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

Directory of Open Access Journals (Sweden)

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

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

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Fulcher, Ben D; Jones, Nick S

2017-11-22

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

Automated Feature Design for Time Series Classification by Genetic Programming

OpenAIRE

Harvey, Dustin Yewell

2014-01-01

Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process contr...

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

Directory of Open Access Journals (Sweden)

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.

Relating interesting quantitative time series patterns with text events and text features

Science.gov (United States)

Wanner, Franz; Schreck, Tobias; Jentner, Wolfgang; Sharalieva, Lyubka; Keim, Daniel A.

2013-12-01

In many application areas, the key to successful data analysis is the integrated analysis of heterogeneous data. One example is the financial domain, where time-dependent and highly frequent quantitative data (e.g., trading volume and price information) and textual data (e.g., economic and political news reports) need to be considered jointly. Data analysis tools need to support an integrated analysis, which allows studying the relationships between textual news documents and quantitative properties of the stock market price series. In this paper, we describe a workflow and tool that allows a flexible formation of hypotheses about text features and their combinations, which reflect quantitative phenomena observed in stock data. To support such an analysis, we combine the analysis steps of frequent quantitative and text-oriented data using an existing a-priori method. First, based on heuristics we extract interesting intervals and patterns in large time series data. The visual analysis supports the analyst in exploring parameter combinations and their results. The identified time series patterns are then input for the second analysis step, in which all identified intervals of interest are analyzed for frequent patterns co-occurring with financial news. An a-priori method supports the discovery of such sequential temporal patterns. Then, various text features like the degree of sentence nesting, noun phrase complexity, the vocabulary richness, etc. are extracted from the news to obtain meta patterns. Meta patterns are defined by a specific combination of text features which significantly differ from the text features of the remaining news data. Our approach combines a portfolio of visualization and analysis techniques, including time-, cluster- and sequence visualization and analysis functionality. We provide two case studies, showing the effectiveness of our combined quantitative and textual analysis work flow. The workflow can also be generalized to other

Classification of biosensor time series using dynamic time warping: applications in screening cancer cells with characteristic biomarkers.

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Rai, Shesh N; Trainor, Patrick J; Khosravi, Farhad; Kloecker, Goetz; Panchapakesan, Balaji

2016-01-01

The development of biosensors that produce time series data will facilitate improvements in biomedical diagnostics and in personalized medicine. The time series produced by these devices often contains characteristic features arising from biochemical interactions between the sample and the sensor. To use such characteristic features for determining sample class, similarity-based classifiers can be utilized. However, the construction of such classifiers is complicated by the variability in the time domains of such series that renders the traditional distance metrics such as Euclidean distance ineffective in distinguishing between biological variance and time domain variance. The dynamic time warping (DTW) algorithm is a sequence alignment algorithm that can be used to align two or more series to facilitate quantifying similarity. In this article, we evaluated the performance of DTW distance-based similarity classifiers for classifying time series that mimics electrical signals produced by nanotube biosensors. Simulation studies demonstrated the positive performance of such classifiers in discriminating between time series containing characteristic features that are obscured by noise in the intensity and time domains. We then applied a DTW distance-based k -nearest neighbors classifier to distinguish the presence/absence of mesenchymal biomarker in cancer cells in buffy coats in a blinded test. Using a train-test approach, we find that the classifier had high sensitivity (90.9%) and specificity (81.8%) in differentiating between EpCAM-positive MCF7 cells spiked in buffy coats and those in plain buffy coats.

Sonographic features of thyroid nodules that may help distinguish clinically atypical subacute thyroiditis from thyroid malignancy.

Science.gov (United States)

Pan, Fu-shun; Wang, Wei; Wang, Yan; Xu, Ming; Liang, Jin-yu; Zheng, Yan-ling; Xie, Xiao-yan; Li, Xiao-xi

2015-04-01

The purpose of this study was to evaluate sonographic features for distinguishing clinically atypical subacute thyroiditis from malignant thyroid nodules. A total of 165 hypoechoic thyroid nodules without calcification in 135 patients with histologic diagnosis were included in this study. These nodules were classified into 2 groups: a thyroiditis group (55 nodules in 36 patients) and a malignancy group (110 nodules in 99 patients). The sonographic features of the groups were retrospectively reviewed. No significant differences were detected for the variables of marked echogenicity, a taller-than-wide shape, and mixed vascularity. However, a poorly defined margin was detected more frequently in the thyroiditis group than the malignancy group (P thyroiditis, with sensitivity and specificity of 87.3% and 80.9%, respectively. Centripetal reduction echogenicity was observed exclusively in the thyroiditis group, with high specificity (100%) but low sensitivity (21.8%) for atypical subacute thyroiditis diagnosis. All of the thyroiditis nodules with a positive color signal showed noninternal vascularity (negative predictive value, 100%). There is a considerable overlap between the sonographic features of atypical subacute thyroiditis and thyroid malignancy. However, the margin, echogenicity, and vascularity type are helpful indicators for differential diagnosis of atypical subacute thyroiditis. © 2015 by the American Institute of Ultrasound in Medicine.

Hidden discriminative features extraction for supervised high-order time series modeling.

Science.gov (United States)

Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2016-11-01

In this paper, an orthogonal Tucker-decomposition-based extraction of high-order discriminative subspaces from a tensor-based time series data structure is presented, named as Tensor Discriminative Feature Extraction (TDFE). TDFE relies on the employment of category information for the maximization of the between-class scatter and the minimization of the within-class scatter to extract optimal hidden discriminative feature subspaces that are simultaneously spanned by every modality for supervised tensor modeling. In this context, the proposed tensor-decomposition method provides the following benefits: i) reduces dimensionality while robustly mining the underlying discriminative features, ii) results in effective interpretable features that lead to an improved classification and visualization, and iii) reduces the processing time during the training stage and the filtering of the projection by solving the generalized eigenvalue issue at each alternation step. Two real third-order tensor-structures of time series datasets (an epilepsy electroencephalogram (EEG) that is modeled as channel×frequency bin×time frame and a microarray data that is modeled as gene×sample×time) were used for the evaluation of the TDFE. The experiment results corroborate the advantages of the proposed method with averages of 98.26% and 89.63% for the classification accuracies of the epilepsy dataset and the microarray dataset, respectively. These performance averages represent an improvement on those of the matrix-based algorithms and recent tensor-based, discriminant-decomposition approaches; this is especially the case considering the small number of samples that are used in practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantifying memory in complex physiological time-series.

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Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

A Two-Dimensional Solar Tracking Stationary Guidance Method Based on Feature-Based Time Series

Directory of Open Access Journals (Sweden)

Keke Zhang

2018-01-01

Full Text Available The amount of satellite energy acquired has a direct impact on operational capacities of the satellite. As for practical high functional density microsatellites, solar tracking guidance design of solar panels plays an extremely important role. Targeted at stationary tracking problems incurred in a new system that utilizes panels mounted in the two-dimensional turntable to acquire energies to the greatest extent, a two-dimensional solar tracking stationary guidance method based on feature-based time series was proposed under the constraint of limited satellite attitude coupling control capability. By analyzing solar vector variation characteristics within an orbit period and solar vector changes within the whole life cycle, such a method could be adopted to establish a two-dimensional solar tracking guidance model based on the feature-based time series to realize automatic switching of feature-based time series and stationary guidance under the circumstance of different β angles and the maximum angular velocity control, which was applicable to near-earth orbits of all orbital inclination. It was employed to design a two-dimensional solar tracking stationary guidance system, and a mathematical simulation for guidance performance was carried out in diverse conditions under the background of in-orbit application. The simulation results show that the solar tracking accuracy of two-dimensional stationary guidance reaches 10∘ and below under the integrated constraints, which meet engineering application requirements.

Time series analysis of the developed financial markets' integration using visibility graphs

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Zhuang, Enyu; Small, Michael; Feng, Gang

2014-09-01

A time series representing the developed financial markets' segmentation from 1973 to 2012 is studied. The time series reveals an obvious market integration trend. To further uncover the features of this time series, we divide it into seven windows and generate seven visibility graphs. The measuring capabilities of the visibility graphs provide means to quantitatively analyze the original time series. It is found that the important historical incidents that influenced market integration coincide with variations in the measured graphical node degree. Through the measure of neighborhood span, the frequencies of the historical incidents are disclosed. Moreover, it is also found that large "cycles" and significant noise in the time series are linked to large and small communities in the generated visibility graphs. For large cycles, how historical incidents significantly affected market integration is distinguished by density and compactness of the corresponding communities.

TU-D-207B-01: A Prediction Model for Distinguishing Radiation Necrosis From Tumor Progression After Gamma Knife Radiosurgery Based On Radiomics Features From MR Images

International Nuclear Information System (INIS)

Zhang, Z; Ho, A; Wang, X; Brown, P; Guha-Thakurta, N; Ferguson, S; Fave, X; Zhang, L; Mackin, D; Court, L; Li, J; Yang, J

2016-01-01

Purpose: To develop and validate a prediction model using radiomics features extracted from MR images to distinguish radiation necrosis from tumor progression for brain metastases treated with Gamma knife radiosurgery. Methods: The images used to develop the model were T1 post-contrast MR scans from 71 patients who had had pathologic confirmation of necrosis or progression; 1 lesion was identified per patient (17 necrosis and 54 progression). Radiomics features were extracted from 2 images at 2 time points per patient, both obtained prior to resection. Each lesion was manually contoured on each image, and 282 radiomics features were calculated for each lesion. The correlation for each radiomics feature between two time points was calculated within each group to identify a subset of features with distinct values between two groups. The delta of this subset of radiomics features, characterizing changes from the earlier time to the later one, was included as a covariate to build a prediction model using support vector machines with a cubic polynomial kernel function. The model was evaluated with a 10-fold cross-validation. Results: Forty radiomics features were selected based on consistent correlation values of approximately 0 for the necrosis group and >0.2 for the progression group. In performing the 10-fold cross-validation, we narrowed this number down to 11 delta radiomics features for the model. This 11-delta-feature model showed an overall prediction accuracy of 83.1%, with a true positive rate of 58.8% in predicting necrosis and 90.7% for predicting tumor progression. The area under the curve for the prediction model was 0.79. Conclusion: These delta radiomics features extracted from MR scans showed potential for distinguishing radiation necrosis from tumor progression. This tool may be a useful, noninvasive means of determining the status of an enlarging lesion after radiosurgery, aiding decision-making regarding surgical resection versus conservative medical

TU-D-207B-01: A Prediction Model for Distinguishing Radiation Necrosis From Tumor Progression After Gamma Knife Radiosurgery Based On Radiomics Features From MR Images

Energy Technology Data Exchange (ETDEWEB)

Zhang, Z [Central South University Xiangya Hospital, Changsha, Hunan (China); MD Anderson Cancer Center, Houston, TX (United States); Ho, A [University of Houston, Houston, TX (United States); Wang, X; Brown, P; Guha-Thakurta, N; Ferguson, S; Fave, X; Zhang, L; Mackin, D; Court, L; Li, J; Yang, J [MD Anderson Cancer Center, Houston, TX (United States)

2016-06-15

Purpose: To develop and validate a prediction model using radiomics features extracted from MR images to distinguish radiation necrosis from tumor progression for brain metastases treated with Gamma knife radiosurgery. Methods: The images used to develop the model were T1 post-contrast MR scans from 71 patients who had had pathologic confirmation of necrosis or progression; 1 lesion was identified per patient (17 necrosis and 54 progression). Radiomics features were extracted from 2 images at 2 time points per patient, both obtained prior to resection. Each lesion was manually contoured on each image, and 282 radiomics features were calculated for each lesion. The correlation for each radiomics feature between two time points was calculated within each group to identify a subset of features with distinct values between two groups. The delta of this subset of radiomics features, characterizing changes from the earlier time to the later one, was included as a covariate to build a prediction model using support vector machines with a cubic polynomial kernel function. The model was evaluated with a 10-fold cross-validation. Results: Forty radiomics features were selected based on consistent correlation values of approximately 0 for the necrosis group and >0.2 for the progression group. In performing the 10-fold cross-validation, we narrowed this number down to 11 delta radiomics features for the model. This 11-delta-feature model showed an overall prediction accuracy of 83.1%, with a true positive rate of 58.8% in predicting necrosis and 90.7% for predicting tumor progression. The area under the curve for the prediction model was 0.79. Conclusion: These delta radiomics features extracted from MR scans showed potential for distinguishing radiation necrosis from tumor progression. This tool may be a useful, noninvasive means of determining the status of an enlarging lesion after radiosurgery, aiding decision-making regarding surgical resection versus conservative medical

HIV is Now a Manageable Long-Term Condition, But What Makes it Unique? A Qualitative Study Exploring Views About Distinguishing Features from Multi-Professional HIV Specialists in North West England.

Science.gov (United States)

Jelliman, Pauline; Porcellato, Lorna

HIV is evolving from a life-threatening infection to a long-term, manageable condition because of medical advances, radical changes in health and social care policy, and the impact of an aging population. However, HIV remains complex, presenting unique characteristics distinguishing it from other long-term conditions (LTCs). Our aim in this qualitative descriptive study was to identify and explore these features in the context of LTCs. A focus group (FG) method was used to gather the views and experiences of multi-professional HIV specialists who worked in North West England. Twenty-four staff participated in FGs (n = 3), which were audio recorded, manually transcribed, and thematically analyzed. We found four main themes: (a) stigma, (b) challenges faced by HIV specialists, (c) lack HIV-related knowledge, and (d) unique features, termed "stand alone." We concluded that these distinguishing features hindered full recognition and acceptance of HIV as an LTC. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

The Hues of English. NCTE Distinguished Lectures 1969.

Science.gov (United States)

National Council of Teachers of English, Champaign, IL.

The third volume in the NCTE Distinguished Lectures Series, this collection of papers includes (1) William Stafford on poetry and the language of everyday life, (2) Fred Stocking linking Shakespeare to his time and all time by analysing "temperance" in Sonnet 18, (3) Alan Downer discussing the nature of comedy in drama and the universal…

Complex network approach to characterize the statistical features of the sunspot series

International Nuclear Information System (INIS)

Zou, Yong; Liu, Zonghua; Small, Michael; Kurths, Jürgen

2014-01-01

Complex network approaches have been recently developed as an alternative framework to study the statistical features of time-series data. We perform a visibility-graph analysis on both the daily and monthly sunspot series. Based on the data, we propose two ways to construct the network: one is from the original observable measurements and the other is from a negative-inverse-transformed series. The degree distribution of the derived networks for the strong maxima has clear non-Gaussian properties, while the degree distribution for minima is bimodal. The long-term variation of the cycles is reflected by hubs in the network that span relatively large time intervals. Based on standard network structural measures, we propose to characterize the long-term correlations by waiting times between two subsequent events. The persistence range of the solar cycles has been identified over 15–1000 days by a power-law regime with scaling exponent γ = 2.04 of the occurrence time of two subsequent strong minima. In contrast, a persistent trend is not present in the maximal numbers, although maxima do have significant deviations from an exponential form. Our results suggest some new insights for evaluating existing models. (paper)

Distinguishing synchronous from metachronous manifestation of distant metastases: a prognostic feature in differentiated thyroid carcinoma

Energy Technology Data Exchange (ETDEWEB)

Sabet, Amir [University Duisburg-Essen, Department of Nuclear Medicine, Essen (Germany); Saarland University Hospital, Department of Nuclear Medicine, Homburg (Germany); Binse, Ina; Koch, Andrea; Rosenbaum-Krumme, Sandra J. [University Duisburg-Essen, Department of Nuclear Medicine, Essen (Germany); Dogan, Semih; Biersack, Hans-Juergen [University Hospital, Department of Nuclear Medicine, Bonn (Germany); Biermann, Kim [University Hospital, Department of Nuclear Medicine, Bonn (Germany); Confessional Hospital ' ' Barmherzige Brueder' ' , Department of Radiology and Nuclear Medicine, Trier (Germany); Ezziddin, Samer [Saarland University Hospital, Department of Nuclear Medicine, Homburg (Germany); University Hospital, Department of Nuclear Medicine, Bonn (Germany)

2017-02-15

Distant metastasis has a negative impact on survival in differentiated thyroid carcinoma (DTC). The timing of this manifestation, however, is of unknown prognostic relevance. The aim of this retrospective study was to investigate the potential significance of discriminating synchronous versus metachronous distant metastases (SDM vs. MDM) for the outcome of patients with DTC. We retrospectively analyzed a consecutive cohort of n = 89 patients with distant metastases of DTC (43 with follicular, 46 with papillary DTC histology; mean age 52.6 ± 17.7 years) undergoing radioiodine treatment at our institution. All patients were treated with the same protocol consisting of ablative radioiodine therapy (RIT, 3.7 GBq) and one post-ablation treatment after 3 months (3.7-11.1 GBq). Further cycles of RIT were administered for recurrent, progressive or newly developed metastatic disease. We distinguished 2 types of distant metastases according to the time of manifestation: SDM (within ≤12 months after DTC diagnosis) and MDM (occurring >12 months after diagnosis). Tumor-related survival was analyzed using the Kaplan-Meier method. Uni- and multivariate analyses including the Cox proportional hazards model were performed with a significance level of p < 0.05. The mean follow-up period was 13.8 ± 1.2 years. SDM were present in 49 (55.1 %), MDM in 40 (44.9 %) patients. MDM were associated with shorter tumor-related survival (p = 0.002). 5-year and 10-year survival rates were 68.5 % and 34.8 % for MDM, and 84.3 % and 66.9 % for SDM, respectively. Within both age subgroups of <45 and ≥45 years, SDM were also linked with longer survival. No effect on tumor-related survival was found for the co-variables sex, lymph node metastases and histologic type. Distinguishing synchronous from metachronous manifestation of distant metastases may add an important prognostic feature to risk stratification in DTC, as proven metachronous appearance is associated with impaired survival. (orig.)

Sleep Spindle Detection and Prediction Using a Mixture of Time Series and Chaotic Features

Directory of Open Access Journals (Sweden)

Amin Hekmatmanesh

2017-01-01

Full Text Available It is well established that sleep spindles (bursts of oscillatory brain electrical activity are significant indicators of learning, memory and some disease states. Therefore, many attempts have been made to detect these hallmark patterns automatically. In this pilot investigation, we paid special attention to nonlinear chaotic features of EEG signals (in combination with linear features to investigate the detection and prediction of sleep spindles. These nonlinear features included: Higuchi's, Katz's and Sevcik's Fractal Dimensions, as well as the Largest Lyapunov Exponent and Kolmogorov's Entropy. It was shown that the intensity map of various nonlinear features derived from the constructive interference of spindle signals could improve the detection of the sleep spindles. It was also observed that the prediction of sleep spindles could be facilitated by means of the analysis of these maps. Two well-known classifiers, namely the Multi-Layer Perceptron (MLP and the K-Nearest Neighbor (KNN were used to distinguish between spindle and non-spindle patterns. The MLP classifier produced a~high discriminative capacity (accuracy = 94.93%, sensitivity = 94.31% and specificity = 95.28% with significant robustness (accuracy ranging from 91.33% to 94.93%, sensitivity varying from 91.20% to 94.31%, and specificity extending from 89.79% to 95.28% in separating spindles from non-spindles. This classifier also generated the best results in predicting sleep spindles based on chaotic features. In addition, the MLP was used to find out the best time window for predicting the sleep spindles, with the experimental results reaching 97.96% accuracy.

Detecting dynamical changes in time series by using the Jensen Shannon divergence

Science.gov (United States)

Mateos, D. M.; Riveaud, L. E.; Lamberti, P. W.

2017-08-01

Most of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between chaotic and aleatory signals is difficult because they have a common wide band power spectrum, a delta like autocorrelation function, and share other features as well. In general, signals are presented as continuous records and require to be discretized for being analyzed. In this work, we introduce different schemes for discretizing and for detecting dynamical changes in time series. One of the main motivations is to detect transitions between the chaotic and random regime. The tools here used here originate from the Information Theory. The schemes proposed are applied to simulated and real life signals, showing in all cases a high proficiency for detecting changes in the dynamics of the associated time series.

Scoring system to distinguish uncomplicated from complicated acute appendicitis

NARCIS (Netherlands)

Atema, J. J.; van Rossem, C. C.; Leeuwenburgh, M. M.; Stoker, J.; Boermeester, M. A.

2015-01-01

Non-operative management may be an alternative for uncomplicated appendicitis, but preoperative distinction between uncomplicated and complicated disease is challenging. This study aimed to develop a scoring system based on clinical and imaging features to distinguish uncomplicated from complicated

Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

Science.gov (United States)

Jiang, Zhixing; Zhang, David; Lu, Guangming

2018-04-19

Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.

Activity recognition from minimal distinguishing subsequence mining

Science.gov (United States)

Iqbal, Mohammad; Pao, Hsing-Kuo

2017-08-01

Human activity recognition is one of the most important research topics in the era of Internet of Things. To separate different activities given sensory data, we utilize a Minimal Distinguishing Subsequence (MDS) mining approach to efficiently find distinguishing patterns among different activities. We first transform the sensory data into a series of sensor triggering events and operate the MDS mining procedure afterwards. The gap constraints are also considered in the MDS mining. Given the multi-class nature of most activity recognition tasks, we modify the MDS mining approach from a binary case to a multi-class one to fit the need for multiple activity recognition. We also study how to select the best parameter set including the minimal and the maximal support thresholds in finding the MDSs for effective activity recognition. Overall, the prediction accuracy is 86.59% on the van Kasteren dataset which consists of four different activities for recognition.

Evaluating public awareness of new currency design features

Science.gov (United States)

DiNunzio, Lisa; Church, Sara E.

2002-04-01

One of the goals of the 1996 series design was to integrate highly recognizable features that enable the general public to more easily distinguish counterfeit from genuine notes, thereby reducing the chance of counterfeit notes being passed. The purpose of this study is to evaluate how knowledgeable the public is concerning the new currency, to identify the channels through which the public learns about new currency design, and to assess the usefulness of the new currency's authentication features. Also, the study will serve as a baseline measurement for future design studies and in comparative analysis with other countries. The results of the qualitative research will be described in the following sections of this paper. The quantitative research is scheduled to begin in February 2002, at the same time as the Netherlands' opinion poll of the Euro and NLG-notes in an effort to compare results.

Distinguishing among potential mechanisms of singleton suppression.

Science.gov (United States)

Gaspelin, Nicholas; Luck, Steven J

2018-04-01

Previous research has revealed that people can suppress salient stimuli that might otherwise capture visual attention. The present study tests between 3 possible mechanisms of visual suppression. According to first-order feature suppression models , items are suppressed on the basis of simple feature values. According to second-order feature suppression models , items are suppressed on the basis of local discontinuities within a given feature dimension. According to global-salience suppression models , items are suppressed on the basis of their dimension-independent salience levels. The current study distinguished among these models by varying the predictability of the singleton color value. If items are suppressed by virtue of salience alone, then it should not matter whether the singleton color is predictable. However, evidence from probe processing and eye movements indicated that suppression is possible only when the color values are predictable. Moreover, the ability to suppress salient items developed gradually as participants gained experience with the feature that defined the salient distractor. These results are consistent with first-order feature suppression models, and are inconsistent with the other models of suppression. In other words, people primarily suppress salient distractors on the basis of their simple features and not on the basis of salience per se. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Identification of pests and diseases of Dalbergia hainanensis based on EVI time series and classification of decision tree

Science.gov (United States)

Luo, Qiu; Xin, Wu; Qiming, Xiong

2017-06-01

In the process of vegetation remote sensing information extraction, the problem of phenological features and low performance of remote sensing analysis algorithm is not considered. To solve this problem, the method of remote sensing vegetation information based on EVI time-series and the classification of decision-tree of multi-source branch similarity is promoted. Firstly, to improve the time-series stability of recognition accuracy, the seasonal feature of vegetation is extracted based on the fitting span range of time-series. Secondly, the decision-tree similarity is distinguished by adaptive selection path or probability parameter of component prediction. As an index, it is to evaluate the degree of task association, decide whether to perform migration of multi-source decision tree, and ensure the speed of migration. Finally, the accuracy of classification and recognition of pests and diseases can reach 87%--98% of commercial forest in Dalbergia hainanensis, which is significantly better than that of MODIS coverage accuracy of 80%--96% in this area. Therefore, the validity of the proposed method can be verified.

A novel distinguishing system for the diagnosis of malignant pancreatic cystic neoplasm

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Shen, Xiaoyong, E-mail: shanlixinc@163.com [Department of Radiology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (China); Lu, Di, E-mail: lcyxld@126.com [Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (China); Xu, Xiao, E-mail: zdyyxx@163.com [Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (China); Wang, Jianguo, E-mail: 21118059@zju.edu.cn [Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (China); Wu, Jian, E-mail: drwujian@hotmail.com [Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (China); Yan, Sheng, E-mail: shengyan@zju.edu.cn [Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (China); Zheng, Shu-sen, E-mail: zyzss@zju.edu.cn [Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (China)

2013-11-01

Purpose: To explore a simple and reliable non-invasive distinguishing system for the pre-operative evaluation of malignancy in pancreatic cystic neoplasm (PCN). Methods: This study first enrolled an observation cohort of 102 consecutive PCN patients. Demographic information, results of laboratory examinations, and computed tomography (CT) presentations were recorded and analyzed to achieve a distinguishing model/system for malignancy. A group of 21 patients was then included to validate the model/system prospectively. Results: Based on the 11 malignancy-related features identified by univariate analysis, a distinguishing model for malignancy in PCN was established by multivariate analysis: PCN malignant score = 2.967 × elevated fasting blood glucose (FBG) (≥6.16 mmol/L) ± 4.496 × asymmetrically thickened wall (or mural nodules ≥ 4 mm) ± 1.679 × septum thickening (≥2 mm) − 5.134. With the optimal cut-off value selected as −2.8 in reference to the Youden index, the proposed system for malignant PCN was established: septum thickening (>2 mm), asymmetrically thickened wall (or mural nodules > 4 mm), or elevated FBG (>6.16 mmol/L, accompanying commonly known malignant signs), the presence of at least one of these 3 features indicated malignancy in PCN. The accuracy, sensitivity and specificity of this system were 81.4%, 95.8% and 76.9%, respectively. MRI was performed on 32 patients, making correct prediction of malignancy explicitly in only 68.8% (22/32). The subsequent prospective validation study showed that the proposed distinguishing system had a predictive accuracy of 85.7% (18/21). Moreover, a higher model score, or aggregation of the features in the proposed system, indicated a higher grade of malignancy (carcinoma) in PCN. Conclusion: Elevated FBG (>6.16 mmol/L), asymmetrically thickened wall (or mural nodules > 4 mm) and septum thickening (>2 mm) are of great value in differentiating the malignancy in PCN. The developed distinguishing system is

Performance analysis of power swing blocking feature in ABB 670 series impedance relays

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Maciej Łosiński

2012-12-01

Full Text Available This paper presents test results of a distance protection’s PSD power swing detection feature in ABB 670 series relays. A RED670 relay was tested, which is part of the hydroelectric set protection in Żarnowiec Pumped Storage Plant. The power swing blocking feature’s performance was analysed on the basis of the results of object tests made with an Omicron digital tester. Also presented are simulation results that illustrate the PSD feature’s response to power swings caused by a disturbance in the power system. It is also shown how a distance protection may react to the same fault, depending on its settings.

Plasma complement biomarkers distinguish multiple sclerosis and neuromyelitis optica spectrum disorder.

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Hakobyan, Svetlana; Luppe, Sebastian; Evans, David Rs; Harding, Katharine; Loveless, Samantha; Robertson, Neil P; Morgan, B Paul

2017-06-01

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are autoimmune inflammatory demyelinating diseases of the central nervous system. Although distinguished by clinicoradiological and demographic features, early manifestations can be similar complicating management. Antibodies against aquaporin-4 support the diagnosis of NMOSD but are negative in some patients. Therefore, there is unmet need for biomarkers that enable early diagnosis and disease-specific intervention. We investigated whether plasma complement proteins are altered in MS and NMOSD and provide biomarkers that distinguish these diseases. Plasma from 54 NMOSD, 40 MS and 69 control donors was tested in multiplex assays measuring complement activation products and proteins. Using logistic regression, we tested whether combinations of complement analytes distinguished NMOSD from controls and MS. All activation products were elevated in NMOSD compared to either control or MS. Four complement proteins (C1inh, C1s, C5 and FH) were higher in NMOSD compared to MS or controls. A model comprising C1inh and terminal complement complex (TCC) distinguished NMOSD from MS (area under the curve (AUC): 0.98), while C1inh and C5 distinguished NMOSD from controls (AUC: 0.94). NMOSD is distinguished from MS by plasma complement biomarkers. Selected complement analytes enable differential diagnosis. Findings support trials of anti-complement therapies in NMOSD.

Distinguish self- and hetero-perceived stress through behavioral imaging and physiological features.

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Spodenkiewicz, Michel; Aigrain, Jonathan; Bourvis, Nadège; Dubuisson, Séverine; Chetouani, Mohamed; Cohen, David

2018-03-02

Stress reactivity is a complex phenomenon associated to multiple and multimodal expressions. Response to stressors has an obvious survival function and may be seen as an internal regulation to adapt to threat or danger. The intensity of this internal response can be assessed as the self-perception of the stress response. In species with social organization, this response also serves a communicative function, so-called hetero-perception. Our study presents multimodal stress detection assessment - a new methodology combining behavioral imaging and physiological monitoring for analyzing stress from these two perspectives. The system is based on automatic extraction of 39 behavioral (2D+3D video recording) and 62 physiological (Nexus-10 recording) features during a socially evaluated mental arithmetic test. The analysis with machine learning techniques for automatic classification using Support Vector Machine (SVM) show that self-perception and hetero-perception of social stress are both close but different phenomena: self-perception was significantly correlated with hetero-perception but significantly differed from it. Also, assessing stress with SVM through multimodality gave excellent classification results (F1 score values: 0.9±0.012 for hetero-perception and 0.87±0.021 for self-perception). In the best selected feature subsets, we found some common behavioral and physiological features that allow classification of both self- and hetero-perceived stress. However, we also found the contributing features for automatic classifications had opposite distributions: self-perception classification was mainly based on physiological features and hetero-perception was mainly based on behavioral features. Copyright © 2017. Published by Elsevier Inc.

DISTINGUISHED CHARACTERISTICS OF INFECTIVE ENDOCARDITIS IN HIV/AIDS AMONG INTRAVENOUS DRUGS ABUSED

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E. Y. Ponomareva

2011-01-01

Full Text Available The aim – definition of distinguished characteristics of the right-sided infective endocarditis (IE inintravenous drugs abused with human immunodeficiency virus (HIV/acquired immunodeficiency syndrome (AIDS.Materials and methods. The study included 10 patients with right-sided IE in conjunction with HIV/AIDS. All patients were male, age – from 28to 36 years.Results. Course of the IE in HIV/AIDS among intravenous drugs abused in general corresponds to features specific to IE in intravenous drug users without HIV infection. Distinctive features of IE in these patients are a large burden of lung disease, its disseminated character, more tissue oxygenation disorders and marked pulmonary hypertension and haematological disorders (lymphopenia, anemia, and late diagnosis of IE.Conclusion. Features of the current right-sided IE in intravenous drugs abused with HIV/AIDS are distinguished . Difficulties in diagnosis of IE inHIV infection are due to variety of causes of prolonged fever, which should guide doctors to more frequent use of transthoracic echocardiography during prolonged fever in HIV-infected patients.

