or experience and can reach a large audience. Users can influence others to buy a product, have certain political or social views, etc. Therefore, identifying the most influential bloggers has become very significant as this can help us in the fields of commerce, advertisement and product knowledge searching. Existing approaches consider some basic features, but lack to consider some other features like the importance of the blog on which the post has been created. This paper presents a new metric, MIIB (Metric for Identification of Influential Bloggers, based on various features of bloggers' productivity and popularity. Productivity refers to bloggers' blogging activity and popularity measures bloggers' influence in the blogging community. The novel module of BlogRank depicts the importance of blog sites where bloggers create their posts. The MIIB has been evaluated against the standard model and existing metrics for finding the influential bloggers using dataset from the real-world blogosphere. The obtained results confirm that the MIIB is able to find the most influential bloggers in a more effective manner.

A statistical-textural-features based approach for classification of solid drugs using surface microscopic images.

Science.gov (United States)

Tahir, Fahima; Fahiem, Muhammad Abuzar

2014-01-01

The quality of pharmaceutical products plays an important role in pharmaceutical industry as well as in our lives. Usage of defective tablets can be harmful for patients. In this research we proposed a nondestructive method to identify defective and nondefective tablets using their surface morphology. Three different environmental factors temperature, humidity and moisture are analyzed to evaluate the performance of the proposed method. Multiple textural features are extracted from the surface of the defective and nondefective tablets. These textural features are gray level cooccurrence matrix, run length matrix, histogram, autoregressive model and HAAR wavelet. Total textural features extracted from images are 281. We performed an analysis on all those 281, top 15, and top 2 features. Top 15 features are extracted using three different feature reduction techniques: chi-square, gain ratio and relief-F. In this research we have used three different classifiers: support vector machine, K-nearest neighbors and naïve Bayes to calculate the accuracies against proposed method using two experiments, that is, leave-one-out cross-validation technique and train test models. We tested each classifier against all selected features and then performed the comparison of their results. The experimental work resulted in that in most of the cases SVM performed better than the other two classifiers.

Computation and Evaluation of Features of Surface Electromyogram to Identify the Force of Muscle Contraction and Muscle Fatigue

Directory of Open Access Journals (Sweden)

Sridhar P. Arjunan

2014-01-01

Full Text Available The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC. Six features were considered in this study: normalised spectral index (NSM5, median frequency, root mean square, waveform length, normalised root mean square (NRMS, and increase in synchronization (IIS index. Analysis of variance (ANOVA and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P0.05.

Computation and evaluation of features of surface electromyogram to identify the force of muscle contraction and muscle fatigue.

Science.gov (United States)

Arjunan, Sridhar P; Kumar, Dinesh K; Naik, Ganesh

2014-01-01

The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P 0.05).

Identifying Key Features of Student Performance in Educational Video Games and Simulations through Cluster Analysis

Science.gov (United States)

Kerr, Deirdre; Chung, Gregory K. W. K.

2012-01-01

The assessment cycle of "evidence-centered design" (ECD) provides a framework for treating an educational video game or simulation as an assessment. One of the main steps in the assessment cycle of ECD is the identification of the key features of student performance. While this process is relatively simple for multiple choice tests, when…

Distinctive MRI features of the epileptogenic zone in children with tuberous sclerosis

International Nuclear Information System (INIS)

Jahodova, A.; Krsek, P.; Kyncl, M.; Jezdik, P.; Kudr, M.; Komarek, V.; Jayakar, P.; Miller, I.; Resnick, T.

2014-01-01

Objective: Localization of the epileptogenic zone (EZ) is challenging in children with tuberous sclerosis complex (TSC). We sought to ascertain whether brain MRI could identify the EZ in TSC patients independent of the clinical and diagnostic data. Methods: Presurgical MRI's of 34 children with TSC who underwent epilepsy surgery at Miami Children's Hospital were retrospectively reevaluated by experts blinded to all other data. Changes typical of TSC (tubers, calcifications, cystic changes) and abnormalities of the perituberal cortex typical of focal cortical dysplasia (FCD) (increased cortical thickness, abnormal gyration, transmantle change, gray/white matter junction blurring) were identified and their localization was compared with the resection site. Sensitivity, specificity and accuracy of individual MRI features to localize the EZ were determined and statistically compared between postoperatively seizure-free and non-seizure-free patients as well as clusters of features typical of FCD and TSC. Results: MRI alone correctly localized the resection cavity in all 19 postoperatively seizure-free patients and 12 of 15 non-seizure-free subjects. Sensitivity, specificity and accuracy of MRI features typical of FCD to localize EZ (90%, 96% and 96%, respectively) were superior to those typical of TCS (79%, 75% and 75%, p < 0.0001). Increased cortical thickness and abnormal gyral formation outside tubers occurred only in the resection site. Resection sites were better predicted by MRI in seizure-free than in non-seizure-free patients. Conclusion: Thorough MRI evaluation identifies the EZ in a significant proportion of TSC patients. Epileptogenic regions were mostly characterized by “FCD-like” changes outside cortical tubers. The findings may have important practical consequences for surgical planning in TSC

Distinctive MRI features of the epileptogenic zone in children with tuberous sclerosis

Energy Technology Data Exchange (ETDEWEB)

Jahodova, A., E-mail: a.jagoda@email.cz [Department of Pediatric Neurology, Charles University, Second Medical School, Motol University Hospital, V Uvalu 84, Prague 5 150 06 (Czech Republic); Krsek, P., E-mail: pavel.krsek@post.cz [Department of Pediatric Neurology, Charles University, Second Medical School, Motol University Hospital, V Uvalu 84, Prague 5 150 06 (Czech Republic); Kyncl, M., E-mail: martinkyn@seznam.cz [Department of Radiology, Charles University, Second Medical School, Motol University Hospital, V Uvalu 84, Prague 5 150 06 (Czech Republic); Jezdik, P., E-mail: jezdip1@feld.cvut.cz [Department of Measurement, Faculty of Electric, Czech Technical University Prague, Technicka 2, CZ 166 27 Prague 6 (Czech Republic); Kudr, M., E-mail: mat.kudr@gmail.com [Department of Pediatric Neurology, Charles University, Second Medical School, Motol University Hospital, V Uvalu 84, Prague 5 150 06 (Czech Republic); Komarek, V., E-mail: vladimir.komarek@fnmotol.cz [Department of Pediatric Neurology, Charles University, Second Medical School, Motol University Hospital, V Uvalu 84, Prague 5 150 06 (Czech Republic); Jayakar, P., E-mail: Prasanna.Jayakar@mch.com [Department of Neurology and Comprehensive Epilepsy Program, Brain Institute, Miami Children' s Hospital, 3200 S.W. 60th Court, Miami, FL (United States); Miller, I., E-mail: ian.miller@mchdocs.com [Department of Neurology and Comprehensive Epilepsy Program, Brain Institute, Miami Children' s Hospital, 3200 S.W. 60th Court, Miami, FL (United States); Resnick, T., E-mail: trevor.resnick@mch.com [Department of Neurology and Comprehensive Epilepsy Program, Brain Institute, Miami Children' s Hospital, 3200 S.W. 60th Court, Miami, FL (United States); Department of Neurology, University of Miami Miller School of Medicine, Miami, FL (United States); and others

2014-04-15

Objective: Localization of the epileptogenic zone (EZ) is challenging in children with tuberous sclerosis complex (TSC). We sought to ascertain whether brain MRI could identify the EZ in TSC patients independent of the clinical and diagnostic data. Methods: Presurgical MRI's of 34 children with TSC who underwent epilepsy surgery at Miami Children's Hospital were retrospectively reevaluated by experts blinded to all other data. Changes typical of TSC (tubers, calcifications, cystic changes) and abnormalities of the perituberal cortex typical of focal cortical dysplasia (FCD) (increased cortical thickness, abnormal gyration, transmantle change, gray/white matter junction blurring) were identified and their localization was compared with the resection site. Sensitivity, specificity and accuracy of individual MRI features to localize the EZ were determined and statistically compared between postoperatively seizure-free and non-seizure-free patients as well as clusters of features typical of FCD and TSC. Results: MRI alone correctly localized the resection cavity in all 19 postoperatively seizure-free patients and 12 of 15 non-seizure-free subjects. Sensitivity, specificity and accuracy of MRI features typical of FCD to localize EZ (90%, 96% and 96%, respectively) were superior to those typical of TCS (79%, 75% and 75%, p < 0.0001). Increased cortical thickness and abnormal gyral formation outside tubers occurred only in the resection site. Resection sites were better predicted by MRI in seizure-free than in non-seizure-free patients. Conclusion: Thorough MRI evaluation identifies the EZ in a significant proportion of TSC patients. Epileptogenic regions were mostly characterized by “FCD-like” changes outside cortical tubers. The findings may have important practical consequences for surgical planning in TSC.

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....

Identify alternative splicing events based on position-specific evolutionary conservation.

Directory of Open Access Journals (Sweden)

Liang Chen

Full Text Available The evolution of eukaryotes is accompanied by the increased complexity of alternative splicing which greatly expands genome information. One of the greatest challenges in the post-genome era is a complete revelation of human transcriptome with consideration of alternative splicing. Here, we introduce a comparative genomics approach to systemically identify alternative splicing events based on the differential evolutionary conservation between exons and introns and the high-quality annotation of the ENCODE regions. Specifically, we focus on exons that are included in some transcripts but are completely spliced out for others and we call them conditional exons. First, we characterize distinguishing features among conditional exons, constitutive exons and introns. One of the most important features is the position-specific conservation score. There are dramatic differences in conservation scores between conditional exons and constitutive exons. More importantly, the differences are position-specific. For flanking intronic regions, the differences between conditional exons and constitutive exons are also position-specific. Using the Random Forests algorithm, we can classify conditional exons with high specificities (97% for the identification of conditional exons from intron regions and 95% for the classification of known exons and fair sensitivities (64% and 32% respectively. We applied the method to the human genome and identified 39,640 introns that actually contain conditional exons and classified 8,813 conditional exons from the current RefSeq exon list. Among those, 31,673 introns containing conditional exons and 5,294 conditional exons classified from known exons cannot be inferred from RefSeq, UCSC or Ensembl annotations. Some of these de novo predictions were experimentally verified.

Deep Visual Attributes vs. Hand-Crafted Audio Features on Multidomain Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Michalis Papakostas

2017-06-01

Full Text Available Emotion recognition from speech may play a crucial role in many applications related to human–computer interaction or understanding the affective state of users in certain tasks, where other modalities such as video or physiological parameters are unavailable. In general, a human’s emotions may be recognized using several modalities such as analyzing facial expressions, speech, physiological parameters (e.g., electroencephalograms, electrocardiograms etc. However, measuring of these modalities may be difficult, obtrusive or require expensive hardware. In that context, speech may be the best alternative modality in many practical applications. In this work we present an approach that uses a Convolutional Neural Network (CNN functioning as a visual feature extractor and trained using raw speech information. In contrast to traditional machine learning approaches, CNNs are responsible for identifying the important features of the input thus, making the need of hand-crafted feature engineering optional in many tasks. In this paper no extra features are required other than the spectrogram representations and hand-crafted features were only extracted for validation purposes of our method. Moreover, it does not require any linguistic model and is not specific to any particular language. We compare the proposed approach using cross-language datasets and demonstrate that it is able to provide superior results vs. traditional ones that use hand-crafted features.

Multiple song features are related to paternal effort in common nightingales.

Science.gov (United States)

Bartsch, Conny; Weiss, Michael; Kipper, Silke

2015-06-18

Sexual ornamentation may be related to the degree of paternal care and the 'good-parent' model predicts that male secondary characters honestly advertise paternal investment. In most birds, males are involved in bringing up the young and successful reproduction highly depends on male contribution during breeding. In passerines, male song is indicative of male attributes and for few species it has been shown that song features also signal paternal investment to females. Males of nightingales Luscinia megarhynchos are famous for their elaborate singing but so far there is only little knowledge on the role of male song in intersexual communication, and it is unknown whether male song predicts male parenting abilities. Using RFID technology to record male feeding visits to the nest, we found that nightingale males substantially contribute to chick feeding. Also, we analyzed male nocturnal song with focus on song features that have been shown to signal male quality before. We found that several song features, namely measures of song complexity and song sequencing, were correlated with male feeding rates. Moreover, the combination of these song features had strong predictive power for male contribution to nestling feeding. Since male nightingales are involved in chick rearing, paternal investment might be a crucial variable for female mate choice in this species. Females may assess future paternal care on the basis of song features identified in our study and thus these features may have evolved to signal direct benefits to females. Additionally we underline the importance of multiple acoustic cues for female mating decisions especially in species with complex song such as the nightingale.

Using manipulated photographs to identify features of streetscapes that may encourage older adults to walk for transport.

Directory of Open Access Journals (Sweden)

Jelle Van Cauwenberg

Full Text Available Experimental evidence of environmental features important for physical activity is challenging to procure in real world settings. The current study aimed to investigate the causal effects of environmental modifications on a photographed street's appeal for older adults' walking for transport. Secondly, we examined whether these effects differed according to gender, functional limitations, and current level of walking for transport. Thirdly, we examined whether different environmental modifications interacted with each other. Qualitative responses were also reported to gain deeper insight into the observed quantitative relationships. Two sets of 16 panoramic photographs of a streetscape were created, in which six environmental factors were manipulated (sidewalk evenness, traffic level, general upkeep, vegetation, separation from traffic, and benches. Sixty older adults sorted these photographs on appeal for walking for transport on a 7-point scale and reported qualitative information on the reasons for their rankings. Sidewalk evenness appeared to have the strongest influence on a street's appeal for transport-related walking. The effect of sidewalk evenness was even stronger when the street's overall upkeep was good and when traffic was absent. Absence of traffic, presence of vegetation, and separation from traffic also increased a street's appeal for walking for transport. There were no moderating effects by gender or functional limitations. The presence of benches increased the streetscape's appeal among participants who already walked for transport at least an hour/week. The protocols and methods used in the current study carry the potential to further our understanding of environment-PA relationships. Our findings indicated sidewalk evenness as the most important environmental factor influencing a street's appeal for walking for transport among older adults. However, future research in larger samples and in real-life settings is needed to

Using manipulated photographs to identify features of streetscapes that may encourage older adults to walk for transport.

Science.gov (United States)

Van Cauwenberg, Jelle; Van Holle, Veerle; De Bourdeaudhuij, Ilse; Clarys, Peter; Nasar, Jack; Salmon, Jo; Goubert, Liesbet; Deforche, Benedicte

2014-01-01

Experimental evidence of environmental features important for physical activity is challenging to procure in real world settings. The current study aimed to investigate the causal effects of environmental modifications on a photographed street's appeal for older adults' walking for transport. Secondly, we examined whether these effects differed according to gender, functional limitations, and current level of walking for transport. Thirdly, we examined whether different environmental modifications interacted with each other. Qualitative responses were also reported to gain deeper insight into the observed quantitative relationships. Two sets of 16 panoramic photographs of a streetscape were created, in which six environmental factors were manipulated (sidewalk evenness, traffic level, general upkeep, vegetation, separation from traffic, and benches). Sixty older adults sorted these photographs on appeal for walking for transport on a 7-point scale and reported qualitative information on the reasons for their rankings. Sidewalk evenness appeared to have the strongest influence on a street's appeal for transport-related walking. The effect of sidewalk evenness was even stronger when the street's overall upkeep was good and when traffic was absent. Absence of traffic, presence of vegetation, and separation from traffic also increased a street's appeal for walking for transport. There were no moderating effects by gender or functional limitations. The presence of benches increased the streetscape's appeal among participants who already walked for transport at least an hour/week. The protocols and methods used in the current study carry the potential to further our understanding of environment-PA relationships. Our findings indicated sidewalk evenness as the most important environmental factor influencing a street's appeal for walking for transport among older adults. However, future research in larger samples and in real-life settings is needed to confirm current

Intelligent feature selection techniques for pattern classification of Lamb wave signals

International Nuclear Information System (INIS)

Hinders, Mark K.; Miller, Corey A.

2014-01-01

Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crosshole tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy

Features for detecting smoke in laparoscopic videos

Directory of Open Access Journals (Sweden)

Jalal Nour Aldeen

2017-09-01

Full Text Available Video-based smoke detection in laparoscopic surgery has different potential applications, such as the automatic addressing of surgical events associated with the electrocauterization task and the development of automatic smoke removal. In the literature, video-based smoke detection has been studied widely for fire surveillance systems. Nevertheless, the proposed methods are insufficient for smoke detection in laparoscopic videos because they often depend on assumptions which rarely hold in laparoscopic surgery such as static camera. In this paper, ten visual features based on motion, texture and colour of smoke are proposed and evaluated for smoke detection in laparoscopic videos. These features are RGB channels, energy-based feature, texture features based on gray level co-occurrence matrix (GLCM, HSV colour space feature, features based on the detection of moving regions using optical flow and the smoke colour in HSV colour space. These features were tested on four laparoscopic cholecystectomy videos. Experimental observations show that each feature can provide valuable information in performing the smoke detection task. However, each feature has weaknesses to detect the presence of smoke in some cases. By combining all proposed features smoke with high and even low density can be identified robustly and the classification accuracy increases significantly.

Cemento-osseous dysplasia of the jaw bones: key radiographic features.

Science.gov (United States)

Alsufyani, N A; Lam, E W N

2011-03-01

The purpose of this study is to assess possible diagnostic differences between general dentists (GPs) and oral and maxillofacial radiologists (RGs) in the identification of pathognomonic radiographic features of cemento-osseous dysplasia (COD) and its interpretation. Using a systematic objective survey instrument, 3 RGs and 3 GPs reviewed 50 image sets of COD and similarly appearing entities (dense bone island, cementoblastoma, cemento-ossifying fibroma, fibrous dysplasia, complex odontoma and sclerosing osteitis). Participants were asked to identify the presence or absence of radiographic features and then to make an interpretation of the images. RGs identified a well-defined border (odds ratio (OR) 6.67, P < 0.05); radiolucent periphery (OR 8.28, P < 0.005); bilateral occurrence (OR 10.23, P < 0.01); mixed radiolucent/radiopaque internal structure (OR 10.53, P < 0.01); the absence of non-concentric bony expansion (OR 7.63, P < 0.05); and the association with anterior and posterior teeth (OR 4.43, P < 0.05) as key features of COD. Consequently, RGs were able to correctly interpret 79.3% of COD cases. In contrast, GPs identified the absence of root resorption (OR 4.52, P < 0.05) and the association with anterior and posterior teeth (OR 3.22, P = 0.005) as the only key features of COD and were able to correctly interpret 38.7% of COD cases. There are statistically significant differences between RGs and GPs in the identification and interpretation of the radiographic features associated with COD (P < 0.001). We conclude that COD is radiographically discernable from other similarly appearing entities only if the characteristic radiographic features are correctly identified and then correctly interpreted.