Infectious mononucleosis mimicking lymphoma: distinguishing morphological and immunophenotypic features.

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Louissaint, Abner; Ferry, Judith A; Soupir, Chad P; Hasserjian, Robert P; Harris, Nancy L; Zukerberg, Lawrence R

2012-08-01

The diagnosis of infectious mononucleosis (acute Epstein-Barr virus (EBV) infection) is usually made on the basis of clinical and laboratory findings. However, an atypical clinical presentation occasionally results in a lymph node or tonsillar biopsy. The morphological features of EBV-infected lymphoid tissue can easily mimic lymphoma. Furthermore, the immunophenotype of the immunoblasts has not been well characterized. To assess the morphological spectrum of acute EBV infection and the utility of immunohistochemistry in diagnosing difficult cases that resemble lymphoma, we reviewed 18 cases of acute EBV infection submitted in consultation to our institution with an initial diagnosis of/or suspicion for lymphoma. Patients included nine male and nine female individuals with a median age of 18 years (range 9-69). Biopsies were obtained from lymph nodes (3/18) or Waldeyer's ring (15/18). Infectious mononucleosis was confirmed by monospot or serological assays in 72% of cases (13/18). All cases featured architectural distortion by a polymorphous infiltrate with an immunoblastic proliferation, sometimes forming sheets. Reed-Sternberg-like cells were present in 8/18 (44%) of the cases. Infiltrates were often accompanied by necrosis (10/18) and mucosal ulceration (6/15). The majority of immunoblasts in all cases were CD20+ B cells with a post-germinal center immunophenotype (strongly positive for MUM1/IRF4 (18/18), CD10- (18/18 negative) and BCL-6- (16/18 negative; 2/18 faint BCL-6 expression in mononucleosis, and warrants additional consideration before a diagnosis of lymphoma is made.

Cloud and surface textural features in polar regions

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Welch, Ronald M.; Kuo, Kwo-Sen; Sengupta, Sailes K.

1990-01-01

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

Model distinguishability and inference robustness in mechanisms of cholera transmission and loss of immunity

OpenAIRE

Lee, Elizabeth C.; Kelly, Michael R.; Ochocki, Brad M.; Akinwumi, Segun M.; Hamre, Karen E. S.; Tien, Joseph H.; Eisenberg, Marisa C.

2016-01-01

Mathematical models of cholera and waterborne disease vary widely in their structures, in terms of transmission pathways, loss of immunity, and other features. These differences may yield different predictions and parameter estimates from the same data. Given the increasing use of models to inform public health decision-making, it is important to assess distinguishability (whether models can be distinguished based on fit to data) and inference robustness (whether model inferences are robust t...

Case series and descriptive cohort studies in neurosurgery: the confusion and solution.

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Esene, Ignatius N; Ngu, Julius; El Zoghby, Mohamed; Solaroglu, Ihsan; Sikod, Anna M; Kotb, Ali; Dechambenoit, Gilbert; El Husseiny, Hossam

2014-08-01

Case series (CS) are well-known designs in contemporary use in neurosurgery but are sometimes used in contexts that are incompatible with their true meaning as defined by epidemiologists. This inconsistent, inappropriate and incorrect use, and mislabeling impairs the appropriate indexing and sorting of evidence. Using PubMed, we systematically identified published articles that had "case series" in the "title" in 15 top-ranked neurosurgical journals from January 2008 to December 2012. The abstracts and/or full articles were scanned to identify those with descriptions of the principal method as being "case series" and then classified as "true case series" or "non-case series" by two independent investigators with 100 % inter-rater agreement. Sixty-four articles had the label "case series" in their "titles." Based on the definition of "case series" and our appraisal of the articles using Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, 18 articles (28.13 %) were true case series, while 46 (71.87 %) were mislabeled. Thirty-five articles (54.69 %) mistook retrospective (descriptive) cohorts for CS. CS are descriptive with an outcome-based sampling, while "descriptive cohorts" have an exposure-based sampling of patients, followed over time to assess outcome(s). A comparison group is not a defining feature of a cohort study and distinguishes descriptive from analytic cohorts. A distinction between a case report, case series, and descriptive cohorts is absolutely necessary to enable the appropriate indexing, sorting, and application of evidence. Researchers need better training in methods and terminology, and editors and reviewers should scrutinize more carefully manuscripts claiming to be "case series" studies.

Characterizing time series via complexity-entropy curves

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Ribeiro, Haroldo V.; Jauregui, Max; Zunino, Luciano; Lenzi, Ervin K.

2017-06-01

The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis q entropy) and after considering the proper generalization of the statistical complexity (q complexity), we build up a parametric curve (the q -complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.

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

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Treisman, A; Souther, J

1985-09-01

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

The distinguishing motor features of cataplexy: a study from video-recorded attacks.

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Pizza, Fabio; Antelmi, Elena; Vandi, Stefano; Meletti, Stefano; Erro, Roberto; Baumann, Christian R; Bhatia, Kailash P; Dauvilliers, Yves; Edwards, Mark J; Iranzo, Alex; Overeem, Sebastiaan; Tinazzi, Michele; Liguori, Rocco; Plazzi, Giuseppe

2018-05-01

To describe the motor pattern of cataplexy and to determine its phenomenological differences from pseudocataplexy in the differential diagnosis of episodic falls. We selected 30 video-recorded cataplexy and 21 pseudocataplexy attacks in 17 and 10 patients evaluated for suspected narcolepsy and with final diagnosis of narcolepsy type 1 and conversion disorder, respectively, together with self-reported attacks features, and asked expert neurologists to blindly evaluate the motor features of the attacks. Video documented and self-reported attack features of cataplexy and pseudocataplexy were contrasted. Video-recorded cataplexy can be positively differentiated from pseudocataplexy by the occurrence of facial hypotonia (ptosis, mouth opening, tongue protrusion) intermingled by jerks and grimaces abruptly interrupting laughter behavior (i.e. smile, facial expression) and postural control (head drops, trunk fall) under clear emotional trigger. Facial involvement is present in both partial and generalized cataplexy. Conversely, generalized pseudocataplexy is associated with persistence of deep tendon reflexes during the attack. Self-reported features confirmed the important role of positive emotions (laughter, telling a joke) in triggering the attacks, as well as the more frequent occurrence of partial body involvement in cataplexy compared with pseudocataplexy. Cataplexy is characterized by abrupt facial involvement during laughter behavior. Video recording of suspected cataplexy attacks allows the identification of positive clinical signs useful for diagnosis and, possibly in the future, for severity assessment.

Distinguishing stress fractures from pathologic fractures: a multimodality approach

International Nuclear Information System (INIS)

Fayad, Laura M.; Kamel, Ihab R.; Kawamoto, Satomi; Bluemke, David A.; Fishman, Elliot K.; Frassica, Frank J.

2005-01-01

Whereas stress fractures occur in normal or metabolically weakened bones, pathologic fractures occur at the site of a bone tumor. Unfortunately, stress fractures may share imaging features with pathologic fractures on plain radiography, and therefore other modalities are commonly utilized to distinguish these entities. Additional cross-sectional imaging with CT or MRI as well as scintigraphy and PET scanning is often performed for further evaluation. For the detailed assessment of a fracture site, CT offers a high-resolution view of the bone cortex and periosteum which aids the diagnosis of a pathologic fracture. The character of underlying bone marrow patterns of destruction can also be ascertained along with evidence of a soft tissue mass. MRI, however, is a more sensitive technique for the detection of underlying bone marrow lesions at a fracture site. In addition, the surrounding soft tissues, including possible involvement of adjacent muscle, can be well evaluated with MRI. While bone scintigraphy and FDG-PET are not specific, they offer a whole-body screen for metastases in the case of a suspected malignant pathologic fracture. In this review, we present select examples of fractures that underscore imaging features that help distinguish stress fractures from pathologic fractures, since accurate differentiation of these entities is paramount. (orig.)

Distinguishing the rates of gene activation from phenotypic variations

OpenAIRE

Chen, Ye; Lv, Cheng; Li, Fangting; Li, Tiejun

2015-01-01

Background Stochastic genetic switching driven by intrinsic noise is an important process in gene expression. When the rates of gene activation/inactivation are relatively slow, fast, or medium compared with the synthesis/degradation rates of mRNAs and proteins, the variability of protein and mRNA levels may exhibit very different dynamical patterns. It is desirable to provide a systematic approach to identify their key dynamical features in different regimes, aiming at distinguishing which r...

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

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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.

Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia

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Dana Mastrovito

Full Text Available Autism and schizophrenia share overlapping genetic etiology, common changes in brain structure and common cognitive deficits. A number of studies using resting state fMRI have shown that machine learning algorithms can distinguish between healthy controls and individuals diagnosed with either autism spectrum disorder or schizophrenia. However, it has not yet been determined whether machine learning algorithms can be used to distinguish between the two disorders. Using a linear support vector machine, we identify features that are most diagnostic for each disorder and successfully use them to classify an independent cohort of subjects. We find both common and divergent connectivity differences largely in the default mode network as well as in salience, and motor networks. Using divergent connectivity differences, we are able to distinguish autistic subjects from those with schizophrenia. Understanding the common and divergent connectivity changes associated with these disorders may provide a framework for understanding their shared cognitive deficits. Keywords: Schizophrenia, Autism, Resting state, Classification, Connectivity, fMRI, Default mode network

Distinguishing the relevant features of frequent suicide attempters.

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

2011-05-01

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

Clinical features of symptomatic patellofemoral joint osteoarthritis

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2012-01-01

Introduction Patellofemoral joint osteoarthritis (OA) is common and leads to pain and disability. However, current classification criteria do not distinguish between patellofemoral and tibiofemoral joint OA. The objective of this study was to provide empirical evidence of the clinical features of patellofemoral joint OA (PFJOA) and to explore the potential for making a confident clinical diagnosis in the community setting. Methods This was a population-based cross-sectional study of 745 adults aged ≥50 years with knee pain. Information on risk factors and clinical signs and symptoms was gathered by a self-complete questionnaire, and standardised clinical interview and examination. Three radiographic views of the knee were obtained (weight-bearing semi-flexed posteroanterior, supine skyline and lateral) and individuals were classified into four subsets (no radiographic OA, isolated PFJOA, isolated tibiofemoral joint OA, combined patellofemoral/tibiofemoral joint OA) according to two different cut-offs: 'any OA' and 'moderate to severe OA'. A series of binary logistic and multinomial regression functions were performed to compare the clinical features of each subset and their ability in combination to discriminate PFJOA from other subsets. Results Distinctive clinical features of moderate to severe isolated PFJOA included a history of dramatic swelling, valgus deformity, markedly reduced quadriceps strength, and pain on patellofemoral joint compression. Mild isolated PFJOA was barely distinguished from no radiographic OA (AUC 0.71, 95% CI 0.66, 0.76) with only difficulty descending stairs and coarse crepitus marginally informative over age, sex and body mass index. Other cardinal signs of knee OA - the presence of effusion, bony enlargement, reduced flexion range of movement, mediolateral instability and varus deformity - were indicators of tibiofemoral joint OA. Conclusions Early isolated PFJOA is clinically manifest in symptoms and self-reported functional

Morphological and anatomical relationships in Alpine-Dinaric populations of the genus Iris L., Pallidae series (A. Kern. Trinajstić (Iridaceae

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Bożena Mitić

2014-01-01

Full Text Available The relationships within the Alpine-Dinaric and cultivated populations of the genus Iris, Pallidae series, have been analysed. Seven morphological characteristics (stem length, length of the largest leaf, greatest width of the largest leaf, length of the smallest leaf, greatest width of the smallest leaf, the number of leaves and the number of flowers and seven leaf anatomical (length and width of stomata, length and width of epidermal cells, number of stomata and epidermal cells per mm'- and length of styloids have been used for this purpose. Relationships between populations were analysed by methods of multivariate statistics (Cluster, PCA and MST analyses. The results of Cluster and PCA analyses showed that, owing to leaf anatomical features, five main groups of the populations could be distinguished within the Pallidae series. Four of them belong to the species L. pallida, L. cengialti, L. illyrica and I. pseudopallida. The MST analyses showed that the fifth group contained mixed populations of I. illyrica and I. pseudopallida. The results point at the lack of taxonomic usefulness of the leaf anatomical features analysed and indicate that they caused successive geographical differentiation of the populations of the Pallidae series.

Distinguishing the Transcription Regulation Patterns in Promoters of Human Genes with Different Function or Evolutionary Age

KAUST Repository

Alam, Tanvir

2012-07-01

Distinguishing transcription regulatory patterns of different gene groups is a common problem in various bioinformatics studies. In this work we developed a methodology to deal with such a problem based on machine learning techniques. We applied our method to two biologically important problems related to detecting a difference in transcription regulation of: a/ protein-coding and long non-coding RNAs (lncRNAs) in human, as well as b/ a difference between primate-specific and non-primate-specific long non-coding RNAs. Our method is capable to classify RNAs using various regulatory features of genes that transcribe into these RNAs, such as nucleotide frequencies, transcription factor binding sites, de novo sequence motifs, CpG islands, repetitive elements, histone modification marks, and others. Ten-fold cross-validation tests suggest that our model can distinguish protein-coding and non-coding RNAs with accuracy above 80%. Twenty-fold cross-validation tests suggest that our model can distinguish primate-specific from non-primate-specific promoters of lncRNAs with accuracy above 80%. Consequently, we can hypothesize that transcription of the groups of genes mentioned above are regulated by different mechanisms. Feature selection techniques allowed us to reduce the number of features significantly while keeping the accuracy around 80%. Consequently, we can conclude that selected features play significant role in transcription regulation of coding and non-coding genes, as well as primate-specific and non-primate-specific lncRNA genes.

Distinguishing Features of Cuban Children Referred for Professional Help Because of ADHD: Looking beyond the Symptoms

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Schneider, Barry H.; Normand, Sebastien; Sotares deToro, Maria del Pilar; Santana Gonzalez, Yorkys; Guilarte Tellez, Jorge Antonio; Carbonell Naranjo, Migdalia; Musle, Miriam; Diaz Socarras, Felix Javier; Robaey, Philippe

2011-01-01

Objective: To distinguish Cuban children clinically referred because of ADHD from an at-risk community sample and a community control group in terms of symptoms, associated difficulties and impairment of family and peer relations. Method: Parents and teachers of 1,036 children (6-8 years old) completed an established ADHD rating scale and a…

Memory-Based Specification of Verbal Features for Classifying Animals into Super-Ordinate and Sub-Ordinate Categories

OpenAIRE

Takahiro Soshi; Norio Fujimaki; Atsushi Matsumoto; Aya S. Ihara

2017-01-01

Accumulating evidence suggests that category representations are based on features. Distinguishing features are considered to define categories, because of all-or-none responses for objects in different categories; however, it is unclear how distinguishing features actually classify objects at various category levels. The present study included 75 animals within three classes (mammal, bird, and fish), along with 195 verbal features. Healthy adults participated in memory-based feature-animal m...

Face-iris multimodal biometric scheme based on feature level fusion

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Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

2015-11-01

Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.

Interdisciplinary Distinguished Seminar Series

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2014-08-29

courtesy) at Carnegie Mellon University. Before joining academia, Professor Ricketts spent 8 years in industry developing over 40 intergrated circuits...synchronization landscape. These results have also strong implications for optimization and trade -offs in network synchronization with delays. Prof. Gyorgy

Joint approach based on clinical and imaging features to distinguish non-neoplastic from neoplastic pituitary stalk lesions.

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Ji Ye Lee

Full Text Available Distinguishing non-neoplastic pituitary stalk lesions (non-NPSLs from neoplastic pituitary stalk lesions (NPSLs is a major concern in guiding treatment for a thickened pituitary stalk. Our study aimed to aid provide preoperative diagnostic assistance by combining clinical and magnetic resonance imaging (MRI findings to distinguish non-NPSLs from NPSLs.We recruited 158 patients with thickened pituitary stalk lesions visible on MRI. Laboratory findings included hypopituitarism, diabetes insipidus (DI, and hyperprolactinemia. MR images were assessed for anterior-posterior thickness (mm, diffuse pituitary stalk thickening, cystic changes, a high T1 signal, and glandular or extrasellar involvement. A diagnostic model was developed using a recursive partitioning logistic regression analysis. The model was validated in an independent dataset comprising 63 patients, and its diagnostic performance was compared with that of the original radiological reports.A univariate analysis found significant associations of DI (P = 0.006, absence of extrasellar involvement (P = 0.002, and lower stalk thickness (P = 0.031 with non-NPSLs. A diagnostic model was created using the following parameters (in order of priority: 1 lack of extrasellar involvement, 2 stalk thickness < 5.3 mm, and 3 presence of DI. The diagnostic performance (area under the curve; AUC of this model in the independent set was 0.813, representing a significant improvement over the original radiological reports (AUC: 0.713, P = 0.029.The joint diagnostic approach based on clinical and imaging-based factors robustly distinguished non-NPSLs from NPSLs. This approach could guide treatment strategies and prevent unnecessary surgery in patients with non-NPSL.

76 FR 71048 - Sixth Annual Philip S. Chen, Jr. Distinguished Lecture on Innovation and Technology Transfer

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2011-11-16

... present ``Treatment of Cancer with Recombinant Immunotoxins: From Technology Transfer to the Patient.'' Dr. Pastan is an NIH Distinguished Investigator and Chief, Laboratory of Molecular Biology, National Cancer Institute Center for Cancer Research. This annual series honors Dr. Philip S. Chen, Jr. for his almost 50...

Time series analysis of diverse extreme phenomena: universal features

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Eftaxias, K.; Balasis, G.

2012-04-01

The field of study of complex systems holds that the dynamics of complex systems are founded on universal principles that may used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We suggest that earthquake, epileptic seizures, solar flares, and magnetic storms dynamics can be analyzed within similar mathematical frameworks. A central property of aforementioned extreme events generation is the occurrence of coherent large-scale collective behavior with very rich structure, resulting from repeated nonlinear interactions among the corresponding constituents. Consequently, we apply the Tsallis nonextensive statistical mechanics as it proves an appropriate framework in order to investigate universal principles of their generation. First, we examine the data in terms of Tsallis entropy aiming to discover common "pathological" symptoms of transition to a significant shock. By monitoring the temporal evolution of the degree of organization in time series we observe similar distinctive features revealing significant reduction of complexity during their emergence. Second, a model for earthquake dynamics coming from a nonextensive Tsallis formalism, starting from first principles, has been recently introduced. This approach leads to an energy distribution function (Gutenberg-Richter type law) for the magnitude distribution of earthquakes, providing an excellent fit to seismicities generated in various large geographic areas usually identified as seismic regions. We show that this function is able to describe the energy distribution (with similar non-extensive q-parameter) of solar flares, magnetic storms, epileptic and earthquake shocks. The above mentioned evidence of a universal statistical behavior suggests the possibility of a common approach for studying space weather, earthquakes and epileptic seizures.

Cyclo-speed reducer 6000 series; Saikuro {reg_sign} gensokuki 6000 series

Energy Technology Data Exchange (ETDEWEB)

NONE

2000-04-20

This series was put on the market as the advanced speed reducer '6000 series' in April, 2000 after further improvement of various previous excellent features by adopting innovative technologies. Various series of this cyclo-speed reducers adopting a unique inscribed epicyclic gear mechanism reach 7 million units in sales success. Main specifications: (1) Input capacity range: 0.1-132kW, (2) Output torque: 24-68,200N(center dot)m, (3) Reduction ratio: 6-1,000,000. Features: (1) High efficiency and long life by adopting the analysis system based on the latest analytical technology, (2) Noise reduction by a maximum of nearly 6dB, and tone improvement by adopting a new tooth profile, (3) Weight reduction by a maximum of nearly 40% by adopting a motor direct-coupled mechanism. (translated by NEDO)

Connected to TV series: Quantifying series watching engagement.

Science.gov (United States)

Tóth-Király, István; Bőthe, Beáta; Tóth-Fáber, Eszter; Hága, Győző; Orosz, Gábor

2017-12-01

Background and aims Television series watching stepped into a new golden age with the appearance of online series. Being highly involved in series could potentially lead to negative outcomes, but the distinction between highly engaged and problematic viewers should be distinguished. As no appropriate measure is available for identifying such differences, a short and valid measure was constructed in a multistudy investigation: the Series Watching Engagement Scale (SWES). Methods In Study 1 (N Sample1  = 740 and N Sample2  = 740), exploratory structural equation modeling and confirmatory factor analysis were used to identify the most important facets of series watching engagement. In Study 2 (N = 944), measurement invariance of the SWES was investigated between males and females. In Study 3 (N = 1,520), latent profile analysis (LPA) was conducted to identify subgroups of viewers. Results Five factors of engagement were identified in Study 1 that are of major relevance: persistence, identification, social interaction, overuse, and self-development. Study 2 supported the high levels of equivalence between males and females. In Study 3, three groups of viewers (low-, medium-, and high-engagement viewers) were identified. The highly engaged at-risk group can be differentiated from the other two along key variables of watching time and personality. Discussion The present findings support the overall validity, reliability, and usefulness of the SWES and the results of the LPA showed that it might be useful to identify at-risk viewers before the development of problematic use.

TIGER/Line Shapefile, 2014, Series Information for the All Roads County-based Shapefile

Data.gov (United States)

US Census Bureau, Department of Commerce — The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC)...

Duality between Time Series and Networks

Science.gov (United States)

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

Science.gov (United States)

Savala, Rajiv; Dey, Pranab; Gupta, Nalini

2018-03-01

To distinguish follicular adenoma (FA) and follicular carcinoma (FC) of thyroid in fine needle aspiration cytology (FNAC) is a challenging problem. In this article, we attempted to build an artificial neural network (ANN) model from the cytological and morphometric features of the FNAC smears of thyroid to distinguish FA from FC. The cytological features and morphometric analysis were done on the FNAC smears of histology proven cases of FA (26) and FC (31). The cytological features were analysed semi-quantitatively by two independent observers (RS and PD). These data were used to make an ANN model to differentiate FA versus FC on FNAC material. The performance of this ANN model was assessed by analysing the confusion matrix and receiving operator curve. There were 39 cases in training set, 9 cases each in validation and test sets. In the test group, ANN model successfully distinguished all cases (9/9) of FA and FC. The area under receiver operating curve was 1. The present ANN model is efficient to diagnose follicular adenoma and carcinoma cases on cytology smears without any error. In future, this ANN model will be able to diagnose follicular adenoma and carcinoma cases on thyroid aspirate. This study has immense potential in future. This is an open ended ANN model and more parameters and more cases can be included to make the model much stronger. © 2017 Wiley Periodicals, Inc.

A simple and fast representation space for classifying complex time series

International Nuclear Information System (INIS)

Zunino, Luciano; Olivares, Felipe; Bariviera, Aurelio F.; Rosso, Osvaldo A.

2017-01-01

In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease. - Highlights: • A bidimensional scheme has been tested for classification purposes. • A multiscale generalization is introduced. • Several practical applications confirm its usefulness. • Different sets of financial and physiological data are efficiently distinguished. • This multiscale bidimensional approach has high potential as discriminative tool.

A simple and fast representation space for classifying complex time series

Energy Technology Data Exchange (ETDEWEB)

Zunino, Luciano, E-mail: lucianoz@ciop.unlp.edu.ar [Centro de Investigaciones Ópticas (CONICET La Plata – CIC), C.C. 3, 1897 Gonnet (Argentina); Departamento de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), 1900 La Plata (Argentina); Olivares, Felipe, E-mail: olivaresfe@gmail.com [Instituto de Física, Pontificia Universidad Católica de Valparaíso (PUCV), 23-40025 Valparaíso (Chile); Bariviera, Aurelio F., E-mail: aurelio.fernandez@urv.cat [Department of Business, Universitat Rovira i Virgili, Av. Universitat 1, 43204 Reus (Spain); Rosso, Osvaldo A., E-mail: oarosso@gmail.com [Instituto de Física, Universidade Federal de Alagoas (UFAL), BR 104 Norte km 97, 57072-970, Maceió, Alagoas (Brazil); Instituto Tecnológico de Buenos Aires (ITBA) and CONICET, C1106ACD, Av. Eduardo Madero 399, Ciudad Autónoma de Buenos Aires (Argentina); Complex Systems Group, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de los Andes, Av. Mons. Álvaro del Portillo 12.455, Las Condes, Santiago (Chile)

2017-03-18

In the context of time series analysis considerable effort has been directed towards the implementation of efficient discriminating statistical quantifiers. Very recently, a simple and fast representation space has been introduced, namely the number of turning points versus the Abbe value. It is able to separate time series from stationary and non-stationary processes with long-range dependences. In this work we show that this bidimensional approach is useful for distinguishing complex time series: different sets of financial and physiological data are efficiently discriminated. Additionally, a multiscale generalization that takes into account the multiple time scales often involved in complex systems has been also proposed. This multiscale analysis is essential to reach a higher discriminative power between physiological time series in health and disease. - Highlights: • A bidimensional scheme has been tested for classification purposes. • A multiscale generalization is introduced. • Several practical applications confirm its usefulness. • Different sets of financial and physiological data are efficiently distinguished. • This multiscale bidimensional approach has high potential as discriminative tool.

A Novel Approach for Automatic Machining Feature Recognition with Edge Blend Feature

OpenAIRE

Keong Chen Wong; Yusof Yusri

2017-01-01

This paper presents an algorithm for efficiently recognizing and determining the convexity of an edge blend feature. The algorithm first recognizes all of the edge blend features from the Boundary Representation of a part; then a series of convexity test have been run on the recognized edge blend features. The novelty of the presented algorithm lies in, instead of each recognized blend feature is suppressed as most of researchers did, the recognized blend features of this research are gone th...

Enhanced feature integration in musicians

DEFF Research Database (Denmark)

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

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

Time-series analysis of climatologic measurements: a method to distinguish future climatic changes

International Nuclear Information System (INIS)

Duband, D.

1992-01-01

Time-series analysis of climatic parameters as air temperature, rivers flow rate, lakes or seas level is an indispensable basis to detect a possible significant climatic change. These observations, when they are carefully analyzed and criticized, constitute the necessary reference for testing and validation numerical climatic models which try to simulate the physical and dynamical process of the ocean-atmosphere couple, taking continents into account. 32 refs., 13 figs

Motif distributions in phase-space networks for characterizing experimental two-phase flow patterns with chaotic features.

Science.gov (United States)

Gao, Zhong-Ke; Jin, Ning-De; Wang, Wen-Xu; Lai, Ying-Cheng

2010-07-01

The dynamics of two-phase flows have been a challenging problem in nonlinear dynamics and fluid mechanics. We propose a method to characterize and distinguish patterns from inclined water-oil flow experiments based on the concept of network motifs that have found great usage in network science and systems biology. In particular, we construct from measured time series phase-space complex networks and then calculate the distribution of a set of distinct network motifs. To gain insight, we first test the approach using time series from classical chaotic systems and find a universal feature: motif distributions from different chaotic systems are generally highly heterogeneous. Our main finding is that the distributions from experimental two-phase flows tend to be heterogeneous as well, suggesting the underlying chaotic nature of the flow patterns. Calculation of the maximal Lyapunov exponent provides further support for this. Motif distributions can thus be a feasible tool to understand the dynamics of realistic two-phase flow patterns.

Current features of primary tuberculosis on medical imaging based on a series of fourteen cases

International Nuclear Information System (INIS)

Ouzidane, L.; Adamsbaum, C.; Cohen, P.A.; Kalifa, G.; Gendrel, D.

1995-01-01

Active pulmonary tuberculosis, a source of contamination, is currently undergoing a recrudescence in developed countries, particularly in clinical contexts of immuno-depression. The authors report a retrospective series of 14 cases of primary tuberculosis in a paediatric population (7 girls and 7 boys) with a mean age of 3.5 years (range: 4 months - 16 years) observed over a 3-year period. After reviewing the current radiological features of patent primary tuberculosis, the authors emphasize the contribution of chest CT scan in latent forms with a normal chest x-ray and a difficult bacteriological diagnosis. Imaging remains an essential tool in early diagnosis, therapeutic management and active surveillance of this form. The authors propose a decisional flow-chart in the case of suspected primary tuberculosis in children. (authors). 20 refs., 8 figs

Distinguishing molecular features and clinical characteristics of a putative new rhinovirus species, human rhinovirus C (HRV C.

Directory of Open Access Journals (Sweden)

Peter McErlean

Full Text Available BACKGROUND: Human rhinoviruses (HRVs are the most frequently detected pathogens in acute respiratory tract infections (ARTIs and yet little is known about the prevalence, recurrence, structure and clinical impact of individual members. During 2007, the complete coding sequences of six previously unknown and highly divergent HRV strains were reported. To catalogue the molecular and clinical features distinguishing the divergent HRV strains, we undertook, for the first time, in silico analyses of all available polyprotein sequences and performed retrospective reviews of the medical records of cases in which variants of the prototype strain, HRV-QPM, had been detected. METHODOLOGY/PRINCIPLE FINDINGS: Genomic analyses revealed that the six divergent strains, residing within a clade we previously called HRV A2, had the shortest polyprotein of all picornaviruses investigated. Structure-based amino acid alignments identified conserved motifs shared among members of the genus Rhinovirus as well as substantive deletions and insertions unique to the divergent strains. Deletions mostly affected regions encoding proteins traditionally involved in antigenicity and serving as HRV and HEV receptor footprints. Because the HRV A2 strains cannot yet be cultured, we created homology models of predicted HRV-QPM structural proteins. In silico comparisons confirmed that HRV-QPM was most closely related to the major group HRVs. HRV-QPM was most frequently detected in infants with expiratory wheezing or persistent cough who had been admitted to hospital and required supplemental oxygen. It was the only virus detected in 65% of positive individuals. These observations contributed to an objective clinical impact ranging from mild to severe. CONCLUSIONS: The divergent strains did not meet classification requirements for any existing species of the genus Rhinovirus or Enterovirus. HRV A2 strains should be partitioned into at least one new species, putatively called Human

Feature Assignment in Perception of Auditory Figure

Science.gov (United States)

Gregg, Melissa K.; Samuel, Arthur G.

2012-01-01

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

The Sliced Pineapple Grid Feature for Predicting Grasping Affordances

DEFF Research Database (Denmark)

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

2017-01-01

The problem of grasping unknown objects utilising vision is addressed in this work by introducing a novel feature, the Sliced Pineapple Grid Feature (SPGF). The SPGF encode semi-local surfaces and allows for distinguishing structures such as “walls”,“edges” and “rims”. These structures are shown...