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.

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

Science.gov (United States)

Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

2017-08-18

Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

Clinical features, proximate causes, and consequences of active convulsive epilepsy in Africa.

Science.gov (United States)

Kariuki, Symon M; Matuja, William; Akpalu, Albert; Kakooza-Mwesige, Angelina; Chabi, Martin; Wagner, Ryan G; Connor, Myles; Chengo, Eddie; Ngugi, Anthony K; Odhiambo, Rachael; Bottomley, Christian; White, Steven; Sander, Josemir W; Neville, Brian G R; Newton, Charles R J C; Twine, Rhian; Gómez Olivé, F Xavier; Collinson, Mark; Kahn, Kathleen; Tollman, Stephen; Masanja, Honratio; Mathew, Alexander; Pariyo, George; Peterson, Stefan; Ndyomughenyi, Donald; Bauni, Evasius; Kamuyu, Gathoni; Odera, Victor Mung'ala; Mageto, James O; Ae-Ngibise, Ken; Akpalu, Bright; Agbokey, Francis; Adjei, Patrick; Owusu-Agyei, Seth; Kleinschmidt, Immo; Doku, Victor C K; Odermatt, Peter; Nutman, Thomas; Wilkins, Patricia; Noh, John

2014-01-01

Epilepsy is common in sub-Saharan Africa (SSA), but the clinical features and consequences are poorly characterized. Most studies are hospital-based, and few studies have compared different ecological sites in SSA. We described active convulsive epilepsy (ACE) identified in cross-sectional community-based surveys in SSA, to understand the proximate causes, features, and consequences. We performed a detailed clinical and neurophysiologic description of ACE cases identified from a community survey of 584,586 people using medical history, neurologic examination, and electroencephalography (EEG) data from five sites in Africa: South Africa; Tanzania; Uganda; Kenya; and Ghana. The cases were examined by clinicians to discover risk factors, clinical features, and consequences of epilepsy. We used logistic regression to determine the epilepsy factors associated with medical comorbidities. Half (51%) of the 2,170 people with ACE were children and 69% of seizures began in childhood. Focal features (EEG, seizure types, and neurologic deficits) were present in 58% of ACE cases, and these varied significantly with site. Status epilepticus occurred in 25% of people with ACE. Only 36% received antiepileptic drugs (phenobarbital was the most common drug [95%]), and the proportion varied significantly with the site. Proximate causes of ACE were adverse perinatal events (11%) for onset of seizures before 18 years; and acute encephalopathy (10%) and head injury prior to seizure onset (3%). Important comorbidities were malnutrition (15%), cognitive impairment (23%), and neurologic deficits (15%). The consequences of ACE were burns (16%), head injuries (postseizure) (1%), lack of education (43%), and being unmarried (67%) or unemployed (57%) in adults, all significantly more common than in those without epilepsy. There were significant differences in the comorbidities across sites. Focal features are common in ACE, suggesting identifiable and preventable causes. Malnutrition and

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.

Novel PCA-VIP scheme for ranking MRI protocols and identifying computer-extracted MRI measurements associated with central gland and peripheral zone prostate tumors.

Science.gov (United States)

Ginsburg, Shoshana B; Viswanath, Satish E; Bloch, B Nicolas; Rofsky, Neil M; Genega, Elizabeth M; Lenkinski, Robert E; Madabhushi, Anant

2015-05-01

To identify computer-extracted features for central gland and peripheral zone prostate cancer localization on multiparametric magnetic resonance imaging (MRI). Preoperative T2-weighted (T2w), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) MRI were acquired from 23 men with confirmed prostate cancer. Following radical prostatectomy, the cancer extent was delineated by a pathologist on ex vivo histology and mapped to MRI by nonlinear registration of histology and corresponding MRI slices. In all, 244 computer-extracted features were extracted from MRI, and principal component analysis (PCA) was employed to reduce the data dimensionality so that a generalizable classifier could be constructed. A novel variable importance on projection (VIP) measure for PCA (PCA-VIP) was leveraged to identify computer-extracted MRI features that discriminate between cancer and normal prostate, and these features were used to construct classifiers for cancer localization. Classifiers using features selected by PCA-VIP yielded an area under the curve (AUC) of 0.79 and 0.85 for peripheral zone and central gland tumors, respectively. For tumor localization in the central gland, T2w, DCE, and DWI MRI features contributed 71.6%, 18.1%, and 10.2%, respectively; for peripheral zone tumors T2w, DCE, and DWI MRI contributed 29.6%, 21.7%, and 48.7%, respectively. PCA-VIP identified relatively stable subsets of MRI features that performed well in localizing prostate cancer on MRI. © 2014 Wiley Periodicals, Inc.

Feature-based morphometry: discovering group-related anatomical patterns.

Science.gov (United States)

Toews, Matthew; Wells, William; Collins, D Louis; Arbel, Tal

2010-02-01

This paper presents feature-based morphometry (FBM), a new fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). Copyright (c) 2009 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2014-08-01

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

Breast cancer molecular subtype classifier that incorporates MRI features.

Science.gov (United States)

Sutton, Elizabeth J; Dashevsky, Brittany Z; Oh, Jung Hun; Veeraraghavan, Harini; Apte, Aditya P; Thakur, Sunitha B; Morris, Elizabeth A; Deasy, Joseph O

2016-07-01

To use features extracted from magnetic resonance (MR) images and a machine-learning method to assist in differentiating breast cancer molecular subtypes. This retrospective Health Insurance Portability and Accountability Act (HIPAA)-compliant study received Institutional Review Board (IRB) approval. We identified 178 breast cancer patients between 2006-2011 with: 1) ERPR + (n = 95, 53.4%), ERPR-/HER2 + (n = 35, 19.6%), or triple negative (TN, n = 48, 27.0%) invasive ductal carcinoma (IDC), and 2) preoperative breast MRI at 1.5T or 3.0T. Shape, texture, and histogram-based features were extracted from each tumor contoured on pre- and three postcontrast MR images using in-house software. Clinical and pathologic features were also collected. Machine-learning-based (support vector machines) models were used to identify significant imaging features and to build models that predict IDC subtype. Leave-one-out cross-validation (LOOCV) was used to avoid model overfitting. Statistical significance was determined using the Kruskal-Wallis test. Each support vector machine fit in the LOOCV process generated a model with varying features. Eleven out of the top 20 ranked features were significantly different between IDC subtypes with P machine-learning-based predictive model using features extracted from MRI that can distinguish IDC subtypes with significant predictive power. J. Magn. Reson. Imaging 2016;44:122-129. © 2016 Wiley Periodicals, Inc.

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.

Feature Scaling via Second-Order Cone Programming

Directory of Open Access Journals (Sweden)

Zhizheng Liang

2016-01-01

Full Text Available Feature scaling has attracted considerable attention during the past several decades because of its important role in feature selection. In this paper, a novel algorithm for learning scaling factors of features is proposed. It first assigns a nonnegative scaling factor to each feature of data and then adopts a generalized performance measure to learn the optimal scaling factors. It is of interest to note that the proposed model can be transformed into a convex optimization problem: second-order cone programming (SOCP. Thus the scaling factors of features in our method are globally optimal in some sense. Several experiments on simulated data, UCI data sets, and the gene data set are conducted to demonstrate that the proposed method is more effective than previous methods.

Why is variability important for performance assessment and what are its consequences for site characterisation and repository design?

International Nuclear Information System (INIS)

Dverstorp, B.; Smith, P.A.; Zuidema, P.

1998-01-01

The importance of spatial variability is discussed in terms of its consequences for site characterisation and for repository design and safety. Variability is described in terms of various scales of discrete structural features and a pragmatic classification is proposed according to whether the features are: feasibility-determining (i.e. features within which repository construction and operation is not practical and which preclude long-term safety); layout-determining (i.e. features which, if avoided, would enhance long-term safety); safety-determining features (i.e. features which cannot be shown to be avoidable and which strongly influence the calculated long-term safety of the repository system). The significance with respect to the geosphere-transport barrier of small-scale pore structure within the various classes of feature is also discussed. The practical problems of characterising variability and modelling its effects on radionuclide transport are described. Key factors affecting groundwater flow and radionuclide transport are identified, models that incorporate spatial variability are described and the estimation of appropriate parameters for these models is discussed. (author)

On the Use of Memory Models in Audio Features

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2011-01-01

Audio feature estimation is potentially improved by including higher- level models. One such model is the Short Term Memory (STM) model. A new paradigm of audio feature estimation is obtained by adding the influence of notes in the STM. These notes are identified when the perceptual spectral flux...

Large scale features of the hot component of the interstellar medium

International Nuclear Information System (INIS)

Garmire, G.P.

1983-01-01

The interstellar medium contains identifiable hot plasma clouds occupying up to about 35% of the volume of the local galactic disc. The temperature of these clouds is not uniform but ranges from 10 5 up to 4 x 10 6 K. Besides the high temperature which places the emission spectrum in the soft X-ray band, the implied pressure of the hot plasma compared to the cooler gas reveals the importance of this component in determining the motions and evolution of the cooler gas in the disc, as well as providing a source of hot gas which may extend above the galactic disc to form a corona. The author presents data from the A-2 soft X-ray experiment on the HEAO-1 spacecraft concerning the large scale features of this gas. These features are interpreted in terms of the late phases of supernovae expansion, multiple supernovae and the possible creation of a hot halo surrounding the region of the galactic nucleus. (Auth.)

Identification of informative features for predicting proinflammatory potentials of engine exhausts.

Science.gov (United States)

Wang, Chia-Chi; Lin, Ying-Chi; Lin, Yuan-Chung; Jhang, Syu-Ruei; Tung, Chun-Wei

2017-08-18

The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment. To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm. A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively. The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.

Efficient Identification Using a Prime-Feature-Based Technique

DEFF Research Database (Denmark)

Hussain, Dil Muhammad Akbar; Haq, Shaiq A.; Valente, Andrea

2011-01-01

. Fingerprint identification system, implemented on PC/104 based real-time systems, can accurately identify the operator. Traditionally, the uniqueness of a fingerprint is determined by the overall pattern of ridges and valleys as well as the local ridge anomalies e.g., a ridge bifurcation or a ridge ending......, which are called minutiae points. Designing a reliable automatic fingerprint matching algorithm for minimal platform is quite challenging. In real-time systems, efficiency of the matching algorithm is of utmost importance. To achieve this goal, a prime-feature-based indexing algorithm is proposed......Identification of authorized train drivers through biometrics is a growing area of interest in locomotive radio remote control systems. The existing technique of password authentication is not very reliable and potentially unauthorized personnel may also operate the system on behalf of the operator...

Identifying continuous quality improvement publications: what makes an improvement intervention 'CQI'?

Science.gov (United States)

O'Neill, Sean M; Hempel, Susanne; Lim, Yee-Wei; Danz, Marjorie S; Foy, Robbie; Suttorp, Marika J; Shekelle, Paul G; Rubenstein, Lisa V

2011-12-01

The term continuous quality improvement (CQI) is often used to refer to a method for improving care, but no consensus statement exists on the definition of CQI. Evidence reviews are critical for advancing science, and depend on reliable definitions for article selection. As a preliminary step towards improving CQI evidence reviews, this study aimed to use expert panel methods to identify key CQI definitional features and develop and test a screening instrument for reliably identifying articles with the key features. We used a previously published method to identify 106 articles meeting the general definition of a quality improvement intervention (QII) from 9427 electronically identified articles from PubMed. Two raters then applied a six-item CQI screen to the 106 articles. Per cent agreement ranged from 55.7% to 75.5% for the six items, and reviewer-adjusted intra-class correlation ranged from 0.43 to 0.62. 'Feedback of systematically collected data' was the most common feature (64%), followed by being at least 'somewhat' adapted to local conditions (61%), feedback at meetings involving participant leaders (46%), using an iterative development process (40%), being at least 'somewhat' data driven (34%), and using a recognised change method (28%). All six features were present in 14.2% of QII articles. We conclude that CQI features can be extracted from QII articles with reasonable reliability, but only a small proportion of QII articles include all features. Further consensus development is needed to support meaningful use of the term CQI for scientific communication.

Perceived cultural importance and actual self-importance of values in cultural identification.

Science.gov (United States)

Wan, Ching; Chiu, Chi-yue; Tam, Kim-pong; Lee, Sau-lai; Lau, Ivy Yee-man; Peng, Siqing

2007-02-01

Cross-cultural psychologists assume that core cultural values define to a large extent what a culture is. Typically, core values are identified through an actual self-importance approach, in which core values are those that members of the culture as a group strongly endorse. In this article, the authors propose a perceived cultural importance approach to identifying core values, in which core values are values that members of the culture as a group generally believe to be important in the culture. In 5 studies, the authors examine the utility of the perceived cultural importance approach. Results consistently showed that, compared with values of high actual self-importance, values of high perceived cultural importance play a more important role in cultural identification. These findings have important implications for conceptualizing and measuring cultures. ((c) 2007 APA, all rights reserved).

Influenza-associated Encephalitis/Encephalopathy Identified by the Australian Childhood Encephalitis Study 2013-2015.

Science.gov (United States)

Britton, Philip N; Dale, Russell C; Blyth, Christopher C; Macartney, Kristine; Crawford, Nigel W; Marshall, Helen; Clark, Julia E; Elliott, Elizabeth J; Webster, Richard I; Cheng, Allen C; Booy, Robert; Jones, Cheryl A

2017-11-01

Influenza-associated encephalitis/encephalopathy (IAE) is an important cause of acute encephalitis syndrome in children. IAE includes a series of clinicoradiologic syndromes or acute encephalopathy syndromes that have been infrequently reported outside East Asia. We aimed to describe cases of IAE identified by the Australian Childhood Encephalitis study. Children ≤ 14 years of age with suspected encephalitis were prospectively identified in 5 hospitals in Australia. Demographic, clinical, laboratory, imaging, and outcome at discharge data were reviewed by an expert panel and cases were categorized by using predetermined case definitions. We extracted cases associated with laboratory identification of influenza virus for this analysis; among these cases, specific IAE syndromes were identified where clinical and radiologic features were consistent with descriptions in the published literature. We identified 13 cases of IAE during 3 southern hemisphere influenza seasons at 5 tertiary children's hospitals in Australia; 8 children with specific acute encephalopathy syndromes including: acute necrotizing encephalopathy, acute encephalopathy with biphasic seizures and late diffusion restriction, mild encephalopathy with reversible splenial lesion, and hemiconvulsion-hemiplegia syndrome. Use of influenza-specific antiviral therapy and prior influenza vaccination were infrequent. In contrast, death or significant neurologic morbidity occurred in 7 of the 13 children (54%). The conditions comprising IAE are heterogeneous with varied clinical features, magnetic resonance imaging changes, and outcomes. Overall, outcome of IAE is poor emphasizing the need for optimized prevention, early recognition, and empiric management.

Feature and Meta-Models in Clafer: Mixed, Specialized, and Coupled

DEFF Research Database (Denmark)

Bąk, Kacper; Czarnecki, Krzysztof; Wasowski, Andrzej

2011-01-01

constraints (such as mapping feature configurations to component configurations or model templates). Clafer also allows arranging models into multiple specialization and extension layers via constraints and inheritance. We identify four key mechanisms allowing a meta-modeling language to express feature...

Exploring the relationship between fractal features and bacterial essential genes

International Nuclear Information System (INIS)

Yu Yong-Ming; Yang Li-Cai; Zhao Lu-Lu; Liu Zhi-Ping; Zhou Qian

2016-01-01

Essential genes are indispensable for the survival of an organism in optimal conditions. Rapid and accurate identifications of new essential genes are of great theoretical and practical significance. Exploring features with predictive power is fundamental for this. Here, we calculate six fractal features from primary gene and protein sequences and then explore their relationship with gene essentiality by statistical analysis and machine learning-based methods. The models are applied to all the currently available identified genes in 27 bacteria from the database of essential genes (DEG). It is found that the fractal features of essential genes generally differ from those of non-essential genes. The fractal features are used to ascertain the parameters of two machine learning classifiers: Naïve Bayes and Random Forest. The area under the curve (AUC) of both classifiers show that each fractal feature is satisfactorily discriminative between essential genes and non-essential genes individually. And, although significant correlations exist among fractal features, gene essentiality can also be reliably predicted by various combinations of them. Thus, the fractal features analyzed in our study can be used not only to construct a good essentiality classifier alone, but also to be significant contributors for computational tools identifying essential genes. (paper)

Identifying Knowledge and Communication

Directory of Open Access Journals (Sweden)

Eduardo Coutinho Lourenço de Lima

2006-12-01

Full Text Available In this paper, I discuss how the principle of identifying knowledge which Strawson advances in ‘Singular Terms and Predication’ (1961, and in ‘Identifying Reference and Truth-Values’ (1964 turns out to constrain communication. The principle states that a speaker’s use of a referring expression should invoke identifying knowledge on the part of the hearer, if the hearer is to understand what the speaker is saying, and also that, in so referring, speakers are attentive to hearers’ epistemic states. In contrasting it with Russell’s Principle (Evans 1982, as well as with the principle of identifying descriptions (Donnellan 1970, I try to show that the principle of identifying knowledge, ultimately a condition for understanding, makes sense only in a situation of conversation. This allows me to conclude that the cooperative feature of communication (Grice 1975 and reference (Clark andWilkes-Gibbs 1986 holds also at the understanding level. Finally, I discuss where Strawson’s views seem to be unsatisfactory, and suggest how they might be improved.

INTERESTING TASKS, INDEPENDENCE OR IMPORTANCE TO SOCIETY? - THE VOCATIONAL EXPECTATIONS OF GENERATION Y

Directory of Open Access Journals (Sweden)

Kirsten Wüst

2015-12-01

Full Text Available Choosing a profession is complex and often affects many areas of one’s future life. In a representative study we analyzed data of 4,447 German adolescents, aged seventeen, who were interviewed in the years between 2000 and 2013. The aim of the study was to identify the effects of gender, school type, personality and leisure activities on vocational expectations and career-choice stages of generation Y. Especially, it was of interest which effect remained as a generational time effect after controlling for the named variables. For the analysis we used descriptive statistics with rank orders and mean values as well as linear and logistic regression analyses. Engagement in different leisure activities, gender and form of education all greatly affect the perceived importance of profession characteristics. While young women and students from German grammar schools rank “stimulating tasks” first, young men and students from all other school forms feel that a “secure position” is the most important. Also, personality factors influence the perceived importance of vocational features, with agreeable and extravert adolescents rating “contact to others”, “importance to society”, “helping others” and similar features significantly higher. After controlling for the named variables, there remained a significant correlation between the survey year and the term “secure position” which became less important, and the terms “working conditions”, “importance for society” and “helping others” all three of which became more important. A trend towards a higher valuation of one’s individual social responsibility can thus be noticed.

Disruption of visual feature binding in working memory.

Science.gov (United States)

Ueno, Taiji; Allen, Richard J; Baddeley, Alan D; Hitch, Graham J; Saito, Satoru

2011-01-01

In a series of five experiments, we studied the effect of a visual suffix on the retention in short-term visual memory of both individual visual features and objects involving the binding of two features. Experiments 1A, 1B, and 2 involved suffixes consisting of features external to the to-be-remembered set and revealed a modest but equivalent disruption on individual and bound feature conditions. Experiments 3A and 3B involved suffixes comprising features that could potentially have formed part of the to-be-remembered set (but did not on that trial). Both experiments showed greater disruption of retention for objects comprising bound features than for their individual features. The results are interpreted as differentiating two components of suffix interference, one affecting memory for features and bindings equally, the other affecting memory for bindings. The general component is tentatively identified with the attentional cost of operating a filter to prevent the suffix from entering visual working memory, whereas the specific component is attributed to the particular fragility of bound representations when the filter fails.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Directory of Open Access Journals (Sweden)

Ahmed Majid Taha

2013-01-01

Full Text Available When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets.

Naive Bayes-Guided Bat Algorithm for Feature Selection

Science.gov (United States)

Taha, Ahmed Majid; Mustapha, Aida; Chen, Soong-Der

2013-01-01

When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets. PMID:24396295

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,…

Accounts of bullying on Twitter in relation to dentofacial features and orthodontic treatment.

Science.gov (United States)

Chan, A; Antoun, J S; Morgaine, K C; Farella, M

2017-04-01

Social media offers an accessible resource for gaining valuable insights into the social culture of bullying. The purpose of this study was to qualitatively analyse Twitter posts for common themes relating to dentofacial features, braces and bullying. Twitter's database was searched from 2010 to 2014 using keywords relevant to bullying, teeth and orthodontics. Two investigators assessed the Twitter posts, and selected those that conveyed the experiences or opinions of bullying victims. The posts were qualitatively analysed using thematic analysis. Of the 548 posts screened, 321 were included in the final sample. Four primary categories relating to 'dental-related bullying' were identified: (i) morphological features, (ii) psychological and psychosocial impact, (iii) coping mechanisms and (iv) the role of family. Bullied individuals reported a diverse range of psychological impacts and coping mechanisms. Secondary categories were also identified. Family members, for example, were found to play both a contributory and mediatory role in bullying. In summary, social media can provide new and valuable information about the causal factors and social issues associated with oral health-related bullying. Importantly, some coping mechanisms may mitigate the negative effects of bullying. © 2017 John Wiley & Sons Ltd.

Spectral features in the cosmic ray fluxes

Science.gov (United States)

Lipari, Paolo

2018-01-01

The cosmic ray energy distributions contain spectral features, that is narrow energy regions where the slope of the spectrum changes rapidly. The identification and study of these features is of great importance to understand the astrophysical mechanisms of acceleration and propagation that form the spectra. In first approximation a spectral feature is often described as a discontinuous change in slope, however very valuable information is also contained in its width, that is the length of the energy interval where the change in spectral index develops. In this work we discuss the best way to define and parameterize the width a spectral feature, and for illustration discuss some of the most prominent known structures.

Inference for feature selection using the Lasso with high-dimensional data

DEFF Research Database (Denmark)

Brink-Jensen, Kasper; Ekstrøm, Claus Thorn

2014-01-01

Penalized regression models such as the Lasso have proved useful for variable selection in many fields - especially for situations with high-dimensional data where the numbers of predictors far exceeds the number of observations. These methods identify and rank variables of importance but do...... not generally provide any inference of the selected variables. Thus, the variables selected might be the "most important" but need not be significant. We propose a significance test for the selection found by the Lasso. We introduce a procedure that computes inference and p-values for features chosen...... by the Lasso. This method rephrases the null hypothesis and uses a randomization approach which ensures that the error rate is controlled even for small samples. We demonstrate the ability of the algorithm to compute $p$-values of the expected magnitude with simulated data using a multitude of scenarios...

Simulation study and guidelines to generate Laser-induced Surface Acoustic Waves for human skin feature detection

Science.gov (United States)

Li, Tingting; Fu, Xing; Chen, Kun; Dorantes-Gonzalez, Dante J.; Li, Yanning; Wu, Sen; Hu, Xiaotang

2015-12-01

Despite the seriously increasing number of people contracting skin cancer every year, limited attention has been given to the investigation of human skin tissues. To this regard, Laser-induced Surface Acoustic Wave (LSAW) technology, with its accurate, non-invasive and rapid testing characteristics, has recently shown promising results in biological and biomedical tissues. In order to improve the measurement accuracy and efficiency of detecting important features in highly opaque and soft surfaces such as human skin, this paper identifies the most important parameters of a pulse laser source, as well as provides practical guidelines to recommended proper ranges to generate Surface Acoustic Waves (SAWs) for characterization purposes. Considering that melanoma is a serious type of skin cancer, we conducted a finite element simulation-based research on the generation and propagation of surface waves in human skin containing a melanoma-like feature, determine best pulse laser parameter ranges of variation, simulation mesh size and time step, working bandwidth, and minimal size of detectable melanoma.

Identifying Important Career Indicators of Undergraduate Geoscience Students Upon Completion of Their Degree

Science.gov (United States)

Wilson, C. E.; Keane, C. M.; Houlton, H. R.

2012-12-01

The American Geosciences Institute (AGI) decided to create the National Geoscience Student Exit Survey in order to identify the initial pathways into the workforce for these graduating students, as well as assess their preparedness for entering the workforce upon graduation. The creation of this survey stemmed from a combination of experiences with the AGI/AGU Survey of Doctorates and discussions at the following Science Education Research Center (SERC) workshops: "Developing Pathways to Strong Programs for the Future", "Strengthening Your Geoscience Program", and "Assessing Geoscience Programs". These events identified distinct gaps in understanding the experiences and perspectives of geoscience students during one of their most profound professional transitions. Therefore, the idea for the survey arose as a way to evaluate how the discipline is preparing and educating students, as well as identifying the students' desired career paths. The discussions at the workshops solidified the need for this survey and created the initial framework for the first pilot of the survey. The purpose of this assessment tool is to evaluate student preparedness for entering the geosciences workforce; identify student decision points for entering geosciences fields and remaining in the geosciences workforce; identify geosciences fields that students pursue in undergraduate and graduate school; collect information on students' expected career trajectories and geosciences professions; identify geosciences career sectors that are hiring new graduates; collect information about salary projections; overall effectiveness of geosciences departments regionally and nationally; demonstrate the value of geosciences degrees to future students, the institutions, and employers; and establish a benchmark to perform longitudinal studies of geosciences graduates to understand their career pathways and impacts of their educational experiences on these decisions. AGI's Student Exit Survey went through

Visual Search for Feature and Conjunction Targets with an Attention Deficit

OpenAIRE

Arguin, Martin; Joanette, Yves; Cavanagh, Patrick

1993-01-01

Brain-damaged subjects who had previously been identified as suffering from a visual attention deficit for contralesional stimulation were tested on a series of visual search tasks. The experiments examined the hypothesis that the processing of single features is preattentive but that feature integration, necessary for the correct perception of conjunctions of features, requires attention (Treisman & Gelade, 1980 Treisman & Sato, 1990). Subjects searched for a feature target (orientation or c...

Including product features in process redesign

DEFF Research Database (Denmark)

Hvam, Lars; Hauksdóttir, Dagný; Mortensen, Niels Henrik

2017-01-01

do not take into account how the product features are applied throughout the process, which makes it difficult to obtain a comprehensive understanding of the activities in the processes and to generate significant improvements. The suggested approach models the product family using the so......This article suggests a visual modelling method for integrating models of product features with business process models for redesigning the business processes involving specifications of customer-tailored products and services. The current methods for redesigning these types of business processes......-called product variant master and the business process modelling notation for modelling the process flow. The product model is combined with the process map by identifying features used in each step of the process flow. Additionally, based on the information absorbed from the integrated model, the value stream...

Experimental assessment of the importance of amino acid positions identified by an entropy-based correlation analysis of multiple-sequence alignments.

Science.gov (United States)

Dietrich, Susanne; Borst, Nadine; Schlee, Sandra; Schneider, Daniel; Janda, Jan-Oliver; Sterner, Reinhard; Merkl, Rainer

2012-07-17

The analysis of a multiple-sequence alignment (MSA) with correlation methods identifies pairs of residue positions whose occupation with amino acids changes in a concerted manner. It is plausible to assume that positions that are part of many such correlation pairs are important for protein function or stability. We have used the algorithm H2r to identify positions k in the MSAs of the enzymes anthranilate phosphoribosyl transferase (AnPRT) and indole-3-glycerol phosphate synthase (IGPS) that show a high conn(k) value, i.e., a large number of significant correlations in which k is involved. The importance of the identified residues was experimentally validated by performing mutagenesis studies with sAnPRT and sIGPS from the archaeon Sulfolobus solfataricus. For sAnPRT, five H2r mutant proteins were generated by replacing nonconserved residues with alanine or the prevalent residue of the MSA. As a control, five residues with conn(k) values of zero were chosen randomly and replaced with alanine. The catalytic activities and conformational stabilities of the H2r and control mutant proteins were analyzed by steady-state enzyme kinetics and thermal unfolding studies. Compared to wild-type sAnPRT, the catalytic efficiencies (k(cat)/K(M)) were largely unaltered. In contrast, the apparent thermal unfolding temperature (T(M)(app)) was lowered in most proteins. Remarkably, the strongest observed destabilization (ΔT(M)(app) = 14 °C) was caused by the V284A exchange, which pertains to the position with the highest correlation signal [conn(k) = 11]. For sIGPS, six H2r mutant and four control proteins with alanine exchanges were generated and characterized. The k(cat)/K(M) values of four H2r mutant proteins were reduced between 13- and 120-fold, and their T(M)(app) values were decreased by up to 5 °C. For the sIGPS control proteins, the observed activity and stability decreases were much less severe. Our findings demonstrate that positions with high conn(k) values have an

Clinical features of SMARCA2 duplication overlap with Coffin-Siris syndrome.

Science.gov (United States)

Miyake, Noriko; Abdel-Salam, Ghada; Yamagata, Takanori; Eid, Maha M; Osaka, Hitoshi; Okamoto, Nobuhiko; Mohamed, Amal M; Ikeda, Takahiro; Afifi, Hanan H; Piard, Juliette; van Maldergem, Lionel; Mizuguchi, Takeshi; Miyatake, Satoko; Tsurusaki, Yoshinori; Matsumoto, Naomichi

2016-10-01

Coffin-Siris syndrome is a rare congenital malformation and intellectual disability syndrome. Mutations in at least seven genes have been identified. Here, we performed copy number analysis in 37 patients with features of CSS in whom no causative mutations were identified by exome sequencing. We identified a patient with a 9p24.3-p22.2 duplication and another patient with the chromosome der(6)t(6;9)(p25;p21)mat. Both patients share a duplicated 15.8-Mb region containing 46 protein coding genes, including SMARCA2. Dominant negative effects of SMARCA2 mutations may contribute to Nicolaides-Baraitser syndrome. We conclude that their features better resemble Coffin-Siris syndrome, rather than Nicolaides-Baraitser syndrome and that these features likely arise from SMARCA2 over-dosage. Pure 9p duplications (not caused by unbalanced translocations) are rare. Copy number analysis in patients with features that overlap with Coffin-Siris syndrome is recommended to further determine their genetic aspects. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Salient features in 3-D haptic shape perception

NARCIS (Netherlands)

Plaisier, Myrthe A; Bergmann Tiest, Wouter M.; Kappers, Astrid M L

2009-01-01

Shape is an important cue for recognizing an object by touch. Several features, such as edges, curvature, surface area, and aspect ratio, are associated with 3-D shape. To investigate the saliency of 3-D shape features, we developed a haptic search task. The target and distractor items consisted of

Biometric features and privacy : condemned, based upon your finger print

NARCIS (Netherlands)

Bullee, Jan-Willem; Veldhuis, Raymond N.J.

What information is available in biometric features besides that needed for the biometric recognition process? What if a biometric feature contains Personally Identifiable Information? Will the whole biometric system become a threat to privacy? This paper is an attempt to quantifiy the link between

Features Selection for Skin Micro-Image Symptomatic Recognition

Institute of Scientific and Technical Information of China (English)

HUYue-li; CAOJia-lin; ZHAOQian; FENGXu

2004-01-01

Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92% using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

Features Selection for Skin Micro-Image Symptomatic Recognition

Institute of Scientific and Technical Information of China (English)

HU Yue-li; CAO Jia-lin; ZHAO Qian; FENG Xu

2004-01-01

Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92 % using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

A landscape ecology approach identifies important drivers of urban biodiversity.

Science.gov (United States)

Turrini, Tabea; Knop, Eva

2015-04-01

Cities are growing rapidly worldwide, yet a mechanistic understanding of the impact of urbanization on biodiversity is lacking. We assessed the impact of urbanization on arthropod diversity (species richness and evenness) and abundance in a study of six cities and nearby intensively managed agricultural areas. Within the urban ecosystem, we disentangled the relative importance of two key landscape factors affecting biodiversity, namely the amount of vegetated area and patch isolation. To do so, we a priori selected sites that independently varied in the amount of vegetated area in the surrounding landscape at the 500-m scale and patch isolation at the 100-m scale, and we hold local patch characteristics constant. As indicator groups, we used bugs, beetles, leafhoppers, and spiders. Compared to intensively managed agricultural ecosystems, urban ecosystems supported a higher abundance of most indicator groups, a higher number of bug species, and a lower evenness of bug and beetle species. Within cities, a high amount of vegetated area increased species richness and abundance of most arthropod groups, whereas evenness showed no clear pattern. Patch isolation played only a limited role in urban ecosystems, which contrasts findings from agro-ecological studies. Our results show that urban areas can harbor a similar arthropod diversity and abundance compared to intensively managed agricultural ecosystems. Further, negative consequences of urbanization on arthropod diversity can be mitigated by providing sufficient vegetated space in the urban area, while patch connectivity is less important in an urban context. This highlights the need for applying a landscape ecological approach to understand the mechanisms shaping urban biodiversity and underlines the potential of appropriate urban planning for mitigating biodiversity loss. © 2015 John Wiley & Sons Ltd.

Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

Science.gov (United States)

Al-Rajab, Murad; Lu, Joan; Xu, Qiang

2017-07-01

This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process. In this research, a three-phase approach was proposed and implemented: Phases One and Two examined the feature selection algorithms and classification algorithms employed separately, and Phase Three examined the performance of the combination of these. It was found from Phase One that the Particle Swarm Optimization (PSO) algorithm performed best with the colon dataset as a feature selection (29 genes selected) and from Phase Two that the Support Vector Machine (SVM) algorithm outperformed other classifications, with an accuracy of almost 86%. It was also found from Phase Three that the combined use of PSO and SVM surpassed other algorithms in accuracy and performance, and was faster in terms of time analysis (94%). It is concluded that applying feature selection algorithms prior to classification algorithms results in better accuracy than when the latter are applied alone. This conclusion is important and significant to industry and society. Copyright © 2017 Elsevier B.V. All rights reserved.

Why replication is important in landscape genetics: American black bear in the Rocky Mountains

Science.gov (United States)

Short, Bull R.A.; Cushman, S.A.; MacE, R.; Chilton, T.; Kendall, K.C.; Landguth, E.L.; Schwartz, Maurice L.; McKelvey, K.; Allendorf, F.W.; Luikart, G.

2011-01-01

We investigated how landscape features influence gene flow of black bears by testing the relative support for 36 alternative landscape resistance hypotheses, including isolation by distance (IBD) in each of 12 study areas in the north central U.S. Rocky Mountains. The study areas all contained the same basic elements, but differed in extent of forest fragmentation, altitude, variation in elevation and road coverage. In all but one of the study areas, isolation by landscape resistance was more supported than IBD suggesting gene flow is likely influenced by elevation, forest cover, and roads. However, the landscape features influencing gene flow varied among study areas. Using subsets of loci usually gave models with the very similar landscape features influencing gene flow as with all loci, suggesting the landscape features influencing gene flow were correctly identified. To test if the cause of the variability of supported landscape features in study areas resulted from landscape differences among study areas, we conducted a limiting factor analysis. We found that features were supported in landscape models only when the features were highly variable. This is perhaps not surprising but suggests an important cautionary note – that if landscape features are not found to influence gene flow, researchers should not automatically conclude that the features are unimportant to the species’ movement and gene flow. Failure to investigate multiple study areas that have a range of variability in landscape features could cause misleading inferences about which landscape features generally limit gene flow. This could lead to potentially erroneous identification of corridors and barriers if models are transferred between areas with different landscape characteristics.

Obscene Video Recognition Using Fuzzy SVM and New Sets of Features

Directory of Open Access Journals (Sweden)

Alireza Behrad

2013-02-01

Full Text Available In this paper, a novel approach for identifying normal and obscene videos is proposed. In order to classify different episodes of a video independently and discard the need to process all frames, first, key frames are extracted and skin regions are detected for groups of video frames starting with key frames. In the second step, three different features including 1- structural features based on single frame information, 2- features based on spatiotemporal volume and 3-motion-based features, are extracted for each episode of video. The PCA-LDA method is then applied to reduce the size of structural features and select more distinctive features. For the final step, we use fuzzy or a Weighted Support Vector Machine (WSVM classifier to identify video episodes. We also employ a multilayer Kohonen network as an initial clustering algorithm to increase the ability to discriminate between the extracted features into two classes of videos. Features based on motion and periodicity characteristics increase the efficiency of the proposed algorithm in videos with bad illumination and skin colour variation. The proposed method is evaluated using 1100 videos in different environmental and illumination conditions. The experimental results show a correct recognition rate of 94.2% for the proposed algorithm.

Text feature extraction based on deep learning: a review.

Science.gov (United States)

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

2017-01-01

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

MRI features of tuberculosis of peripheral joints

Energy Technology Data Exchange (ETDEWEB)

Sawlani, V.; Chandra, T.; Mishra, R.N.; Aggarwal, A.; Jain, U.K.; Gujral, R.B. E-mail: gujralrb@sgpgi.ac.in

2003-10-01

The aim of this article is to present the magnetic resonance imaging (MRI) features of peripheral tubercular arthritis. The clinical presentation of peripheral tubercular arthritis is variable and simulates other chronic inflammatory arthritic disorders. MRI is a highly sensitive technique which demonstrates fine anatomical details and identifies the early changes of arthritis, which are not visible on radiographs. The MRI features of tubercular arthritis include synovitis, effusion, central and peripheral erosions, active and chronic pannus, abscess, bone chips and hypo-intense synovium. These imaging features in an appropriate clinical setting may help in the diagnosis of tubercular arthritis. Early diagnosis and treatment can effectively eliminate the long-term morbidity of joints affected by tuberculosis.