Distinguishing the rates of gene activation from phenotypic variations.

Science.gov (United States)

Chen, Ye; Lv, Cheng; Li, Fangting; Li, Tiejun

2015-06-18

Stochastic genetic switching driven by intrinsic noise is an important process in gene expression. When the rates of gene activation/inactivation are relatively slow, fast, or medium compared with the synthesis/degradation rates of mRNAs and proteins, the variability of protein and mRNA levels may exhibit very different dynamical patterns. It is desirable to provide a systematic approach to identify their key dynamical features in different regimes, aiming at distinguishing which regime a considered gene regulatory network is in from their phenotypic variations. We studied a gene expression model with positive feedbacks when genetic switching rates vary over a wide range. With the goal of providing a method to distinguish the regime of the switching rates, we first focus on understanding the essential dynamics of gene expression system in different cases. In the regime of slow switching rates, we found that the effective dynamics can be reduced to independent evolutions on two separate layers corresponding to gene activation and inactivation states, and the transitions between two layers are rare events, after which the system goes mainly along deterministic ODE trajectories on a particular layer to reach new steady states. The energy landscape in this regime can be well approximated by using Gaussian mixture model. In the regime of intermediate switching rates, we analyzed the mean switching time to investigate the stability of the system in different parameter ranges. We also discussed the case of fast switching rates from the viewpoint of transition state theory. Based on the obtained results, we made a proposal to distinguish these three regimes in a simulation experiment. We identified the intermediate regime from the fact that the strength of cellular memory is lower than the other two cases, and the fast and slow regimes can be distinguished by their different perturbation-response behavior with respect to the switching rates perturbations. We proposed a

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

Science.gov (United States)

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.

Distinguishing Hidden Markov Chains

OpenAIRE

Kiefer, Stefan; Sistla, A. Prasad

2015-01-01

Hidden Markov Chains (HMCs) are commonly used mathematical models of probabilistic systems. They are employed in various fields such as speech recognition, signal processing, and biological sequence analysis. We consider the problem of distinguishing two given HMCs based on an observation sequence that one of the HMCs generates. More precisely, given two HMCs and an observation sequence, a distinguishing algorithm is expected to identify the HMC that generates the observation sequence. Two HM...

Analysis of three amphibian populations with quarter-century long time-series.

OpenAIRE

Meyer, A H; Schimidt, B R; Grossenbacher, K

1998-01-01

Amphibians are in decline in many parts of the world. Long tme-series of amphibian populations are necessary to distinguish declines from the often strong fluctuations observed in natural populations. Time-series may also help to understand the causes of these declines. We analysed 23-28-year long time-series of the frog Rana temporaria. Only one of the three studied populations showed a negative trend which was probably caused by the introduction of fish. Two populations appeared to be densi...

Imaging features of benign adrenal cysts

International Nuclear Information System (INIS)

Sanal, Hatice Tuba; Kocaoglu, Murat; Yildirim, Duzgun; Bulakbasi, Nail; Guvenc, Inanc; Tayfun, Cem; Ucoz, Taner

2006-01-01

Benign adrenal gland cysts (BACs) are rare lesions with a variable histological spectrum and may mimic not only each other but also malignant ones. We aimed to review imaging features of BACs which can be helpful in distinguishing each entity and determining the subsequent appropriate management

Is MRI a useful tool to distinguish between serous and mucinous borderline ovarian tumours?

International Nuclear Information System (INIS)

Bazot, M.; Haouy, D.; Daraï, E.; Cortez, A.; Dechoux-Vodovar, S.; Thomassin-Naggara, I.

2013-01-01

Aim: To analyse the morphological magnetic resonance imaging (MRI) features of borderline ovarian tumours (BOT) and to evaluate whether MRI can be used to distinguish serous from mucinous subtypes. Materials and methods: A retrospective study of 72 patients who underwent BOT resection was undertaken. MRI images were reviewed blindly by two radiologists to assess MRI features: size, tumour type, grouped and irregular thickened septa, number of septa, loculi of different signal intensity, vegetations, solid portion, signal intensity of vegetations, normal ovarian parenchyma, and pelvic ascites. Statistical analysis was performed using Mann–Whitney and Fisher's exact tests. Logistic regression analysis was used to assess the predictive value of the MRI findings for histological subtypes. Results: At histology, there were 33 serous BOT (SBOT) and 39 mucinous BOT (MBOT). Predictive MRI criteria for SBOT were bilaterality, predominantly solid tumour, and the presence of vegetations, especially exophytic or with a high T2 signal (p < 0.01), whereas predictive MRI criteria for MBOT were multilocularity, number of septa, loculi of different signal intensity, and grouped and irregular thickened septa (p < 0.01). Using multivariate analysis, vegetations were independently associated with SBOT [odds ratio (OR) = 29.5] and multilocularity with MBOT (OR = 3.9). Conclusion: Vegetations and multilocularity are two independent MRI features that can help to distinguish between SBOT and MBOT.

Scale-dependent intrinsic entropies of complex time series.

Science.gov (United States)

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

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

Directory of Open Access Journals (Sweden)

Antonio Jose da Rocha

2013-09-01

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

A Feature Fusion Based Forecasting Model for Financial Time Series

Science.gov (United States)

Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

2014-01-01

Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

Memory-Based Specification of Verbal Features for Classifying Animals into Super-Ordinate and Sub-Ordinate Categories

Directory of Open Access Journals (Sweden)

Takahiro Soshi

2017-09-01

Full Text Available Accumulating evidence suggests that category representations are based on features. Distinguishing features are considered to define categories, because of all-or-none responses for objects in different categories; however, it is unclear how distinguishing features actually classify objects at various category levels. The present study included 75 animals within three classes (mammal, bird, and fish, along with 195 verbal features. Healthy adults participated in memory-based feature-animal matching verification tests. Analyses included a hierarchical clustering analysis, support vector machine, and independent component analysis to specify features effective for classifications. Quantitative and qualitative comparisons for significant features were conducted between super-ordinate and sub-ordinate levels. The number of significant features was larger for super-ordinate than sub-ordinate levels. Qualitatively, the proportion of biological features was larger than cultural/affective features in both the levels, while the proportion of affective features increased at the sub-ordinate level. To summarize, the two types of features differentially function to establish category representations.

Audiovisual laughter detection based on temporal features

NARCIS (Netherlands)

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

2008-01-01

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

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.

A Distinguish Attack on COSvd Cipher

OpenAIRE

Mohammad Ali Orumiehchi ha; R. Mirghadri

2007-01-01

The COSvd Ciphers has been proposed by Filiol and others (2004). It is a strengthened version of COS stream cipher family denoted COSvd that has been adopted for at least one commercial standard. We propose a distinguish attack on this version, and prove that, it is distinguishable from a random stream. In the COSvd Cipher used one S-Box (10×8) on the final part of cipher. We focus on S-Box and use weakness this S-Box for distinguish attack. In addition, found a leak on HNLL that the sub s-bo...

TIGER/Line Shapefile, 2015, Series Information for the 2015 TIGER/Line Shapefile All Roads County-based Shapefile

Data.gov (United States)

US Census Bureau, Department of Commerce — The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC)...

Effectiveness of Multivariate Time Series Classification Using Shapelets

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2015-01-01

Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.

Local and Global Distinguishability in Quantum Interferometry

International Nuclear Information System (INIS)

Durkin, Gabriel A.; Dowling, Jonathan P.

2007-01-01

A statistical distinguishability based on relative entropy characterizes the fitness of quantum states for phase estimation. This criterion is employed in the context of a Mach-Zehnder interferometer and used to interpolate between two regimes of local and global phase distinguishability. The scaling of distinguishability in these regimes with photon number is explored for various quantum states. It emerges that local distinguishability is dependent on a discrepancy between quantum and classical rotational energy. Our analysis demonstrates that the Heisenberg limit is the true upper limit for local phase sensitivity. Only the ''NOON'' states share this bound, but other states exhibit a better trade-off when comparing local and global phase regimes

Distinguishing between hypochondriasis and somatization disorder: a review of the existing literature.

Science.gov (United States)

Noyes, Russell; Stuart, Scott; Watson, David B; Langbehn, Douglas R

2006-01-01

A valid classification is important for further understanding of the somatoform disorders. The main disorders in this grouping - somatization disorder and hypochondriasis - have lengthy historical traditions and are defined in a contrasting manner. Various authors point to distinguishing demographic and clinical features, but there have been few direct comparisons of patients with these disorders. A review of the literature indicates those domains where differences are most likely to be found. Research assessing these may serve to refine and validate these key somatoform categories and/or dimensions.

Fall Detection Using Smartphone Audio Features.

Science.gov (United States)

Cheffena, Michael

2016-07-01

An automated fall detection system based on smartphone audio features is developed. The spectrogram, mel frequency cepstral coefficents (MFCCs), linear predictive coding (LPC), and matching pursuit (MP) features of different fall and no-fall sound events are extracted from experimental data. Based on the extracted audio features, four different machine learning classifiers: k-nearest neighbor classifier (k-NN), support vector machine (SVM), least squares method (LSM), and artificial neural network (ANN) are investigated for distinguishing between fall and no-fall events. For each audio feature, the performance of each classifier in terms of sensitivity, specificity, accuracy, and computational complexity is evaluated. The best performance is achieved using spectrogram features with ANN classifier with sensitivity, specificity, and accuracy all above 98%. The classifier also has acceptable computational requirement for training and testing. The system is applicable in home environments where the phone is placed in the vicinity of the user.

Storage of feature conjunctions in transient auditory memory.

Science.gov (United States)

Gomes, H; Bernstein, R; Ritter, W; Vaughan, H G; Miller, J

1997-11-01

The purpose of this study was to determine whether feature conjunctions are stored in transient auditory memory. The mismatch negativity (MMN), an event-related potential that is elicited by stimuli that differ from a series of preceding stimuli, was used in this endeavour. A tone that differed from the preceding series of stimuli in the conjunction of two of its features, both present in preceding stimuli but in different combinations, was found to elicit the MMN. The data are interpreted to indicate that information about the conjunction of features is stored in the memory.

Distinguished trajectories in time dependent vector fields

OpenAIRE

Madrid, J. A. Jimenez; Mancho, Ana M.

2008-01-01

We introduce a new definition of distinguished trajectory that generalizes the concepts of fixed point and periodic orbit to aperiodic dynamical systems. This new definition is valid for identifying distinguished trajectories with hyperbolic and nonhyperbolic types of stability. The definition is implemented numerically and the procedure consists of determining a path of limit coordinates. It has been successfully applied to known examples of distinguished trajectories. In the context of high...

Magnetic resonance imaging of anterior temporal lobe cysts in children: discriminating special imaging features in a particular group of diseases

International Nuclear Information System (INIS)

Hoffmann Nunes, Renato; Torres Pacheco, Felipe; Rocha, Antonio Jose da

2014-01-01

We hypothesized that disorders with anterior temporal lobe (ATL) cysts might exhibit common peculiarities and distinguishable imaging features that could be useful for diagnosis. We reviewed a series of patients for neuroimaging contributions to specific diagnoses. A literature search was conducted, and institutional imaging files were reviewed to identify MR examinations with ATL cysts in children. Patients were divided according to head size, calcifications, white matter and cortical abnormalities. Unsupervised hierarchical clustering of patients on the basis of their MR and CT items was performed. We identified 23 patients in our database in whom MR revealed ATL cysts. Our series included five patients with congenital muscular dystrophy (05/23 = 21.7 %), six with megalencephalic leukoencephalopathy with subcortical cysts (06/23 = 26.1 %), three with non-megalencephalic leukoencephalopathy with subcortical cysts (03/23 = 13.1 %), seven with congenital cytomegalovirus disease (07/23 = 30.4 %) and two with Aicardi-Goutieres syndrome (02/23 = 8.7 %). After analysis, 11 clusters resulted in the highest discriminative indices. Thereafter, patients' clusters were linked to their underlying diseases. The features that best discriminated between clusters included brainstem abnormalities, cerebral calcifications and some peculiar grey and white matter abnormalities. A flow chart was drafted to guide the radiologist in these diagnoses. The authors encourage the combined interpretation of these features in the herein proposed approach that confidently predicted the final diagnosis in this particular group of disorders associated with ATL cysts. (orig.)

Magnetic resonance imaging of anterior temporal lobe cysts in children: discriminating special imaging features in a particular group of diseases

Energy Technology Data Exchange (ETDEWEB)

Hoffmann Nunes, Renato; Torres Pacheco, Felipe; Rocha, Antonio Jose da [Fleury Medicina e Saude, Division of Neuroradiology, Sao Paulo (Brazil); Servico de Diagnostico por Imagem, Division of Neuroradiology, Santa Casa de Misericordia de Sao Paulo Paulo, Sao Paulo (Brazil)

2014-07-15

We hypothesized that disorders with anterior temporal lobe (ATL) cysts might exhibit common peculiarities and distinguishable imaging features that could be useful for diagnosis. We reviewed a series of patients for neuroimaging contributions to specific diagnoses. A literature search was conducted, and institutional imaging files were reviewed to identify MR examinations with ATL cysts in children. Patients were divided according to head size, calcifications, white matter and cortical abnormalities. Unsupervised hierarchical clustering of patients on the basis of their MR and CT items was performed. We identified 23 patients in our database in whom MR revealed ATL cysts. Our series included five patients with congenital muscular dystrophy (05/23 = 21.7 %), six with megalencephalic leukoencephalopathy with subcortical cysts (06/23 = 26.1 %), three with non-megalencephalic leukoencephalopathy with subcortical cysts (03/23 = 13.1 %), seven with congenital cytomegalovirus disease (07/23 = 30.4 %) and two with Aicardi-Goutieres syndrome (02/23 = 8.7 %). After analysis, 11 clusters resulted in the highest discriminative indices. Thereafter, patients' clusters were linked to their underlying diseases. The features that best discriminated between clusters included brainstem abnormalities, cerebral calcifications and some peculiar grey and white matter abnormalities. A flow chart was drafted to guide the radiologist in these diagnoses. The authors encourage the combined interpretation of these features in the herein proposed approach that confidently predicted the final diagnosis in this particular group of disorders associated with ATL cysts. (orig.)

Drunk driving detection based on classification of multivariate time series.

Science.gov (United States)

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Magnetic resonance imaging: a useful tool to distinguish between keratocystic odontogenic tumours and odontogenic cysts.

Science.gov (United States)

Probst, F A; Probst, M; Pautke, Ch; Kaltsi, E; Otto, S; Schiel, S; Troeltzsch, M; Ehrenfeld, M; Cornelius, C P; Müller-Lisse, U G

2015-03-01

In contrast to odontogenic cysts, keratocystic odontogenic tumours often recur and require more aggressive surgical treatment, so we tried to find features that distinguished between them on magnetic resonance imaging (MRI). Without knowing the diagnosis, two radiologists reviewed intensity (low, intermediate, or high) and homogeneity (homogeneous or heterogeneous) of signals in short-tau-inversion-recovery (STIR), T1- and T2-weighted, and fat-suppressed, contrast-enhanced MRI in 20 consecutive patients with oval, radiolucent lesions of the mandible on panoramic radiography, and who were subsequently confirmed histopathologically to have either an odontogenic cyst or a keratocystic odontogenic tumour (n=10 in each group). Fisher's exact test was statistically significant at pkeratocystic odontogenic tumours (3/10, p=0.02, and 1/10, p=0.01, respectively). One radiologist found odontogenic cysts were more likely to be homogeneous on unenhanced T1-weighted images (odontogenic cysts 9/10, keratocystic odontogenic tumours 3/10, p=0.02) and one on contrast-enhanced MRI, when the cyst wall was enhanced (odontogenic cysts 7/9, keratocystic odontogenic tumours 0/3, p=0.01). There were no other significant distinguishing features on MRI. In conclusion, the signal intensity of the enhanced wall seems to be a feature on contrast-enhanced MRI that differentiates odontogenic cysts from keratocystic odontogenic tumours. Copyright © 2014 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Geometry of the Borel - de Siebenthal discrete series

DEFF Research Database (Denmark)

Ørsted, Bent; Wolf, Joseph A

Let G0 be a connected, simply connected real simple Lie group. Suppose that G0 has a compact Cartan subgroup T0, so it has discrete series representations. Relative to T0 there is a distinguished positive root system + for which there is a unique noncompact simple root , the “Borel – de Siebenthal...... system”. There is a lot of fascinating geometry associated to the corresponding “Borel – de Siebenthal discrete series” representations of G0. In this paper we explore some of those geometric aspects and we work out the K0–spectra of the Borel – de Siebenthal discrete series representations. This has...

Beyond Fractals and 1/f Noise: Multifractal Analysis of Complex Physiological Time Series

Science.gov (United States)

Ivanov, Plamen Ch.; Amaral, Luis A. N.; Ashkenazy, Yosef; Stanley, H. Eugene; Goldberger, Ary L.; Hausdorff, Jeffrey M.; Yoneyama, Mitsuru; Arai, Kuniharu

2001-03-01

We investigate time series with 1/f-like spectra generated by two physiologic control systems --- the human heartbeat and human gait. We show that physiological fluctuations exhibit unexpected ``hidden'' structures often described by scaling laws. In particular, our studies indicate that when analyzed on different time scales the heartbeat fluctuations exhibit cascades of branching patterns with self-similar (fractal) properties, characterized by long-range power-law anticorrelations. We find that these scaling features change during sleep and wake phases, and with pathological perturbations. Further, by means of a new wavelet-based technique, we find evidence of multifractality in the healthy human heartbeat even under resting conditions, and show that the multifractal character and nonlinear properties of the healthy heart are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure. In contrast to the heartbeat, we find that the interstride interval time series of healthy human gait, a voluntary process under neural regulation, is described by a single fractal dimension (such as classical 1/f noise) indicating monofractal behavior. Thus our approach can help distinguish physiological and physical signals with comparable frequency spectra and two-point correlations, and guide modeling of their control mechanisms.

Integral and Multidimensional Linear Distinguishers with Correlation Zero

DEFF Research Database (Denmark)

Bogdanov, Andrey; Leander, Gregor; Nyberg, Kaisa

2012-01-01

Zero-correlation cryptanalysis uses linear approximations holding with probability exactly 1/2. In this paper, we reveal fundamental links of zero-correlation distinguishers to integral distinguishers and multidimensional linear distinguishers. We show that an integral implies zero-correlation li...... weak key assumptions. © International Association for Cryptologic Research 2012....

The motor and cognitive features of Parkinson's disease in patients with concurrent Gaucher disease over 2 years: a case series.

Science.gov (United States)

Collins, Lucy M; Williams-Gray, Caroline H; Morris, Elizabeth; Deegan, Patrick; Cox, Timothy M; Barker, Roger A

2018-05-29

We report the cognitive features and progression of Parkinson's disease (PD) in five patients with concurrent Gaucher disease. The patients presented at an earlier age than patients with sporadic PD, as previously noted by others; but in contrast to many previous reports, our patients followed a variable clinical course. While two patients developed early cognitive deficits and dementia, three others remained cognitively intact over the follow-up period. Thus, in this small case series, PD in the context of GD more closely resembles idiopathic PD in terms of its clinical heterogeneity in contrast to PD associated with GBA heterozygote mutations.

Correlation optics in progress: introduction to the feature issue

DEFF Research Database (Denmark)

Angelsky, Oleg V.; Desyatnikov, Anton S.; Gbur, Gregory J.

2014-01-01

This feature issue of Applied Optics contains a series of selected papers reflecting recent progress of correlation optics and showing, in part, the trend from micro-optics to nano-optics.......This feature issue of Applied Optics contains a series of selected papers reflecting recent progress of correlation optics and showing, in part, the trend from micro-optics to nano-optics....

Secondary psychotic features in refugees diagnosed with post-traumatic stress disorder

DEFF Research Database (Denmark)

Nygaard, Mette Kathrine; Sonne, Charlotte Kærgaard; Carlsson, Jessica

2017-01-01

at Competence Centre for Transcultural Psychiatry (CTP) were examined, and all the PTSD patients were divided into two groups; one group with secondary psychotic features (PTSD-SP group) and one without (PTSD group). A categorisation and description of the secondary psychotic features was undertaken. RESULTS......-SP prevalence in a clinical refugee population with PTSD. The study points to the difficulties distinguishing psychotic features from flashbacks and the authors call for attention to psychotic features in PTSD patients in order to improve documentation and understanding of the disorder....

Methods for summing general Kapteyn series

Energy Technology Data Exchange (ETDEWEB)

Tautz, R C [Zentrum fuer Astronomie und Astrophysik, Technische Universitaet Berlin, Hardenbergstrasse 36, D-10623 Berlin (Germany); Lerche, I [Institut fuer Geowissenschaften, Naturwissenschaftliche Fakultaet III, Martin-Luther-Universitaet Halle, D-06099 Halle (Germany); Dominici, D, E-mail: rct@gmx.eu, E-mail: lercheian@yahoo.com, E-mail: dominicd@newpaltz.edu [Department of Mathematics, State University of New York at New Paltz, 1 Hawk Dr, New Paltz, NY 12561-2443 (United States)

2011-09-23

The general features and characteristics of Kapteyn series, which are a special type of series involving the Bessel function, are investigated. For many applications in physics, astrophysics and mathematics, it is crucial to have closed-form expressions in order to determine their functional structure and parametric behavior. The closed-form expressions of Kapteyn series have mostly been limited to special cases, even though there are often similarities in the approaches used to reduce the series to analytically tractable forms. The goal of this paper is to review the previous work in the area and to show that Kapteyn series can be expressed as trigonometric or gamma function series, which can be evaluated in a closed form for specific parameters. Two examples with a similar structure are given, showing the complexity of Kapteyn series. (paper)

Signatures of cytoplasmic proteins in the exoproteome distinguish community- and hospital-associated methicillin-resistant Staphylococcus aureus USA300 lineages

DEFF Research Database (Denmark)

Mekonnen, Solomon A.; Palma Medina, Laura M.; Glasner, Corinna

2017-01-01

Methicillin-resistant Staphylococcus aureus (MRSA) is the common name for a heterogeneous group of highly drug-resistant staphylococci. Two major MRSA classes are distinguished based on epidemiology, namely community-associated (CA) and hospital-associated (HA) MRSA. Notably, the distinction of CA......- and HA-MRSA based on molecular traits remains difficult due to the high genomic plasticity of S. aureus. Here we sought to pinpoint global distinguishing features of CA- and HA-MRSA through a comparative genome and proteome analysis of the notorious MRSA lineage USA300. We show for the first time that CA......- and HA-MRSA isolates can be distinguished by 2 distinct extracellular protein abundance clusters that are predictive not only for epidemiologic behavior, but also for their growth and survival within epithelial cells. This ‘exoproteome profiling’ also groups more distantly related HA-MRSA isolates...

Spectral features of nasals in Standard Latvian

Directory of Open Access Journals (Sweden)

Jana Taperte

2015-12-01

Full Text Available In the article, the acoustic features of nasals in Standard Latvian are investigated. The aim of the study is to examine whether some of the spectral properties of nasal murmur (namely anti-formant frequency, as well as frequency and bandwidth of the first nasal formant can be considered as efficient cues for distinguishing between nasal places of articulation.Speech recordings from 10 native speakers of Standard Latvian, five male and five female, aged 19–39, without any disorders or dialectal traces in their pronunciation, were used for the analysis. Prevocalic nasals [m; n; ɲ] were analyzed in isolated CVC syllables, where C is one of the nasals and V is one of the vowels [i(ː; e(ː; æ(ː; ɑ(ː; ɔ(ː; u(ː]. The velar [ŋ] — the allophone of the phoneme /n/ — was recorded in postvocalic position in [k]V[ŋks] structure units. 1260 items were analyzed in total.According to the results, the nasals of Standard Latvian can be distinguished by anti-formant frequencies rather efficiently, and the results generally agree with those obtained in previous research of Latvian as well as data reported for other languages. The frequencies and the bandwidths of the first nasal formant are less informative regarding nasal place of articulation and can be used only for distinguishing between [ŋ] and [m; n; ɲ]. Conducting perception tests to assess the auditory relevance of these acoustic features is necessary.

Modeling financial time series with S-plus

CERN Document Server

Zivot, Eric

2003-01-01

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics This is the first book to show the power of S-PLUS for the analysis of time series data It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department at the University of Washington, and is co-director of the nascent Professional Master's Program in Computational Finance He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the He...

Time series clustering in large data sets

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2011-01-01

Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.

Comparisons of Circular Transmit and Linear Receive Compact Polarimetric SAR Features for Oil Slicks Discrimination

Directory of Open Access Journals (Sweden)

Yu Li

2015-01-01

Full Text Available Compact polarimetric (CP synthetic aperture radar (SAR has proven its potential in distinguishing oil slicks and look-alikes. Polarimetric information can be retrieved directly from scattering vector or from reconstructed pseudo-Quad-Pol covariance matrix of CP SAR data. In this paper, we analysed features from Circular Transmit and Linear Receive (CTLR CP SAR data that are derived by taking both of these two methods. K-means clustering followed by accuracy assessment was also implemented for performance evaluation. Through experiments that were conducted based on L-band UAVSAR fully polarimetric data, it was found that optimum extraction methods varied for different features. The histogram analysis and segmentation results also demonstrated the comparable performance of CP SAR features in distinguishing different damping properties within oil slicks. This study proposed a framework of statistically analyzing polarimetric SAR (Pol-SAR features and provided guidelines for determining optimum feature extraction methods from CP SAR data and for marine oil-spills detection and classification.

Method for distinguishing fuel pellets

International Nuclear Information System (INIS)

Sagami, Masaharu; Kurihara, Kunitoshi.

1978-01-01

Purpose: To distinguish correctly and efficiently the kind of fuel substance enclosed in a cladding tube. Method: Elements such as manganess 55, copper 65, vanadium 51, zinc 64, scandium 45 and the like, each having a large neutron absorption cross section and discharging gamma rays of inherent bright line spectra are applied to or mixed in fuel pellets of different kinds in uranium enrichment degree, plutonium concentration, burnable poison concentration or the like. These fuel rods are irradiated with neutron beams, and energy spectra of gamma rays discharged upon this occasion are observed to carry out distinguishing of fuel pellets. (Aizawa, K.)

Language categories in Russian morphology

OpenAIRE

زهرایی زهرایی

2009-01-01

When studying Russian morphology, one can distinguish two categories. These categories are “grammatical” and “lexico-grammatical”. Grammatical categories can be specified through a series of grammatical features of words. Considering different criteria, Russian grammarians and linguists divide grammatical categories of their language into different types. In determining lexico-grammatical types, in addition to a series of grammatical features, they also consider a series of lexico-semantic fe...

Depression and anxiety in a case series of amyotrophic lateral sclerosis: frequency and association with clinical features.

Science.gov (United States)

Prado, Laura de Godoy Rousseff; Bicalho, Isabella Carolina Santos; Vidigal-Lopes, Mauro; Prado, Vitor de Godoy Rousseff; Gomez, Rodrigo Santiago; de Souza, Leonardo Cruz; Teixeira, Antônio Lúcio

2017-01-01

To investigate the frequency of anxiety and depression and their association with clinical features of amyotrophic lateral sclerosis. This is a cross-sectional and descriptive study including a consecutive series of patients with sporadic amyotrophic lateral sclerosis according to Awaji's criteria. Patients underwent clinical and psychiatric assessment (anxiety and depression symptoms). We included 76 patients. The men/women ratio was 1.6:1. Participants' mean age at disease onset was 55 years (SD±12.1). Sixty-six patients (86.8%) were able to complete psychiatric evaluation. Clinically significant anxiety was found in 23 patients (34.8%) while clinically significant depression was found in 24 patients (36.4%). When we compared patients with and without depression a significant difference was seen only in the frequency of anxiety symptoms (pescala funcional. Foi encontrada correlação positiva entre os sintomas de ansiedade e depressão (pescala funcional.

Heterogeneity of triple-negative breast cancer: mammographic, US, and MR imaging features according to androgen receptor expression

Energy Technology Data Exchange (ETDEWEB)

Bae, Min Sun; Song, Sung Eun; Kim, Won Hwa; Lee, Su Hyun; Moon, Woo Kyung [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Park, So Yeon; Park, In-Ae [Seoul National University College of Medicine, Department of Pathology, Seoul (Korea, Republic of); Han, Wonshik; Noh, Dong-Young [Seoul National University College of Medicine, Department of Surgery, Seoul (Korea, Republic of)

2014-09-16

Our aim was to determine whether triple-negative breast cancers (TNBCs) with and without androgen receptor (AR) expression have distinguishing imaging features on mammography, breast ultrasound (US), and magnetic resonance (MR) imaging. AR expression was assessed immunohistochemically in 125 patients with TNBC from a consecutive series of 1,086 operable invasive breast cancers. Two experienced radiologists blinded to clinicopathological findings reviewed all imaging studies in consensus using the BI-RADS lexicon. The imaging and pathological features of 33 AR-positive TNBCs were compared with those of 92 AR-negative TNBCs. The presence of mammographic calcifications with or without a mass (p < 0.001), non-mass enhancement on MR imaging (p < 0.001), and masses with irregular shape or spiculated margins on US (p < 0.001 and p = 0.002) and MR imaging (p = 0.001 and p < 0.001) were significantly associated with AR-positive TNBC. Compared with AR-negative TNBC, AR-positive TNBC was more likely to have a ductal carcinoma in situ component (59.8 % vs. 90.9 %, p = 0.001) and low Ki-67 expression (30.4 % vs. 51.5 %, p = 0.030). AR-positive and AR-negative TNBCs have different imaging features, and certain imaging findings can be useful to predict AR status in TNBC. (orig.)

Orofacial clinical features in Arnold Chiari type I malformation: A case series.

Science.gov (United States)

de Arruda, José-Alcides; Figueiredo, Eugênia; Monteiro, João-Luiz; Barbosa, Livia-Mirelle; Rodrigues, Cleomar; Vasconcelos, Belmiro

2018-04-01

Arnold Chiari malformation (ACM) is characterized by an anatomical defect at the base of the skull where the cerebellum and the spinal cord herniate through the foramen magnum into the cervical spinal canal. Among the subtypes of the condition, ACM type I (ACM-I) is particularly outstanding because of the severity of symptoms. This study aimed to analyze the orofacial clinical manifestations of patients with ACM-I, and discuss their demographic distribution and clinical features in light of the literature. A case series with patients with ACM-I treated between 2012 and 2015 was described. The sample consisted of patients who were referred by the Department of Neurosurgery to the Oral and Maxillofacial Surgery Service of Hospital da Restauração in Brazil for the assessment of facial symptomatology. A questionnaire was applied to evaluate the presence of painful orofacial findings. Data are reported using descriptive statistical methods. Mean patient age was 39.3 years and the sample consisted mostly of male patients. A high prevalence of headache (50%) and pain in the neck (66.7%) and masticatory muscles (50%) was found. Only one patient reported difficulty in performing mandibular movements and two reported jaw clicking sounds. Mean mouth opening was 40.83 mm. ACM-I patients may exhibit orofacial symptoms which may mimic temporomandibular joint disorders. This study brings interesting information that could help clinicians and oral and maxillofacial surgeons to understand this uncommon condition and also help with the diagnosis of patients with similar physical characteristics by referring them to a neurosurgeon. Key words: Arnold-Chiari malformation, facial pain, diagnosis, orofacial.

Optics in computing: introduction to the feature issue.

Science.gov (United States)

Drabik, T; Thienpont, H; Ishikawa, M

2000-02-10

This issue of Applied Optics features 21 papers that describe the implementation of optics in computer systems and applications. This feature is the eighth in a series on the application of optics in the field of computing.

Diagnosis of Hair Loss: Clinical features of common causes of hair loss

OpenAIRE

Coupe, Robert L.M.

1992-01-01

Common causes of hair loss include androgenic hair loss, alopecia areata, trichotillomania, tinea capitis, telogen effluvium, and traction alopecia. The author discusses their distinguishing clinical features and those of less common alopecias.

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...

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.

PSYCHOLOGICAL FEATURES OF CONFLICT BEHAVIOUR AMONG FEMALE INMATES

Directory of Open Access Journals (Sweden)

Anna Leonidovna Plotnikova

2017-04-01

Full Text Available In this article the results of the research concerning the special features of behaviour in the conflicts among the female inmates are given, psychological features of the female inmates are analysed, their psychological typology is presented, inmates gender differences are characterized as well as psychological reasons of interpersonal conflicts among the female inmates in the correctional facilities, the most conflict categories of female inmates are distinguished. Purpose: revealing of dominant strategies of behaviour in the conflict of the female inmates, specific features of female inmates conflict behaviour according to age and type of committed crime. Method: ascertaining experiment Results: dominant strategies of female inmates conflict behaviour are compromise and adjustment. Areas of use: the penitentiary system.

Triangle Computer Science Distinguished Lecture Series

Science.gov (United States)

2018-01-30

scientific inquiry - the cell, the brain, the market - as well as in the models developed by scientists over the centuries for studying them. Human...the great objects of scientific inquiry - the cell, the brain, the market - as well as in the models developed by scientists over the centuries for...in principle , secure system operation can be achieved. Massive-Scale Streaming Analytics David Bader, Georgia Institute of Technology (telecast from

Biomedical Imaging Modality Classification Using Combined Visual Features and Textual Terms

Directory of Open Access Journals (Sweden)

Xian-Hua Han

2011-01-01

extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

Distinguishing attack on five-round Feistel networks

DEFF Research Database (Denmark)

Knudsen, Lars Ramkilde; Raddum, H

2003-01-01

Recently it was shown (by J. Patarin) how to distinguish a general five-round Feistel network from a random permutation using O(2/sup 3n/2/) chosen plaintexts or O(2/sup 7n/4/) known plaintexts. The present authors report improvement of these results and a distinguisher is presented which uses ro...

Distinguishing between gaming and gambling activities in addiction research.

Science.gov (United States)

King, Daniel L; Gainsbury, Sally M; Delfabbro, Paul H; Hing, Nerilee; Abarbanel, Brett

2015-12-01

Gambling and gaming activities have become increasingly recognised as sharing many common features at a structural and aesthetic level. Both have also been implicated as contributing to harm through excessive involvement. Despite this, relatively little attention has been given to the fundamental characteristics that differentiate these two classes of activity, especially in situations where the boundaries between them may be particularly hard to distinguish. This is evident, for example, in digital games that incorporate free and paid virtual currencies or items, as well as the capacity for wagering. Such overlaps create problems for regulatory classifications, screening, diagnosis and treatment. Is the problem related to the gambling or gaming content? In this paper, we review the principal sources of overlap between the activity classes in terms of several dimensions: interactivity, monetisation, betting and wagering, types of outcomes, structural fidelity, context and centrality of content, and advertising. We argue that gaming is principally defined by its interactivity, skill-based play, and contextual indicators of progression and success. In contrast, gambling is defined by betting and wagering mechanics, predominantly chance-determined outcomes, and monetisation features that involve risk and payout to the player. A checklist measure is provided, with practical examples, to examine activities according to features of design and function, which may inform guidelines for policy makers, researchers and treatment providers. We suggest that, in some instances, using category-based nomenclature (e.g., "gambling-like game") may be too vague or cumbersome to adequately organise our understanding of new gaming/gambling hybrid activities.

Distinguishability of countable quantum states and von Neumann lattice

International Nuclear Information System (INIS)

Kawakubo, Ryûitirô; Koike, Tatsuhiko

2016-01-01

The condition for distinguishability of a countably infinite number of pure states by a single measurement is given. Distinguishability is to be understood as the possibility of an unambiguous measurement. For a finite number of states, it is known that the necessary and sufficient condition of distinguishability is that the states are linearly independent. For an infinite number of states, several natural classes of distinguishability can be defined. We give a necessary and sufficient condition for a system of pure states to be distinguishable. It turns out that each level of distinguishability naturally corresponds to one of the generalizations of linear independence to families of infinite vectors. As an important example, we apply the general theory to von Neumann’s lattice, a subsystem of coherent states which corresponds to a lattice in the classical phase space. We prove that the condition for distinguishability is that the area of the fundamental region of the lattice is greater than the Planck constant, and also find subtle behavior on the threshold. These facts reveal the measurement theoretical meaning of the Planck constant and give a justification for the interpretation that it is the smallest unit of area in the phase space. The cases of uncountably many states and of mixed states are also discussed. (paper)

Research on oral test modeling based on multi-feature fusion

Science.gov (United States)

Shi, Yuliang; Tao, Yiyue; Lei, Jun

2018-04-01

In this paper, the spectrum of speech signal is taken as an input of feature extraction. The advantage of PCNN in image segmentation and other processing is used to process the speech spectrum and extract features. And a new method combining speech signal processing and image processing is explored. At the same time of using the features of the speech map, adding the MFCC to establish the spectral features and integrating them with the features of the spectrogram to further improve the accuracy of the spoken language recognition. Considering that the input features are more complicated and distinguishable, we use Support Vector Machine (SVM) to construct the classifier, and then compare the extracted test voice features with the standard voice features to achieve the spoken standard detection. Experiments show that the method of extracting features from spectrograms using PCNN is feasible, and the fusion of image features and spectral features can improve the detection accuracy.

Combination of radiological and gray level co-occurrence matrix textural features used to distinguish solitary pulmonary nodules by computed tomography.

Science.gov (United States)

Wu, Haifeng; Sun, Tao; Wang, Jingjing; Li, Xia; Wang, Wei; Huo, Da; Lv, Pingxin; He, Wen; Wang, Keyang; Guo, Xiuhua

2013-08-01

The objective of this study was to investigate the method of the combination of radiological and textural features for the differentiation of malignant from benign solitary pulmonary nodules by computed tomography. Features including 13 gray level co-occurrence matrix textural features and 12 radiological features were extracted from 2,117 CT slices, which came from 202 (116 malignant and 86 benign) patients. Lasso-type regularization to a nonlinear regression model was applied to select predictive features and a BP artificial neural network was used to build the diagnostic model. Eight radiological and two textural features were obtained after the Lasso-type regularization procedure. Twelve radiological features alone could reach an area under the ROC curve (AUC) of 0.84 in differentiating between malignant and benign lesions. The 10 selected characters improved the AUC to 0.91. The evaluation results showed that the method of selecting radiological and textural features appears to yield more effective in the distinction of malignant from benign solitary pulmonary nodules by computed tomography.

Differential role of molten globule and protein folding in distinguishing unique features of botulinum neurotoxin.

Science.gov (United States)

Kumar, Raj; Kukreja, Roshan V; Cai, Shuowei; Singh, Bal R

2014-06-01

Botulinum neurotoxins (BoNTs) are proteins of great interest not only because of their extreme toxicity but also paradoxically for their therapeutic applications. All the known serotypes (A-G) have varying degrees of longevity and potency inside the neuronal cell. Differential chemical modifications such as phosphorylation and ubiquitination have been suggested as possible mechanisms for their longevity, but the molecular basis of the longevity remains unclear. Since the endopeptidase domain (light chain; LC) of toxin apparently survives inside the neuronal cells for months, it is important to examine the structural features of this domain to understand its resistance to intracellular degradation. Published crystal structures (both botulinum neurotoxins and endopeptidase domain) have not provided adequate explanation for the intracellular longevity of the domain. Structural features obtained from spectroscopic analysis of LCA and LCB were similar, and a PRIME (PReImminent Molten Globule Enzyme) conformation appears to be responsible for their optimal enzymatic activity at 37°C. LCE, on the other hand, was although optimally active at 37°C, but its active conformation differed from the PRIME conformation of LCA and LCB. This study establishes and confirms our earlier finding that an optimally active conformation of these proteins in the form of PRIME exists for the most poisonous poison, botulinum neurotoxin. There are substantial variations in the structural and functional characteristics of these active molten globule related structures among the three BoNT endopeptidases examined. These differential conformations of LCs are important in understanding the fundamental structural features of proteins, and their possible connection to intracellular longevity could provide significant clues for devising new countermeasures and effective therapeutics. Copyright © 2014 Elsevier B.V. All rights reserved.

Distinguishing humans from computers in the game of go: A complex network approach

Science.gov (United States)

Coquidé, C.; Georgeot, B.; Giraud, O.

2017-08-01

We compare complex networks built from the game of go and obtained from databases of human-played games with those obtained from computer-played games. Our investigations show that statistical features of the human-based networks and the computer-based networks differ, and that these differences can be statistically significant on a relatively small number of games using specific estimators. We show that the deterministic or stochastic nature of the computer algorithm playing the game can also be distinguished from these quantities. This can be seen as a tool to implement a Turing-like test for go simulators.

Clinicopathologic and prognostic features of breast cancer in young women: a series from North of Morocco.

Science.gov (United States)

Bakkach, Joaira; Mansouri, Mohamed; Derkaoui, Touria; Loudiyi, Ali; Fihri, Mohamed; Hassani, Samia; Barakat, Amina; Ghailani Nourouti, Naima; Bennani Mechita, Mohcine

2017-11-09

Literature data reported a higher frequency of breast cancer in young women (BCYW) in developing countries. BCYW is associated with delayed diagnosis, aggressive biology and poor prognosis. However, our knowledge of biological profile, treatment received and outcome of young patients is still limited in Morocco. We propose to analyze clinicopathologic, therapeutic and prognostic features of BCYW among a series of patients native and/or inhabitant of North of Morocco. We carried out a retro-prospective study of 331 infiltrating breast cancer cases registered between January 2010 and December 2015. Details of tumor pathology, treatment and outcome were collected. Disease-Free Survival (DFS) and Overall Survival (OS) were assessed by Kaplan-Meier analysis. A total of 82 patients were diagnosed with breast cancer at the age of 40 or younger (24.8%). Median age was 36 years. More than one quarter (26%) of patients had family history of breast or ovarian cancer. Advanced stages accounted for 34.2% of cases. Median tumor diameter was 2.8 cm. Intermediate and high-grade tumors represented 47.6% and 40.2%, respectively. Nodal involvement was present in 58.5% and lymphovascular invasion was found in 47.7% of the patients. About two thirds (66.2%) of tumors were hormone receptor positive, 29.2% over-expressed HER2 receptor and 23% were triple negative. Patients underwent breast conserving surgery in 38.2% of cases, 61.7% were offered adjuvant chemotherapy and 84.6% received hormone therapy. Five-year DFS and OS were respectively 88.9% and 75.6%. Locoregional recurrence occurred in 2.8% of cases and 8.3% of patients developed distant metastases. Our findings are in accordance with previous studies that have shown a higher frequency of breast cancer among Moroccan young women. In line with literature data, clinicopathologic profile seems to be aggressive and prognosis is pejorative in our series.

Relevance of echo-structure and texture features

DEFF Research Database (Denmark)

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

2010-01-01

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

Smarandachely Adjacent-Vertex-Distinguishing Proper Edge Chromatic Number of Cm∨Kn

OpenAIRE

Shunqin Liu

2016-01-01

According to different conditions, researchers have defined a great deal of coloring problems and the corresponding chromatic numbers. Such as, adjacent-vertex-distinguishing total chromatic number, adjacent-vertex-distinguishing proper edge chromatic number, smarandachely-adjacent-vertex-distinguishing proper edge chromatic number, smarandachely-adjacent-vertex-distinguishing proper total chromatic number. And we focus on the smarandachely adjacent-vertex-distinguishing proper edge chromatic...

Feature Optimization for Long-Range Visual Homing in Changing Environments

Directory of Open Access Journals (Sweden)

Qidan Zhu

2014-02-01

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

Textural kinetics: a novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification.

Science.gov (United States)

Agner, Shannon C; Soman, Salil; Libfeld, Edward; McDonald, Margie; Thomas, Kathleen; Englander, Sarah; Rosen, Mark A; Chin, Deanna; Nosher, John; Madabhushi, Anant

2011-06-01

Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) of the breast has emerged as an adjunct imaging tool to conventional X-ray mammography due to its high detection sensitivity. Despite the increasing use of breast DCE-MRI, specificity in distinguishing malignant from benign breast lesions is low, and interobserver variability in lesion classification is high. The novel contribution of this paper is in the definition of a new DCE-MRI descriptor that we call textural kinetics, which attempts to capture spatiotemporal changes in breast lesion texture in order to distinguish malignant from benign lesions. We qualitatively and quantitatively demonstrated on 41 breast DCE-MRI studies that textural kinetic features outperform signal intensity kinetics and lesion morphology features in distinguishing benign from malignant lesions. A probabilistic boosting tree (PBT) classifier in conjunction with textural kinetic descriptors yielded an accuracy of 90%, sensitivity of 95%, specificity of 82%, and an area under the curve (AUC) of 0.92. Graph embedding, used for qualitative visualization of a low-dimensional representation of the data, showed the best separation between benign and malignant lesions when using textural kinetic features. The PBT classifier results and trends were also corroborated via a support vector machine classifier which showed that textural kinetic features outperformed the morphological, static texture, and signal intensity kinetics descriptors. When textural kinetic attributes were combined with morphologic descriptors, the resulting PBT classifier yielded 89% accuracy, 99% sensitivity, 76% specificity, and an AUC of 0.91.

DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

Distinguishing papillary endothelial hyperplasia and angiosarcoma on core needle biopsy of the breast: The importance of clinical and radiologic correlation.

Science.gov (United States)

Guilbert, Marie-Christine; Frost, Elisabeth P; Brock, Jane E; Lester, Susan C

2018-02-24

Papillary endothelial hyperplasia (PEH) is a rare non-neoplastic exuberant organizing hematoma that can closely mimic angiosarcoma due to a resemblance to malignant anastomosing blood vessels. It could be particularly difficult to distinguish PEH from angiosarcoma in breast core needle biopsies. We identified all cases of these lesions diagnosed on core needle biopsy in order to identify clinical, radiologic, and pathologic features that could prove helpful to arrive at the correct diagnosis. Four cases of PEH and 4 cases of angiosarcoma were identified. The mean age at diagnosis was 62 for PEH and 33 for primary angiosarcoma. All cases of PEH formed small masses with circumscribed or lobulated margins by imaging (mean size 0.9 cm). In 3 cases, the masses were difficult or impossible to identify after the biopsy. Angiosarcomas presented as larger masses with ill-defined margins (mean size 2.8 cm) that were unchanged in size after biopsy. PEH was surrounded by adipose tissue, whereas angiosarcoma invaded into fibrous stroma and involved lobules. The pseudopapillary structures of PEH were composed mainly of collagen, and thus, additional histologic stains for fibrin were not helpful for diagnosis. The 4 patients with PEH received no further treatment and are alive and disease-free at 2-11 years of follow-up. In contrast, the patients with angiosarcoma underwent mastectomy and chemotherapy or radiation therapy. Two of the patients with angiosarcoma died 3 years after diagnosis and the other 2 patients are alive without disease at 5 and 6 years. Therefore, distinguishing PEH and angiosarcoma is essential for appropriate management. This is the first series to compare these lesions on core needle biopsy and the first to note important clinical, imaging, and histologic differences that aid in making a diagnosis of PEH with confidence on breast core needle biopsy. © 2018 Wiley Periodicals, Inc.

Electrocardiographic features of sudden unexpected death in epilepsy.

Science.gov (United States)

Chyou, Janice Y; Friedman, Daniel; Cerrone, Marina; Slater, William; Guo, Yu; Taupin, Daniel; O'Rourke, Sean; Priori, Silvia G; Devinsky, Orrin

2016-07-01

Sudden unexpected death in epilepsy (SUDEP) is the most common cause of epilepsy-related mortality. We hypothesized that electrocardiography (ECG) features may distinguish SUDEP cases from living subjects with epilepsy. Using a matched case-control design, we compared ECG studies of 12 consecutive cases of SUDEP over 10 years and 22 epilepsy controls matched for age, sex, epilepsy type (focal, generalized, or unknown/mixed type), concomitant antiepileptic, and psychotropic drug classes. Conduction intervals and prevalence of abnormal ventricular conduction diagnosis (QRS ≥110 msec), abnormal ventricular conduction pattern (QRS <110 msec, morphology of incomplete right or left bundle branch block or intraventricular conduction delay), early repolarization, and features of inherited cardiac channelopathies were assessed. Abnormal ventricular conduction diagnosis and pattern distinguished SUDEP cases from matched controls. Abnormal ventricular conduction diagnosis was present in two cases and no controls. Abnormal ventricular conduction pattern was more common in cases than controls (58% vs. 18%, p = 0.04). Early repolarization was similarly prevalent in cases and controls, but the overall prevalence exceeded that of published community-based cohorts. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Distinguishing computable mixtures of quantum states

Science.gov (United States)

Grande, Ignacio H. López; Senno, Gabriel; de la Torre, Gonzalo; Larotonda, Miguel A.; Bendersky, Ariel; Figueira, Santiago; Acín, Antonio

2018-05-01

In this article we extend results from our previous work [Bendersky et al., Phys. Rev. Lett. 116, 230402 (2016), 10.1103/PhysRevLett.116.230402] by providing a protocol to distinguish in finite time and with arbitrarily high success probability any algorithmic mixture of pure states from the maximally mixed state. Moreover, we include an experimental realization, using a modified quantum key distribution setup, where two different random sequences of pure states are prepared; these sequences are indistinguishable according to quantum mechanics, but they become distinguishable when randomness is replaced with pseudorandomness within the experimental preparation process.

Genetic architecture distinguishes systemic juvenile idiopathic arthritis from otherforms of juvenile idiopathic arthritis: clinical and therapeutic implications

OpenAIRE

Ombrello, Michael J.; Arthur, Victoria L.; Remmers, Elaine F.; Hinks, Anne; Tachmazidou, Ioanna; Grom, Alexei A.; Foell, Dirk; Martini, Alberto; Gattorno, Marco; Ozen, Seza; Prahalad, Sampath; Zeft, Andrew S.; Bohnsack, John F.; Ilowite, Norman T.; Mellins, Elizabeth D.

2016-01-01

Objectives: Juvenile idiopathic arthritis (JIA) is a heterogeneous group of conditions unified by the presence of chronic childhood arthritis without an identifiable cause. Systemic JIA (sJIA) is a rare form of JIA characterized by systemic inflammation. sJIA is distinguished from other forms of JIA by unique clinical features and treatment responses that are similar to autoinflammatory diseases. However approximately half of children with sJIA develop destructive, longstanding arthritis that...

Energy-Based Wavelet De-Noising of Hydrologic Time Series

Science.gov (United States)

Sang, Yan-Fang; Liu, Changming; Wang, Zhonggen; Wen, Jun; Shang, Lunyu

2014-01-01

De-noising is a substantial issue in hydrologic time series analysis, but it is a difficult task due to the defect of methods. In this paper an energy-based wavelet de-noising method was proposed. It is to remove noise by comparing energy distribution of series with the background energy distribution, which is established from Monte-Carlo test. Differing from wavelet threshold de-noising (WTD) method with the basis of wavelet coefficient thresholding, the proposed method is based on energy distribution of series. It can distinguish noise from deterministic components in series, and uncertainty of de-noising result can be quantitatively estimated using proper confidence interval, but WTD method cannot do this. Analysis of both synthetic and observed series verified the comparable power of the proposed method and WTD, but de-noising process by the former is more easily operable. The results also indicate the influences of three key factors (wavelet choice, decomposition level choice and noise content) on wavelet de-noising. Wavelet should be carefully chosen when using the proposed method. The suitable decomposition level for wavelet de-noising should correspond to series' deterministic sub-signal which has the smallest temporal scale. If too much noise is included in a series, accurate de-noising result cannot be obtained by the proposed method or WTD, but the series would show pure random but not autocorrelation characters, so de-noising is no longer needed. PMID:25360533

Time averaging, ageing and delay analysis of financial time series

Science.gov (United States)

Cherstvy, Andrey G.; Vinod, Deepak; Aghion, Erez; Chechkin, Aleksei V.; Metzler, Ralf

2017-06-01

We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

Clinical Features Of Malaria And Typhoid Fever | Mba | Journal of ...

African Journals Online (AJOL)

Features to distinguish Malaria from Typhoid fever. These can be discerned from a good and detailed clinical history, in addition to a thorough physical examination. The following would help. The paroxysms of malaria fever as against the step ladder pattern fever of typhoid fever. The prominence of headaches in typhoid ...

Characterization of time series via Rényi complexity-entropy curves

Science.gov (United States)

Jauregui, M.; Zunino, L.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2018-05-01

One of the most useful tools for distinguishing between chaotic and stochastic time series is the so-called complexity-entropy causality plane. This diagram involves two complexity measures: the Shannon entropy and the statistical complexity. Recently, this idea has been generalized by considering the Tsallis monoparametric generalization of the Shannon entropy, yielding complexity-entropy curves. These curves have proven to enhance the discrimination among different time series related to stochastic and chaotic processes of numerical and experimental nature. Here we further explore these complexity-entropy curves in the context of the Rényi entropy, which is another monoparametric generalization of the Shannon entropy. By combining the Rényi entropy with the proper generalization of the statistical complexity, we associate a parametric curve (the Rényi complexity-entropy curve) with a given time series. We explore this approach in a series of numerical and experimental applications, demonstrating the usefulness of this new technique for time series analysis. We show that the Rényi complexity-entropy curves enable the differentiation among time series of chaotic, stochastic, and periodic nature. In particular, time series of stochastic nature are associated with curves displaying positive curvature in a neighborhood of their initial points, whereas curves related to chaotic phenomena have a negative curvature; finally, periodic time series are represented by vertical straight lines.

Performance comparison of deep learning and segmentation-based radiomic methods in the task of distinguishing benign and malignant breast lesions on DCE-MRI

Science.gov (United States)

Antropova, Natasha; Huynh, Benjamin; Giger, Maryellen

2017-03-01

Intuitive segmentation-based CADx/radiomic features, calculated from the lesion segmentations of dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) have been utilized in the task of distinguishing between malignant and benign lesions. Additionally, transfer learning with pre-trained deep convolutional neural networks (CNNs) allows for an alternative method of radiomics extraction, where the features are derived directly from the image data. However, the comparison of computer-extracted segmentation-based and CNN features in MRI breast lesion characterization has not yet been conducted. In our study, we used a DCE-MRI database of 640 breast cases - 191 benign and 449 malignant. Thirty-eight segmentation-based features were extracted automatically using our quantitative radiomics workstation. Also, 2D ROIs were selected around each lesion on the DCE-MRIs and directly input into a pre-trained CNN AlexNet, yielding CNN features. Each method was investigated separately and in combination in terms of performance in the task of distinguishing between benign and malignant lesions. Area under the ROC curve (AUC) served as the figure of merit. Both methods yielded promising classification performance with round-robin cross-validated AUC values of 0.88 (se =0.01) and 0.76 (se=0.02) for segmentationbased and deep learning methods, respectively. Combination of the two methods enhanced the performance in malignancy assessment resulting in an AUC value of 0.91 (se=0.01), a statistically significant improvement over the performance of the CNN method alone.

Experimental investigation of distinguishable and non-distinguishable grayscales applicable in active-matrix organic light-emitting diodes for quality engineering

Science.gov (United States)

Yang, Henglong; Chang, Wen-Cheng; Lin, Yu-Hsuan; Chen, Ming-Hong

2017-08-01

The distinguishable and non-distinguishable 6-bit (64) grayscales of green and red organic light-emitting diode (OLED) were experimentally investigated by using high-sensitive photometric instrument. The feasibility of combining external detection system for quality engineering to compensate the grayscale loss based on preset grayscale tables was also investigated by SPICE simulation. The degradation loss of OLED deeply affects image quality as grayscales become inaccurate. The distinguishable grayscales are indicated as those brightness differences and corresponding current increments are differentiable by instrument. The grayscales of OLED in 8-bit (256) or higher may become nondistinguishable as current or voltage increments are in the same order of noise level in circuitry. The distinguishable grayscale tables for individual red, green, blue, and white colors can be experimentally established as preset reference for quality engineering (QE) in which the degradation loss is compensated by corresponding grayscale numbers shown in preset table. The degradation loss of each OLED colors is quantifiable by comparing voltage increments to those in preset grayscale table if precise voltage increments are detectable during operation. The QE of AMOLED can be accomplished by applying updated grayscale tables. Our preliminary simulation result revealed that it is feasible to quantify degradation loss in terms of grayscale numbers by using external detector circuitry.

Normed algebras and the geometric series test

Directory of Open Access Journals (Sweden)

Robert Kantrowitz

2017-11-01

Full Text Available The purpose of this article is to survey a class of normed algebras that share many central features of Banach algebras, save for completeness. The likeness of these algebras to Banach algebras derives from the fact that the geometric series test is valid, whereas the lack of completeness points to the failure of the absolute convergence test for series in the algebra. Our main result is a compendium of conditions that are all equivalent to the validity of the geometric series test for commutative unital normed algebras. Several examples in the final section showcase some incomplete normed algebras for which the geometric series test is valid, and still others for which it is not.

Distinguishing Osteomyelitis From Ewing Sarcoma on Radiography and MRI

Science.gov (United States)

McCarville, M. Beth; Chen, Jim Y.; Coleman, Jamie L.; Li, Yimei; Li, Xingyu; Adderson, Elisabeth E.; Neel, Mike D.; Gold, Robert E.; Kaufman, Robert A.

2017-01-01

OBJECTIVE The purpose of this study was to determine whether clinical and imaging features can distinguish osteomyelitis from Ewing sarcoma (EWS) and to assess the accuracy of percutaneous biopsy versus open biopsy in the diagnosis of these diseases. MATERIALS AND METHODS Three radiologists reviewed the radiographs and MRI examinations of 32 subjects with osteomyelitis and 31 subjects with EWS to determine the presence of 36 imaging parameters. Information on demographic characteristics, history, physical examination findings, laboratory findings, biopsy type, and biopsy results were recorded. Individual imaging and clinical parameters and combinations of these parameters were tested for correlation with findings from histologic analysis. The diagnostic accuracy of biopsy was also determined. RESULTS On radiography, the presence of joint or metaphyseal involvement, a wide transition zone, a Codman triangle, a periosteal reaction, or a soft-tissue mass, when tested individually, was more likely to be noted in subjects with EWS (p ≤ 0.05) than in subjects with osteomyelitis. On MRI, permeative cortical involvement and soft-tissue mass were more likely in subjects with EWS (p ≤ 0.02), whereas a serpiginous tract was more likely to be seen in subjects with osteomyelitis (p = 0.04). African Americans were more likely to have osteomyelitis than EWS (p = 0). According to the results of multiple regression analysis, only ethnicity and soft-tissue mass remained statistically significant (p ≤ 0.01). The findings from 100% of open biopsies (18/18) and 58% of percutaneous biopsies (7/12) resulted in the diagnosis of osteomyelitis, whereas the findings from 88% of open biopsies (22/25) and 50% of percutaneous biopsies (3/6) resulted in a diagnosis of EWS. CONCLUSION Several imaging features are significantly associated with either EWS or osteomyelitis, but many features are associated with both diseases. Other than ethnicity, no clinical feature improved diagnostic

Can responses to basic non-numerical visual features explain neural numerosity responses?

Science.gov (United States)

Harvey, Ben M; Dumoulin, Serge O

2017-04-01

Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and perception of numerosity, and visual features often co-vary with numerosity. Therefore, it is debated whether numerosity or co-varying low-level visual features underlie neural and behavioral responses to numerosity. To test the hypothesis that non-numerical visual features underlie neural numerosity responses in a human parietal numerosity map, we analyze responses to a group of numerosity stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. Using ultra-high-field (7T) fMRI, we measure responses to these stimulus configurations in an area of posterior parietal cortex whose responses are believed to reflect numerosity-selective activity. We describe an fMRI analysis method to distinguish between alternative models of neural response functions, following a population receptive field (pRF) modeling approach. For each stimulus configuration, we first quantify the relationships between numerosity and several non-numerical visual features that have been proposed to underlie performance in numerosity discrimination tasks. We then determine how well responses to these non-numerical visual features predict the observed fMRI responses, and compare this to the predictions of responses to numerosity. We demonstrate that a numerosity response model predicts observed responses more accurately than models of responses to simple non-numerical visual features. As such, neural responses in cognitive processing need not reflect simpler properties of early sensory inputs. Copyright © 2017 Elsevier Inc. All rights reserved.

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

Science.gov (United States)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

Comparison between Decision Tree and Genetic Programming to distinguish healthy from stroke postural sway patterns.

Science.gov (United States)

Marrega, Luiz H G; Silva, Simone M; Manffra, Elisangela F; Nievola, Julio C

2015-01-01

Maintaining balance is a motor task of crucial importance for humans to perform their daily activities safely and independently. Studies in the field of Artificial Intelligence have considered different classification methods in order to distinguish healthy subjects from patients with certain motor disorders based on their postural strategies during the balance control. The main purpose of this paper is to compare the performance between Decision Tree (DT) and Genetic Programming (GP) - both classification methods of easy interpretation by health professionals - to distinguish postural sway patterns produced by healthy and stroke individuals based on 16 widely used posturographic variables. For this purpose, we used a posturographic dataset of time-series of center-of-pressure displacements derived from 19 stroke patients and 19 healthy matched subjects in three quiet standing tasks of balance control. Then, DT and GP models were trained and tested under two different experiments where accuracy, sensitivity and specificity were adopted as performance metrics. The DT method has performed statistically significant (P < 0.05) better in both cases, showing for example an accuracy of 72.8% against 69.2% from GP in the second experiment of this paper.