MRI features of tuberculosis of peripheral joints

International Nuclear Information System (INIS)

Sawlani, V.; Chandra, T.; Mishra, R.N.; Aggarwal, A.; Jain, U.K.; Gujral, R.B.

2003-01-01

The aim of this article is to present the magnetic resonance imaging (MRI) features of peripheral tubercular arthritis. The clinical presentation of peripheral tubercular arthritis is variable and simulates other chronic inflammatory arthritic disorders. MRI is a highly sensitive technique which demonstrates fine anatomical details and identifies the early changes of arthritis, which are not visible on radiographs. The MRI features of tubercular arthritis include synovitis, effusion, central and peripheral erosions, active and chronic pannus, abscess, bone chips and hypo-intense synovium. These imaging features in an appropriate clinical setting may help in the diagnosis of tubercular arthritis. Early diagnosis and treatment can effectively eliminate the long-term morbidity of joints affected by tuberculosis

Feature selection for high-dimensional integrated data

KAUST Repository

Zheng, Charles

2012-04-26

Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.

Feature selection for high-dimensional integrated data

KAUST Repository

Zheng, Charles; Schwartz, Scott; Chapkin, Robert S.; Carroll, Raymond J.; Ivanov, Ivan

2012-01-01

Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.

Human listeners provide insights into echo features used by dolphins (Tursiops truncatus) to discriminate among objects.

Science.gov (United States)

Delong, Caroline M; Au, Whitlow W L; Harley, Heidi E; Roitblat, Herbert L; Pytka, Lisa

2007-08-01

Echolocating bottlenose dolphins (Tursiops truncatus) discriminate between objects on the basis of the echoes reflected by the objects. However, it is not clear which echo features are important for object discrimination. To gain insight into the salient features, the authors had a dolphin perform a match-to-sample task and then presented human listeners with echoes from the same objects used in the dolphin's task. In 2 experiments, human listeners performed as well or better than the dolphin at discriminating objects, and they reported the salient acoustic cues. The error patterns of the humans and the dolphin were compared to determine which acoustic features were likely to have been used by the dolphin. The results indicate that the dolphin did not appear to use overall echo amplitude, but that it attended to the pattern of changes in the echoes across different object orientations. Human listeners can quickly identify salient combinations of echo features that permit object discrimination, which can be used to generate hypotheses that can be tested using dolphins as subjects.

MRI features can predict EGFR expression in lower grade gliomas. A voxel-based radiomic analysis

Energy Technology Data Exchange (ETDEWEB)

Li, Yiming; Liu, Xing; Qian, Zenghui; Fan, Xing; Li, Shaowu; Jiang, Tao [Capital Medical University, Beijing Neurosurgical Institute, Beijing (China); Xu, Kaibin [Chinese Academy of Sciences, Institute of Automation, Beijing (China); Wang, Kai [Beijing Tiantan Hospital, Department of Neuroradiology, Beijing (China); Wang, Yinyan [Beijing Tiantan Hospital, Department of Neuroradiology, Beijing (China); Beijing Tiantan Hospital, Capital Medical University, Department of Neurosurgery, Beijing (China)

2018-01-15

To identify the magnetic resonance imaging (MRI) features associated with epidermal growth factor (EGFR) expression level in lower grade gliomas using radiomic analysis. 270 lower grade glioma patients with known EGFR expression status were randomly assigned into training (n=200) and validation (n=70) sets, and were subjected to feature extraction. Using a logistic regression model, a signature of MRI features was identified to be predictive of the EGFR expression level in lower grade gliomas in the training set, and the accuracy of prediction was assessed in the validation set. A signature of 41 MRI features achieved accuracies of 82.5% (area under the curve [AUC] = 0.90) in the training set and 90.0% (AUC = 0.95) in the validation set. This radiomic signature consisted of 25 first-order statistics or related wavelet features (including range, standard deviation, uniformity, variance), one shape and size-based feature (spherical disproportion), and 15 textural features or related wavelet features (including sum variance, sum entropy, run percentage). A radiomic signature allowing for the prediction of the EGFR expression level in patients with lower grade glioma was identified, suggesting that using tumour-derived radiological features for predicting genomic information is feasible. (orig.)

Acoustic Features Influence Musical Choices Across Multiple Genres.

Science.gov (United States)

Barone, Michael D; Bansal, Jotthi; Woolhouse, Matthew H

2017-01-01

Based on a large behavioral dataset of music downloads, two analyses investigate whether the acoustic features of listeners' preferred musical genres influence their choice of tracks within non-preferred, secondary musical styles. Analysis 1 identifies feature distributions for pairs of genre-defined subgroups that are distinct. Using correlation analysis, these distributions are used to test the degree of similarity between subgroups' main genres and the other music within their download collections. Analysis 2 explores the issue of main-to-secondary genre influence through the production of 10 feature-influence matrices, one per acoustic feature, in which cell values indicate the percentage change in features for genres and subgroups compared to overall population averages. In total, 10 acoustic features and 10 genre-defined subgroups are explored within the two analyses. Results strongly indicate that the acoustic features of people's main genres influence the tracks they download within non-preferred, secondary musical styles. The nature of this influence and its possible actuating mechanisms are discussed with respect to research on musical preference, personality, and statistical learning.

Characteristic Features and Contributory Factors in Fatal Ciguatera Fish Poisoning—Implications for Prevention and Public Education

Science.gov (United States)

Chan, Thomas Y. K.

2016-01-01

In this review, the main objective was to describe the characteristic features of fatal ciguatera fish poisoning and identify contributory factors, with a view to promote prevention and public education. Ciguatera-related deaths, although rare, have been reported from the Pacific, Caribbean, and Indian Ocean regions. The clinical features were generally dominated by convulsions and coma, with various focal neurological signs. Several contributory factors could be identified, including consumption of ciguatoxin (CTX)-rich fish parts (viscera and head) in larger amounts, the most ciguatoxic fish species (e.g., Gymnothorax flavimarginatus) and reef fish collected after storms and individuals' susceptibility. Mass ciguatera fish poisoning with mortalities also occurred when G. flavimarginatus and other ciguatoxic fish species were shared in gatherings and parties. The characteristic features of fatal ciguatera fish poisoning must be recognized early. The public should be repeatedly reminded to avoid eating the most ciguatoxic fish species and the CTX-rich parts of reef fish. To prevent mass poisoning in gatherings and parties, the most ciguatoxic fish species and potentially toxic fish species must be avoided. Particularly after hits by disastrous storms, it is important to monitor the toxicity of reef fish and the incidence rates of ciguatera. PMID:26787145

Characteristic Features and Contributory Factors in Fatal Ciguatera Fish Poisoning--Implications for Prevention and Public Education.

Science.gov (United States)

Chan, Thomas Y K

2016-04-01

In this review, the main objective was to describe the characteristic features of fatal ciguatera fish poisoning and identify contributory factors, with a view to promote prevention and public education. Ciguatera-related deaths, although rare, have been reported from the Pacific, Caribbean, and Indian Ocean regions. The clinical features were generally dominated by convulsions and coma, with various focal neurological signs. Several contributory factors could be identified, including consumption of ciguatoxin (CTX)-rich fish parts (viscera and head) in larger amounts, the most ciguatoxic fish species (e.g.,Gymnothorax flavimarginatus) and reef fish collected after storms and individuals' susceptibility. Mass ciguatera fish poisoning with mortalities also occurred when G. flavimarginatus and other ciguatoxic fish species were shared in gatherings and parties. The characteristic features of fatal ciguatera fish poisoning must be recognized early. The public should be repeatedly reminded to avoid eating the most ciguatoxic fish species and the CTX-rich parts of reef fish. To prevent mass poisoning in gatherings and parties, the most ciguatoxic fish species and potentially toxic fish species must be avoided. Particularly after hits by disastrous storms, it is important to monitor the toxicity of reef fish and the incidence rates of ciguatera. © The American Society of Tropical Medicine and Hygiene.

The PRC2-binding long non-coding RNAs in human and mouse genomes are associated with predictive sequence features

Science.gov (United States)

Tu, Shiqi; Yuan, Guo-Cheng; Shao, Zhen

2017-01-01

Recently, long non-coding RNAs (lncRNAs) have emerged as an important class of molecules involved in many cellular processes. One of their primary functions is to shape epigenetic landscape through interactions with chromatin modifying proteins. However, mechanisms contributing to the specificity of such interactions remain poorly understood. Here we took the human and mouse lncRNAs that were experimentally determined to have physical interactions with Polycomb repressive complex 2 (PRC2), and systematically investigated the sequence features of these lncRNAs by developing a new computational pipeline for sequences composition analysis, in which each sequence is considered as a series of transitions between adjacent nucleotides. Through that, PRC2-binding lncRNAs were found to be associated with a set of distinctive and evolutionarily conserved sequence features, which can be utilized to distinguish them from the others with considerable accuracy. We further identified fragments of PRC2-binding lncRNAs that are enriched with these sequence features, and found they show strong PRC2-binding signals and are more highly conserved across species than the other parts, implying their functional importance.

Feature extraction for classification in the data mining process

NARCIS (Netherlands)

Pechenizkiy, M.; Puuronen, S.; Tsymbal, A.

2003-01-01

Dimensionality reduction is a very important step in the data mining process. In this paper, we consider feature extraction for classification tasks as a technique to overcome problems occurring because of "the curse of dimensionality". Three different eigenvector-based feature extraction approaches

A national-scale model of linear features improves predictions of farmland biodiversity.

Science.gov (United States)

Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H

2017-12-01

Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.

A Comprehensive Study of Features and Algorithms for URL-Based Topic Classification

CERN Document Server

Weber, I; Henzinger, M; Baykan, E

2011-01-01

Given only the URL of a Web page, can we identify its topic? We study this problem in detail by exploring a large number of different feature sets and algorithms on several datasets. We also show that the inherent overlap between topics and the sparsity of the information in URLs makes this a very challenging problem. Web page classification without a page's content is desirable when the content is not available at all, when a classification is needed before obtaining the content, or when classification speed is of utmost importance. For our experiments we used five different corpora comprising a total of about 3 million (URL, classification) pairs. We evaluated several techniques for feature generation and classification algorithms. The individual binary classifiers were then combined via boosting into metabinary classifiers. We achieve typical F-measure values between 80 and 85, and a typical precision of around 86. The precision can be pushed further over 90 while maintaining a typical level of recall betw...

The imaging features of neurologic complications of left atrial myxomas

Energy Technology Data Exchange (ETDEWEB)

Liao, Wei-Hua; Ramkalawan, Divya; Liu, Jian-Ling; Shi, Wei [Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan (China); Zee, Chi-Shing [Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033 (United States); Yang, Xiao-Su; Li, Guo-Liang; Li, Jing [Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, Hunan (China); Wang, Xiao-Yi, E-mail: cjr.wangxiaoyi@vip.163.com [Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan (China)

2015-05-15

Background: Neurologic complications may be the first symptoms of atrial myxomas. Understanding the imaging features of neurologic complications of atrial myxomas can be helpful for the prompt diagnosis. Objective: To identify neuroimaging features for patients with neurologic complications attributed to atrial myxoma. Methods: We retrospectively reviewed the medical records of 103 patients with pathologically confirmed atrial myxoma at Xiangya Hospital from January 2009 to January 2014. The neuroimaging data for patients with neurologic complications were analyzed. Results: Eight patients with atrial myxomas (7.77%) presented with neurologic manifestations, which constituted the initial symptoms for seven patients (87.5%). Neuroimaging showed five cases of cerebral infarctions and three cases of aneurysms. The main patterns of the infarctions were multiplicity (100.0%) and involvement of the middle cerebral artery territory (80.0%). The aneurysms were fusiform in shape, multiple in number (100.0%) and located in the distal middle cerebral artery (100.0%). More specifically, high-density in the vicinity of the aneurysms was observed on CT for two patients (66.7%), and homogenous enhancement surrounding the aneurysms was detected in the enhanced imaging for two patients (66.7%). Conclusion: Neurologic complications secondary to atrial myxoma consist of cerebral infarctions and aneurysms, which show certain characteristic features in neuroimaging. Echocardiography should be performed in patients with multiple cerebral infarctions, and multiple aneurysms, especially when aneurysms are distal in location. More importantly, greater attention should be paid to the imaging changes surrounding the aneurysms when myxomatous aneurysms are suspected and these are going to be the relevant features in our article.

The imaging features of neurologic complications of left atrial myxomas

International Nuclear Information System (INIS)

Liao, Wei-Hua; Ramkalawan, Divya; Liu, Jian-Ling; Shi, Wei; Zee, Chi-Shing; Yang, Xiao-Su; Li, Guo-Liang; Li, Jing; Wang, Xiao-Yi

2015-01-01

Background: Neurologic complications may be the first symptoms of atrial myxomas. Understanding the imaging features of neurologic complications of atrial myxomas can be helpful for the prompt diagnosis. Objective: To identify neuroimaging features for patients with neurologic complications attributed to atrial myxoma. Methods: We retrospectively reviewed the medical records of 103 patients with pathologically confirmed atrial myxoma at Xiangya Hospital from January 2009 to January 2014. The neuroimaging data for patients with neurologic complications were analyzed. Results: Eight patients with atrial myxomas (7.77%) presented with neurologic manifestations, which constituted the initial symptoms for seven patients (87.5%). Neuroimaging showed five cases of cerebral infarctions and three cases of aneurysms. The main patterns of the infarctions were multiplicity (100.0%) and involvement of the middle cerebral artery territory (80.0%). The aneurysms were fusiform in shape, multiple in number (100.0%) and located in the distal middle cerebral artery (100.0%). More specifically, high-density in the vicinity of the aneurysms was observed on CT for two patients (66.7%), and homogenous enhancement surrounding the aneurysms was detected in the enhanced imaging for two patients (66.7%). Conclusion: Neurologic complications secondary to atrial myxoma consist of cerebral infarctions and aneurysms, which show certain characteristic features in neuroimaging. Echocardiography should be performed in patients with multiple cerebral infarctions, and multiple aneurysms, especially when aneurysms are distal in location. More importantly, greater attention should be paid to the imaging changes surrounding the aneurysms when myxomatous aneurysms are suspected and these are going to be the relevant features in our article

Identifying continuous quality improvement publications: what makes an improvement intervention ‘CQI’?

Science.gov (United States)

Hempel, Susanne; Lim, Yee-Wei; Danz, Marjorie S; Foy, Robbie; Suttorp, Marika J; Shekelle, Paul G; Rubenstein, Lisa V

2011-01-01

Background The term continuous quality improvement (CQI) is often used to refer to a method for improving care, but no consensus statement exists on the definition of CQI. Evidence reviews are critical for advancing science, and depend on reliable definitions for article selection. Methods As a preliminary step towards improving CQI evidence reviews, this study aimed to use expert panel methods to identify key CQI definitional features and develop and test a screening instrument for reliably identifying articles with the key features. We used a previously published method to identify 106 articles meeting the general definition of a quality improvement intervention (QII) from 9427 electronically identified articles from PubMed. Two raters then applied a six-item CQI screen to the 106 articles. Results Per cent agreement ranged from 55.7% to 75.5% for the six items, and reviewer-adjusted intra-class correlation ranged from 0.43 to 0.62. ‘Feedback of systematically collected data’ was the most common feature (64%), followed by being at least ‘somewhat’ adapted to local conditions (61%), feedback at meetings involving participant leaders (46%), using an iterative development process (40%), being at least ‘somewhat’ data driven (34%), and using a recognised change method (28%). All six features were present in 14.2% of QII articles. Conclusions We conclude that CQI features can be extracted from QII articles with reasonable reliability, but only a small proportion of QII articles include all features. Further consensus development is needed to support meaningful use of the term CQI for scientific communication. PMID:21727199

Controlled searching in reversibly de-identified medical imaging archives.

Science.gov (United States)

Silva, Jorge Miguel; Pinho, Eduardo; Monteiro, Eriksson; Silva, João Figueira; Costa, Carlos

2018-01-01

Nowadays, digital medical imaging in healthcare has become a fundamental tool for medical diagnosis. This growth has been accompanied by the development of technologies and standards, such as the DICOM standard and PACS. This environment led to the creation of collaborative projects where there is a need to share medical data between different institutions for research and educational purposes. In this context, it is necessary to maintain patient data privacy and provide an easy and secure mechanism for authorized personnel access. This paper presents a solution that fully de-identifies standard medical imaging objects, including metadata and pixel data, providing at the same time a reversible de-identifier mechanism that retains search capabilities from the original data. The last feature is important in some scenarios, for instance, in collaborative platforms where data is anonymized when shared with the community but searchable for data custodians or authorized entities. The solution was integrated into an open source PACS archive and validated in a multidisciplinary collaborative scenario. Copyright © 2017 Elsevier Inc. All rights reserved.

Features Related to Faunal Activity

NARCIS (Netherlands)

Kooistra, M.J.; Pulleman, M.M.

2010-01-01

Soil fauna plays an important role in transporting and altering various soil components, in particular the decomposition of organic matter and the development of soil structure. Fauna-induced features are found in all types of soils and can be so abundant that they determine the nature and intensity

Detection of Seed Methods for Quantification of Feature Confinement

DEFF Research Database (Denmark)

Olszak, Andrzej; Bouwers, Eric; Jørgensen, Bo Nørregaard

2012-01-01

The way features are implemented in source code has a significant influence on multiple quality aspects of a software system. Hence, it is important to regularly evaluate the quality of feature confinement. Unfortunately, existing approaches to such measurement rely on expert judgement for tracin...

Shared genetic variance between the features of the metabolic syndrome: Heritability studies

NARCIS (Netherlands)

Povel, C.M.; Boer, J.M.A.; Feskens, E.J.M.

2011-01-01

Heritability estimates of MetS range from approximately 10%–30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation

Visual feature extraction and establishment of visual tags in the intelligent visual internet of things

Science.gov (United States)

Zhao, Yiqun; Wang, Zhihui

2015-12-01

The Internet of things (IOT) is a kind of intelligent networks which can be used to locate, track, identify and supervise people and objects. One of important core technologies of intelligent visual internet of things ( IVIOT) is the intelligent visual tag system. In this paper, a research is done into visual feature extraction and establishment of visual tags of the human face based on ORL face database. Firstly, we use the principal component analysis (PCA) algorithm for face feature extraction, then adopt the support vector machine (SVM) for classifying and face recognition, finally establish a visual tag for face which is already classified. We conducted a experiment focused on a group of people face images, the result show that the proposed algorithm have good performance, and can show the visual tag of objects conveniently.