Phase-modified CTQW unable to distinguish strongly regular graphs efficiently

International Nuclear Information System (INIS)

Mahasinghe, A; Wijerathna, J K; Izaac, J A; Wang, J B

2015-01-01

Various quantum walk-based algorithms have been developed, aiming to distinguish non-isomorphic graphs with polynomial scaling, within both the discrete-time quantum walk (DTQW) and continuous-time quantum walk (CTQW) frameworks. Whilst both the single-particle DTQW and CTQW have failed to distinguish non-isomorphic strongly regular graph families (prompting the move to multi-particle graph isomorphism (GI) algorithms), the single-particle DTQW has been successfully modified by the introduction of a phase factor to distinguish a wide range of graphs in polynomial time. In this paper, we prove that an analogous phase modification to the single particle CTQW does not have the same distinguishing power as its discrete-time counterpart, in particular it cannot distinguish strongly regular graphs with the same family parameters with the same efficiency. (paper)

MAPPING DISTURBANCE DYNAMICS IN WET SCLEROPHYLL FORESTS USING TIME SERIES LANDSAT

Directory of Open Access Journals (Sweden)

A. Haywood

2016-06-01

Full Text Available In this study, we characterised the temporal-spectral patterns associated with identifying acute-severity disturbances and low-severity disturbances between 1985 and 2011 with the objective to test whether different disturbance agents within these categories can be identified with annual Landsat time series data. We analysed a representative State forest within the Central Highlands which has been exposed to a range of disturbances over the last 30 years, including timber harvesting (clearfell, selective and thinning and fire (wildfire and prescribed burning. We fitted spectral time series models to annual normal burn ratio (NBR and Tasseled Cap Indices (TCI, from which we extracted a range of disturbance and recovery metrics. With these metrics, three hierarchical random forest models were trained to 1 distinguish acute-severity disturbances from low-severity disturbances; 2a attribute the disturbance agents most likely within the acute-severity class; 2b and attribute the disturbance agents most likely within the low-severity class. Disturbance types (acute severity and low-severity were successfully mapped with an overall accuracy of 72.9 %, and the individual disturbance types were successfully attributed with overall accuracies ranging from 53.2 % to 64.3 %. Low-severity disturbance agents were successfully mapped with an overall accuracy of 80.2 %, and individual agents were successfully attributed with overall accuracies ranging from 25.5 % to 95.1. Acute-severity disturbance agents were successfully mapped with an overall accuracy of 95.4 %, and individual agents were successfully attributed with overall accuracies ranging from 94.2 % to 95.2 %. Spectral metrics describing the disturbance magnitude were more important for distinguishing the disturbance agents than the post-disturbance response slope. Spectral changes associated with planned burning disturbances had generally lower magnitudes than selective harvesting

Hornbills can distinguish between primate alarm calls.

Science.gov (United States)

Rainey, Hugo J.; Zuberbühler, Klaus; Slater, Peter J. B.

2004-01-01

Some mammals distinguish between and respond appropriately to the alarm calls of other mammal and bird species. However, the ability of birds to distinguish between mammal alarm calls has not been investigated. Diana monkeys (Cercopithecus diana) produce different alarm calls to two predators: crowned eagles (Stephanoaetus coronatus) and leopards (Panthera pardus). Yellow-casqued hornbills (Ceratogymna elata) are vulnerable to predation by crowned eagles but are not preyed on by leopards and might therefore be expected to respond to the Diana monkey eagle alarm call but not to the leopard alarm call. We compared responses of hornbills to playback of eagle shrieks, leopard growls, Diana monkey eagle alarm calls and Diana monkey leopard alarm calls and found that they distinguished appropriately between the two predator vocalizations as well as between the two Diana monkey alarm calls. We discuss possible mechanisms leading to these responses. PMID:15209110

Flow-like Features On Europa

Science.gov (United States)

1997-01-01

This image shows features on Jupiter's moon Europa that may be 'flows' from ice volcanoes. It was taken by the Galileo spacecraft solid state imaging (CCD) system during its seventh orbit around Jupiter. North is to the top of the image. The sun illuminates the scene from the left, showing features with shapes similar to lava flows on Earth. Two such features can be seen in the northwest corner of the image. The southern feature appears to have flowed over a ridge along its western edge. Scientists use these types of relationships to determine which feature formed first. In this case, the ridge probably formed before the flow-like feature that covers it.The image, centered at 22.6 degrees north latitude and 106.7 degrees west longitude, covers an area of 180 by 215 kilometers (112 by 134 miles). The smallest distinguishable features in the image are about 1.1 kilometers (0.7 miles) across. This image was obtained on April 28, 1997, when Galileo was 27,590 kilometers (16,830 miles) from Europa.The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

Breast as an unusual site of metastasis- series of 3 cases and review of literature.

Science.gov (United States)

Hebbar, Ashwin K; Shashidhar, K; S, Krishna Murthy; Kumar, Veerendra; Arjunan, Ravi

2014-09-01

Background and objectives Metastasis to the breast from extra mammary sites is uncommon with an incidence ranging from 1.2 to 2 % in clinical reports. Approximately 300 cases of breast metastasis from extra mammary sites have been reported, mostly in small series or as a single case report. Gastrointestinal adenocarcinoma metastasising to the breast is also very rare and only 30 cases have been reported in the literature. Metastatic deposits within the breast may be difficult to distinguish from primary breast carcinoma. Radiological features and immunohistochemistry especially for steroid hormone receptors (ER/PR) and expression of gross cystic disease fluid protein (GCDFP) and presence of other immunohistochemistry protein factors in breast metastasis which are specific to primary site may be helpful in differentiating these two conditions. Materials and methods In this series of 3 cases of breast as an unusual site of metastasis, we present different cases of adenocarcinoma of stomach, sigmoid colon and kidney with metastasis to the breast and discuss the differential diagnosis and management plans. Conclusion In conclusion, secondary tumors to the breast are rare and thus differentiating primary tumors from metastatic breast carcinoma is important for rational and optimum therapy and avoidance of unnecessary radical surgery. Palpable breast lump without typical radiological signs of primary breast carcinoma in patients with known primary should be suspected of representing metastasis.

Extended local binary pattern features for improving settlement type classification of quickbird images

CSIR Research Space (South Africa)

Mdakane, L

2012-11-01

Full Text Available Despite the fact that image texture features extracted from high-resolution remotely sensed images over urban areas have demonstrated their ability to distinguish different classes, they are still far from being ideal. Multiresolution grayscale...

Clustering of financial time series

Science.gov (United States)

D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

2013-05-01

This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

Can responses to basic non-numerical visual features explain neural numerosity responses?

NARCIS (Netherlands)

Harvey, Ben M; Dumoulin, Serge O

2017-01-01

Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and

Persistent topological features of dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Maletić, Slobodan, E-mail: slobodan@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia); Zhao, Yi, E-mail: zhao.yi@hitsz.edu.cn [Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen (China); Rajković, Milan, E-mail: milanr@vinca.rs [Institute of Nuclear Sciences Vinča, University of Belgrade, Belgrade (Serbia)

2016-05-15

Inspired by an early work of Muldoon et al., Physica D 65, 1–16 (1993), we present a general method for constructing simplicial complex from observed time series of dynamical systems based on the delay coordinate reconstruction procedure. The obtained simplicial complex preserves all pertinent topological features of the reconstructed phase space, and it may be analyzed from topological, combinatorial, and algebraic aspects. In focus of this study is the computation of homology of the invariant set of some well known dynamical systems that display chaotic behavior. Persistent homology of simplicial complex and its relationship with the embedding dimensions are examined by studying the lifetime of topological features and topological noise. The consistency of topological properties for different dynamic regimes and embedding dimensions is examined. The obtained results shed new light on the topological properties of the reconstructed phase space and open up new possibilities for application of advanced topological methods. The method presented here may be used as a generic method for constructing simplicial complex from a scalar time series that has a number of advantages compared to the mapping of the same time series to a complex network.

Biomedical imaging modality classification using combined visual features and textual terms.

Science.gov (United States)

Han, Xian-Hua; Chen, Yen-Wei

2011-01-01

We describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign (ImageCLEF). This paper is focused on the process of feature extraction from medical images and fuses the different extracted visual features and textual feature for modality classification. To extract visual features from the images, we used histogram descriptor of edge, gray, or color intensity and block-based variation as global features and SIFT histogram as local feature. For textual feature of image representation, the binary histogram of some predefined vocabulary words from image captions is used. Then, we combine the different features using normalized kernel functions for SVM classification. Furthermore, for some easy misclassified modality pairs such as CT and MR or PET and NM modalities, a local classifier is used for distinguishing samples in the pair modality to improve performance. The proposed strategy is evaluated with the provided modality dataset by ImageCLEF 2010.

A distinguishing gravitational property for gravitational equation in higher dimensions

International Nuclear Information System (INIS)

Dadhich, Naresh

2016-01-01

It is well known that Einstein gravity is kinematic (meaning that there is no non-trivial vacuum solution; i.e. the Riemann tensor vanishes whenever the Ricci tensor does so) in 3 dimension because the Riemann tensor is entirely given in terms of the Ricci tensor. Could this property be universalized for all odd dimensions in a generalized theory? The answer is yes, and this property uniquely singles out pure Lovelock (it has only one Nth order term in the action) gravity for which the Nth order Lovelock-Riemann tensor is indeed given in terms of the corresponding Ricci tensor for all odd, d = 2N + 1, dimensions. This feature of gravity is realized only in higher dimensions and it uniquely picks out pure Lovelock gravity from all other generalizations of Einstein gravity. It serves as a good distinguishing and guiding criterion for the gravitational equation in higher dimensions. (orig.)

A distinguishing gravitational property for gravitational equation in higher dimensions

Science.gov (United States)

Dadhich, Naresh

2016-03-01

It is well known that Einstein gravity is kinematic (meaning that there is no non-trivial vacuum solution; i.e. the Riemann tensor vanishes whenever the Ricci tensor does so) in 3 dimension because the Riemann tensor is entirely given in terms of the Ricci tensor. Could this property be universalized for all odd dimensions in a generalized theory? The answer is yes, and this property uniquely singles out pure Lovelock (it has only one Nth order term in the action) gravity for which the Nth order Lovelock-Riemann tensor is indeed given in terms of the corresponding Ricci tensor for all odd, d=2N+1, dimensions. This feature of gravity is realized only in higher dimensions and it uniquely picks out pure Lovelock gravity from all other generalizations of Einstein gravity. It serves as a good distinguishing and guiding criterion for the gravitational equation in higher dimensions.

Individual Identification Using Linear Projection of Heartbeat Features

Directory of Open Access Journals (Sweden)

Yogendra Narain Singh

2014-01-01

Full Text Available This paper presents a novel method to use the electrocardiogram (ECG signal as biometrics for individual identification. The ECG characterization is performed using an automated approach consisting of analytical and appearance methods. The analytical method extracts the fiducial features from heartbeats while the appearance method extracts the morphological features from the ECG trace. We linearly project the extracted features into a subspace of lower dimension using an orthogonal basis that represent the most significant features for distinguishing heartbeats among the subjects. Result demonstrates that the proposed characterization of the ECG signal and subsequently derived eigenbeat features are insensitive to signal variations and nonsignal artifacts. The proposed system utilizing ECG biometric method achieves the best identification rates of 85.7% for the subjects of MIT-BIH arrhythmia database and 92.49% for the healthy subjects of our IIT (BHU database. These results are significantly better than the classification accuracies of 79.55% and 84.9%, reported using support vector machine on the tested subjects of MIT-BIH arrhythmia database and our IIT (BHU database, respectively.

Temporality of Features in Near-Death Experience Narratives

Directory of Open Access Journals (Sweden)

Charlotte Martial

2017-06-01

Full Text Available Background: After an occurrence of a Near-Death Experience (NDE, Near-Death Experiencers (NDErs usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area.Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives as well as the most frequently reported temporality sequences of features.Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32. A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features.Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs.Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon.

Using CNN Features to Better Understand What Makes Visual Artworks Special

Directory of Open Access Journals (Sweden)

Anselm Brachmann

2017-05-01

Full Text Available One of the goal of computational aesthetics is to understand what is special about visual artworks. By analyzing image statistics, contemporary methods in computer vision enable researchers to identify properties that distinguish artworks from other (non-art types of images. Such knowledge will eventually allow inferences with regard to the possible neural mechanisms that underlie aesthetic perception in the human visual system. In the present study, we define measures that capture variances of features of a well-established Convolutional Neural Network (CNN, which was trained on millions of images to recognize objects. Using an image dataset that represents traditional Western, Islamic and Chinese art, as well as various types of non-art images, we show that we need only two variance measures to distinguish between the artworks and non-art images with a high classification accuracy of 93.0%. Results for the first variance measure imply that, in the artworks, the subregions of an image tend to be filled with pictorial elements, to which many diverse CNN features respond (richness of feature responses. Results for the second measure imply that this diversity is tied to a relatively large variability of the responses of individual CNN feature across the subregions of an image. We hypothesize that this combination of richness and variability of CNN feature responses is one of properties that makes traditional visual artworks special. We discuss the possible neural underpinnings of this perceptual quality of artworks and propose to study the same quality also in other types of aesthetic stimuli, such as music and literature.

Classification of time-series images using deep convolutional neural networks

Science.gov (United States)

Hatami, Nima; Gavet, Yann; Debayle, Johan

2018-04-01

Convolutional Neural Networks (CNN) has achieved a great success in image recognition task by automatically learning a hierarchical feature representation from raw data. While the majority of Time-Series Classification (TSC) literature is focused on 1D signals, this paper uses Recurrence Plots (RP) to transform time-series into 2D texture images and then take advantage of the deep CNN classifier. Image representation of time-series introduces different feature types that are not available for 1D signals, and therefore TSC can be treated as texture image recognition task. CNN model also allows learning different levels of representations together with a classifier, jointly and automatically. Therefore, using RP and CNN in a unified framework is expected to boost the recognition rate of TSC. Experimental results on the UCR time-series classification archive demonstrate competitive accuracy of the proposed approach, compared not only to the existing deep architectures, but also to the state-of-the art TSC algorithms.

Recurrence Density Enhanced Complex Networks for Nonlinear Time Series Analysis

Science.gov (United States)

Costa, Diego G. De B.; Reis, Barbara M. Da F.; Zou, Yong; Quiles, Marcos G.; Macau, Elbert E. N.

We introduce a new method, which is entitled Recurrence Density Enhanced Complex Network (RDE-CN), to properly analyze nonlinear time series. Our method first transforms a recurrence plot into a figure of a reduced number of points yet preserving the main and fundamental recurrence properties of the original plot. This resulting figure is then reinterpreted as a complex network, which is further characterized by network statistical measures. We illustrate the computational power of RDE-CN approach by time series by both the logistic map and experimental fluid flows, which show that our method distinguishes different dynamics sufficiently well as the traditional recurrence analysis. Therefore, the proposed methodology characterizes the recurrence matrix adequately, while using a reduced set of points from the original recurrence plots.

Harry Potter book series - trivial or not?

Directory of Open Access Journals (Sweden)

Brigita Pavšič

2006-12-01

Full Text Available The article explores  the extcnt to which the features  of trivial literature appear in the Harry Potter series by J. K. Rowling.This is done in comparison with another popular children's series, The Famous Five by Enid Blyton, which was analysed  by Igor Saksida. The main focus of the analysis is on the schematic representation of plot, characters and the exotic nature of the setting and time of the stories.

5 CFR 838.612 - Distinguishing between annuities and contributions.

Science.gov (United States)

2010-01-01

... 5 Administrative Personnel 2 2010-01-01 2010-01-01 false Distinguishing between annuities and... Orders Affecting Employee Annuities or Refunds of Employee Contributions Identification of Benefits § 838.612 Distinguishing between annuities and contributions. (a) A court order using “annuities,” “pensions...

MRI features of tuberculosis of the knee

Energy Technology Data Exchange (ETDEWEB)

Sanghvi, Darshana A.; Iyer, Veena R.; Deshmukh, Tejaswini; Hoskote, Sumedh S. [Seth GS Medical College and KEM Hospital, Department of Radiology, Mumbai (India)

2009-03-15

The objective of this study was to describe the magnetic resonance imaging (MRI) features of tuberculosis (TB) of the knee joint. The MRI features in 15 patients with TB of the knee, as confirmed by histology of the biopsied joint synovium, were reviewed retrospectively. The images were assessed for intra-articular and peri-articular abnormalities. All patients had florid synovial proliferation. The proliferating synovium showed intermediate to low T2 signal intensity. In the patients who were administered intravenous contrast, the hypertrophic synovium was intensely enhancing. Marrow edema (n = 9), osteomyelitis (n = 4), cortical erosions (n = 5), myositis (n = 6), cellulitis (n = 2), abscesses (n = 3), and skin ulceration/sinus formation (n = 2) were seen in the adjacent bone and soft tissue. Synovial proliferation associated with tuberculous arthritis is typically hypointense on T2-weighted images. This appearance, in conjunction with other peri-articular MRI features described, can help in distinguishing TB arthritis from other proliferating synovial arthropathies. (orig.)

Application of higher order spectral features and support vector machines for bearing faults classification.

Science.gov (United States)

Saidi, Lotfi; Ben Ali, Jaouher; Fnaiech, Farhat

2015-01-01

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals. Copyright © 2014 ISA

Charles L. Brewer Award for Distinguished Teaching of Psychology: Neil Lutsky

Science.gov (United States)

American Psychologist, 2011

2011-01-01

The American Psychological Foundation (APF) Charles L. Brewer Award for Distinguished Teaching of Psychology recognizes an outstanding career contribution to the teaching of psychology. The 2011 recipient of the Distinguished Teaching Award is Neil Lutsky. Dorothy W. Cantor, president of the APF, will present the APF Distinguished Teaching Award…

EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Selection of morphological features of pollen grains for chosen tree taxa

Directory of Open Access Journals (Sweden)

Agnieszka Kubik-Komar

2018-05-01

Full Text Available The basis of aerobiological studies is to monitor airborne pollen concentrations and pollen season timing. This task is performed by appropriately trained staff and is difficult and time consuming. The goal of this research is to select morphological characteristics of grains that are the most discriminative for distinguishing between birch, hazel and alder taxa and are easy to determine automatically from microscope images. This selection is based on the split attributes of the J4.8 classification trees built for different subsets of features. Determining the discriminative features by this method, we provide specific rules for distinguishing between individual taxa, at the same time obtaining a high percentage of correct classification. The most discriminative among the 13 morphological characteristics studied are the following: number of pores, maximum axis, minimum axis, axes difference, maximum oncus width, and number of lateral pores. The classification result of the tree based on this subset is better than the one built on the whole feature set and it is almost 94%. Therefore, selection of attributes before tree building is recommended. The classification results for the features easiest to obtain from the image, i.e. maximum axis, minimum axis, axes difference, and number of lateral pores, are only 2.09 pp lower than those obtained for the complete set, but 3.23 pp lower than the results obtained for the selected most discriminating attributes only.

A New Feature Extraction Method Based on EEMD and Multi-Scale Fuzzy Entropy for Motor Bearing

Directory of Open Access Journals (Sweden)

Huimin Zhao

2016-12-01

Full Text Available Feature extraction is one of the most important, pivotal, and difficult problems in mechanical fault diagnosis, which directly relates to the accuracy of fault diagnosis and the reliability of early fault prediction. Therefore, a new fault feature extraction method, called the EDOMFE method based on integrating ensemble empirical mode decomposition (EEMD, mode selection, and multi-scale fuzzy entropy is proposed to accurately diagnose fault in this paper. The EEMD method is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs with a different physical significance. The correlation coefficient analysis method is used to calculate and determine three improved IMFs, which are close to the original signal. The multi-scale fuzzy entropy with the ability of effective distinguishing the complexity of different signals is used to calculate the entropy values of the selected three IMFs in order to form a feature vector with the complexity measure, which is regarded as the inputs of the support vector machine (SVM model for training and constructing a SVM classifier (EOMSMFD based on EDOMFE and SVM for fulfilling fault pattern recognition. Finally, the effectiveness of the proposed method is validated by real bearing vibration signals of the motor with different loads and fault severities. The experiment results show that the proposed EDOMFE method can effectively extract fault features from the vibration signal and that the proposed EOMSMFD method can accurately diagnose the fault types and fault severities for the inner race fault, the outer race fault, and rolling element fault of the motor bearing. Therefore, the proposed method provides a new fault diagnosis technology for rotating machinery.

A visual perceptual descriptor with depth feature for image retrieval

Science.gov (United States)

Wang, Tianyang; Qin, Zhengrui

2017-07-01

This paper proposes a visual perceptual descriptor (VPD) and a new approach to extract perceptual depth feature for 2D image retrieval. VPD mimics human visual system, which can easily distinguish regions that have different textures, whereas for regions which have similar textures, color features are needed for further differentiation. We apply VPD on the gradient direction map of an image, capture texture-similar regions to generate a VPD map. We then impose the VPD map on a quantized color map and extract color features only from the overlapped regions. To reflect the nature of perceptual distance in single 2D image, we propose and extract the perceptual depth feature by computing the nuclear norm of the sparse depth map of an image. Extracted color features and the perceptual depth feature are both incorporated to a feature vector, we utilize this vector to represent an image and measure similarity. We observe that the proposed VPD + depth method achieves a promising result, and extensive experiments prove that it outperforms other typical methods on 2D image retrieval.

Financial time series analysis based on information categorization method

Science.gov (United States)

Tian, Qiang; Shang, Pengjian; Feng, Guochen

2014-12-01

The paper mainly applies the information categorization method to analyze the financial time series. The method is used to examine the similarity of different sequences by calculating the distances between them. We apply this method to quantify the similarity of different stock markets. And we report the results of similarity in US and Chinese stock markets in periods 1991-1998 (before the Asian currency crisis), 1999-2006 (after the Asian currency crisis and before the global financial crisis), and 2007-2013 (during and after global financial crisis) by using this method. The results show the difference of similarity between different stock markets in different time periods and the similarity of the two stock markets become larger after these two crises. Also we acquire the results of similarity of 10 stock indices in three areas; it means the method can distinguish different areas' markets from the phylogenetic trees. The results show that we can get satisfactory information from financial markets by this method. The information categorization method can not only be used in physiologic time series, but also in financial time series.

The parametric modified limited penetrable visibility graph for constructing complex networks from time series

Science.gov (United States)

Li, Xiuming; Sun, Mei; Gao, Cuixia; Han, Dun; Wang, Minggang

2018-02-01

This paper presents the parametric modified limited penetrable visibility graph (PMLPVG) algorithm for constructing complex networks from time series. We modify the penetrable visibility criterion of limited penetrable visibility graph (LPVG) in order to improve the rationality of the original penetrable visibility and preserve the dynamic characteristics of the time series. The addition of view angle provides a new approach to characterize the dynamic structure of the time series that is invisible in the previous algorithm. The reliability of the PMLPVG algorithm is verified by applying it to three types of artificial data as well as the actual data of natural gas prices in different regions. The empirical results indicate that PMLPVG algorithm can distinguish the different time series from each other. Meanwhile, the analysis results of natural gas prices data using PMLPVG are consistent with the detrended fluctuation analysis (DFA). The results imply that the PMLPVG algorithm may be a reasonable and significant tool for identifying various time series in different fields.

Michael Tomasello: Award for Distinguished Scientific Contributions.

Science.gov (United States)

2015-11-01

The APA Awards for Distinguished Scientific Contributions are presented to persons who, in the opinion of the Committee on Scientific Awards, have made distinguished theoretical or empirical contributions to basic research in psychology. One of the 2015 award winners is Michael Tomasello, who received this award for "outstanding empirical and theoretical contributions to understanding what makes the human mind unique. Michael Tomasello's pioneering research on the origins of social cognition has led to revolutionary insights in both developmental psychology and primate cognition." Tomasello's award citation, biography, and a selected bibliography are presented here. (c) 2015 APA, all rights reserved).

Charles L. Brewer Award for Distinguished Teaching of Psychology

Science.gov (United States)

American Psychologist, 2009

2009-01-01

The American Psychological Foundation (APF) Charles L. Brewer Distinguished Teaching of Psychology Award recognizes an outstanding career contribution to the teaching of psychology. The 2009 recipient of the Distinguished Teaching Award is William Buskist. Dorothy W. Cantor, president of the APF, will present the APF Teaching Award at the 117th…

Time Series Modelling using Proc Varmax

DEFF Research Database (Denmark)

Milhøj, Anders

2007-01-01

In this paper it will be demonstrated how various time series problems could be met using Proc Varmax. The procedure is rather new and hence new features like cointegration, testing for Granger causality are included, but it also means that more traditional ARIMA modelling as outlined by Box...

Inverse statistical approach in heartbeat time series

International Nuclear Information System (INIS)

Ebadi, H; Shirazi, A H; Mani, Ali R; Jafari, G R

2011-01-01

We present an investigation on heart cycle time series, using inverse statistical analysis, a concept borrowed from studying turbulence. Using this approach, we studied the distribution of the exit times needed to achieve a predefined level of heart rate alteration. Such analysis uncovers the most likely waiting time needed to reach a certain change in the rate of heart beat. This analysis showed a significant difference between the raw data and shuffled data, when the heart rate accelerates or decelerates to a rare event. We also report that inverse statistical analysis can distinguish between the electrocardiograms taken from healthy volunteers and patients with heart failure

Clinical features of GH deficiency and effects of 3 years of GH replacement in adults with controlled Cushing's disease

DEFF Research Database (Denmark)

Höybye, Charlotte; Ragnarsson, Oskar; Jönsson, Peter J

2010-01-01

Patients in remission from Cushing's disease (CD) have many clinical features that are difficult to distinguish from those of concomitant GH deficiency (GHD). In this study, we evaluated the features of GHD in a large cohort of controlled CD patients, and assessed the effect of GH treatment....

8-13 μm spectrophotometry of V1016 Cyg and the shape of the 'silicate' feature

International Nuclear Information System (INIS)

Aitken, D.K.; Roche, P.F.; Spenser, P.M.

1980-01-01

8 to 13μm spectrophotometry of V1016 Cyg shows a broad emission feature attributed to radiation from silicate grains. This emission feature more closely resembles that of the circumstellar shells of oxygen-rich supergiants than the more dilute feature, typical of the interstellar medium, which is observed from the Trapezium source in the Orion nebula. It appears to be possible to distinguish the evolutionary status of an object from the form of its silicate excess. (author)

The idiopathic interstitial pneumonias: understanding key radiological features

Energy Technology Data Exchange (ETDEWEB)

Dixon, S. [Department of Radiology, Churchill Hospital, Old Road, Oxford OX3 7LJ (United Kingdom); Benamore, R., E-mail: Rachel.Benamore@orh.nhs.u [Department of Radiology, Churchill Hospital, Old Road, Oxford OX3 7LJ (United Kingdom)

2010-10-15

Many radiologists find it challenging to distinguish between the different interstitial idiopathic pneumonias (IIPs). The British Thoracic Society guidelines on interstitial lung disease (2008) recommend the formation of multidisciplinary meetings, with diagnoses made by combined radiological, pathological, and clinical findings. This review focuses on understanding typical and atypical radiological features on high-resolution computed tomography between the different IIPs, to help the radiologist determine when a confident diagnosis can be made and how to deal with uncertainty.

The idiopathic interstitial pneumonias: understanding key radiological features

International Nuclear Information System (INIS)

Dixon, S.; Benamore, R.

2010-01-01

Many radiologists find it challenging to distinguish between the different interstitial idiopathic pneumonias (IIPs). The British Thoracic Society guidelines on interstitial lung disease (2008) recommend the formation of multidisciplinary meetings, with diagnoses made by combined radiological, pathological, and clinical findings. This review focuses on understanding typical and atypical radiological features on high-resolution computed tomography between the different IIPs, to help the radiologist determine when a confident diagnosis can be made and how to deal with uncertainty.

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

Science.gov (United States)

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

2017-09-22

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

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods

Directory of Open Access Journals (Sweden)

Kaiyang Qu

2017-09-01

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

EEG Eye State Identification Using Incremental Attribute Learning with Time-Series Classification

Directory of Open Access Journals (Sweden)

Ting Wang

2014-01-01

Full Text Available Eye state identification is a kind of common time-series classification problem which is also a hot spot in recent research. Electroencephalography (EEG is widely used in eye state classification to detect human's cognition state. Previous research has validated the feasibility of machine learning and statistical approaches for EEG eye state classification. This paper aims to propose a novel approach for EEG eye state identification using incremental attribute learning (IAL based on neural networks. IAL is a novel machine learning strategy which gradually imports and trains features one by one. Previous studies have verified that such an approach is applicable for solving a number of pattern recognition problems. However, in these previous works, little research on IAL focused on its application to time-series problems. Therefore, it is still unknown whether IAL can be employed to cope with time-series problems like EEG eye state classification. Experimental results in this study demonstrates that, with proper feature extraction and feature ordering, IAL can not only efficiently cope with time-series classification problems, but also exhibit better classification performance in terms of classification error rates in comparison with conventional and some other approaches.

Main features of the geological structure of upper-Frasnian barrier reefs in relation to their petroleum content

Energy Technology Data Exchange (ETDEWEB)

Nikonov, N.I.

1981-01-01

Analysis of new geological geophysical and industrial materials has made it possible to distinguish in the boundary part of the late Devonician shoal carbonate shelf barrier reefs of various ages. In confines of individual distinguished reefs there have been established deposits of oil (Western Tebuksk, Pashsor and Khar'yatinsk). There are given prospecting features of classification of buried reefs and prognoses for the finding possible oil deposits in them (Beyaksk, Sandiveis reefs).

MRI of superficial soft tissue masses: analysis of features useful in distinguishing between benign and malignant lesions

Energy Technology Data Exchange (ETDEWEB)

Calleja, Michele; Dimigen, Marion; Saifuddin, Asif [Royal National Orthopaedic Hospital, Stanmore (United Kingdom)

2012-12-15

To identify the MRI features of superficial soft tissue masses, that may allow differentiation between malignant and non-malignant lesions. A total of 136 consecutive patients referred to a supra-regional musculoskeletal oncology center over a 10-year period with the diagnosis of a superficial soft tissue mass were included in this retrospective study. Features analyzed included patient demographics, lesion size, MRI signal characteristics, margins, lobulation, hemorrhage, necrosis, fascial edema, relationship to the fascia, as well as involvement of the skin. Comparison was then made with the final histological diagnosis. Of the patients reviewed, 58 were male and 78 were female, and the mean age was 49.9 years. The mean age for malignant lesions was 57.9 years, and that for non-neoplastic and benign conditions 41.9 years (p < 0.001). A significant relationship was identified between malignancy and lobulation (p < 0.01), hemorrhage (p < 0.001), fascial edema (p < 0.001), hemorrhage (p < 0.0001) and necrosis (p < 0.001). The relationship between skin thickening and skin contact and malignancy was also found to be significant. However, size was not found to be an important determining factor for malignancy, with a significant proportion of malignant superficial sarcomas measuring less than 5 cm in maximal diameter. This study has shown that a significant proportion of malignant superficial sarcomas measured less than 5 cm in maximal diameter. Fascial edema, skin thickening, skin contact, hemorrhage, and necrosis were found to be highly significant factors indicative of malignancy. Lobulation and peritumoral edema were also significant MRI features. (orig.)

Distinguishing method for contamination/radio-activation of radioactive wastes

International Nuclear Information System (INIS)

Fukazawa, Takuji; Kato, Keiichiro; Koda, Satoshi.

1994-01-01

The present invention concerns a method of distinguishing the contamination/radio-activation of radioactive wastes used in processing wastes generated upon dismantling of exhausted nuclear reactors. Especially, contaminated/radio-activation is distinguished for wastes having openings such as pipes and valves, by utilizing scattering of γ-rays or γ-ray to β-ray ratio. That is, ratio of scattered γ-rays and direct γ-rays or ratio of β-rays and γ-rays from radioactive wastes are measured and compared by a radiation detector, to distinguish whether the radioactive wastes contaminated materials or radio-activated materials. For example, when an object to be measured having an opening is contaminated at the inner side, the radiation detector facing to the opening mainly detects high direct γ-rays emitted from the object to be measured while a radiation detector not facing the opening mainly detects high scattered γ-rays relatively. On the other hand, when the object is a radio-activated material, any of the detectors detect scattered γ-rays, so that they can be distinguished by these ratios. (I.S.)

Entropic Lower Bound for Distinguishability of Quantum States

Directory of Open Access Journals (Sweden)

Seungho Yang

2015-01-01

Full Text Available For a system randomly prepared in a number of quantum states, we present a lower bound for the distinguishability of the quantum states, that is, the success probability of determining the states in the form of entropy. When the states are all pure, acquiring the entropic lower bound requires only the density operator and the number of the possible states. This entropic bound shows a relation between the von Neumann entropy and the distinguishability.

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.

New features of the Helioviewer Project

Science.gov (United States)

Ireland, J.; Zahniy, S.; Nicula, B.; Mueller, D.; Felix, S.; Verstringe, F.; Bourgoignie, B.

2016-12-01

This year saw the release of major new upgrades to the capabilities of helioviewer.org and JHelioviewer. The helioviewer.org interface was completely re-designed, and now provides image and feature/event time-lines and data download capabilities. JHelioviewer introduced interactive time-series, the ability to query different servers for different data, and image reprojection. We introduce the new features of these software releases and give use cases. We will summarize our latest usage statistics, and discuss what's coming up next for the Helioviewer Project. We will also be soliciting bug reports, requests for new features and comments on the effectiveness of helioviewer.org and JHelioviewer. What would you like to see next from the Helioviewer Project?

A new feature constituting approach to detection of vocal fold pathology

Science.gov (United States)

Hariharan, M.; Polat, Kemal; Yaacob, Sazali

2014-08-01

In the last two decades, non-invasive methods through acoustic analysis of voice signal have been proved to be excellent and reliable tool to diagnose vocal fold pathologies. This paper proposes a new feature vector based on the wavelet packet transform and singular value decomposition for the detection of vocal fold pathology. k-means clustering based feature weighting is proposed to increase the distinguishing performance of the proposed features. In this work, two databases Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database and MAPACI speech pathology database are used. Four different supervised classifiers such as k-nearest neighbour (k-NN), least-square support vector machine, probabilistic neural network and general regression neural network are employed for testing the proposed features. The experimental results uncover that the proposed features give very promising classification accuracy of 100% for both MEEI database and MAPACI speech pathology database.

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

Science.gov (United States)

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

Directory of Open Access Journals (Sweden)

Wenjia Liu

2013-01-01

Full Text Available This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate.

Measurements of spatial population synchrony: influence of time series transformations.

Science.gov (United States)

Chevalier, Mathieu; Laffaille, Pascal; Ferdy, Jean-Baptiste; Grenouillet, Gaël

2015-09-01

Two mechanisms have been proposed to explain spatial population synchrony: dispersal among populations, and the spatial correlation of density-independent factors (the "Moran effect"). To identify which of these two mechanisms is driving spatial population synchrony, time series transformations (TSTs) of abundance data have been used to remove the signature of one mechanism, and highlight the effect of the other. However, several issues with TSTs remain, and to date no consensus has emerged about how population time series should be handled in synchrony studies. Here, by using 3131 time series involving 34 fish species found in French rivers, we computed several metrics commonly used in synchrony studies to determine whether a large-scale climatic factor (temperature) influenced fish population dynamics at the regional scale, and to test the effect of three commonly used TSTs (detrending, prewhitening and a combination of both) on these metrics. We also tested whether the influence of TSTs on time series and population synchrony levels was related to the features of the time series using both empirical and simulated time series. For several species, and regardless of the TST used, we evidenced a Moran effect on freshwater fish populations. However, these results were globally biased downward by TSTs which reduced our ability to detect significant signals. Depending on the species and the features of the time series, we found that TSTs could lead to contradictory results, regardless of the metric considered. Finally, we suggest guidelines on how population time series should be processed in synchrony studies.

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...

Feature Extraction in the North Sinai Desert Using Spaceborne Synthetic Aperture Radar: Potential Archaeological Applications

Directory of Open Access Journals (Sweden)

Christopher Stewart

2016-10-01

Full Text Available Techniques were implemented to extract anthropogenic features in the desert region of North Sinai using data from the first- and second-generation Phased Array type L-band Synthetic Aperture Radar (PALSAR-1 and 2. To obtain a synoptic view over the study area, a mosaic of average, multitemporal (De Grandi filtered PALSAR-1 σ° backscatter of North Sinai was produced. Two subset regions were selected for further analysis. The first included an area of abundant linear features of high relative backscatter in a strategic, but sparsely developed area between the Wadi Tumilat and Gebel Maghara. The second included an area of low backscatter anomaly features in a coastal sabkha around the archaeological sites of Tell el-Farama, Tell el-Mahzan, and Tell el-Kanais. Over the subset region between the Wadi Tumilat and Gebel Maghara, algorithms were developed to extract linear features and convert them to vector format to facilitate interpretation. The algorithms were based on mathematical morphology, but to distinguish apparent man-made features from sand dune ridges, several techniques were applied. The first technique took as input the average σ° backscatter and used a Digital Elevation Model (DEM derived Local Incidence Angle (LAI mask to exclude sand dune ridges. The second technique, which proved more effective, used the average interferometric coherence as input. Extracted features were compared with other available information layers and in some cases revealed partially buried roads. Over the coastal subset region a time series of PALSAR-2 spotlight data were processed. The coefficient of variation (CoV of De Grandi filtered imagery clearly revealed anomaly features of low CoV. These were compared with the results of an archaeological field walking survey carried out previously. The features generally correspond with isolated areas identified in the field survey as having a higher density of archaeological finds, and interpreted as possible

The Economics of the Duration of the Baseball World Series

Science.gov (United States)

Cassuto, Alexander E.; Lowenthal, Franklin

2007-01-01

This note examines some statistical features of the major league baseball World Series. We show that, based upon actual historical data, we cannot reject the hypothesis that the two World Series teams are evenly matched. Yet, we can also calculate the relative strengths of the teams that would best match the actual outcomes, and we find that those…

About some distinguishing features of weak interactions

International Nuclear Information System (INIS)

Beshtoev, Kh.M.

1999-01-01

It is shown that, in contrast to strong and electromagnetic theories, additive conserved numbers (such as lepton, aromatic and another numbers) and γ 5 anomaly do not appear in the standard weak interaction theory. It means that in this interaction the additive numbers cannot be conserved. These results are the consequence of specific character of the weak interaction: the right components of spinors do not participate in this interaction. The schemes of violation of the aromatic and lepton numbers were considered

Javanese Character Feature Extraction Based on Shape Energy

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Galih Hendra Wibowo

2017-07-01

Full Text Available Javanese character is one of Indonesia's noble culture, especially in Java. However, the number of Javanese people who are able to read the letter has decreased so that there need to be conservation efforts in the form of a system that is able to recognize the characters. One solution to these problem lies in Optical Character Recognition (OCR studies, where one of its heaviest points lies in feature extraction which is to distinguish each character. Shape Energy is one of feature extraction method with the basic idea of how the character can be distinguished simply through its skeleton. Based on the basic idea, then the development of feature extraction is done based on its components to produce an angular histogram with various variations of multiples angle. Furthermore, the performance test of this method and its basic method is performed in Javanese character dataset, which has been obtained from various images, is 240 data with 19 labels by using K-Nearest Neighbors as its classification method. Performance values were obtained based on the accuracy which is generated through the Cross-Validation process of 80.83% in the angular histogram with an angle of 20 degrees, 23% better than Shape Energy. In addition, other test results show that this method is able to recognize rotated character with the lowest performance value of 86% at 180-degree rotation and the highest performance value of 96.97% at 90-degree rotation. It can be concluded that this method is able to improve the performance of Shape Energy in the form of recognition of Javanese characters as well as robust to the rotation.

Effect of parameter calculation in direct estimation of the Lyapunov exponent in short time series

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A. M. López Jiménez

2002-01-01

Full Text Available The literature about non-linear dynamics offers a few recommendations, which sometimes are divergent, about the criteria to be used in order to select the optimal calculus parameters in the estimation of Lyapunov exponents by direct methods. These few recommendations are circumscribed to the analysis of chaotic systems. We have found no recommendation for the estimation of λ starting from the time series of classic systems. The reason for this is the interest in distinguishing variability due to a chaotic behavior of determinist dynamic systems of variability caused by white noise or linear stochastic processes, and less in the identification of non-linear terms from the analysis of time series. In this study we have centered in the dependence of the Lyapunov exponent, obtained by means of direct estimation, of the initial distance and the time evolution. We have used generated series of chaotic systems and generated series of classic systems with varying complexity. To generate the series we have used the logistic map.

Distinguishing attack and second-preimage attack on encrypted message authentication codes (EMAC)

Science.gov (United States)

Ariwibowo, Sigit; Windarta, Susila

2016-02-01

In this paper we show that distinguisher on CBC-MAC can be applied to Encrypted Message Authentication Code (EMAC) scheme. EMAC scheme in general is vulnerable to distinguishing attack and second preimage attack. Distinguishing attack simulation on AES-EMAC using 225 message modifications, no collision have been found. According to second preimage attack simulation on AES-EMAC no collision found between EMAC value of S1 and S2, i.e. no second preimage found for messages that have been tested. Based on distinguishing attack simulation on truncated AES-EMAC we found collision in every message therefore we cannot distinguish truncated AES-EMAC with random function. Second-preimage attack is successfully performed on truncated AES-EMAC.

The morphing of geographical features by Fourier transformation.

Science.gov (United States)

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

Introduction to time series analysis and forecasting

CERN Document Server

Montgomery, Douglas C; Kulahci, Murat

2015-01-01

Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

Assessment of features for automatic CTG analysis based on expert annotation.

Science.gov (United States)

Chudácek, Vacláv; Spilka, Jirí; Lhotská, Lenka; Janku, Petr; Koucký, Michal; Huptych, Michal; Bursa, Miroslav

2011-01-01

Cardiotocography (CTG) is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO) since 1960's used routinely by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the ever-used features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and the features are assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes. Annotation derived from the panel of experts instead of the commonly utilized pH values was used for evaluation of the features on a large data set (552 records). We conclude the paper by presenting the best uncorrelated features and their individual rank of importance according to the meta-analysis of three different ranking methods. Number of acceleration and deceleration, interval index, as well as Lempel-Ziv complexity and Higuchi's fractal dimension are among the top five features.

Computerized detection of diffuse lung disease in MDCT: the usefulness of statistical texture features

International Nuclear Information System (INIS)

Wang Jiahui; Li Qiang; Li Feng; Doi Kunio

2009-01-01

Accurate detection of diffuse lung disease is an important step for computerized diagnosis and quantification of this disease. It is also a difficult clinical task for radiologists. We developed a computerized scheme to assist radiologists in the detection of diffuse lung disease in multi-detector computed tomography (CT). Two radiologists selected 31 normal and 37 abnormal CT scans with ground glass opacity, reticular, honeycombing and nodular disease patterns based on clinical reports. The abnormal cases in our database must contain at least an abnormal area with a severity of moderate or severe level that was subjectively rated by the radiologists. Because statistical texture features may lack the power to distinguish a nodular pattern from a normal pattern, the abnormal cases that contain only a nodular pattern were excluded. The areas that included specific abnormal patterns in the selected CT images were then delineated as reference standards by an expert chest radiologist. The lungs were first segmented in each slice by use of a thresholding technique, and then divided into contiguous volumes of interest (VOIs) with a 64 x 64 x 64 matrix size. For each VOI, we determined and employed statistical texture features, such as run-length and co-occurrence matrix features, to distinguish abnormal from normal lung parenchyma. In particular, we developed new run-length texture features with clear physical meanings to considerably improve the accuracy of our detection scheme. A quadratic classifier was employed for distinguishing between normal and abnormal VOIs by the use of a leave-one-case-out validation scheme. A rule-based criterion was employed to further determine whether a case was normal or abnormal. We investigated the impact of new and conventional texture features, VOI size and the dimensionality for regions of interest on detecting diffuse lung disease. When we employed new texture features for 3D VOIs of 64 x 64 x 64 voxels, our system achieved the

Feature-specific encoding flexibility in visual working memory.

Directory of Open Access Journals (Sweden)

Aki Kondo

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

Feature-specific encoding flexibility in visual working memory.

Science.gov (United States)

Kondo, Aki; Saiki, Jun

2012-01-01

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

Current Directional Protection of Series Compensated Line Using Intelligent Classifier

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M. Mollanezhad Heydarabadi

2016-12-01

Full Text Available Current inversion condition leads to incorrect operation of current based directional relay in power system with series compensated device. Application of the intelligent system for fault direction classification has been suggested in this paper. A new current directional protection scheme based on intelligent classifier is proposed for the series compensated line. The proposed classifier uses only half cycle of pre-fault and post fault current samples at relay location to feed the classifier. A lot of forward and backward fault simulations under different system conditions upon a transmission line with a fixed series capacitor are carried out using PSCAD/EMTDC software. The applicability of decision tree (DT, probabilistic neural network (PNN and support vector machine (SVM are investigated using simulated data under different system conditions. The performance comparison of the classifiers indicates that the SVM is a best suitable classifier for fault direction discriminating. The backward faults can be accurately distinguished from forward faults even under current inversion without require to detect of the current inversion condition.

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

Science.gov (United States)

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

2009-09-01

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

Corporate governance and audit features: SMEs evidence

OpenAIRE

Al-Najjar, Basil

2018-01-01

Purpose\\ud The purpose of this paper is to investigate the effect of corporate governance factors on audit features, namely, audit fees and the selection of Big 4 audit firms within the UK SMEs context.\\ud \\ud Design/methodology/approach\\ud The author uses different regression models to investigate the impact of corporate governance characteristics on audit features, and employs cross-sectional time series models as well as two-stage least squares technique. In addition, the author has used l...

Distinguishing Entailment and Presupposition Under Negation Test

Directory of Open Access Journals (Sweden)

Gatri Asti Putri Indarti

2016-12-01

Full Text Available Distinguishing entailment from presupposition is quite difficult because their semantic relation seems to be similar. Both entailment and presupposition have an automatic relationship based on the context. However, those semantic relations can still be differentiated by using negation test to show whether a pair is entailment or presupposition. This research focuses on sentences and utterances. Thus, this research aims to analyze and test pairs of entailment and pairs of presupposition by using negation in utterances. The data were twelve comic strips from the Internet and they were analysed by using a negation test. The analysis shows that negation test is useful to test entailment and presupposition in the comic strips. It can be concluded that the difficulty of distinguishing pair of entailment and presupposition in the comic strip using negation test has been successfully solved. In this case, negation test is suitable to test entailment and presupposition. This research can be developed further by other researchers to distinguish entailment and presupposition by using another test if the negation test cannot be used to any further extent.   DOI: https://doi.org/10.24071/llt.2015.180104

Riemannian multi-manifold modeling and clustering in brain networks

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Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

2017-08-01

This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.

Blood N-terminal Pro-brain Natriuretic Peptide and Interleukin-17 for Distinguishing Incomplete Kawasaki Disease from Infectious Diseases.

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Wu, Ling; Chen, Yuanling; Zhong, Shiling; Li, Yunyan; Dai, Xiahua; Di, Yazhen

2015-06-01

To explore the diagnostic value of blood N-terminal pro-brain natriuretic peptide (NT-proBNP) and interleukin-17(IL-17) for incomplete Kawasaki disease. Patients with Kawasaki disease, Incomplete Kawasaki disease and unclear infectious fever were included in this retrospective study. Their clinical features, and laboratory test results of blood NT-proBNP and IL-17 were collected and compared. 766 patients with complete clinical information were recruited, consisting of 291 cases of Kawasaki disease, 74 cases of incomplete Kawasaki disease, and 401 cases of unclear infectious diseases. When the consistency with indicator 2 and 3 in Kawasaki disease diagnosis criteria was assessed with blood IL-17 ?11.55 pg/mL and blood NT-proBNP ? 225.5 pg/dL as the criteria, the sensitivity and specificity for distinguishing incomplete Kawasaki disease and infectious diseases reached 86.5% and 94.8%, respectively. When we chose the consistency with indicator 1 and 2 in Kawasaki disease diagnosis criteria, the appearance of decrustation and/or the BCG erythema, blood IL-17 ?11.55 pg/mL and blood NT-Pro BNP ?225.5 pg/dL as the criteria, the sensitivity and specificity for distinguishing incomplete Kawasaki disease and infectious diseases was 43.2% and 100%, respectively. Blood NT-proBNP and IL-17 are useful laboratory indicators for distinguishing incomplete Kawasaki disease and infectious diseases at the early stage.

Advanced Grid Control Technologies Workshop Series | Energy Systems

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: Smart Grid and Beyond John McDonald, Director, Technical Strategy and Policy Development, General Control Technologies Workshop Series In July 2015, NREL's energy systems integration team hosted workshops the Energy Systems Integration Facility (ESIF) and included a technology showcase featuring projects

An Improved Rotation Forest for Multi-Feature Remote-Sensing Imagery Classification

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Yingchang Xiu

2017-11-01

Full Text Available Multi-feature, especially multi-temporal, remote-sensing data have the potential to improve land cover classification accuracy. However, sometimes it is difficult to utilize all the features efficiently. To enhance classification performance based on multi-feature imagery, an improved rotation forest, combining Principal Component Analysis (PCA and a boosting naïve Bayesian tree (NBTree, is proposed. First, feature extraction was carried out with PCA. The feature set was randomly split into several disjoint subsets; then, PCA was applied to each subset, and new training data for linear extracted features based on original training data were obtained. These steps were repeated several times. Second, based on the new training data, a boosting naïve Bayesian tree was constructed as the base classifier, which aims to achieve lower prediction error than a decision tree in the original rotation forest. At the classification phase, the improved rotation forest has two-layer voting. It first obtains several predictions through weighted voting in a boosting naïve Bayesian tree; then, the first-layer vote predicts by majority to obtain the final result. To examine the classification performance, the improved rotation forest was applied to multi-feature remote-sensing images, including MODIS Enhanced Vegetation Index (EVI imagery time series, MODIS Surface Reflectance products and ancillary data in Shandong Province for 2013. The EVI imagery time series was preprocessed using harmonic analysis of time series (HANTS to reduce the noise effects. The overall accuracy of the final classification result was 89.17%, and the Kappa coefficient was 0.71, which outperforms the original rotation forest and other classifier ensemble results, as well as the NASA land cover product. However, this new algorithm requires more computational time, meaning the efficiency needs to be further improved. Generally, the improved rotation forest has a potential advantage in

Picture archiving and communications system EFPACS series

International Nuclear Information System (INIS)

Hirasawa, Teiji; Mukasa, Minoru; Hiramatsu, Jun-ichi

1989-01-01

Fuji EFPACS (Effective Fuji PACS) is a picture archiving and communications system which efficiently executes centralized management of quantities of image data produced in a hospital. Main features of this system are high-speed retrieval and display function resulting from high-grade imaging technology. This system also strongly supports picture management for multi-modalities, picture storage, and education. EFPACS-500 and EFPACS-1000 series are available according to a system scale. An optimal system configuration can be obtained in a building-up style. This paper describes the features and performance of the EFPACS. (author)

Usefulness of confocal microscopy in distinguishing between basal cell carcinoma and intradermal melanocytic nevus on the face.

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Gamo, R; Floristan, U; Pampín, A; Caro, D; Pinedo, F; López-Estebaranz, J L

2015-10-01

The clinical distinction between basal cell carcinoma (BCC) and intradermal melanocytic nevus lesions on the face can be difficult, particularly in young patients or patients with multiple nevi. Dermoscopy is a useful tool for analyzing characteristic dermoscopic features of BCC, such as cartwheel structures, maple leaf-like areas, blue-gray nests and dots, and ulceration. It also reveals arborizing telangiectatic vessels and prominent curved vessels, which are typical of BCC, and comma vessels, which are typical of intradermal melanocytic nevi. It is, however, not always easy to distinguish between these 2 conditions, even when dermoscopy is used. We describe 2 facial lesions that posed a clinical and dermoscopic challenge in two 38-year-old patients; confocal microscopy showed separation between tumor nests and stroma and polarized nuclei, which are confocal microscopy features of basal cell carcinoma. Copyright © 2014 Elsevier España, S.L.U. y AEDV. All rights reserved.

Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

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Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

2017-07-01

Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

Long Range Dependence Prognostics for Bearing Vibration Intensity Chaotic Time Series

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Qing Li

2016-01-01

Full Text Available According to the chaotic features and typical fractional order characteristics of the bearing vibration intensity time series, a forecasting approach based on long range dependence (LRD is proposed. In order to reveal the internal chaotic properties, vibration intensity time series are reconstructed based on chaos theory in phase-space, the delay time is computed with C-C method and the optimal embedding dimension and saturated correlation dimension are calculated via the Grassberger–Procaccia (G-P method, respectively, so that the chaotic characteristics of vibration intensity time series can be jointly determined by the largest Lyapunov exponent and phase plane trajectory of vibration intensity time series, meanwhile, the largest Lyapunov exponent is calculated by the Wolf method and phase plane trajectory is illustrated using Duffing-Holmes Oscillator (DHO. The Hurst exponent and long range dependence prediction method are proposed to verify the typical fractional order features and improve the prediction accuracy of bearing vibration intensity time series, respectively. Experience shows that the vibration intensity time series have chaotic properties and the LRD prediction method is better than the other prediction methods (largest Lyapunov, auto regressive moving average (ARMA and BP neural network (BPNN model in prediction accuracy and prediction performance, which provides a new approach for running tendency predictions for rotating machinery and provide some guidance value to the engineering practice.

Voice Disorder Classification Based on Multitaper Mel Frequency Cepstral Coefficients Features

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Ömer Eskidere

2015-01-01

Full Text Available The Mel Frequency Cepstral Coefficients (MFCCs are widely used in order to extract essential information from a voice signal and became a popular feature extractor used in audio processing. However, MFCC features are usually calculated from a single window (taper characterized by large variance. This study shows investigations on reducing variance for the classification of two different voice qualities (normal voice and disordered voice using multitaper MFCC features. We also compare their performance by newly proposed windowing techniques and conventional single-taper technique. The results demonstrate that adapted weighted Thomson multitaper method could distinguish between normal voice and disordered voice better than the results done by the conventional single-taper (Hamming window technique and two newly proposed windowing methods. The multitaper MFCC features may be helpful in identifying voices at risk for a real pathology that has to be proven later.

Textural features of 18F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection.

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Saleem, Ben R; Beukinga, Roelof J; Boellaard, Ronald; Glaudemans, Andor W J M; Reijnen, Michel M P J; Zeebregts, Clark J; Slart, Riemer H J A

2017-05-01

The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although 18 F-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of this retrospective study was to examine the feasibility and utility of 18 F-FDG uptake heterogeneity characterized by textural features to diagnose AGI. Thirty patients with a history of aortic graft reconstruction who underwent 18 F-FDG PET/CT scanning were included. Sixteen patients were suspected to have an AGI (group I). AGI was considered proven only in the case of a positive bacterial culture. Positive cultures were found in 10 of the 16 patients (group Ia), and in the other six patients, cultures remained negative (group Ib). A control group was formed of 14 patients undergoing 18 F-FDG PET for other reasons (group II). PET images were assessed using conventional maximal standardized uptake value (SUVmax), tissue-to-background ratio (TBR), and visual grading scale (VGS). Additionally, 64 different 18 F-FDG PET based textural features were applied to characterize 18 F-FDG uptake heterogeneity. To select candidate predictors, univariable logistic regression analysis was performed (α = 0.16). The accuracy was satisfactory in case of an AUC > 0.8. The feature selection process yielded the textural features named variance (AUC = 0.88), high grey level zone emphasis (AUC = 0.87), small zone low grey level emphasis (AUC = 0.80), and small zone high grey level emphasis (AUC = 0.81) most optimal for distinguishing between groups I and II. SUVmax, TBR, and VGS were also able to distinguish between these groups with AUCs of 0.87, 0.78, and 0.90, respectively. The textural feature named short run high grey level emphasis was able to distinguish group Ia from Ib (AUC = 0.83), while for the same task the TBR and VGS were not found to be predictive. SUVmax

Determination of Sample Entropy and Fuzzy Measure Entropy Parameters for Distinguishing Congestive Heart Failure from Normal Sinus Rhythm Subjects

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Lina Zhao

2015-09-01

Full Text Available Entropy provides a valuable tool for quantifying the regularity of physiological time series and provides important insights for understanding the underlying mechanisms of the cardiovascular system. Before any entropy calculation, certain common parameters need to be initialized: embedding dimension m, tolerance threshold r and time series length N. However, no specific guideline exists on how to determine the appropriate parameter values for distinguishing congestive heart failure (CHF from normal sinus rhythm (NSR subjects in clinical application. In the present study, a thorough analysis on the selection of appropriate values of m, r and N for sample entropy (SampEn and recently proposed fuzzy measure entropy (FuzzyMEn is presented for distinguishing two group subjects. 44 long-term NRS and 29 long-term CHF RR interval recordings from http://www.physionet.org were used as the non-pathological and pathological data respectively. Extreme (>2 s and abnormal heartbeat RR intervals were firstly removed from each RR recording and then the recording was segmented with a non-overlapping segment length N of 300 and 1000, respectively. SampEn and FuzzyMEn were performed for each RR segment under different parameter combinations: m of 1, 2, 3 and 4, and r of 0.10, 0.15, 0.20 and 0.25 respectively. The statistical significance between NSR and CHF groups under each combination of m, r and N was observed. The results demonstrated that the selection of m, r and N plays a critical role in determining the SampEn and FuzzyMEn outputs. Compared with SampEn, FuzzyMEn shows a better regularity when selecting the parameters m and r. In addition, FuzzyMEn shows a better relative consistency for distinguishing the two groups, that is, the results of FuzzyMEn in the NSR group were consistently lower than those in the CHF group while SampEn were not. The selections of m of 2 and 3 and r of 0.10 and 0.15 for SampEn and the selections of m of 1 and 2 whenever r (herein

Familial identification: population structure and relationship distinguishability.

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Rohlfs, Rori V; Fullerton, Stephanie Malia; Weir, Bruce S

2012-02-01

With the expansion of offender/arrestee DNA profile databases, genetic forensic identification has become commonplace in the United States criminal justice system. Implementation of familial searching has been proposed to extend forensic identification to family members of individuals with profiles in offender/arrestee DNA databases. In familial searching, a partial genetic profile match between a database entrant and a crime scene sample is used to implicate genetic relatives of the database entrant as potential sources of the crime scene sample. In addition to concerns regarding civil liberties, familial searching poses unanswered statistical questions. In this study, we define confidence intervals on estimated likelihood ratios for familial identification. Using these confidence intervals, we consider familial searching in a structured population. We show that relatives and unrelated individuals from population samples with lower gene diversity over the loci considered are less distinguishable. We also consider cases where the most appropriate population sample for individuals considered is unknown. We find that as a less appropriate population sample, and thus allele frequency distribution, is assumed, relatives and unrelated individuals become more difficult to distinguish. In addition, we show that relationship distinguishability increases with the number of markers considered, but decreases for more distant genetic familial relationships. All of these results indicate that caution is warranted in the application of familial searching in structured populations, such as in the United States.

Familial identification: population structure and relationship distinguishability.

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Rori V Rohlfs

2012-02-01

Full Text Available With the expansion of offender/arrestee DNA profile databases, genetic forensic identification has become commonplace in the United States criminal justice system. Implementation of familial searching has been proposed to extend forensic identification to family members of individuals with profiles in offender/arrestee DNA databases. In familial searching, a partial genetic profile match between a database entrant and a crime scene sample is used to implicate genetic relatives of the database entrant as potential sources of the crime scene sample. In addition to concerns regarding civil liberties, familial searching poses unanswered statistical questions. In this study, we define confidence intervals on estimated likelihood ratios for familial identification. Using these confidence intervals, we consider familial searching in a structured population. We show that relatives and unrelated individuals from population samples with lower gene diversity over the loci considered are less distinguishable. We also consider cases where the most appropriate population sample for individuals considered is unknown. We find that as a less appropriate population sample, and thus allele frequency distribution, is assumed, relatives and unrelated individuals become more difficult to distinguish. In addition, we show that relationship distinguishability increases with the number of markers considered, but decreases for more distant genetic familial relationships. All of these results indicate that caution is warranted in the application of familial searching in structured populations, such as in the United States.

Issues and special features of animal health research

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Ducrot Christian

2011-08-01

Full Text Available Abstract In the rapidly changing context of research on animal health, INRA launched a collective discussion on the challenges facing the field, its distinguishing features, and synergies with biomedical research. As has been declared forcibly by the heads of WHO, FAO and OIE, the challenges facing animal health, beyond diseases transmissible to humans, are critically important and involve food security, agriculture economics, and the ensemble of economic activities associated with agriculture. There are in addition issues related to public health (zoonoses, xenobiotics, antimicrobial resistance, the environment, and animal welfare. Animal health research is distinguished by particular methodologies and scientific questions that stem from the specific biological features of domestic species and from animal husbandry practices. It generally does not explore the same scientific questions as research on human biology, even when the same pathogens are being studied, and the discipline is rooted in a very specific agricultural and economic context. Generic and methodological synergies nevertheless exist with biomedical research, particularly with regard to tools and biological models. Certain domestic species furthermore present more functional similarities with humans than laboratory rodents. The singularity of animal health research in relation to biomedical research should be taken into account in the organization, evaluation, and funding of the field through a policy that clearly recognizes the specific issues at stake. At the same time, the One Health approach should facilitate closer collaboration between biomedical and animal health research at the level of research teams and programmes.

Issues and special features of animal health research.