Microbiological Features of KPC-Producing Enterobacter Isolates Identified in a U.S. Hospital System

Science.gov (United States)

Ahn, Chulsoo; Syed, Alveena; Hu, Fupin; O’Hara, Jessica A.; Rivera, Jesabel I.; Doi, Yohei

2014-01-01

Microbiological data regarding KPC-producing Enterobacter spp. are scarce. In this study, 11 unique KPC-producing Enterobacter isolates were identified among 44 ertapenem-non-susceptible Enterobacter isolates collected between 2009 and 2013 at a hospital system in Western Pennsylvania. All cases were healthcare-associated and occurred in medically complex patients. While pulsed-field gel electrophoresis (PFGE) showed diverse restriction patterns overall, multilocus sequence typing (MLST) identified Enterobacter cloacae isolates with sequence types (STs) 93 and 171 from two hospitals each. The levels of carbapenem minimum inhibitory concentrations were highly variable. All isolates remained susceptible to colistin, tigecycline, and the majority to amikacin and doxycycline. A blaKPC-carrying IncN plasmid conferring trimethoprim-sulfamethoxazole resistance was identified in three of the isolates. Spread of blaKPC in Enterobacter spp. appears to be due to a combination of plasmid-mediated and clonal processes. PMID:25053203

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

Science.gov (United States)

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

2012-09-01

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

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.

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.

How important is importance for prospective memory? A review

Directory of Open Access Journals (Sweden)

Stefan eWalter

2014-06-01

Full Text Available Forgetting to carry out an intention as planned can have serious consequences in everyday life. People sometimes even forget intentions that they consider as very important. Here, we review the literature on the impact of importance on prospective memory performance. We highlight different methods used to manipulate the importance of a prospective memory task such as providing rewards, importance relative to other ongoing activities, absolute importance, and providing social motives. Moreover, we address the relationship between importance and other factors known to affect prospective memory and ongoing task performance such as type of prospective memory task (time-, event- or activity-based, cognitive loads, and cue focality. Finally, we provide a connection to motivation, we summarize the effects of task importance and we identify important venues for future research.

How important is importance for prospective memory? A review

Science.gov (United States)

Walter, Stefan; Meier, Beat

2014-01-01

Forgetting to carry out an intention as planned can have serious consequences in everyday life. People sometimes even forget intentions that they consider as very important. Here, we review the literature on the impact of importance on prospective memory performance. We highlight different methods used to manipulate the importance of a prospective memory task such as providing rewards, importance relative to other ongoing activities, absolute importance, and providing social motives. Moreover, we address the relationship between importance and other factors known to affect prospective memory and ongoing task performance such as type of prospective memory task (time-, event-, or activity-based), cognitive loads, and processing overlaps. Finally, we provide a connection to motivation, we summarize the effects of task importance and we identify important venues for future research. PMID:25018743

Determination of morphological features and molecular interactions ...

African Journals Online (AJOL)

This research focused on identifying the morphological features and molecular interactions of the Nigerian Bentonitic clays using Scanning Electron Microscope (SEM) characterisation technique. The SEM microstructure images indicated that the bentonite samples are generally moderately dispersive to dispersive with ...

Connecting infrared spectra with plant traits to identify species

Science.gov (United States)

Buitrago, Maria F.; Skidmore, Andrew K.; Groen, Thomas A.; Hecker, Christoph A.

2018-05-01

Plant traits are used to define species, but also to evaluate the health status of forests, plantations and crops. Conventional methods of measuring plant traits (e.g. wet chemistry), although accurate, are inefficient and costly when applied over large areas or with intensive sampling. Spectroscopic methods, as used in the food industry and mineralogy, are nowadays applied to identify plant traits, however, most studies analysed visible to near infrared, while infrared spectra of longer wavelengths have been little used for identifying the spectral differences between plant species. This study measured the infrared spectra (1.4-16.0 μm) on individual, fresh leaves of 19 species (from herbaceous to woody species), as well as 14 leaf traits for each leaf. The results describe at which wavelengths in the infrared the leaves' spectra can differentiate most effectively between these plant species. A Quadratic Discrimination Analysis (QDA) shows that using five bands in the SWIR or the LWIR is enough to accurately differentiate these species (Kappa: 0.93, 0.94 respectively), while the MWIR has a lower classification accuracy (Kappa: 0.84). This study also shows that in the infrared spectra of fresh leaves, the identified species-specific features are correlated with leaf traits as well as changes in their values. Spectral features in the SWIR (1.66, 1.89 and 2.00 μm) are common to all species and match the main features of pure cellulose and lignin spectra. The depth of these features varies with changes of cellulose and leaf water content and can be used to differentiate species in this region. In the MWIR and LWIR, the absorption spectra of leaves are formed by key species-specific traits including lignin, cellulose, water, nitrogen and leaf thickness. The connection found in this study between leaf traits, features and spectral signatures are novel tools to assist when identifying plant species by spectroscopy and remote sensing.

SHBG is an important factor in stemness induction of cells by DHT in vitro and associated with poor clinical features of prostate carcinomas.

Science.gov (United States)

Ma, Yuanyuan; Liang, Dongming; Liu, Jian; Wen, Jian-Guo; Servoll, Einar; Waaler, Gudmund; Sæter, Thorstein; Axcrona, Karol; Vlatkovic, Ljiljana; Axcrona, Ulrika; Paus, Elisabeth; Yang, Yue; Zhang, Zhiqian; Kvalheim, Gunnar; Nesland, Jahn M; Suo, Zhenhe

2013-01-01

Androgen plays a vital role in prostate cancer development. However, it is not clear whether androgens influence stem-like properties of prostate cancer, a feature important for prostate cancer progression. In this study, we show that upon DHT treatment in vitro, prostate cancer cell lines LNCaP and PC-3 were revealed with higher clonogenic potential and higher expression levels of stemness related factors CD44, CD90, Oct3/4 and Nanog. Moreover, sex hormone binding globulin (SHBG) was also simultaneously upregulated in these cells. When the SHBG gene was blocked by SHBG siRNA knock-down, the induction of Oct3/4, Nanog, CD44 and CD90 by DHT was also correspondingly blocked in these cells. Immunohistochemical evaluation of clinical samples disclosed weakly positive, and areas negative for SHBG expression in the benign prostate tissues, while most of the prostate carcinomas were strongly positive for SHBG. In addition, higher levels of SHBG expression were significantly associated with higher Gleason score, more seminal vesicle invasions and lymph node metastases. Collectively, our results show a role of SHBG in upregulating stemness of prostate cancer cells upon DHT exposure in vitro, and SHBG expression in prostate cancer samples is significantly associated with poor clinicopathological features, indicating a role of SHBG in prostate cancer progression.

New method for identifying features of an image on a digital video display

Science.gov (United States)

Doyle, Michael D.

1991-04-01

The MetaMap process extends the concept of direct manipulation human-computer interfaces to new limits. Its specific capabilities include the correlation of discrete image elements to relevant text information and the correlation of these image features to other images as well as to program control mechanisms. The correlation is accomplished through reprogramming of both the color map and the image so that discrete image elements comprise unique sets of color indices. This process allows the correlation to be accomplished with very efficient data storage and program execution times. Image databases adapted to this process become object-oriented as a result. Very sophisticated interrelationships can be set up between images text and program control mechanisms using this process. An application of this interfacing process to the design of an interactive atlas of medical histology as well as other possible applications are described. The MetaMap process is protected by U. S. patent #4

Features for culturally appropriate avatars for behavior-change promotion in at-risk populations

Directory of Open Access Journals (Sweden)

Lisetti C

2009-09-01

Full Text Available We explore how avatars can be used as social orthotics defined as therapeutic computer-based social companions aimed at promoting healthy behaviors. We review some of the health interventions deployed in helping at-risk populations along with some of the unique advantages that computer-based interventions can add to face-to-face interventions. We posit that artificial intelligence has rendered possible the creation of culturally appropriate dialog-agents for interventions and we identify specific features for social avatars that are important - if not necessary - when applied to the domain of social orthotic systems for health promotion.

Predicting establishment of non-native fishes in Greece: identifying key features

Directory of Open Access Journals (Sweden)

Christos Gkenas

2015-11-01

Full Text Available Non-native fishes are known to cause economic damage to human society and are considered a major threat to biodiversity loss in freshwater ecosystems. The growing concern about these impacts has driven to an investigation of the biological traits that facilitate the establishment of non-native fish. However, invalid assessment in choosing the appropriate statistical model can lead researchers to ambiguous conclusions. Here, we present a comprehensive comparison of traditional and alternative statistical methods for predicting fish invasions using logistic regression, classification trees, multicorrespondence analysis and random forest analysis to determine characteristics of successful and failed non-native fishes in Hellenic Peninsula through establishment. We defined fifteen categorical predictor variables with biological relevance and measures of human interest. Our study showed that accuracy differed according to the model and the number of factors considered. Among all the models tested, random forest and logistic regression performed best, although all approaches predicted non-native fish establishment with moderate to excellent results. Detailed evaluation among the models corresponded with differences in variables importance, with three biological variables (parental care, distance from nearest native source and maximum size and two variables of human interest (prior invasion success and propagule pressure being important in predicting establishment. The analyzed statistical methods presented have a high predictive power and can be used as a risk assessment tool to prevent future freshwater fish invasions in this region with an imperiled fish fauna.

Childhood Precursors of Adult Borderline Personality Disorder Features: A Longitudinal Study.

Science.gov (United States)

Cramer, Phebe

2016-07-01

This study identifies childhood personality traits that are precursors of adult Borderline Personality Disorder (BPD) features. In a longitudinal study, childhood personality traits were assessed at age 11 (N = 100) using the California Child Q-set (CCQ: Block and Block, 1980). A number of these Q-items were found to be significantly correlated (p personality dimensions: Impulsivity and Nonconformity/Aggression. The findings thus provide evidence that childhood personality traits predict adult BPD features. Identifying such childhood precursors provides an opportunity for early intervention.

a Landmark Extraction Method Associated with Geometric Features and Location Distribution

Science.gov (United States)

Zhang, W.; Li, J.; Wang, Y.; Xiao, Y.; Liu, P.; Zhang, S.

2018-04-01

Landmark plays an important role in spatial cognition and spatial knowledge organization. Significance measuring model is the main method of landmark extraction. It is difficult to take account of the spatial distribution pattern of landmarks because that the significance of landmark is built in one-dimensional space. In this paper, we start with the geometric features of the ground object, an extraction method based on the target height, target gap and field of view is proposed. According to the influence region of Voronoi Diagram, the description of target gap is established to the geometric representation of the distribution of adjacent targets. Then, segmentation process of the visual domain of Voronoi K order adjacent is given to set up target view under the multi view; finally, through three kinds of weighted geometric features, the landmarks are identified. Comparative experiments show that this method has a certain coincidence degree with the results of traditional significance measuring model, which verifies the effectiveness and reliability of the method and reduces the complexity of landmark extraction process without losing the reference value of landmark.

Identifying Differences in Cultural Behavior in Online Groups

Energy Technology Data Exchange (ETDEWEB)

Gregory, Michelle L.; Engel, David W.; Bell, Eric B.; Mcgrath, Liam R.

2012-07-23

We have developed methods to identify online communities, or groups, using a combination of structural information variables and content information variables from weblog posts and their comments to build a characteristic footprint for groups. We have worked with both explicitly connected groups and 'abstract' groups, in which the connection between individuals is in interest (as determined by content based features) and behavior (metadata based features) as opposed to explicit links. We find that these variables do a good job at identifying groups, placing members within a group, and helping determine the appropriate granularity for group boundaries. The group footprint can then be used to identify differences between the online groups. In the work described here we are interested in determining how an individual's online behavior is influenced by their membership in more than one group. For example, individuals belong to a certain culture; they may belong as well to a demographic group, and other 'chosen' groups such as churches or clubs. There is a plethora of evidence surrounding the culturally sensitive adoption, use, and behavior on the Internet. In this work we begin to investigate how culturally defined internet behaviors may influence behaviors of subgroups. We do this through a series of experiments in which we analyze the interaction between culturally defined behaviors and the behaviors of the subgroups. Our goal is to (a) identify if our features can capture cultural distinctions in internet use, and (b) determine what kinds of interaction there are between levels and types of groups.

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

Science.gov (United States)

Chin, Wei-Chien-Benny; Wen, Tzai-Hung

2015-01-01

A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR) and Geographical PageRank (GPR)-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.

Enhancing the Pronunciation of English Suprasegmental Features through Reflective Learning Method

Science.gov (United States)

Suwartono

2014-01-01

Suprasegmental features are of paramount importance in spoken English. Yet, these pronunciation features are marginalised in EFL/ESL teaching-learning. This article reported a study that was aimed at improving the students' mastery of English suprasegmental features through the use of reflective learning method. The study adopted Kemmis and…

Large anterior temporal Virchow-Robin spaces: unique MR imaging features

Energy Technology Data Exchange (ETDEWEB)

Lim, Anthony T. [Monash University, Neuroradiology Service, Monash Imaging, Monash Health, Melbourne, Victoria (Australia); Chandra, Ronil V. [Monash University, Neuroradiology Service, Monash Imaging, Monash Health, Melbourne, Victoria (Australia); Monash University, Department of Surgery, Faculty of Medicine, Nursing and Health Sciences, Melbourne (Australia); Trost, Nicholas M. [St Vincent' s Hospital, Neuroradiology Service, Melbourne (Australia); McKelvie, Penelope A. [St Vincent' s Hospital, Anatomical Pathology, Melbourne (Australia); Stuckey, Stephen L. [Monash University, Neuroradiology Service, Monash Imaging, Monash Health, Melbourne, Victoria (Australia); Monash University, Southern Clinical School, Faculty of Medicine, Nursing and Health Sciences, Melbourne (Australia)

2015-05-01

Large Virchow-Robin (VR) spaces may mimic cystic tumor. The anterior temporal subcortical white matter is a recently described preferential location, with only 18 reported cases. Our aim was to identify unique MR features that could increase prospective diagnostic confidence. Thirty-nine cases were identified between November 2003 and February 2014. Demographic, clinical data and the initial radiological report were retrospectively reviewed. Two neuroradiologists reviewed all MR imaging; a neuropathologist reviewed histological data. Median age was 58 years (range 24-86 years); the majority (69 %) was female. There were no clinical symptoms that could be directly referable to the lesion. Two thirds were considered to be VR spaces on the initial radiological report. Mean maximal size was 9 mm (range 5-17 mm); majority (79 %) had perilesional T2 or fluid-attenuated inversion recovery (FLAIR) hyperintensity. The following were identified as potential unique MR features: focal cortical distortion by an adjacent branch of the middle cerebral artery (92 %), smaller adjacent VR spaces (26 %), and a contiguous cerebrospinal fluid (CSF) intensity tract (21 %). Surgery was performed in three asymptomatic patients; histopathology confirmed VR spaces. Unique MR features were retrospectively identified in all three patients. Large anterior temporal lobe VR spaces commonly demonstrate perilesional T2 or FLAIR signal and can be misdiagnosed as cystic tumor. Potential unique MR features that could increase prospective diagnostic confidence include focal cortical distortion by an adjacent branch of the middle cerebral artery, smaller adjacent VR spaces, and a contiguous CSF intensity tract. (orig.)

Finding an optimum immuno-histochemical feature set to distinguish benign phyllodes from fibroadenoma.

Science.gov (United States)

Maity, Priti Prasanna; Chatterjee, Subhamoy; Das, Raunak Kumar; Mukhopadhyay, Subhalaxmi; Maity, Ashok; Maulik, Dhrubajyoti; Ray, Ajoy Kumar; Dhara, Santanu; Chatterjee, Jyotirmoy

2013-05-01

Benign phyllodes and fibroadenoma are two well-known breast tumors with remarkable diagnostic ambiguity. The present study is aimed at determining an optimum set of immuno-histochemical features to distinguish them by analyzing important observations on expressions of important genes in fibro-glandular tissue. Immuno-histochemically, the expressions of p63 and α-SMA in myoepithelial cells and collagen I, III and CD105 in stroma of tumors and their normal counterpart were studied. Semi-quantified features were analyzed primarily by ANOVA and ranked through F-scores for understanding relative importance of group of features in discriminating three classes followed by reduction in F-score arranged feature space dimension and application of inter-class Bhattacharyya distances to distinguish tumors with an optimum set of features. Among thirteen studied features except one all differed significantly in three study classes. F-Ranking of features revealed highest discriminative potential of collagen III (initial region). F-Score arranged feature space dimension and application of Bhattacharyya distance gave rise to a feature set of lower dimension which can discriminate benign phyllodes and fibroadenoma effectively. The work definitely separated normal breast, fibroadenoma and benign phyllodes, through an optimal set of immuno-histochemical features which are not only useful to address diagnostic ambiguity of the tumors but also to spell about malignant potentiality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Reductio ad discrimen: Where features come from

Directory of Open Access Journals (Sweden)

Elizabeth Cowper

2015-04-01

Full Text Available This paper addresses two fundamental questions about the nature of formal features in phonology and morphosyntax: what is their expressive power, and where do they come from? To answer these questions, we begin with the most restrictive possible hypothesis (all features are privative, and are wholly dictated by Universal Grammar, with no room for cross-linguistic variation, and examine the extent to which empirical evidence from a variety of languages compels a retreat from this position. We argue that there is little to be gained by positing a universal set of specific features, and propose instead that the crucial contribution of UG is the language learner's ability to construct features by identifying correlations between contrasts at different levels of linguistic structure. This view resonates with current research on how the interaction between UG and external 'third factors' shapes the structure of language, while at the same time harking back to the Saussurean notion that contrast is the central function of linguistic representations.

Optical security features for plastic card documents

Science.gov (United States)

Hossick Schott, Joachim

1998-04-01

Print-on-demand is currently a major trend in the production of paper based documents. This fully digital production philosophy will likely have ramifications also for the secure identification document market. Here, plastic cards increasingly replace traditionally paper based security sensitive documents such as drivers licenses and passports. The information content of plastic cards can be made highly secure by using chip cards. However, printed and other optical security features will continue to play an important role, both for machine readable and visual inspection. Therefore, on-demand high resolution print technologies, laser engraving, luminescent pigments and laminated features such as holograms, kinegrams or phase gratings will have to be considered for the production of secure identification documents. Very important are also basic optical, surface and material durability properties of the laminates as well as the strength and nature of the adhesion between the layers. This presentation will address some of the specific problems encountered when optical security features such as high resolution printing and laser engraving are to be integrated in the on-demand production of secure plastic card identification documents.

Statistical methods for detecting differentially abundant features in clinical metagenomic samples.