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Ducrot, Christian; Bed'hom, Bertrand; Béringue, Vincent; Coulon, Jean-Baptiste; Fourichon, Christine; Guérin, Jean-Luc; Krebs, Stéphane; Rainard, Pascal; Schwartz-Cornil, Isabelle; Torny, Didier; Vayssier-Taussat, Muriel; Zientara, Stephan; Zundel, Etienne; Pineau, Thierry

2011-08-24

In the rapidly changing context of research on animal health, INRA launched a collective discussion on the challenges facing the field, its distinguishing features, and synergies with biomedical research. As has been declared forcibly by the heads of WHO, FAO and OIE, the challenges facing animal health, beyond diseases transmissible to humans, are critically important and involve food security, agriculture economics, and the ensemble of economic activities associated with agriculture. There are in addition issues related to public health (zoonoses, xenobiotics, antimicrobial resistance), the environment, and animal welfare.Animal health research is distinguished by particular methodologies and scientific questions that stem from the specific biological features of domestic species and from animal husbandry practices. It generally does not explore the same scientific questions as research on human biology, even when the same pathogens are being studied, and the discipline is rooted in a very specific agricultural and economic context.Generic and methodological synergies nevertheless exist with biomedical research, particularly with regard to tools and biological models. Certain domestic species furthermore present more functional similarities with humans than laboratory rodents.The singularity of animal health research in relation to biomedical research should be taken into account in the organization, evaluation, and funding of the field through a policy that clearly recognizes the specific issues at stake. At the same time, the One Health approach should facilitate closer collaboration between biomedical and animal health research at the level of research teams and programmes.

The application of complex network time series analysis in turbulent heated jets

International Nuclear Information System (INIS)

Charakopoulos, A. K.; Karakasidis, T. E.; Liakopoulos, A.; Papanicolaou, P. N.

2014-01-01

In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series corresponding to regions that are close to the jet axis from time series originating at regions with a different dynamical regime based on the constructed network properties. Applying the transformation phase space method (k nearest neighbors) and also the visibility algorithm, we transformed time series into networks and evaluated the topological properties of the networks such as degree distribution, average path length, diameter, modularity, and clustering coefficient. The results show that the complex network approach allows distinguishing, identifying, and exploring in detail various dynamical regions of the jet flow, and associate it to the corresponding physical behavior. In addition, in order to reject the hypothesis that the studied networks originate from a stochastic process, we generated random network and we compared their statistical properties with that originating from the experimental data. As far as the efficiency of the two methods for network construction is concerned, we conclude that both methodologies lead to network properties that present almost the same qualitative behavior and allow us to reveal the underlying system dynamics

Entropy of Mixing of Distinguishable Particles

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Kozliak, Evguenii I.

2014-01-01

The molar entropy of mixing yields values that depend only on the number of mixing components rather than on their chemical nature. To explain this phenomenon using the logic of chemistry, this article considers mixing of distinguishable particles, thus complementing the well-known approach developed for nondistinguishable particles, for example,…

Heterogeneity of Monosymptomatic Resting Tremor in a Prospective Study: Clinical Features, Electrophysiological Test, and Dopamine Transporter Positron Emission Tomography

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Hua-Guang Zheng

2015-01-01

Conclusions: mRT is heterogeneous in presynaptic nigrostriatal dopaminergic degeneration, which can be determined by DAT-PET brain imaging. Clinical and electrophysiological features may provide clues to distinguish PD from SWEDDs.

Breast cancer molecular subtype classifier that incorporates MRI features.

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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.

Mid-Infrared Silicate Dust Features in Seyfert 1 Spectra

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

2007-12-01

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

Feature Selection from a Facial Image for Distinction of Sasang Constitution

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Imhoi Koo

2009-01-01

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

Feature Selection from a Facial Image for Distinction of Sasang Constitution

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

2009-01-01

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

Iniencephaly: Radiological and pathological features of a series of three cases

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Panduranga Chikkannaiah

2014-01-01

Full Text Available Iniencephaly is a rare form of neural tube defect with an incidence of 0.1-10 in 10,000 pregnancies. It is characterized by the presence of occipital bone defects at foramen magnum, fixed retroflexion of head, spinal dysmorphism, and lordosis of cervicothoracic vertebrae. It is usually associated with central nervous system, gastrointestinal, and cardiovascular anomalies. We present radiological and autopsy findings in a series of 3 cases of iniencephaly (gestational ages 29.3, 23, and 24 weeks first fetus in addition showed omphalocele, pulmonary hypoplasia, two lobes in right lung, accessory spleen, atrial septal defect, bilateral clubfoot, ambiguous genitalia, and single umbilical artery. Second fetus was a classical case of iniencephaly apertus with spina bifida. Third fetus had colpocephaly and bifid spine.

The use of synthetic input sequences in time series modeling

International Nuclear Information System (INIS)

Oliveira, Dair Jose de; Letellier, Christophe; Gomes, Murilo E.D.; Aguirre, Luis A.

2008-01-01

In many situations time series models obtained from noise-like data settle to trivial solutions under iteration. This Letter proposes a way of producing a synthetic (dummy) input, that is included to prevent the model from settling down to a trivial solution, while maintaining features of the original signal. Simulated benchmark models and a real time series of RR intervals from an ECG are used to illustrate the procedure

Model distinguishability and inference robustness in mechanisms of cholera transmission and loss of immunity.

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Lee, Elizabeth C; Kelly, Michael R; Ochocki, Brad M; Akinwumi, Segun M; Hamre, Karen E S; Tien, Joseph H; Eisenberg, Marisa C

2017-05-07

Mathematical models of cholera and waterborne disease vary widely in their structures, in terms of transmission pathways, loss of immunity, and a range of other features. These differences can affect model dynamics, with different models potentially yielding different predictions and parameter estimates from the same data. Given the increasing use of mathematical models to inform public health decision-making, it is important to assess model distinguishability (whether models can be distinguished based on fit to data) and inference robustness (whether inferences from the model are robust to realistic variations in model structure). In this paper, we examined the effects of uncertainty in model structure in the context of epidemic cholera, testing a range of models with differences in transmission and loss of immunity structure, based on known features of cholera epidemiology. We fit these models to simulated epidemic and long-term data, as well as data from the 2006 Angola epidemic. We evaluated model distinguishability based on fit to data, and whether the parameter values, model behavior, and forecasting ability can accurately be inferred from incidence data. In general, all models were able to successfully fit to all data sets, both real and simulated, regardless of whether the model generating the simulated data matched the fitted model. However, in the long-term data, the best model fits were achieved when the loss of immunity structures matched those of the model that simulated the data. Two parameters, one representing person-to-person transmission and the other representing the reporting rate, were accurately estimated across all models, while the remaining parameters showed broad variation across the different models and data sets. The basic reproduction number (R 0 ) was often poorly estimated even using the correct model, due to practical unidentifiability issues in the waterborne transmission pathway which were consistent across all models. Forecasting

Land Cover Classification Using Integrated Spectral, Temporal, and Spatial Features Derived from Remotely Sensed Images

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Yongguang Zhai

2018-03-01

Full Text Available Obtaining accurate and timely land cover information is an important topic in many remote sensing applications. Using satellite image time series data should achieve high-accuracy land cover classification. However, most satellite image time-series classification methods do not fully exploit the available data for mining the effective features to identify different land cover types. Therefore, a classification method that can take full advantage of the rich information provided by time-series data to improve the accuracy of land cover classification is needed. In this paper, a novel method for time-series land cover classification using spectral, temporal, and spatial information at an annual scale was introduced. Based on all the available data from time-series remote sensing images, a refined nonlinear dimensionality reduction method was used to extract the spectral and temporal features, and a modified graph segmentation method was used to extract the spatial features. The proposed classification method was applied in three study areas with land cover complexity, including Illinois, South Dakota, and Texas. All the Landsat time series data in 2014 were used, and different study areas have different amounts of invalid data. A series of comparative experiments were conducted on the annual time-series images using training data generated from Cropland Data Layer. The results demonstrated higher overall and per-class classification accuracies and kappa index values using the proposed spectral-temporal-spatial method compared to spectral-temporal classification methods. We also discuss the implications of this study and possibilities for future applications and developments of the method.

Predicting delayed cerebral ischemia after subarachnoid hemorrhage using physiological time series data.

Science.gov (United States)

Park, Soojin; Megjhani, Murad; Frey, Hans-Peter; Grave, Edouard; Wiggins, Chris; Terilli, Kalijah L; Roh, David J; Velazquez, Angela; Agarwal, Sachin; Connolly, E Sander; Schmidt, J Michael; Claassen, Jan; Elhadad, Noemie

2018-03-20

To develop and validate a prediction model for delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) using a temporal unsupervised feature engineering approach, demonstrating improved precision over standard features. 488 consecutive SAH admissions from 2006 to 2014 to a tertiary care hospital were included. Models were trained on 80%, while 20% were set aside for validation testing. Baseline information and standard grading scales were evaluated: age, sex, Hunt Hess grade, modified Fisher Scale (mFS), and Glasgow Coma Scale (GCS). An unsupervised approach applying random kernels was used to extract features from physiological time series (systolic and diastolic blood pressure, heart rate, respiratory rate, and oxygen saturation). Classifiers (Partial Least Squares, linear and kernel Support Vector Machines) were trained on feature subsets of the derivation dataset. Models were applied to the validation dataset. The performances of the best classifiers on the validation dataset are reported by feature subset. Standard grading scale (mFS): AUC 0.58. Combined demographics and grading scales: AUC 0.60. Random kernel derived physiologic features: AUC 0.74. Combined baseline and physiologic features with redundant feature reduction: AUC 0.77. Current DCI prediction tools rely on admission imaging and are advantageously simple to employ. However, using an agnostic and computationally inexpensive learning approach for high-frequency physiologic time series data, we demonstrated that our models achieve higher classification accuracy.

Acute ischaemic stroke prediction from physiological time series patterns

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Qing Zhang,

2013-05-01

Full Text Available BackgroundStroke is one of the major diseases with human mortality. Recent clinical research has indicated that early changes in common physiological variables represent a potential therapeutic target, thus the manipulation of these variables may eventually yield an effective way to optimise stroke recovery.AimsWe examined correlations between physiological parameters of patients during the first 48 hours after a stroke, and their stroke outcomes after 3 months. We wanted to discover physiological determinants that could be used to improve health outcomes by supporting the medical decisions that need to be made early on a patient’s stroke experience.Method We applied regression-based machine learning techniques to build a prediction algorithm that can forecast 3-month outcomes from initial physiological time series data during the first 48 hours after stroke. In our method, not only did we use statistical characteristics as traditional prediction features, but also we adopted trend patterns of time series data as new key features.ResultsWe tested our prediction method on a real physiological data set of stroke patients. The experiment results revealed an average high precision rate: 90%. We also tested prediction methods only considering statistical characteristics of physiological data, and concluded an average precision rate: 71%.ConclusionWe demonstrated that using trend pattern features in prediction methods improved the accuracy of stroke outcome prediction. Therefore, trend patterns of physiological time series data have an important role in the early treatment of patients with acute ischaemic stroke.

Is the Binding of Visual Features in Working Memory Resource-Demanding?

Science.gov (United States)

Allen, Richard J.; Baddeley, Alan D.; Hitch, Graham J.

2006-01-01

The episodic buffer component of working memory is assumed to play a role in the binding of features into chunks. A series of experiments compared memory for arrays of colors or shapes with memory for bound combinations of these features. Demanding concurrent verbal tasks were used to investigate the role of general attentional processes,…

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.

Textural features of {sup 18}F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection

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Saleem, Ben R.; Zeebregts, Clark J. [University of Groningen, University Medical Center Groningen, Department of Surgery, Division of Vascular Surgery, P.O. Box 30 001, Groningen (Netherlands); Beukinga, Roelof J.; Slart, Riemer H.J.A. [University of Groningen, University Medical Center Groningen, Nuclear Medicine and Molecular Imaging, Groningen (Netherlands); University of Twente, Department of Biomedical Photonic Imaging (BMPI), Enschede (Netherlands); Boellaard, Ronald; Glaudemans, Andor W.J.M. [University of Groningen, University Medical Center Groningen, Nuclear Medicine and Molecular Imaging, Groningen (Netherlands); Reijnen, Michel M.P.J. [Rijnstate Hospital, Department of Surgery, Arnhem (Netherlands)

2017-05-15

The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although {sup 18}F-fluorodeoxyglucose ({sup 18}F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of this retrospective study was to examine the feasibility and utility of {sup 18}F-FDG uptake heterogeneity characterized by textural features to diagnose AGI. Thirty patients with a history of aortic graft reconstruction who underwent {sup 18}F-FDG PET/CT scanning were included. Sixteen patients were suspected to have an AGI (group I). AGI was considered proven only in the case of a positive bacterial culture. Positive cultures were found in 10 of the 16 patients (group Ia), and in the other six patients, cultures remained negative (group Ib). A control group was formed of 14 patients undergoing {sup 18}F-FDG PET for other reasons (group II). PET images were assessed using conventional maximal standardized uptake value (SUVmax), tissue-to-background ratio (TBR), and visual grading scale (VGS). Additionally, 64 different {sup 18}F-FDG PET based textural features were applied to characterize {sup 18}F-FDG uptake heterogeneity. To select candidate predictors, univariable logistic regression analysis was performed (α = 0.16). The accuracy was satisfactory in case of an AUC > 0.8. The feature selection process yielded the textural features named variance (AUC = 0.88), high grey level zone emphasis (AUC = 0.87), small zone low grey level emphasis (AUC = 0.80), and small zone high grey level emphasis (AUC = 0.81) most optimal for distinguishing between groups I and II. SUVmax, TBR, and VGS were also able to distinguish between these groups with AUCs of 0.87, 0.78, and 0.90, respectively. The textural feature named short run high grey level emphasis was able to distinguish group Ia from Ib (AUC = 0.83), while for the same task the TBR and VGS were not found to be predictive

Textural features of "1"8F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection

International Nuclear Information System (INIS)

Saleem, Ben R.; Zeebregts, Clark J.; Beukinga, Roelof J.; Slart, Riemer H.J.A.; Boellaard, Ronald; Glaudemans, Andor W.J.M.; Reijnen, Michel M.P.J.

2017-01-01

The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although "1"8F-fluorodeoxyglucose ("1"8F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of this retrospective study was to examine the feasibility and utility of "1"8F-FDG uptake heterogeneity characterized by textural features to diagnose AGI. Thirty patients with a history of aortic graft reconstruction who underwent "1"8F-FDG PET/CT scanning were included. Sixteen patients were suspected to have an AGI (group I). AGI was considered proven only in the case of a positive bacterial culture. Positive cultures were found in 10 of the 16 patients (group Ia), and in the other six patients, cultures remained negative (group Ib). A control group was formed of 14 patients undergoing "1"8F-FDG PET for other reasons (group II). PET images were assessed using conventional maximal standardized uptake value (SUVmax), tissue-to-background ratio (TBR), and visual grading scale (VGS). Additionally, 64 different "1"8F-FDG PET based textural features were applied to characterize "1"8F-FDG uptake heterogeneity. To select candidate predictors, univariable logistic regression analysis was performed (α = 0.16). The accuracy was satisfactory in case of an AUC > 0.8. The feature selection process yielded the textural features named variance (AUC = 0.88), high grey level zone emphasis (AUC = 0.87), small zone low grey level emphasis (AUC = 0.80), and small zone high grey level emphasis (AUC = 0.81) most optimal for distinguishing between groups I and II. SUVmax, TBR, and VGS were also able to distinguish between these groups with AUCs of 0.87, 0.78, and 0.90, respectively. The textural feature named short run high grey level emphasis was able to distinguish group Ia from Ib (AUC = 0.83), while for the same task the TBR and VGS were not found to be predictive. SUVmax was found predictive

Case series of probable sporadic Creutzfeldt-Jakob disease from Eastern India

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Atanu Biswas

2013-01-01

Full Text Available Background: Creutzfeldt-Jakob disease is a rapidly progressive, fatal, transmissible neurodegenerative disorder caused by prion protein. It is still considered rare in countries like India. This is probably due to nonavailability of autopsy studies in majority of the center. The recent European diagnostic criterion for sporadic CJD (sCJD is useful for making an early diagnosis. Objective: To report a series of patients of probable sCJD from a neurology institute of eastern India. Materials and Methods: Patients of rapidly developing dementia fulfilling the diagnostic criteria for sCJD were included. All were investigated in detail to find out any possible treatable cause including electroencephalography (EEG, magnetic resonance imaging (MRI of brain, and cerebrospinal fluid analysis. Results: A total 10 patients of probable sCJD diagnosed using the European diagnostic criterion between December 2011 and January 2013. The clinical features are consistent with other reported series. While 60% of patients had the classical EEG findings, 100% had typical MRI features. Eight patients died within a mean duration of 4.56 months from the disease onset. Conclusions: The clinical features are similar to other reported series. Our observation raises question about the prevalence of this disease in India which needs more elaborate studies.

Reservoir Identification: Parameter Characterization or Feature Classification

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Cao, J.

2017-12-01

The ultimate goal of oil and gas exploration is to find the oil or gas reservoirs with industrial mining value. Therefore, the core task of modern oil and gas exploration is to identify oil or gas reservoirs on the seismic profiles. Traditionally, the reservoir is identify by seismic inversion of a series of physical parameters such as porosity, saturation, permeability, formation pressure, and so on. Due to the heterogeneity of the geological medium, the approximation of the inversion model and the incompleteness and noisy of the data, the inversion results are highly uncertain and must be calibrated or corrected with well data. In areas where there are few wells or no well, reservoir identification based on seismic inversion is high-risk. Reservoir identification is essentially a classification issue. In the identification process, the underground rocks are divided into reservoirs with industrial mining value and host rocks with non-industrial mining value. In addition to the traditional physical parameters classification, the classification may be achieved using one or a few comprehensive features. By introducing the concept of seismic-print, we have developed a new reservoir identification method based on seismic-print analysis. Furthermore, we explore the possibility to use deep leaning to discover the seismic-print characteristics of oil and gas reservoirs. Preliminary experiments have shown that the deep learning of seismic data could distinguish gas reservoirs from host rocks. The combination of both seismic-print analysis and seismic deep learning is expected to be a more robust reservoir identification method. The work was supported by NSFC under grant No. 41430323 and No. U1562219, and the National Key Research and Development Program under Grant No. 2016YFC0601

Square summable power series

CERN Document Server

de Branges, Louis

2015-01-01

This text for advanced undergraduate and graduate students introduces Hilbert space and analytic function theory, which is centered around the invariant subspace concept. The book's principal feature is the extensive use of formal power series methods to obtain and sometimes reformulate results of analytic function theory. The presentation is elementary in that it requires little previous knowledge of analysis, but it is designed to lead students to an advanced level of performance. This is achieved chiefly through the use of problems, many of which were proposed by former students. The book's

Recurrent Neural Network Applications for Astronomical Time Series

Science.gov (United States)

Protopapas, Pavlos

2017-06-01

The benefits of good predictive models in astronomy lie in early event prediction systems and effective resource allocation. Current time series methods applicable to regular time series have not evolved to generalize for irregular time series. In this talk, I will describe two Recurrent Neural Network methods, Long Short-Term Memory (LSTM) and Echo State Networks (ESNs) for predicting irregular time series. Feature engineering along with a non-linear modeling proved to be an effective predictor. For noisy time series, the prediction is improved by training the network on error realizations using the error estimates from astronomical light curves. In addition to this, we propose a new neural network architecture to remove correlation from the residuals in order to improve prediction and compensate for the noisy data. Finally, I show how to set hyperparameters for a stable and performant solution correctly. In this work, we circumvent this obstacle by optimizing ESN hyperparameters using Bayesian optimization with Gaussian Process priors. This automates the tuning procedure, enabling users to employ the power of RNN without needing an in-depth understanding of the tuning procedure.

Distinguishability and identifiability of products with small bore connectors according to ISO DIS 80369 series: risk analysis and summative evaluation

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Ibenthal Elisabeth

2017-09-01

Full Text Available The ISO 80369-series replace Luer-connectors in five application areas to fight misconnections. Although the standard avoids the mechanical problem of misconnections, the design of products and packages remains arbitrary. So, packages and products with same functions but different connectors could have similar designs and hence could be mixed-up.

Cost-Sensitive Feature Selection of Numeric Data with Measurement Errors

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Hong Zhao

2013-01-01

Full Text Available Feature selection is an essential process in data mining applications since it reduces a model’s complexity. However, feature selection with various types of costs is still a new research topic. In this paper, we study the cost-sensitive feature selection problem of numeric data with measurement errors. The major contributions of this paper are fourfold. First, a new data model is built to address test costs and misclassification costs as well as error boundaries. It is distinguished from the existing models mainly on the error boundaries. Second, a covering-based rough set model with normal distribution measurement errors is constructed. With this model, coverings are constructed from data rather than assigned by users. Third, a new cost-sensitive feature selection problem is defined on this model. It is more realistic than the existing feature selection problems. Fourth, both backtracking and heuristic algorithms are proposed to deal with the new problem. Experimental results show the efficiency of the pruning techniques for the backtracking algorithm and the effectiveness of the heuristic algorithm. This study is a step toward realistic applications of the cost-sensitive learning.

Rapid molecular technique to distinguish Fusarium species

CSIR Research Space (South Africa)

Lodolo, EJ

1993-03-01

Full Text Available The nuclear DNA (nDNA) of different isolates of three closely related, toxin-producing Fusarium species, F. moniliforme, F. nygamai and F. napiforme, was compared to ascertain the sensitivity of a molecular method to distinguish these three species...

Linking structural features of protein complexes and biological function.

Science.gov (United States)

Sowmya, Gopichandran; Breen, Edmond J; Ranganathan, Shoba

2015-09-01

Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions. © 2015 The Protein Society.

Normalizing the causality between time series

Science.gov (United States)

Liang, X. San

2015-08-01

Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

[Problem and assignment for distinguishing the Usher syndrome type].

Science.gov (United States)

Iwasaki, Satoshi; Yoshimura, Hidekane; Takeichi, Norito; Satou, Hiroaki; Ishikawa, Kotaro; Kaga, Kimitaka; Kumakawa, Kozou; Nagai, Kyoko; Furuya, Nobuhiko; Ikezono, Tetsuo; Nakanishi, Hiroshi; Naitou, Yasu; Fukushima, Kunihiro; Tono, Tetsuya; Kimitsuki, Takashi; Nishio, Shinya; Takumi, Yutaka; Usami, Shinichi

2012-10-01

Usher syndrome is an autosomal-recessive disorder that causes bilateral sensorineural hearing loss, retinitis pigmentosa (RP), and occasionally vestibular dysfunction. Usher syndrome types 1, 2, and 3 can be distinguished by differences in audiovestibular features. The objectives of this retrospective study were to evaluate 26 patients with Usher syndrome clinically. The 26 patients (male: 12 cases, female: 14 cases) with Usher syndrome, with a clinical diagnosis based on symptoms of bilateral sensorineural hearing loss and RP, had been registered from 13 hospitals as a multicenter study. We assessed the clinical history and performed audiovestibular and ophthalmologic examinations, and genetic testing. Eleven of the patients were classified as having Usher type 1 (38.5%), 6 with Usher type 2 (23.1%), and 9 with Usher type 3 (38.5%). However, many patients with atypical Usher type 1 (70%) and type 2 (83.3%) were found compared with Usher type 3 (10%). The conductive rate of vestibular examinations including the caloric test (50%) was low. There were many variations in the clinical symptoms in Usher syndrome patients, therefore the classification of Usher types 1, 2, and 3 has been complicated. We have proposed a flowchart for the diagnosis of Usher types 1, 2, and 3.

A very British affair six Britons and the development of time series analysis during the 20th century

CERN Document Server

Mills, T

2012-01-01

This book develops the major themes of time series analysis from its formal beginnings in the early part of the 20th century to the present day through the research of six distinguished British statisticians, all of whose work is characterised by the British traits of pragmatism and the desire to solve practical problems of importance.

Intraductal papillary mucinous neoplasms of the pancreas: reporting clinically relevant features.

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Del Chiaro, Marco; Verbeke, Caroline

2017-05-01

Intraductal papillary mucinous neoplasms (IPMNs) of the pancreas can exhibit a wide spectrum of macroscopic and microscopic appearances. This not only causes occasional difficulties for the reporting pathologist in distinguishing these tumours from other lesions, but is also relevant clinically. As evidence accumulates, it becomes clear that multiple macroscopic and histological features of these neoplasms are relevant to the risk for malignant transformation and, consequently, of prime importance for clinical patient management. The need for detailed reporting is therefore increasing. This review discusses the panoply of gross and microscopic features of IPMN as well as the recommendations from recent consensus meetings regarding the pathology reporting on this tumour entity. © 2016 John Wiley & Sons Ltd.

Using tactile features to help functionally blind individuals denominate banknotes.

Science.gov (United States)

Lederman, Susan J; Hamilton, Cheryl

2002-01-01

This study, which was conducted for the Bank of Canada, assessed the feasibility of presenting a raised texture feature together with a tactile denomination code on the next Canadian banknote series ($5, $10, $20, $50, and $100). Adding information accessible by hand would permit functionally blind individuals to independently denominate banknotes. In Experiment 1, 20 blindfolded, sighted university students denominated a set of 8 alternate tactile feature designs. Across the 8 design series, the proportion of correct responses never fell below .97; the mean response time per banknote ranged from 11.4 to 13.1 s. In Experiment 2, 27 functionally blind participants denominated 4 of the previous 8 candidate sets of banknotes. The proportion of correct responses never fell below .92; the corresponding mean response time per banknote ranged from 11.7 to 13.0 s. The Bank of Canada selected one of the four raised-texture designs for inclusion on its new banknote series. Other potential applications include designing haptic displays for teleoperation and virtual environment systems.

Using the MCNP Taylor series perturbation feature (efficiently) for shielding problems

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Favorite, Jeffrey

2017-09-01

The Taylor series or differential operator perturbation method, implemented in MCNP and invoked using the PERT card, can be used for efficient parameter studies in shielding problems. This paper shows how only two PERT cards are needed to generate an entire parameter study, including statistical uncertainty estimates (an additional three PERT cards can be used to give exact statistical uncertainties). One realistic example problem involves a detailed helium-3 neutron detector model and its efficiency as a function of the density of its high-density polyethylene moderator. The MCNP differential operator perturbation capability is extremely accurate for this problem. A second problem involves the density of the polyethylene reflector of the BeRP ball and is an example of first-order sensitivity analysis using the PERT capability. A third problem is an analytic verification of the PERT capability.

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.

Distinguishing between symbiotic stars and planetary nebulae

Science.gov (United States)

Iłkiewicz, K.; Mikołajewska, J.

2017-10-01

Context. The number of known symbiotic stars (SySt) is still significantly lower than their predicted population. One of the main problems in finding the total population of SySt is the fact that their spectrum can be confused with other objects, such as planetary nebulae (PNe) or dense H II regions. This problem is reinforced by the fact that in a significant fraction of established SySt the emission lines used to distinguish them from other objects are not present. Aims: We aim at finding new diagnostic diagrams that could help separate SySt from PNe. Additionally, we examine a known sample of extragalactic PNe for candidate SySt. Methods: We employed emission line fluxes of known SySt and PNe from the literature. Results: We found that among the forbidden lines in the optical region of spectrum, only the [O III] and [N II] lines can be used as a tool for distinguishing between SySt and PNe, which is consistent with the fact that they have the highest critical densities. The most useful diagnostic that we propose is based on He I lines, which are more common and stronger in SySt than forbidden lines. All these useful diagnostic diagrams are electron density indicators that better distinguish PNe and ionized symbiotic nebulae. Moreover, we found six new candidate SySt in the Large Magellanic Cloud and one in M 81. If confirmed, the candidate in M 81 would be the farthest known SySt thus far.

Features of two-phase flow in a microchannel of 0.05×20 mm

Science.gov (United States)

Ronshin, Fedor

2017-10-01

We have studied the two-phase flow in a microchannel with cross-section of 0.05×20 mm2. The following two-phase flow regimes have been registered: jet, bubble, stratified, annular, and churn ones. The main features of flow regimes in this channel such as formation of liquid droplets in all two-phase flows have been distinguished.

Case series in cognitive neuropsychology: promise, perils, and proper perspective.

Science.gov (United States)

Rapp, Brenda

2011-10-01

Schwartz and Dell (2010) advocated for a major role for case series investigations in cognitive neuropsychology. They defined the key features of this approach and presented a number of arguments and examples illustrating the benefits of case series studies and their contribution to computational cognitive neuropsychology. In the Special Issue on "Case Series in Cognitive Neuropsychology" there are six commentaries on Schwartz and Dell as well as a response to the six commentaries by Dell and Schwartz (2011 this issue). In this paper, I provide a brief summary of the key points made in Schwartz and Dell, and I review the promise and perils of case series design as revealed by the six commentaries. I conclude by placing the set of papers within a broader perspective, providing some clarification of the historical record on case series and single-case approaches, raising some cautionary notes for case series studies and situating both case series and single-case approaches within the larger context of theory development in the cognitive sciences.

Case Series in Cognitive Neuropsychology: Promise, Perils and Proper Perspective

Science.gov (United States)

Rapp, Brenda

2012-01-01

Schwartz & Dell (2010) advocated for a major role for case series investigations in cognitive neuropsychology. They defined the key features of this approach and presented a number of arguments and examples illustrating the benefits of case series studies and their contribution to computational cognitive neuropsychology. In the Special Issue on “Case Series in Cognitive Neuropsychology” there are six commentaries on Schwartz and Dell (2010) as well as a response to the six commentaries by Dell and Schwartz. In this paper, I provide a brief summary of the key points made in Schwartz and Dell (2010) and I review the promise and perils of case series design as revealed by the six commentaries. I conclude by placing the set of papers within a broader perspective, providing some clarification of the historical record on case series and single case approaches, raising some cautionary notes for case series studies and situating both case series and single case approaches within the larger context of theory development in the cognitive sciences. PMID:22746685

How to Distinguish Patients with pSS among Individuals with Dryness without Invasive Diagnostic Studies

Directory of Open Access Journals (Sweden)

Agata Sebastian

2018-01-01

Full Text Available In the course of pSS, inflammatory cell infiltration consists mainly of lymphocytes infiltrating exocrine glands, which leads to their impaired function. The characteristic feature is generalized dryness. The aim of this study was to attempt to answer the question whether it is possible to distinguish between patients with pSS and individuals with dryness caused by other pathologies without applying invasive studies. The study included 68 patients with pSS and 43 healthy controls with dryness. FS ≥ 1 was observed in 90% of patients with pSS (with or without dryness, and only in 23% of the control group (only with xerostomia. In the pSS group, anaemia (p=0.0085, lymphocytopenia (p=0.0006, elevated ERS (p=0.001, higher RF titer, and ANA antibodies were noted. Configuration of anti-SSA + SSB + Ro52 antibodies was characteristic for the pSS group. Considering the clinical symptoms, statistically significant differences were noted between pSS patients and the control group in frequency (p=0.02 and severity (p=0.042 of fatigue, lymphadenopathy, major salivary gland involvement, and photosensitivity to UV light. In conclusion, invasive methods are pivotal in pSS diagnosis in this salivary gland biopsy. Chronic fatigue syndrome is more common in pSS patients and can be subjective distinguishing factor in the group of people with dryness.