Directory of Open Access Journals (Sweden)

James Robert White

2009-04-01

Full Text Available Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them.We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher's exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software

Frontotemporal dementia with the C9ORF72 hexanucleotide repeat expansion: clinical, neuroanatomical and neuropathological features

Science.gov (United States)

Mahoney, Colin J.; Beck, Jon; Rohrer, Jonathan D.; Lashley, Tammaryn; Mok, Kin; Shakespeare, Tim; Yeatman, Tom; Warrington, Elizabeth K.; Schott, Jonathan M.; Fox, Nick C.; Rossor, Martin N.; Hardy, John; Collinge, John; Revesz, Tamas; Mead, Simon

2012-01-01

with C9ORF72 mutation from the frontotemporal lobar degeneration series identified histomorphological features consistent with either type A or B TAR DNA-binding protein-43 deposition; however, p62-positive (in excess of TAR DNA-binding protein-43 positive) neuronal cytoplasmic inclusions in hippocampus and cerebellum were a consistent feature of these cases, in contrast to the similar frequency of p62 and TAR DNA-binding protein-43 deposition in 53 control cases with frontotemporal lobar degeneration–TAR DNA-binding protein. These findings corroborate the clinical importance of the C9ORF72 mutation in frontotemporal lobar degeneration, delineate phenotypic and neuropathological features that could help to guide genetic testing, and suggest hypotheses for elucidating the neurobiology of a culprit subcortical network. PMID:22366791

Identifying Important Atlantic Areas for the conservation of Balearic shearwaters: Spatial overlap with conservation areas

Science.gov (United States)

Pérez-Roda, Amparo; Delord, Karine; Boué, Amélie; Arcos, José Manuel; García, David; Micol, Thierry; Weimerskirch, Henri; Pinaud, David; Louzao, Maite

2017-07-01

Marine protected areas (MPAs) are considered one of the main tools in both fisheries and conservation management to protect threatened species and their habitats around the globe. However, MPAs are underrepresented in marine environments compared to terrestrial environments. Within this context, we studied the Atlantic non-breeding distribution of the southern population of Balearic shearwaters (Puffinus mauretanicus) breeding in Eivissa during the 2011-2012 period based on global location sensing (GLS) devices. Our objectives were (1) to identify overall Important Atlantic Areas (IAAs) from a southern population, (2) to describe spatio-temporal patterns of oceanographic habitat use, and (3) to assess whether existing conservation areas (Natura 2000 sites and marine Important Bird Areas (IBAs)) cover the main IAAs of Balearic shearwaters. Our results highlighted that the Atlantic staging (from June to October in 2011) dynamic of the southern population was driven by individual segregation at both spatial and temporal scales. Individuals ranged in the North-East Atlantic over four main IAAs (Bay of Biscay: BoB, Western Iberian shelf: WIS, Gulf of Cadiz: GoC, West of Morocco: WoM). While most individuals spent more time on the WIS or in the GoC, a small number of birds visited IAAs at the extremes of their Atlantic distribution range (i.e., BoB and WoM). The chronology of the arrivals to the IAAs showed a latitudinal gradient with northern areas reached earlier during the Atlantic staging. The IAAs coincided with the most productive areas (higher chlorophyll a values) in the NE Atlantic between July and October. The spatial overlap between IAAs and conservation areas was higher for Natura 2000 sites than marine IBAs (areas with and without legal protection, respectively). Concerning the use of these areas, a slightly higher proportion of estimated positions fell within marine IBAs compared to designated Natura 2000 sites, with Spanish and Portuguese conservation

Buying Imported Products Online : A quantitative study about Chinese Online consumer behavior towards imported products

OpenAIRE

Chen, Qianqian; Wang, Yuren

2015-01-01

With the fast growing Chinese online marketplace and the increasing popularity of shopping imported products online in China, more and more practitioners and researchers are interested in understanding the cues that Chinese consumers use to evaluate imported products consumption online. Our quantitative study aims to identify what factors affect the behavior of Chinese online consumers towards imported products and the relationships between the identified factors and purchase intention, and t...

Solid state radiation chemistry. Features important in basic research and applications

International Nuclear Information System (INIS)

Zagorski, Z.P.

1998-01-01

The basic research of chemical radiation effects has been mostly proceeded in aqueous systems. When one turns from aqueous to the 'dry solute' systems, reactions are running in a very different way. The examined compound, previously the solute, becomes then the only constituent of the system, absorbing all ionising energy. Majority of dosimeters and of radiation processed systems is solid: these are crystalline or rigid substances of high viscosity, sometimes of complicated phase-compositions being no longer homogenous like liquids. Main features of the solid (and rigid) state radiation chemistry is to be discussed in five parts: I. Character of absorption process. Absorption of radiation is in all media heterogenous on the molecular level, i.e. with formation of single- and multi-ionisation spurs. The yield of the latters is 15-25% of the total ionisations, depending on the system, even at low LET radiation. In spite of random distribution of initial ionisations, the single-ionisation spurs can turn rapidly into specifically arranged, temporal localisations. The variety of spur reactions is usually more complicated than that in aqueous systems. II. Character of transients. Intermediates in solid state radiation chemistry exhibit very different transport properties: from free electrons moving fast and far, to electrons changing the position by different physicochemical mechanisms, to easy movable H-atoms, and to practically unmovable, only vibrating, new fragments of a lattice or glass. III. Paramagnetic intermediates. Radicals living for microseconds in liquids, when created and trapped in a solid matrix are usually very stable, e.g. they can have a difference of half-life times of 12 orders of magnitude, however their chemical composition remais identical. (author)

Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques

Directory of Open Access Journals (Sweden)

M. Flach

2017-08-01

Full Text Available Today, many processes at the Earth's surface are constantly monitored by multiple data streams. These observations have become central to advancing our understanding of vegetation dynamics in response to climate or land use change. Another set of important applications is monitoring effects of extreme climatic events, other disturbances such as fires, or abrupt land transitions. One important methodological question is how to reliably detect anomalies in an automated and generic way within multivariate data streams, which typically vary seasonally and are interconnected across variables. Although many algorithms have been proposed for detecting anomalies in multivariate data, only a few have been investigated in the context of Earth system science applications. In this study, we systematically combine and compare feature extraction and anomaly detection algorithms for detecting anomalous events. Our aim is to identify suitable workflows for automatically detecting anomalous patterns in multivariate Earth system data streams. We rely on artificial data that mimic typical properties and anomalies in multivariate spatiotemporal Earth observations like sudden changes in basic characteristics of time series such as the sample mean, the variance, changes in the cycle amplitude, and trends. This artificial experiment is needed as there is no gold standard for the identification of anomalies in real Earth observations. Our results show that a well-chosen feature extraction step (e.g., subtracting seasonal cycles, or dimensionality reduction is more important than the choice of a particular anomaly detection algorithm. Nevertheless, we identify three detection algorithms (k-nearest neighbors mean distance, kernel density estimation, a recurrence approach and their combinations (ensembles that outperform other multivariate approaches as well as univariate extreme-event detection methods. Our results therefore provide an effective workflow to

Annotation-based feature extraction from sets of SBML models.

Science.gov (United States)

Alm, Rebekka; Waltemath, Dagmar; Wolfien, Markus; Wolkenhauer, Olaf; Henkel, Ron

2015-01-01

Model repositories such as BioModels Database provide computational models of biological systems for the scientific community. These models contain rich semantic annotations that link model entities to concepts in well-established bio-ontologies such as Gene Ontology. Consequently, thematically similar models are likely to share similar annotations. Based on this assumption, we argue that semantic annotations are a suitable tool to characterize sets of models. These characteristics improve model classification, allow to identify additional features for model retrieval tasks, and enable the comparison of sets of models. In this paper we discuss four methods for annotation-based feature extraction from model sets. We tested all methods on sets of models in SBML format which were composed from BioModels Database. To characterize each of these sets, we analyzed and extracted concepts from three frequently used ontologies, namely Gene Ontology, ChEBI and SBO. We find that three out of the methods are suitable to determine characteristic features for arbitrary sets of models: The selected features vary depending on the underlying model set, and they are also specific to the chosen model set. We show that the identified features map on concepts that are higher up in the hierarchy of the ontologies than the concepts used for model annotations. Our analysis also reveals that the information content of concepts in ontologies and their usage for model annotation do not correlate. Annotation-based feature extraction enables the comparison of model sets, as opposed to existing methods for model-to-keyword comparison, or model-to-model comparison.

Searching for a traveling feature in Saturn's rings in Cassini Imaging Science Subsystem data

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Aye, Klaus-Michael; Rehnberg, Morgan; Brown, Zarah; Esposito, Larry W.

2016-10-01

Introduction: Using Cassini UVIS occultation data, a traveling wave feature has been identified in the Saturn rings that is most likely caused by the radial positions swap of the moons Janus and Epimetheus [1]. The hypothesis is that non-linear interferences between the linear density waves when being relocated by the moon swap create a solitary wave that is traveling outward through the rings. The observations in [1] further lead to the derivation of values for the radial travel speeds of the identified traveling features, from 39.6 km/yr for the Janus 5:4 resonance up to 45.8 for the Janus 4:3 resonance.Previous confirmations in ISS data: Work in [1] also identified the feature in Cassini Imaging Science Subsystem (ISS) data that was taken around the time of the UVIS occultations where the phenomenon was first discovered, so far one ISS image for each Janus resonances 2:1, 4:3, 5:4, and 6:5.Search guided by predicted locations: Using the observation-fitted radial velocities from [1], we can extrapolate these to identify Saturn radii at which the traveling feature should be found at later times. Using this and new image analysis and plotting tools available in [2], we have identified a potential candidate feature in an ISS image that was taken 2.5 years after the feature causing moon swap in January 2006. We intend to expand our search by identifying candidate ISS data by a meta-database search constraining the radius at future times corresponding to the predicted future locations of the hypothesized solitary wave and present our findings at this conference.References: [1] Rehnberg, M.E., Esposito, L.W., Brown, Z.L., Albers, N., Sremčević, M., Stewart, G.R., 2016. A Traveling Feature in Saturn's Rings. Icarus, accepted in June 2016. [2] K.-Michael Aye. (2016). pyciss: v0.5.0. Zenodo. 10.5281/zenodo.53092

Confirmation of a traveling feature in Saturn's rings in Cassini Imaging Science Subsystem data

Science.gov (United States)

Aye, K. M.; Rehnberg, M.; Esposito, L. W.

2017-12-01

Introduction: Using Cassini UVIS occultation data, a traveling wave feature has been identified in the Saturn rings that is most likely caused by the radial positions swap of the moons Janus and Epimetheus [1]. The hypothesis is that non-linear interferences between the density waves when being relocated by the moon swap create a solitary wave that is traveling outward through the rings. The observations in [1] further lead to the derivation of values for the radial travel speeds of the identified traveling features, from 39.6 km/yr for the Janus 5:4 resonance up to 45.8 for the Janus 4:3 resonance. Previous confirmations in ISS data: Work in [1] also identified the feature in Cassini Imaging Science Subsystem (ISS) data that was taken around the time of the UVIS occultations where the phenomenon was first discovered, so far one ISS image for each Janus resonances 2:1, 4:3, 5:4, and 6:5. Searches performed in ISS data: Filtering all existing ISS data down to the best resolutions that include both a clearly identifiable minimum and maximum ring radius, we have visually inspected approx. 200 images, both with and without known resonances within the image, but unbeknownst to the inspector. Identification of a feature of interest happens when train waves are being interrupted by anomalies. Comparing the radial locations of identified ISS features with those in UV data of [1], we have identified several at the same radii. Considering the vast differences in radial resolution, we conclude that the traveling feature causes observable anomalies at both small scales of meters, up to large scales of hundreds of meters to kilometers.References: [1] Rehnberg, M.E., Esposito, L.W., Brown, Z.L., Albers, N., Sremčević, M., Stewart, G.R., 2016. A Traveling Feature in Saturn's Rings. Icarus, accepted in June 2016. [2] K.-Michael Aye (2016, November 11). michaelaye/pyciss: . v0.6.0 Zenodo. https://doi.org/10.5281/zenodo.596802

MRI features of chondroblastoma

International Nuclear Information System (INIS)

Cheng Xiaoguang; Liu Xia; Cheng Kebin; Liu Wei

2009-01-01

Objective: To evaluate the MR imaging features of chondroblastoma. Methods: MRI examinations of 20 patients with histological proven chondmblastoma were reviewed retrospectively. The MRI findings of chondroblastoma including the signal intensity, the shape, the growth patterns, and the surrounding bone marrow edema and the adjacent soft tissue edema, the periosteal reaction, the adjacent joint effusion were analyzed. Results: All 20 cases demonstrated heterogeneous MR signal intensity on T 1 WI and T 2 WI images and showed lobular margins. Sixteen cases demonstrated expansive growth patterns. Surrounding bone marrow edema was found in 18 cases and adjacent soft tissue edema in 14 cases. Periosteal reaction was identified in 6 cases. In 7 cases the tumor extended to adjacent soft tissue. Adjacent joint effusion was visible on MRI in 6 cases. Conclusion: Heterogeneous signal intensity, lobular margins and expansive growth pattern, adjacent bone marrow and soft tissue edema were the common features of chondroblastoma on MRI. (authors)

Mammographic and ultrasound features of invasive lobular carcinoma of the breast

International Nuclear Information System (INIS)

Porter, Alan J.; Evans, Elizabeth B.; Foxcraft, Loani M.; Simpson, Peter T.; Lakhani, Sunil R.

2014-01-01

Invasive lobular cancer (ILC) is an important contributor to false negative mammography. This study aims to assess the value of digital mammography and to identify imaging features that could assist the radiologist to suggest the diagnosis of ILC prior to biopsy. Three hundred sixty-one cases of pure ILC diagnosed at the Wesley Breast Clinic during the period 1995–2010 were reviewed by one of the authors (AP). Radiological features were categorized, and clinical features and needle sampling results were recorded. Mammography was negative in 29.9% of ILCs. The commonest positive finding was a localized spiculated mass (41.8%). Thirty-four point nine per cent of lesions were visible in only one view, usually cranio-caudal. Calcification was not a feature of ILC. The use of digital mammography in 30% of cases did not decrease the false negative rate for ILC. Breast ultrasound (BUS) showed an abnormality in 97.8%, most commonly a localized irregular hypoechoic mass with shadowing. Digital mammography does not reduce false negative mammography in ILC. The poor visibility of ILCs may be partly related to their low density (mass/unit volume). ILCs may sometimes be poor attenuators of X-rays but excellent attenuators of ultrasound, causing marked acoustic shadowing. Bilateral whole BUS has a very low false negative rate in experienced hands and is mandatory in symptomatic women. The combination of poor visibility on mammography with high visibility on ultrasound, as well as certain characteristic ultrasound appearances of ILC, may enable the radiologist to suggest ILC as a diagnostic possibility, prior to biopsy.

Imaging features of juxtacortical chondroma in children

International Nuclear Information System (INIS)

Miller, Stephen F.

2014-01-01

Juxtacortical chondroma is a rare benign bone lesion in children. Children usually present with a mildly painful mass, which prompts diagnostic imaging studies. The rarity of this condition often presents a diagnostic challenge. Correct diagnosis is crucial in guiding surgical management. To describe the characteristic imaging findings of juxtacortical chondroma in children. We identified all children who were diagnosed with juxtacortical chondroma between 1998 and 2012. A single experienced pediatric radiologist reviewed all diagnostic imaging studies, including plain radiographs, CT, MR and bone scans. Seven children (5 boys and 2 girls) with juxtacortical chondroma were identified, ranging in age from 6 years to 16 years (mean 12.3 years). Mild pain and a palpable mass were present in all seven children. Plain radiographs were available in 6/7, MR in 7/7, CT in 4/7 and skeletal scintigraphy in 5/7 children. Three lesions were located in the proximal humerus, with one each in the distal radius, distal femur, proximal tibia and scapula. Radiographic and CT features deemed highly suggestive of juxtacortical chondroma included cortical scalloping, underlying cortical sclerosis and overhanging margins. MRI features consistent with juxtacortical chondroma included isointensity to skeletal muscle on T1, marked hyperintensity on T2 and peripheral rim enhancement after contrast agent administration. One of seven lesions demonstrated intramedullary extension, and 2/7 showed adjacent soft-tissue edema. Juxtacortical chondroma is an uncommon benign lesion in children with characteristic features on plain radiographs, CT and MR. Recognition of these features is invaluable in guiding appropriate surgical management. (orig.)

Imaging features of juxtacortical chondroma in children

Energy Technology Data Exchange (ETDEWEB)

Miller, Stephen F. [St. Jude Children' s Research Hospital, Department of Radiological Sciences, Memphis, TN (United States)

2014-01-15

Juxtacortical chondroma is a rare benign bone lesion in children. Children usually present with a mildly painful mass, which prompts diagnostic imaging studies. The rarity of this condition often presents a diagnostic challenge. Correct diagnosis is crucial in guiding surgical management. To describe the characteristic imaging findings of juxtacortical chondroma in children. We identified all children who were diagnosed with juxtacortical chondroma between 1998 and 2012. A single experienced pediatric radiologist reviewed all diagnostic imaging studies, including plain radiographs, CT, MR and bone scans. Seven children (5 boys and 2 girls) with juxtacortical chondroma were identified, ranging in age from 6 years to 16 years (mean 12.3 years). Mild pain and a palpable mass were present in all seven children. Plain radiographs were available in 6/7, MR in 7/7, CT in 4/7 and skeletal scintigraphy in 5/7 children. Three lesions were located in the proximal humerus, with one each in the distal radius, distal femur, proximal tibia and scapula. Radiographic and CT features deemed highly suggestive of juxtacortical chondroma included cortical scalloping, underlying cortical sclerosis and overhanging margins. MRI features consistent with juxtacortical chondroma included isointensity to skeletal muscle on T1, marked hyperintensity on T2 and peripheral rim enhancement after contrast agent administration. One of seven lesions demonstrated intramedullary extension, and 2/7 showed adjacent soft-tissue edema. Juxtacortical chondroma is an uncommon benign lesion in children with characteristic features on plain radiographs, CT and MR. Recognition of these features is invaluable in guiding appropriate surgical management. (orig.)

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.

How important is vehicle safety in the new vehicle purchase process?

Science.gov (United States)

Koppel, Sjaanie; Charlton, Judith; Fildes, Brian; Fitzharris, Michael

2008-05-01

Whilst there has been a significant increase in the amount of consumer interest in the safety performance of privately owned vehicles, the role that it plays in consumers' purchase decisions is poorly understood. The aims of the current study were to determine: how important vehicle safety is in the new vehicle purchase process; what importance consumers place on safety options/features relative to other convenience and comfort features, and how consumers conceptualise vehicle safety. In addition, the study aimed to investigate the key parameters associated with ranking 'vehicle safety' as the most important consideration in the new vehicle purchase. Participants recruited in Sweden and Spain completed a questionnaire about their new vehicle purchase. The findings from the questionnaire indicated that participants ranked safety-related factors (e.g., EuroNCAP (or other) safety ratings) as more important in the new vehicle purchase process than other vehicle factors (e.g., price, reliability etc.). Similarly, participants ranked safety-related features (e.g., advanced braking systems, front passenger airbags etc.) as more important than non-safety-related features (e.g., route navigation systems, air-conditioning etc.). Consistent with previous research, most participants equated vehicle safety with the presence of specific vehicle safety features or technologies rather than vehicle crash safety/test results or crashworthiness. The key parameters associated with ranking 'vehicle safety' as the most important consideration in the new vehicle purchase were: use of EuroNCAP, gender and education level, age, drivers' concern about crash involvement, first vehicle purchase, annual driving distance, person for whom the vehicle was purchased, and traffic infringement history. The findings from this study are important for policy makers, manufacturers and other stakeholders to assist in setting priorities with regard to the promotion and publicity of vehicle safety features

Imaging features of kaposiform lymphangiomatosis

International Nuclear Information System (INIS)

Goyal, Pradeep; Alomari, Ahmad I.; Shaikh, Raja; Chaudry, Gulraiz; Kozakewich, Harry P.; Perez-Atayde, Antonio R.; Trenor, Cameron C.; Fishman, Steven J.; Greene, Arin K.

2016-01-01

Kaposiform lymphangiomatosis is a rare, aggressive lymphatic disorder. The imaging and presenting features of kaposiform lymphangiomatosis can overlap with those of central conducting lymphatic anomaly and generalized lymphatic anomaly. To analyze the imaging findings of kaposiform lymphangiomatosis disorder and highlight features most suggestive of this diagnosis. We retrospectively identified and characterized 20 children and young adults with histopathological diagnosis of kaposiform lymphangiomatosis and radiologic imaging referred to the vascular anomalies center between 1995 and 2015. The median age at onset was 6.5 years (range 3 months to 27 years). The most common presenting features were respiratory compromise (dyspnea, cough, chest pain; 55.5%), swelling/mass (25%), bleeding (15%) and fracture (5%). The thoracic cavity was involved in all patients; all patients had mediastinal involvement followed by lung parenchymal disease (90%) and pleural (85%) and pericardial (50%) effusions. The most common extra-thoracic sites of disease were the retroperitoneum (80%), bone (60%), abdominal viscera (55%) and muscles (45%). There was characteristic enhancing and infiltrative soft-tissue thickening in the mediastinum and retroperitoneum extending along the lymphatic distribution. Kaposiform lymphangiomatosis has overlapping imaging features with central conducting lymphatic anomaly and generalized lymphatic anomaly. Presence of mediastinal or retroperitoneal enhancing and infiltrative soft-tissue disease along the lymphatic distribution, hemorrhagic effusions and moderate thrombocytopenia (50-100,000/μl) should favor diagnosis of kaposiform lymphangiomatosis. (orig.)

Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean

Science.gov (United States)

Quattrini, Andrea M.; Demopoulos, Amanda W. J.; Singer, Randal; Roa-Varon, Adela; Chaytor, Jason D.

2017-05-01

Recent investigations of demersal fish communities in deepwater (>50 m) habitats have considerably increased our knowledge of the factors that influence the assemblage structure of fishes across mesophotic to deep-sea depths. While different habitat types influence deepwater fish distribution, whether different types of rugged seafloor features provide functionally equivalent habitat for fishes is poorly understood. In the northeastern Caribbean, different types of rugged features (e.g., seamounts, banks, canyons) punctuate insular margins, and thus create a remarkable setting in which to compare demersal fish communities across various features. Concurrently, several water masses are vertically layered in the water column, creating strong stratification layers corresponding to specific abiotic conditions. In this study, we examined differences among fish assemblages across different features (e.g., seamount, canyon, bank/ridge) and water masses at depths ranging from 98 to 4060 m in the northeastern Caribbean. We conducted 26 remotely operated vehicle dives across 18 sites, identifying 156 species of which 42% of had not been previously recorded from particular depths or localities in the region. While rarefaction curves indicated fewer species at seamounts than at other features in the NE Caribbean, assemblage structure was similar among the different types of features. Thus, similar to seamount studies in other regions, seamounts in the Anegada Passage do not harbor distinct communities from other types of rugged features. Species assemblages, however, differed among depths, with zonation generally corresponding to water mass boundaries in the region. High species turnover occurred at depths <1200 m, and may be driven by changes in water mass characteristics including temperature (4.8-24.4 °C) and dissolved oxygen (2.2-9.5 mg per l). Our study suggests the importance of water masses in influencing community structure of benthic fauna, while considerably adding

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

Science.gov (United States)

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

2018-02-01

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

Cytomorphologic features distinguishing Bethesda category IV thyroid lesions from parathyroid

Directory of Open Access Journals (Sweden)

Simon Sung

2017-01-01

Full Text Available Background: Thyroid follicular cells share similar cytomorphological features with parathyroid. Without a clinical suspicion, the distinction between a thyroid neoplasm and an intrathyroidal parathyroid can be challenging. The aim of this study was to assess the distinguishing cytomorphological features of parathyroid (including intrathyroidal and Bethesda category IV (Beth-IV thyroid follicular lesions, which carry a 15%–30% risk of malignancy and are often followed up with surgical resection. Methods: A search was performed to identify “parathyroid” diagnoses in parathyroid/thyroid-designated fine-needle aspirations (FNAs and Beth-IV thyroid FNAs (follicular and Hurthle cell, all with diagnostic confirmation through surgical pathology, immunocytochemical stains, Afirma® analysis, and/or clinical correlation. Unique cytomorphologic features were scored (0-3 or noted as present versus absent. Statistical analysis was performed using R 3.3.1 software. Results: We identified five FNA cases with clinical suspicion of parathyroid neoplasm, hyperthyroidism, or thyroid lesion that had an eventual final diagnosis of the parathyroid lesion (all female; age 20–69 years and 12 Beth-IV diagnoses (11 female, 1 male; age 13–64 years. The following cytomorphologic features are useful distinguishing features (P value: overall pattern (0.001, single cells (0.001, cell size compared to red blood cell (0.01, nuclear irregularity (0.001, presence of nucleoli (0.001, nuclear-to-cytoplasmic ratio (0.007, and nuclear chromatin quality (0.028. Conclusions: There are cytomorphologic features that distinguish Beth-IV thyroid lesions and (intrathyroidal parathyroid. These features can aid in rendering correct diagnoses and appropriate management.

Geomorphic domains and linear features on Landsat images, Circle Quadrangle, Alaska

Science.gov (United States)

Simpson, S.L.

1984-01-01

A remote sensing study using Landsat images was undertaken as part of the Alaska Mineral Resource Assessment Program (AMRAP). Geomorphic domains A and B, identified on enhanced Landsat images, divide Circle quadrangle south of Tintina fault zone into two regional areas having major differences in surface characteristics. Domain A is a roughly rectangular, northeast-trending area of relatively low relief and simple, widely spaced drainages, except where igneous rocks are exposed. In contrast, domain B, which bounds two sides of domain A, is more intricately dissected showing abrupt changes in slope and relatively high relief. The northwestern part of geomorphic domain A includes a previously mapped tectonostratigraphic terrane. The southeastern boundary of domain A occurs entirely within the adjoining tectonostratigraphic terrane. The sharp geomorphic contrast along the southeastern boundary of domain A and the existence of known faults along this boundary suggest that the southeastern part of domain A may be a subdivision of the adjoining terrane. Detailed field studies would be necessary to determine the characteristics of the subdivision. Domain B appears to be divisible into large areas of different geomorphic terrains by east-northeast-trending curvilinear lines drawn on Landsat images. Segments of two of these lines correlate with parts of boundaries of mapped tectonostratigraphic terranes. On Landsat images prominent north-trending lineaments together with the curvilinear lines form a large-scale regional pattern that is transected by mapped north-northeast-trending high-angle faults. The lineaments indicate possible lithlogic variations and/or structural boundaries. A statistical strike-frequency analysis of the linear features data for Circle quadrangle shows that northeast-trending linear features predominate throughout, and that most northwest-trending linear features are found south of Tintina fault zone. A major trend interval of N.64-72E. in the linear

SHBG is an important factor in stemness induction of cells by DHT in vitro and associated with poor clinical features of prostate carcinomas.

Directory of Open Access Journals (Sweden)

Yuanyuan Ma

Full Text Available Androgen plays a vital role in prostate cancer development. However, it is not clear whether androgens influence stem-like properties of prostate cancer, a feature important for prostate cancer progression. In this study, we show that upon DHT treatment in vitro, prostate cancer cell lines LNCaP and PC-3 were revealed with higher clonogenic potential and higher expression levels of stemness related factors CD44, CD90, Oct3/4 and Nanog. Moreover, sex hormone binding globulin (SHBG was also simultaneously upregulated in these cells. When the SHBG gene was blocked by SHBG siRNA knock-down, the induction of Oct3/4, Nanog, CD44 and CD90 by DHT was also correspondingly blocked in these cells. Immunohistochemical evaluation of clinical samples disclosed weakly positive, and areas negative for SHBG expression in the benign prostate tissues, while most of the prostate carcinomas were strongly positive for SHBG. In addition, higher levels of SHBG expression were significantly associated with higher Gleason score, more seminal vesicle invasions and lymph node metastases. Collectively, our results show a role of SHBG in upregulating stemness of prostate cancer cells upon DHT exposure in vitro, and SHBG expression in prostate cancer samples is significantly associated with poor clinicopathological features, indicating a role of SHBG in prostate cancer progression.

SHBG Is an Important Factor in Stemness Induction of Cells by DHT In Vitro and Associated with Poor Clinical Features of Prostate Carcinomas

Science.gov (United States)

Ma, Yuanyuan; Liang, Dongming; Liu, Jian; Wen, Jian-Guo; Servoll, Einar; Waaler, Gudmund; Sæter, Thorstein; Axcrona, Karol; Vlatkovic, Ljiljana; Axcrona, Ulrika; Paus, Elisabeth; Yang, Yue; Zhang, Zhiqian; Kvalheim, Gunnar; Nesland, Jahn M.; Suo, Zhenhe

2013-01-01

Androgen plays a vital role in prostate cancer development. However, it is not clear whether androgens influence stem-like properties of prostate cancer, a feature important for prostate cancer progression. In this study, we show that upon DHT treatment in vitro, prostate cancer cell lines LNCaP and PC-3 were revealed with higher clonogenic potential and higher expression levels of stemness related factors CD44, CD90, Oct3/4 and Nanog. Moreover, sex hormone binding globulin (SHBG) was also simultaneously upregulated in these cells. When the SHBG gene was blocked by SHBG siRNA knock-down, the induction of Oct3/4, Nanog, CD44 and CD90 by DHT was also correspondingly blocked in these cells. Immunohistochemical evaluation of clinical samples disclosed weakly positive, and areas negative for SHBG expression in the benign prostate tissues, while most of the prostate carcinomas were strongly positive for SHBG. In addition, higher levels of SHBG expression were significantly associated with higher Gleason score, more seminal vesicle invasions and lymph node metastases. Collectively, our results show a role of SHBG in upregulating stemness of prostate cancer cells upon DHT exposure in vitro, and SHBG expression in prostate cancer samples is significantly associated with poor clinicopathological features, indicating a role of SHBG in prostate cancer progression. PMID:23936228

Distinguishing obsessive features and worries: the role of thought-action fusion.

Science.gov (United States)

Coles, M E; Mennin, D S; Heimberg, R G

2001-08-01

Obsessions are a key feature of obsessive-compulsive disorder (OCD), and chronic worry is the cardinal feature of generalized anxiety disorder (GAD). However, these two cognitive processes are conceptually very similar, and there is a need to determine how they differ. Recent studies have attempted to identify cognitive processes that may be differentially related to obsessive features and worry. In the current study we proposed that (1) obsessive features and worry could be differentiated and that (2) a measure of the cognitive process thought-action fusion would distinguish between obsessive features and worry, being strongly related to obsessive features after controlling for the effects of worry. These hypotheses were supported in a sample of 173 undergraduate students. Thought-action fusion may be a valuable construct in differentiating between obsessive features and worry.

A case of asymptomatic pancytopenia with clinical features of hemolysis as a presentation of pernicious anemia

Directory of Open Access Journals (Sweden)

Venkateswara K. Kollipara

2016-09-01

Full Text Available Pernicious anemia is an autoimmune disease with a variety of clinical presentations. We describe a case of pernicious anemia presenting with pancytopenia with hemolytic features. Further workup revealed very low vitamin B12 levels and elevated methylmalonic acid. It is important for a general internist to identify pernicious anemia as one of the cause of pancytopenia and hemolytic anemia to avoid extensive workup. Pernicious anemia can present strictly with hematological abnormalities without neurological problems or vice versa as in our case.

Thoughts on identifiers

CERN Multimedia

CERN. Geneva

2005-01-01

As business processes and information transactions have become an inextricably intertwined with the Web, the importance of assignment, registration, discovery, and maintenance of identifiers has increased. In spite of this, integrated frameworks for managing identifiers have been slow to emerge. Instead, identification systems arise (quite naturally) from immediate business needs without consideration for how they fit into larger information architectures. In addition, many legacy identifier systems further complicate the landscape, making it difficult for content managers to select and deploy identifier systems that meet both the business case and long term information management objectives. This presentation will outline a model for evaluating identifier applications and the functional requirements of the systems necessary to support them. The model is based on a layered analysis of the characteristics of identifier systems, including: * Functional characteristics * Technology * Policy * Business * Social T...

Predicting Essential Genes and Proteins Based on Machine Learning and Network Topological Features: A Comprehensive Review

Science.gov (United States)

Zhang, Xue; Acencio, Marcio Luis; Lemke, Ney

2016-01-01

Essential proteins/genes are indispensable to the survival or reproduction of an organism, and the deletion of such essential proteins will result in lethality or infertility. The identification of essential genes is very important not only for understanding the minimal requirements for survival of an organism, but also for finding human disease genes and new drug targets. Experimental methods for identifying essential genes are costly, time-consuming, and laborious. With the accumulation of sequenced genomes data and high-throughput experimental data, many computational methods for identifying essential proteins are proposed, which are useful complements to experimental methods. In this review, we show the state-of-the-art methods for identifying essential genes and proteins based on machine learning and network topological features, point out the progress and limitations of current methods, and discuss the challenges and directions for further research. PMID:27014079

Decomposing price differentials due to ENERGY STARR labels and energy efficiency features in appliances: proxy for market share tracking?

International Nuclear Information System (INIS)

Gardner, John; Skumatz, Lisa A.

2005-01-01

This paper summarizes recent work using statistical methods to examine the portions of the apparent price differences for a variety of appliances that are attributable to efficiency labels or components of efficient measures. The work stems from research examining progress in market transformation. The goal was to monitor market progress in the premium associated with efficient equipment compared to standard equipment - and potentially track these changes (hopefully, according to logic, declining) over time. However, the incremental cost metric is always confounded by the fact that the 'feature bundle' on appliances and lighting is not consistent ( i.e. , many efficient products are loaded up with other, high-end features). Based on work conducted by the authors some years ago, we adapted statistical models to decompose the price differentials for efficient and standard refrigerators, clothes washers, and dish washers. The authors used site visits and web searches to gather data on appliance prices and features for a set of efficient and standard models. The authors first examined apparent (raw) price differentials between efficient and standard models. Then, using regression techniques to control for differences in features on the measures, the differences attributable to various features - and in particular to energy efficient features and logos - were estimated. The results showed that while the apparent (gross) price differences for efficient measures are high, the percentage and dollar differences decrease dramatically when the price differences statistically attributable to other features of the measure are accounted for. The work illustrates a promising approach for three important applications in program planning and evaluation: tracking market progress within and between states or service territories, using a proxy variable that is less expensive and complicated to measure than direct indicators of sales or market share, identifying appropriate levels for

Detection of Fraudulent Emails by Employing Advanced Feature Abundance

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Glasdam, Mathies

2014-01-01

In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features...... are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM [1] which is authors' previous cluster based classification model. The experiments have been performed on diverse feature sets...... and the different classification methods. The comparison of the results is also presented and the evaluations shows that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection...

Low-Dimensional Feature Representation for Instrument Identification

Science.gov (United States)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

Features of the Manufacturing Vision Development Process

DEFF Research Database (Denmark)

Dukovska-Popovska, Iskra; Riis, Jens Ove; Boer, Harry

2005-01-01

of action research. The methodology recommends wide participation of people from different hierarchical and functional positions, who engage in a relatively short, playful and creative process and come up with a vision (concept) for the future manufacturing system in the company. Based on three case studies......This paper discusses the key features of the process of Manufacturing Vision Development, a process that enables companies to develop their future manufacturing concept. The basis for the process is a generic five-phase methodology (Riis and Johansen, 2003) developed as a result of ten years...... of companies going through the initial phases of the methodology, this research identified the key features of the Manufacturing Vision Development process. The paper elaborates the key features by defining them, discussing how and when they can appear, and how they influence the process....

Critical features of acute stress-induced cross-sensitization identified through the hypothalamic-pituitary-adrenal axis output.

Science.gov (United States)

Belda, Xavier; Nadal, Roser; Armario, Antonio

2016-08-11

Stress-induced sensitization represents a process whereby prior exposure to severe stressors leaves animals or humans in a hyper-responsive state to further stressors. Indeed, this phenomenon is assumed to be the basis of certain stress-associated pathologies, including post-traumatic stress disorder and psychosis. One biological system particularly prone to sensitization is the hypothalamic-pituitary-adrenal (HPA) axis, the prototypic stress system. It is well established that under certain conditions, prior exposure of animals to acute and chronic (triggering) stressors enhances HPA responses to novel (heterotypic) stressors on subsequent days (e.g. raised plasma ACTH and corticosterone levels). However, such changes remain somewhat controversial and thus, the present study aimed to identify the critical characteristics of the triggering and challenging stressors that affect acute stress-induced HPA cross-sensitization in adult rats. We found that HPA cross-sensitization is markedly influenced by the intensity of the triggering stressor, whereas the length of exposure mainly affects its persistence. Importantly, HPA sensitization is more evident with mild than strong challenging stressors, and it may remain unnoticed if exposure to the challenging stressor is prolonged beyond 15 min. We speculate that heterotypic HPA sensitization might have developed to optimize biologically adaptive responses to further brief stressors.

IDGenerator: unique identifier generator for epidemiologic or clinical studies

Directory of Open Access Journals (Sweden)

Matthias Olden

2016-09-01

Full Text Available Abstract Background Creating study identifiers and assigning them to study participants is an important feature in epidemiologic studies, ensuring the consistency and privacy of the study data. The numbering system for identifiers needs to be random within certain number constraints, to carry extensions coding for organizational information, or to contain multiple layers of numbers per participant to diversify data access. Available software can generate globally-unique identifiers, but identifier-creating tools meeting the special needs of epidemiological studies are lacking. We have thus set out to develop a software program to generate IDs for epidemiological or clinical studies. Results Our software IDGenerator creates unique identifiers that not only carry a random identifier for a study participant, but also support the creation of structured IDs, where organizational information is coded into the ID directly. This may include study center (for multicenter-studies, study track (for studies with diversified study programs, or study visit (baseline, follow-up, regularly repeated visits. Our software can be used to add a check digit to the ID to minimize data entry errors. It facilitates the generation of IDs in batches and the creation of layered IDs (personal data ID, study data ID, temporary ID, external data ID to ensure a high standard of data privacy. The software is supported by a user-friendly graphic interface that enables the generation of IDs in both standard text and barcode 128B format. Conclusion Our software IDGenerator can create identifiers meeting the specific needs for epidemiologic or clinical studies to facilitate study organization and data privacy. IDGenerator is freeware under the GNU General Public License version 3; a Windows port and the source code can be downloaded at the Open Science Framework website: https://osf.io/urs2g/ .

Identifying novel hypoxia-associated markers of chemoresistance in ovarian cancer.

LENUS (Irish Health Repository)

McEvoy, Lynda M

2015-01-01

Ovarian cancer is associated with poor long-term survival due to late diagnosis and development of chemoresistance. Tumour hypoxia is associated with many features of tumour aggressiveness including increased cellular proliferation, inhibition of apoptosis, increased invasion and metastasis, and chemoresistance, mostly mediated through hypoxia-inducible factor (HIF)-1α. While HIF-1α has been associated with platinum resistance in a variety of cancers, including ovarian, relatively little is known about the importance of the duration of hypoxia. Similarly, the gene pathways activated in ovarian cancer which cause chemoresistance as a result of hypoxia are poorly understood. This study aimed to firstly investigate the effect of hypoxia duration on resistance to cisplatin in an ovarian cancer chemoresistance cell line model and to identify genes whose expression was associated with hypoxia-induced chemoresistance.

Microarray-based large scale detection of single feature ...

Indian Academy of Sciences (India)

2015-12-08

Dec 8, 2015 ... mental stages was used to identify single feature polymorphisms (SFPs). ... on a high-density oligonucleotide expression array in which. ∗ ..... The sign (+/−) with SFPs indicates direction of polymorphism. In the. (−) sign (i.e. ...

Effect of feature-selective attention on neuronal responses in macaque area MT

Science.gov (United States)

Chen, X.; Hoffmann, K.-P.; Albright, T. D.

2012-01-01

Attention influences visual processing in striate and extrastriate cortex, which has been extensively studied for spatial-, object-, and feature-based attention. Most studies exploring neural signatures of feature-based attention have trained animals to attend to an object identified by a certain feature and ignore objects/displays identified by a different feature. Little is known about the effects of feature-selective attention, where subjects attend to one stimulus feature domain (e.g., color) of an object while features from different domains (e.g., direction of motion) of the same object are ignored. To study this type of feature-selective attention in area MT in the middle temporal sulcus, we trained macaque monkeys to either attend to and report the direction of motion of a moving sine wave grating (a feature for which MT neurons display strong selectivity) or attend to and report its color (a feature for which MT neurons have very limited selectivity). We hypothesized that neurons would upregulate their firing rate during attend-direction conditions compared with attend-color conditions. We found that feature-selective attention significantly affected 22% of MT neurons. Contrary to our hypothesis, these neurons did not necessarily increase firing rate when animals attended to direction of motion but fell into one of two classes. In one class, attention to color increased the gain of stimulus-induced responses compared with attend-direction conditions. The other class displayed the opposite effects. Feature-selective activity modulations occurred earlier in neurons modulated by attention to color compared with neurons modulated by attention to motion direction. Thus feature-selective attention influences neuronal processing in macaque area MT but often exhibited a mismatch between the preferred stimulus dimension (direction of motion) and the preferred attention dimension (attention to color). PMID:22170961

DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues.

Science.gov (United States)

Ma, Xin; Guo, Jing; Sun, Xiao

2016-01-01

DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. However, insufficient work has been done on the prediction of DNA-binding proteins from protein sequence information. In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. The hybrid feature contains two types of novel sequence features, which reflect information about the conservation of physicochemical properties of the amino acids, and the binding propensity of DNA-binding residues and non-binding propensities of non-binding residues. The comparisons with each feature demonstrated that these two novel features contributed most to the improvement in predictive ability. Furthermore, to improve the prediction performance of the DNABP model, feature selection using the minimum redundancy maximum relevance (mRMR) method combined with incremental feature selection (IFS) was carried out during the model construction. The results showed that the DNABP model could achieve 86.90% accuracy, 83.76% sensitivity, 90.03% specificity and a Matthews correlation coefficient of 0.727. High prediction accuracy and performance comparisons with previous research suggested that DNABP could be a useful approach to identify DNA-binding proteins from sequence information. The DNABP web server system is freely available at http://www.cbi.seu.edu.cn/DNABP/.

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.

Psychological educational features of professional reflection levels in students of the teacher-training specialties

Directory of Open Access Journals (Sweden)

Asya A. Bekhoeva

2015-03-01

Full Text Available Shaping professional reflection of future teachers is of particular importance in the context of the modernization of the Russian education. However, despite the deep reflection of a problem in Russian pedagogical science the characteristics of development levels of pedagogical reflection among future teacher remains largely fragmented. The paper deals with professional and pedagogical reflection as a process of perceiving essential features of educational process by a teacher, summarizes the main theoretical and methodological approaches to this issue. The research is aimed to identify and describe levels of professional and pedagogical reflection among students. The research is divided in several stages: the stage of theoretical allocation of substantial components of professional pedagogical reflection, the stage of selecting proper research tools, ascertaining stage, and concluding stage. The conceptual basis of the research is to identify the main components that determine the following features of professional and pedagogical reflection: motivational, creative, emotional volitional, communicative, monitoring and evaluative. Based on the empirical results the levels of professional and pedagogical reflection of the students of the teacher-training specialties are identified. The first level is characterized by weak professional reflection and undifferentiated consciousness, self-awareness and self-esteem in the normal course of activities, the second level is associated with certain reflective activity and organization and is characterized by steady demand for professional and personal self-improvement. The indicator of the third level is high development of all components of professional reflection.

The market features of imported non-indigenous polychaetes in Portugal and consequent ecological concerns

Directory of Open Access Journals (Sweden)

Pedro Fidalgo e Costa

2006-12-01

Full Text Available The importance of the market for polychaetes dramatically increased after the discovery of their potential as food in aquaculture. In Portugal, the gathering of polychaetes solely from natural populations is not sufficient to meet market demand, both as bait for sea anglers and as a food item in aquaculture. The requests for worms to polychaete dealers by Portuguese and Spanish seafarms have increased during recent years. Due to the lack of intensive culture of these worms in Portugal and the proximity of southern Spanish farms, a large component of imported polychaetes that arrive in Portugal at Lisbon Airport go directly to Spain by road. In 2002 and 2003 a total of 12,728,379 and 16,866,839 polychaetes respectively were imported to Europe via Lisbon Airport from China and the USA. In 2003 the imports from China and the USA realised 716,180 and 291,845 US dollars respectively. Two species were reported to have been imported in these years, namely the Korean blue ragworm Perinereis aibuhitensis and the American bloodworm Glycera dibranchiata. Imports of non-indigenous species, which are traded and sold alive, may increase the risk of accidental introduction into the wild. This is of special concern as Perinereis aibuhitensis has been successfully reared in captivity within the range of environmental conditions existing in the Ria Formosa coastal lagoon. Other risks associated with introduced species are the transport of foreign pathogens and other associated non-native organisms, which may act as carriers of disease.

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.

Mobility as a feature: Evidence from Zulu

Directory of Open Access Journals (Sweden)

Jochen Zeller

2016-01-01

Full Text Available This paper provides evidence for the view that syntactic movement of an element Y to a position X is not driven by features of the target X, but by features of the moving element Y. The data that constitute evidence for this type of analysis come from A-bar movement constructions (object left and right dislocation; object relativisation in the Bantu language Zulu. As I show, only object-DPs that move out of the VP in Zulu are active Goals for Agree-relations and can trigger object agreement with the verb. The fact that the functional head responsible for object agreement must be able to identify a DP in its c-command domain as an active Goal entails that the “mobility” of this DP must be encoded as a property of the DP. Based on this conclusion, I also discuss two proposals about the nature of the feature that activates a DP for movement in Zulu and examine the conditions that determine how this feature is checked and deleted through movement.

Synoptic evaluation of scale-dependent metrics for hydrographic line feature geometry

Science.gov (United States)

Stanislawski, Larry V.; Buttenfield, Barbara P.; Raposo, Paulo; Cameron, Madeline; Falgout, Jeff T.

2015-01-01

Methods of acquisition and feature simplification for vector feature data impact cartographic representations and scientific investigations of these data, and are therefore important considerations for geographic information science (Haunert and Sester 2008). After initial collection, linear features may be simplified to reduce excessive detail or to furnish a reduced-scale version of the features through cartographic generalization (Regnauld and McMaster 2008, Stanislawski et al. 2014). A variety of algorithms exist to simplify linear cartographic features, and all of the methods affect the positional accuracy of the features (Shahriari and Tao 2002, Regnauld and McMaster 2008, Stanislawski et al. 2012). In general, simplification operations are controlled by one or more tolerance parameters that limit the amount of positional change the operation can make to features. Using a single tolerance value can have varying levels of positional change on features; depending on local shape, texture, or geometric characteristics of the original features (McMaster and Shea 1992, Shahriari and Tao 2002, Buttenfield et al. 2010). Consequently, numerous researchers have advocated calibration of simplification parameters to control quantifiable properties of resulting changes to the features (Li and Openshaw 1990, Raposo 2013, Tobler 1988, Veregin 2000, and Buttenfield, 1986, 1989).This research identifies relations between local topographic conditions and geometric characteristics of linear features that are available in the National Hydrography Dataset (NHD). The NHD is a comprehensive vector dataset of surface 18 th ICA Workshop on Generalisation and Multiple Representation, Rio de Janiero, Brazil 2015 2 water features within the United States that is maintained by the U.S. Geological Survey (USGS). In this paper, geometric characteristics of cartographic representations for natural stream and river features are summarized for subbasin watersheds within entire regions of the

Standard Pathologic Features Can Be Used to Identify a Subset of Estrogen Receptor-Positive, HER2 Negative Patients Likely to Benefit from Neoadjuvant Chemotherapy.

Science.gov (United States)

Petruolo, Oriana A; Pilewskie, Melissa; Patil, Sujata; Barrio, Andrea V; Stempel, Michelle; Wen, Hannah Y; Morrow, Monica

2017-09-01

The benefit of neoadjuvant chemotherapy (NAC) in patients with estrogen receptor-positive (ER+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancers and in invasive lobular carcinoma (ILC) is uncertain due to the low rates of pathologic complete response (pCR). The aim of this study was to determine if pathologic features can identify subsets likely to benefit from NAC. Patients with stage I-III ER+, HER2- breast cancer receiving NAC were retrospectively reviewed. Endpoints were downstaging to breast-conserving surgery (BCS) and nodal pCR after NAC. Patients were grouped by progesterone receptor (PR) status and grade/differentiation (high grade or poor [HP] vs. non-HP). From 2007 to 2016, 402 ER+/HER2- cancers in patients receiving NAC were identified. Median age was 50 years, 98% were clinical stage II-III, and 75% were cN+. Overall pCR rate was 5%; breast pCR in 7% and nodal pCR in 15% of cN+ patients (p benefit from NAC are those with PR- and HP tumors. Patients with ILC are unlikely to downstage in the breast or axilla compared with IDC. The use of these criteria can assist in defining the initial treatment approach.

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.

Identifying the Universal part of TMDs

CERN Document Server

Van der Veken, F.F.

2016-01-01

We attempt to identify a path layout in the definition of transverse-momentum-dependent T-odd parton distribution functions (TMD)s which combines features of both, initial- and final-state interactions, so that it remains universal despite the fact that the Wilson lines entering such TMDs change their orientation. The generic structure of the quark correlator for this path layout is calculated.

Importance of bistatic SAR features from TanDEM-X for forest mapping and monitoring

NARCIS (Netherlands)

Schlund, M.; Poncet, von F.; Hoekman, D.H.; Kuntz, S.; Schmullius, C.

2014-01-01

Deforestation and forest degradation are one of the important sources for human induced carbon dioxide emissions and their rates are highest in tropical forests. For man-kind, it is of great importance to track land-use conversions like deforestation, e.g. for sustainable forest management and land

Classifying web pages with visual features

NARCIS (Netherlands)

de Boer, V.; van Someren, M.; Lupascu, T.; Filipe, J.; Cordeiro, J.

2010-01-01

To automatically classify and process web pages, current systems use the textual content of those pages, including both the displayed content and the underlying (HTML) code. However, a very important feature of a web page is its visual appearance. In this paper, we show that using generic visual

Use of feature extraction techniques for the texture and context information in ERTS imagery. [discrimination of land use categories in Kansas from MSS textural-spectral features

Science.gov (United States)

Haralick, R. M.; Kelly, G. L. (Principal Investigator); Bosley, R. J.

1973-01-01

The author has identified the following significant results. The land use category of subimage regions over Kansas within an MSS image can be identified with an accuracy of about 70% using the textural-spectral features of the multi-images from the four MSS bands.

Imaging features of automated breast volume scanner: Correlation with molecular subtypes of breast cancer

Energy Technology Data Exchange (ETDEWEB)

Zheng, Feng-Yang, E-mail: fyzheng16@fudan.edu.cn [Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Shanghai Institute of Medical Imaging, Shanghai 200032 (China); Lu, Qing, E-mail: lu.qing@zs-hospital.sh.cn [Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Huang, Bei-Jian, E-mail: huang.beijian@zs-hospital.sh.cn [Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Shanghai Institute of Medical Imaging, Shanghai 200032 (China); Xia, Han-Sheng, E-mail: zs12036@126.com [Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Yan, Li-Xia, E-mail: dndyanlixia@163.com [Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Wang, Xi, E-mail: wang.xi@zs-hospital.sh.cn [Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Shanghai Institute of Medical Imaging, Shanghai 200032 (China); Yuan, Wei, E-mail: yuan.wei@zs-hospital.sh.cn [Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Wang, Wen-Ping, E-mail: wang.wenping@zs-hospital.sh.cn [Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032 (China); Shanghai Institute of Medical Imaging, Shanghai 200032 (China)

2017-01-15

Highlights: • ABVS imaging features have a strong correlation with breast cancer molecular subtypes. • Retraction phenomenon on the coronal planes was the most important predictor for Luminal A and Triple Negative subtypes. • ABVS expand the scope of ultrasound in identifying breast cancer molecular subtypes. - Abstract: Objectives: To investigate the correlation between the imaging features obtained by an automated breast volume scanner (ABVS) and molecular subtypes of breast cancer. Methods: We examined 303 malignant breast tumours by ABVS for specific imaging features and by immunohistochemical analysis to determine the molecular subtype. ABVS imaging features, including retraction phenomenon, shape, margins, echogenicity, post-acoustic features, echogenic halo, and calcifications were analysed by univariate and multivariate logistic regression analyses to determine the significant predictive factors of the molecular subtypes. Results: By univariate logistic regression analysis, the predictive factors of the Luminal-A subtype (n = 128) were retraction phenomenon (odds ratio [OR] = 10.188), post-acoustic shadowing (OR = 5.112), and echogenic halo (OR = 3.263, P < 0.001). The predictive factors of the Human-epidermal-growth-factor-receptor-2-amplified subtype (n = 39) were calcifications (OR = 6.210), absence of retraction phenomenon (OR = 4.375), non-mass lesions (OR = 4.286, P < 0.001), absence of echogenic halo (OR = 3.851, P = 0.035), and post-acoustic enhancement (OR = 3.641, P = 0.008). The predictors for the Triple-Negative subtype (n = 47) were absence of retraction phenomenon (OR = 5.884), post-acoustic enhancement (OR = 5.255, P < 0.001), absence of echogenic halo (OR = 4.138, P = 0.002), and absence of calcifications (OR = 3.363, P = 0.001). Predictors for the Luminal-B subtype (n = 89) had a relatively lower association (OR ≤ 2.328). By multivariate logistic regression analysis, retraction phenomenon was the strongest independent predictor for

Imaging features of automated breast volume scanner: Correlation with molecular subtypes of breast cancer

International Nuclear Information System (INIS)

Zheng, Feng-Yang; Lu, Qing; Huang, Bei-Jian; Xia, Han-Sheng; Yan, Li-Xia; Wang, Xi; Yuan, Wei; Wang, Wen-Ping

2017-01-01

Highlights: • ABVS imaging features have a strong correlation with breast cancer molecular subtypes. • Retraction phenomenon on the coronal planes was the most important predictor for Luminal A and Triple Negative subtypes. • ABVS expand the scope of ultrasound in identifying breast cancer molecular subtypes. - Abstract: Objectives: To investigate the correlation between the imaging features obtained by an automated breast volume scanner (ABVS) and molecular subtypes of breast cancer. Methods: We examined 303 malignant breast tumours by ABVS for specific imaging features and by immunohistochemical analysis to determine the molecular subtype. ABVS imaging features, including retraction phenomenon, shape, margins, echogenicity, post-acoustic features, echogenic halo, and calcifications were analysed by univariate and multivariate logistic regression analyses to determine the significant predictive factors of the molecular subtypes. Results: By univariate logistic regression analysis, the predictive factors of the Luminal-A subtype (n = 128) were retraction phenomenon (odds ratio [OR] = 10.188), post-acoustic shadowing (OR = 5.112), and echogenic halo (OR = 3.263, P < 0.001). The predictive factors of the Human-epidermal-growth-factor-receptor-2-amplified subtype (n = 39) were calcifications (OR = 6.210), absence of retraction phenomenon (OR = 4.375), non-mass lesions (OR = 4.286, P < 0.001), absence of echogenic halo (OR = 3.851, P = 0.035), and post-acoustic enhancement (OR = 3.641, P = 0.008). The predictors for the Triple-Negative subtype (n = 47) were absence of retraction phenomenon (OR = 5.884), post-acoustic enhancement (OR = 5.255, P < 0.001), absence of echogenic halo (OR = 4.138, P = 0.002), and absence of calcifications (OR = 3.363, P = 0.001). Predictors for the Luminal-B subtype (n = 89) had a relatively lower association (OR ≤ 2.328). By multivariate logistic regression analysis, retraction phenomenon was the strongest independent predictor for