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

International Nuclear Information System (INIS)

Munoz-Diosdado, A

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

Energy Technology Data Exchange (ETDEWEB)

Munoz-Diosdado, A [Department of Mathematics, Unidad Profesional Interdisciplinaria de Biotecnologia, Instituto Politecnico Nacional, Av. Acueducto s/n, 07340, Mexico City (Mexico)

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.

Single and Combined Diagnostic Value of Clinical Features and Laboratory Tests in Acute Appendicitis

NARCIS (Netherlands)

Laméris, Wytze; van Randen, Adrienne; Go, Peter M. N. Y. H.; Bouma, Wim H.; Donkervoort, Sandra C.; Bossuyt, Patrick M. M.; Stoker, Jaap; Boermeester, Marja A.

2009-01-01

Objectives: The objective was to evaluate the diagnostic accuracy of clinical features and laboratory test results in detecting acute appendicitis. Methods: Clinical features and laboratory test results were prospectively recorded in a consecutive series of 1,101 patients presenting with abdominal

Visibility bound caused by a distinguishable noise particle

International Nuclear Information System (INIS)

Gavenda, Miroslav; Celechovska, Lucie; Dusek, Miloslav; Filip, Radim; Soubusta, Jan

2011-01-01

We investigate how the distinguishability of a 'noise' particle degrades interference of the 'signal' particle. The signal, represented by an equatorial state of a photonic qubit, is mixed with noise, represented by another photonic qubit, via linear coupling on a beam splitter. We report on the degradation of the signal photon interference depending on the degree of indistinguishability between the signal and noise photons. When the photons are completely distinguishable in principle but technically indistinguishable, the visibility drops to the value 1/√(2). As the photons become more indistinguishable, the maximal visibility increases and reaches the unit value for completely indistinguishable photons. We have examined this effect experimentally using a setup with a fiber-optics two-photon Mach-Zehnder interferometer.

The Westinghouse Series 1000 Mobile Phone: Technology and applications

Science.gov (United States)

Connelly, Brian

1993-01-01

Mobile satellite communications will be popularized by the North American Mobile Satellite (MSAT) system. The success of the overall system is dependent upon the quality of the mobile units. Westinghouse is designing our unit, the Series 1000 Mobile Phone, with the user in mind. The architecture and technology aim at providing optimum performance at a low per unit cost. The features and functions of the Series 1000 Mobile Phone have been defined by potential MSAT users. The latter portion of this paper deals with who those users may be.

Distinguishing signatures of determinism and stochasticity in spiking complex systems

Science.gov (United States)

Aragoneses, Andrés; Rubido, Nicolás; Tiana-Alsina, Jordi; Torrent, M. C.; Masoller, Cristina

2013-01-01

We describe a method to infer signatures of determinism and stochasticity in the sequence of apparently random intensity dropouts emitted by a semiconductor laser with optical feedback. The method uses ordinal time-series analysis to classify experimental data of inter-dropout-intervals (IDIs) in two categories that display statistically significant different features. Despite the apparent randomness of the dropout events, one IDI category is consistent with waiting times in a resting state until noise triggers a dropout, and the other is consistent with dropouts occurring during the return to the resting state, which have a clear deterministic component. The method we describe can be a powerful tool for inferring signatures of determinism in the dynamics of complex systems in noisy environments, at an event-level description of their dynamics.

Conversion (dissociative) symptoms as a presenting feature in early onset bipolar disorder: a case series

OpenAIRE

Ghosal, Malay Kumar; Guha, Prathama; Sinha, Mausumi; Majumdar, Debabrata; Sengupta, Payel

2009-01-01

We present three cases of early onset bipolar disorder where dissociative (conversion) symptoms preceded the onset of mania. This case series underscores the significance of dissociative/conversion symptoms as an early atypical presentation in juvenile bipolar disorder.

RECONSTRUCTION OF PRECIPITATION SERIES AND ANALYSIS OF CLIMATE CHANGE OVER PAST 500 YEARS IN NORTHERN CHINA

Institute of Scientific and Technical Information of China (English)

RONG Yan-shu; TU Qi-pu

2005-01-01

It is important and necessary to get a much longer precipitation series in order to research features of drought/flood and climate change.Based on dryness and wetness grades series of 18 stations in Northern China of 533 years from 1470 to 2002, the Moving Cumulative Frequency Method (MCFM) was developed, moving average precipitation series from 1499 to 2002 were reconstructed by testing three kinds of average precipitation, and the features of climate change and dry and wet periods were researched by using reconstructed precipitation series in the present paper.The results showed that there were good relationship between the reconstructed precipitation series and the observation precipitation series since 1954 and their relative root-mean-square error were below 1.89%, that the relation between reconstructed series and the dryness and wetness grades series were nonlinear and this nonlinear relation implied that reconstructed series were reliable and could became foundation data for researching evolution of the drought and flood.Analysis of climate change upon reconstructed precipitation series revealed that although drought intensity of recent dry period from middle 1970s of 20th century until early 21st century was not the strongest in historical climate of Northern China, intensity and duration of wet period was a great deal decreasing and shortening respectively, climate evolve to aridification situation in Northern China.

FEATURE EXTRACTION FOR EMG BASED PROSTHESES CONTROL

Directory of Open Access Journals (Sweden)

R. Aishwarya

2013-01-01

Full Text Available The control of prosthetic limb would be more effective if it is based on Surface Electromyogram (SEMG signals from remnant muscles. The analysis of SEMG signals depend on a number of factors, such as amplitude as well as time- and frequency-domain properties. Time series analysis using Auto Regressive (AR model and Mean frequency which is tolerant to white Gaussian noise are used as feature extraction techniques. EMG Histogram is used as another feature vector that was seen to give more distinct classification. The work was done with SEMG dataset obtained from the NINAPRO DATABASE, a resource for bio robotics community. Eight classes of hand movements hand open, hand close, Wrist extension, Wrist flexion, Pointing index, Ulnar deviation, Thumbs up, Thumb opposite to little finger are taken into consideration and feature vectors are extracted. The feature vectors can be given to an artificial neural network for further classification in controlling the prosthetic arm which is not dealt in this paper.

The influence of noise on nonlinear time series detection based on Volterra-Wiener-Korenberg model

Energy Technology Data Exchange (ETDEWEB)

Lei Min [State Key Laboratory of Vibration, Shock and Noise, Shanghai Jiao Tong University, Shanghai 200030 (China)], E-mail: leimin@sjtu.edu.cn; Meng Guang [State Key Laboratory of Vibration, Shock and Noise, Shanghai Jiao Tong University, Shanghai 200030 (China)

2008-04-15

This paper studies the influence of noises on Volterra-Wiener-Korenberg (VWK) nonlinear test model. Our numerical results reveal that different types of noises lead to different behavior of VWK model detection. For dynamic noise, it is difficult to distinguish chaos from nonchaotic but nonlinear determinism. For time series, measure noise has no impact on chaos determinism detection. This paper also discusses various behavior of VWK model detection with surrogate data for different noises.

Could We Distinguish Child Users from Adults Using Keystroke Dynamics?

OpenAIRE

Uzun, Yasin; Bicakci, Kemal; Uzunay, Yusuf

2015-01-01

Significant portion of contemporary computer users are children, who are vulnerable to threats coming from the Internet. To protect children from such threats, in this study, we investigate how successfully typing data can be used to distinguish children from adults. For this purpose, we collect a dataset comprising keystroke data of 100 users and show that distinguishing child Internet users from adults is possible using Keystroke Dynamics with equal error rates less than 10 percent. However...

Palmprint Verification Using Time Series Method

Directory of Open Access Journals (Sweden)

A. A. Ketut Agung Cahyawan Wiranatha

2013-11-01

Full Text Available The use of biometrics as an automatic recognition system is growing rapidly in solving security problems, palmprint is one of biometric system which often used. This paper used two steps in center of mass moment method for region of interest (ROI segmentation and apply the time series method combined with block window method as feature representation. Normalized Euclidean Distance is used to measure the similarity degrees of two feature vectors of palmprint. System testing is done using 500 samples palms, with 4 samples as the reference image and the 6 samples as test images. Experiment results show that this system can achieve a high performance with success rate about 97.33% (FNMR=1.67%, FMR=1.00 %, T=0.036.

Psychological features of attention in archery

Directory of Open Access Journals (Sweden)

Ekaterina Yu. Korobeynikova

2017-06-01

Full Text Available The issue of attention is one of the leading in sports psychology. Quite often, athletes’ failures in competitions are ultimately connected with the attention processes, i.e. distraction, switching or loss of concentration. Simultaneously, each particular kind of sport is distinguished by a specific competitive situation and accordingly presents a number of requirements to athletes, including attention features. Archery is no exception. Thus, in shooting sports, concentration and stability of attention are often deemed as the most significant features of attention. The paper is devoted to the study of the attention dynamic properties in archers. Attention features of athletes were assessed depending on the sports major, gender, age, experience and level of competence. 65 archers from different regions of Russia took part in the study, including 34 males and 31 females, the average age being 16.29 ± 1.74. Experience ranges from 1 year to 8 years, average experience is 4.46 ± 1.93. The research results showed that archers are characterized by high indicators of stability of attention, and also high efficiency of solving attention problems. The professional success of archery was associated with the ability to distribute attention when necessary. At the same time, there were no significant differences in the features of attention for recurved and compound archers, which indicates the uniformity of tasks related to attention in the sporting practice of archers. Summing up, it is necessary to include skills in the distribution of attention in the program of psychological training of archers.

Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data

Science.gov (United States)

Hernández-Lemus, Enrique; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Fernández-López, J. Carlos; Hidalgo-Miranda, Alfredo; Jiménez-Sánchez, Gerardo

2008-02-01

The statistical study of large scale genomic data has turned out to be a very important tool in population genetics. Quantitative methods are essential to understand and implement association studies in the biomedical and health sciences. Nevertheless, the characterization of recently admixed populations has been an elusive problem due to the presence of a number of complex phenomena. For example, linkage disequilibrium structures are thought to be more complex than their non-recently admixed population counterparts, presenting the so-called ancestry blocks, admixed regions that are not yet smoothed by the effect of genetic recombination. In order to distinguish characteristic features for various populations we have implemented several methods, some of them borrowed or adapted from the analysis of nonlinear time series in statistical physics and quantitative physiology. We calculate the main fractal dimensions (Kolmogorov's capacity, information dimension and correlation dimension, usually named, D0, D1 and D2). We also have made detrended fluctuation analysis and information based similarity index calculations for the probability distribution of correlations of linkage disequilibrium coefficient of six recently admixed (mestizo) populations within the Mexican Genome Diversity Project [1] and for the non-recently admixed populations in the International HapMap Project [2]. Nonlinear correlations showed up as a consequence of internal structure within the haplotype distributions. The analysis of these correlations as well as the scope and limitations of these procedures within the biomedical sciences are discussed.

Liver scintigraphic features associated with alcoholism

International Nuclear Information System (INIS)

Drum, D.E.; Beard, J.O.

1978-01-01

The relationships between scintigraphic features and clinical alcoholism were studied by review of 2406 liver scintiphotos. Two distinct patterns were significantly associated with alcoholism: heterogeneous distribution of radiocolloid in the liver, and jointly increased uptake of tracer by the spleen and vertebral bone marrow. A total of 13 overall patterns were found to distinguish, with considerable reliability, alcoholics from all other patients. This finding reflects the frequency with which alcohol abuse is associated with hepatic dysfunction in hospital patients. These observations indicate an important role for the nuclear medicine physician in detection of alcoholism among patients referred for liver-spleen imaging, and they form a basis for comparison with the diagnostic efficacy of other methods of evaluating diffuse liver diseases

Stochastic nature of series of waiting times

Science.gov (United States)

Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi

2013-06-01

Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2series has a short-range correlation, and then we study its stochastic nature using the Markovian method and determine the corresponding Kramers-Moyal coefficients. As an example, we analyze the velocity fluctuations in high Reynolds number turbulence and determine the level dependence of Markov time scales, as well as the drift and diffusion coefficients. We show that the waiting time distributions exhibit power law tails, and we were able to model the distribution with a continuous time random walk.

Identification of Cytological Features Distinguishing Mucosa-Associated Lymphoid Tissue Lymphoma from Reactive Lymphoid Proliferation Using Thyroid Liquid-Based Cytology

Science.gov (United States)

Suzuki, Ayana; Hirokawa, Mitsuyoshi; Ito, Aki; Takada, Nami; Higuchi, Miyoko; Hayashi, Toshitetsu; Kuma, Seiji; Miyauchi, Akira

2018-01-01

Objective To identify cytological differences between mucosa-associated lymphoid tissue lymphoma (MALT-L) and nonneoplastic lymphocytes using thyroid liquid-based cytology (LBC). Study Design We observed LBC and conventional specimens from 35 MALT-L cases, 3 diffuse large B-cell cell lymphoma (DLBCL) cases, and 44 prominent nonneoplastic lymphocytic infiltration cases. Results In MALT-L cases, the incidence of lymphoglandular bodies in the LBC specimens was lower than that in the conventional specimens (p 10% of the lymphoid cells in LBC specimens. Two cases with prominent nonneoplastic lymphocytic infiltration also exhibited these findings. In LBC specimens, swollen naked nuclei with less punctate chromatin patterns and thin nuclear margins were observed in 92.1% of lymphoma and 20.5% of prominent nonneoplastic lymphocytic infiltration. Elongated nuclei were significantly more apparent in thyroid lymphoma than in prominent nonneoplastic lymphocytic infiltration (p < 0.001), with a significantly higher incidence in LBC specimens than in conventional specimens (p < 0.001). Conclusions Lymphoglandular bodies are not reliable markers for lymphoma diagnosis using LBC specimens. Large, swollen naked, and elongated nuclei are useful in distinguishing thyroid lymphoma from nonneoplastic lymphocytes in LBC specimens. PMID:29597203

Identification of Cytological Features Distinguishing Mucosa-Associated Lymphoid Tissue Lymphoma from Reactive Lymphoid Proliferation Using Thyroid Liquid-Based Cytology.

Science.gov (United States)

Suzuki, Ayana; Hirokawa, Mitsuyoshi; Ito, Aki; Takada, Nami; Higuchi, Miyoko; Hayashi, Toshitetsu; Kuma, Seiji; Miyauchi, Akira

2018-01-01

To identify cytological differences between mucosa-associated lymphoid tissue lymphoma (MALT-L) and nonneoplastic lymphocytes using thyroid liquid-based cytology (LBC). We observed LBC and conventional specimens from 35 MALT-L cases, 3 diffuse large B-cell cell lymphoma (DLBCL) cases, and 44 prominent nonneoplastic lymphocytic infiltration cases. In MALT-L cases, the incidence of lymphoglandular bodies in the LBC specimens was lower than that in the conventional specimens (p 10% of the lymphoid cells in LBC specimens. Two cases with prominent nonneoplastic lymphocytic infiltration also exhibited these findings. In LBC specimens, swollen naked nuclei with less punctate chromatin patterns and thin nuclear margins were observed in 92.1% of lymphoma and 20.5% of prominent nonneoplastic lymphocytic infiltration. Elongated nuclei were significantly more apparent in thyroid lymphoma than in prominent nonneoplastic lymphocytic infiltration (p < 0.001), with a significantly higher incidence in LBC specimens than in conventional specimens (p < 0.001). Lymphoglandular bodies are not reliable markers for lymphoma diagnosis using LBC specimens. Large, swollen naked, and elongated nuclei are useful in distinguishing thyroid lymphoma from nonneoplastic lymphocytes in LBC specimens. © 2018 The Author(s) Published by S. Karger AG, Basell.

Feature Interactions Enable Decoding of Sensorimotor Transformations for Goal-Directed Movement

Science.gov (United States)

Barany, Deborah A.; Della-Maggiore, Valeria; Viswanathan, Shivakumar; Cieslak, Matthew

2014-01-01

Neurophysiology and neuroimaging evidence shows that the brain represents multiple environmental and body-related features to compute transformations from sensory input to motor output. However, it is unclear how these features interact during goal-directed movement. To investigate this issue, we examined the representations of sensory and motor features of human hand movements within the left-hemisphere motor network. In a rapid event-related fMRI design, we measured cortical activity as participants performed right-handed movements at the wrist, with either of two postures and two amplitudes, to move a cursor to targets at different locations. Using a multivoxel analysis technique with rigorous generalization tests, we reliably distinguished representations of task-related features (primarily target location, movement direction, and posture) in multiple regions. In particular, we identified an interaction between target location and movement direction in the superior parietal lobule, which may underlie a transformation from the location of the target in space to a movement vector. In addition, we found an influence of posture on primary motor, premotor, and parietal regions. Together, these results reveal the complex interactions between different sensory and motor features that drive the computation of sensorimotor transformations. PMID:24828640

Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section

Directory of Open Access Journals (Sweden)

Chaolong Jia

2014-01-01

Full Text Available Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.

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

Science.gov (United States)

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

2014-03-01

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

Features of two-phase flow in a microchannel of 0.05×20 mm

Directory of Open Access Journals (Sweden)

Ronshin Fedor

2017-01-01

Full Text Available We have studied the two-phase flow in a microchannel with cross-section of 0.05×20 mm2. The following two-phase flow regimes have been registered: jet, bubble, stratified, annular, and churn ones. The main features of flow regimes in this channel such as formation of liquid droplets in all two-phase flows have been distinguished.

Computation of solar perturbations with Poisson series

Science.gov (United States)

Broucke, R.

1974-01-01

Description of a project for computing first-order perturbations of natural or artificial satellites by integrating the equations of motion on a computer with automatic Poisson series expansions. A basic feature of the method of solution is that the classical variation-of-parameters formulation is used rather than rectangular coordinates. However, the variation-of-parameters formulation uses the three rectangular components of the disturbing force rather than the classical disturbing function, so that there is no problem in expanding the disturbing function in series. Another characteristic of the variation-of-parameters formulation employed is that six rather unusual variables are used in order to avoid singularities at the zero eccentricity and zero (or 90 deg) inclination. The integration process starts by assuming that all the orbit elements present on the right-hand sides of the equations of motion are constants. These right-hand sides are then simple Poisson series which can be obtained with the use of the Bessel expansions of the two-body problem in conjunction with certain interation methods. These Poisson series can then be integrated term by term, and a first-order solution is obtained.

Oculomotor selection underlies feature retention in visual working memory.

Science.gov (United States)

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

2016-02-01

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

Using different classification models in wheat grading utilizing visual features

Science.gov (United States)

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

2018-04-01

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

Temporal acoustic measures distinguish primary progressive apraxia of speech from primary progressive aphasia.

Science.gov (United States)

Duffy, Joseph R; Hanley, Holly; Utianski, Rene; Clark, Heather; Strand, Edythe; Josephs, Keith A; Whitwell, Jennifer L

2017-05-01

The purpose of this study was to determine if acoustic measures of duration and syllable rate during word and sentence repetition, and a measure of within-word lexical stress, distinguish speakers with primary progressive apraxia of speech (PPAOS) from nonapraxic speakers with the agrammatic or logopenic variants of primary progressive aphasia (PPA), and control speakers. Results revealed that the PPAOS group had longer durations and reduced rate of syllable production for most words and sentences, and the measure of lexical stress. Sensitivity and specificity indices for the PPAOS versus the other groups were highest for longer multisyllabic words and sentences. For the PPAOS group, correlations between acoustic measures and perceptual ratings of AOS were moderately high to high. Several temporal measures used in this study may aid differential diagnosis and help quantify features of PPAOS that are distinct from those associated with PPA in which AOS is not present. Copyright © 2017 Elsevier Inc. All rights reserved.

Microprocessor Card for Cuban Series polarimeters Laserpol

International Nuclear Information System (INIS)

Arista Romeu, E.; Mora Mazorra, W.

2012-01-01

We present the design consists of a card based on a micro-processor 8-bit adds new software components and their basic living, which allow to deliver new services and expand the possibilities for use in other applications of the polarimeter LASERPOL series, as the polarimetric detection. Given the limitations of the original card it was necessary to introduce a series of changes that would allow to address new user requirements, and expand the possible applications of the instruments. This was done the expansion of the capacity of the EPROM and RAM memory, the decoder circuit was implemented memory map using a programmable integrated circuit, and introduced a real time clock with nonvolatile RAM, these features are exploited to the introduction of new features such as the realization of the polarimeter calibration by the user from a sample pattern or a calibration pattern used as a reference, and the incorporation of the time and date to the reports of measurements required industry for quality control processes. Card that is achieved along with the rest of the components is compatible with polarimeters LASERPOL 101M Series, 3M and LP4, pin to pin, which facilitates their incorporation into the polarimeters in operation in the industry 'in situ' replacement cards from previous models, allowing to extend the possibilities of statistical processing, precision and accuracy of the instruments. Improved measurements in the industry, resulting in significant savings by elimination of losses in production and raw materials. The improved response speed of reading the polarimeters LASERPOL Use and polarimetric detectors. (Author)

Integral fast reactor safety features

International Nuclear Information System (INIS)

Cahalan, J.E.; Kramer, J.M.; Marchaterre, J.F.; Mueller, C.J.; Pedersen, D.R.; Sevy, R.H.; Wade, D.C.; Wei, T.Y.C.

1988-01-01

The integral fast reactor (IFR) is an advanced liquid-metal-cooled reactor concept being developed at Argonne National Laboratory. The two major goals of the IFR development effort are improved economics and enhanced safety. In addition to liquid metal cooling, the principal design features that distinguish the IFR are: a pool-type primary system, and advanced ternary alloy metallic fuel, and an integral fuel cycle with on-site fuel reprocessing and fabrication. This paper focuses on the technical aspects of the improved safety margins available in the IFR concept. This increased level of safety is made possible by the liquid metal (sodium) coolant and pool-type primary system layout, which together facilitate passive decay heat removal, and a sodium-bonded metallic fuel pin design with thermal and neutronic properties that provide passive core responses which control and mitigate the consequences of reactor accidents

Bayesian near-boundary analysis in basic macroeconomic time series models

NARCIS (Netherlands)

M.D. de Pooter (Michiel); F. Ravazzolo (Francesco); R. Segers (René); H.K. van Dijk (Herman)

2008-01-01

textabstractSeveral lessons learnt from a Bayesian analysis of basic macroeconomic time series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic

Distinguishing feral and managed honeybees (Apis mellifera) using stable carbon isotopes

OpenAIRE

Anderson , Lucy; Dynes , Travis; Berry , Jennifer; Delaplane , Keith; McCormick , Lydia; Brosi , Berry

2014-01-01

International audience; The ability to distinguish feral and managed honeybees (Apis mellifera) has applications in studies of population genetics, parasite transmission, pollination, interspecific interactions, and bee breeding. We evaluated a diagnostic test based on theoretical differences in stable carbon isotope ratios generated by supplemental feeding. We evaluated (1) if carbon isotope ratios can distinguish feral and managed honeybees and (2) the temporal persistence of the signal aft...

Stars in Nutrition and Cancer Lecture Series | Division of Cancer Prevention

Science.gov (United States)

This lecture series features extraordinary contributors or "stars" in the field of cancer and nutrition research. Speakers highlight the important role that nutrition plays in modifying cancer development. Past lectures are videotaped and available for viewing. |

A Model to Partly but Reliably Distinguish DDOS Flood Traffic from Aggregated One

Directory of Open Access Journals (Sweden)

Ming Li

2012-01-01

Full Text Available Reliable distinguishing DDOS flood traffic from aggregated traffic is desperately desired by reliable prevention of DDOS attacks. By reliable distinguishing, we mean that flood traffic can be distinguished from aggregated one for a predetermined probability. The basis to reliably distinguish flood traffic from aggregated one is reliable detection of signs of DDOS flood attacks. As is known, reliably distinguishing DDOS flood traffic from aggregated traffic becomes a tough task mainly due to the effects of flash-crowd traffic. For this reason, this paper studies reliable detection in the underlying DiffServ network to use static-priority schedulers. In this network environment, we present a method for reliable detection of signs of DDOS flood attacks for a given class with a given priority. There are two assumptions introduced in this study. One is that flash-crowd traffic does not have all priorities but some. The other is that attack traffic has all priorities in all classes, otherwise an attacker cannot completely achieve its DDOS goal. Further, we suppose that the protected site is equipped with a sensor that has a signature library of the legitimate traffic with the priorities flash-crowd traffic does not have. Based on those, we are able to reliably distinguish attack traffic from aggregated traffic with the priorities that flash-crowd traffic does not have according to a given detection probability.

Fimbriae have distinguishable roles in Proteus mirabilis biofilm formation.

Science.gov (United States)

Scavone, Paola; Iribarnegaray, Victoria; Caetano, Ana Laura; Schlapp, Geraldine; Härtel, Steffen; Zunino, Pablo

2016-07-01

Proteus mirabilis is one of the most common etiological agents of complicated urinary tract infections, especially those associated with catheterization. This is related to the ability of P. mirabilis to form biofilms on different surfaces. This pathogen encodes 17 putative fimbrial operons, the highest number found in any sequenced bacterial species so far. The present study analyzed the role of four P. mirabilis fimbriae (MR/P, UCA, ATF and PMF) in biofilm formation using isogenic mutants. Experimental approaches included migration over catheter, swimming and swarming motility, the semiquantitative assay based on adhesion and crystal violet staining, and biofilm development by immunofluorescence and confocal microscopy. Different assays were performed using LB or artificial urine. Results indicated that the different fimbriae contribute to the formation of a stable and functional biofilm. Fimbriae revealed particular associated roles. First, all the mutants showed a significantly reduced ability to migrate across urinary catheter sections but neither swimming nor swarming motility were affected. However, some mutants formed smaller biofilms compared with the wild type (MRP and ATF) while others formed significantly larger biofilms (UCA and PMF) showing different bioarchitecture features. It can be concluded that P. mirabilis fimbriae have distinguishable roles in the generation of biofilms, particularly in association with catheters. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

Science.gov (United States)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Is hearing loss a feature of Joubert syndrome, a ciliopathy?

NARCIS (Netherlands)

Kroes, H.Y.; Van Zanten, B.G.A.; De Ru, S.A.; Boon, M.; Mancini, G.M.S.; van der Knaap, M.S.; Poll-The, B.; Lindhout, D.

2010-01-01

Objective: To assess if hearing loss is a feature of Joubert syndrome (JBS), one of the ciliopathies and therefore possibly associated with hearing loss. Design: Retrospective case series. Setting: University Children's Hospital. Patients: Dutch patients with JBS. Main outcome measures: Audiological

Aliens and existential elevators: absurdity and its shadows in Douglas Adams’s Hitch hiker series

Directory of Open Access Journals (Sweden)

M.A. van der Colff

2008-07-01

Full Text Available According to twentieth-century existentialist philosophy, the universe as we know it is steeped in senselessness, and the only possible means of survival is the construction of subjective meaning. Douglas Adams’s fictional universe portrayed in his “Hitch hiker” series reflects the arbitrary nature of existence, and the characters dwelling in this narrative space are faced with two existential choices: the one is defiance in the face of senselessness, the other is bleak despair. This article explores the existential choices made by prominent characters in the “Hitch hiker” series. The article distinguishes between and analyses the Sisyphus characters and their polar opposites (or nihilist shadows in Douglas Adams’s “Hitch hiker” series. Adams’s characters, be they human, alien or sentient machine, all face the same existential choice: actuate individual meaning, or resort to despondency. Characters who choose the first option are regarded as Sisyphus figures, whereas characters who choose the latter are referred to as shadows or nihilist nemeses.

Extraction of Coal and Gangue Geometric Features with Multifractal Detrending Fluctuation Analysis

Directory of Open Access Journals (Sweden)

Kai Liu

2018-03-01

Full Text Available The separation of coal and gangue is an important process of the coal preparation technology. The conventional way of manual selection and separation of gangue from the raw coal can be replaced by computer vision technology. In the literature, research on image recognition and classification of coal and gangue is mainly based on the grayscale and texture features of the coal and gangue. However, there are few studies on characteristics of coal and gangue from the perspective of their outline differences. Therefore, the multifractal detrended fluctuation analysis (MFDFA method is introduced in this paper to extract the geometric features of coal and gangue. Firstly, the outline curves of coal and gangue in polar coordinates are detected and achieved along the centroid, thereby the multifractal characteristics of the series are analyzed and compared. Subsequently, the modified local singular spectrum widths Δ h of the outline curve series are extracted as the characteristic variables of the coal and gangue for pattern recognition. Finally, the extracted geometric features by MFDFA combined with the grayscale and texture features of the images are compared with other methods, indicating that the recognition rate of coal gangue images can be increased by introducing the geometric features.

Characterizing locally distinguishable orthogonal product states

OpenAIRE

Feng, Yuan; Shi, Yaoyun

2007-01-01

Bennett et al. \\cite{BDF+99} identified a set of orthogonal {\\em product} states in the $3\\otimes 3$ Hilbert space such that reliably distinguishing those states requires non-local quantum operations. While more examples have been found for this counter-intuitive ``nonlocality without entanglement'' phenomenon, a complete and computationally verifiable characterization for all such sets of states remains unknown. In this Letter, we give such a characterization for the $3\\otimes 3$ space.

Series: Practical guidance to qualitative research. Part 1: Introduction.

Science.gov (United States)

Moser, Albine; Korstjens, Irene

2017-12-01

In the course of our supervisory work over the years, we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called Frequently Asked Questions. This journal series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By 'novice' we mean Master's students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of papers reporting on qualitative research. This first article describes the key features of qualitative research, provides publications for further learning and reading, and gives an outline of the series.

29 CFR 794.107 - “Establishment” distinguished.

Science.gov (United States)

2010-07-01

... the definition of “enterprise” in section 3(r), as set forth in § 794.106, that the activities of the... § 794.107 “Establishment” distinguished. The “enterprise” referred to in the section 7(b)(3) exemption... “an entire business or enterprise” which may include several separate places of business. (See...

FEATURES BASED ON NEIGHBORHOOD PIXELS DENSITY - A STUDY AND COMPARISON

Directory of Open Access Journals (Sweden)

Satish Kumar

2016-02-01

Full Text Available In optical character recognition applications, the feature extraction method(s used to recognize document images play an important role. The features are the properties of the pattern that can be statistical, structural and/or transforms or series expansion. The structural features are difficult to compute particularly from hand-printed images. The structure of the strokes present inside the hand-printed images can be estimated using statistical means. In this paper three features have been purposed, those are based on the distribution of B/W pixels on the neighborhood of a pixel in an image. We name these features as Spiral Neighbor Density, Layer Pixel Density and Ray Density. The recognition performance of these features has been compared with two more features Neighborhood Pixels Weight and Total Distances in Four Directions already studied in our work. We have used more than 20000 Devanagari handwritten character images for conducting experiments. The experiments are conducted with two classifiers i.e. PNN and k-NN.

Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

Science.gov (United States)

Wang, Na; Li, Dong; Wang, Qiwen

2012-12-01

The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government

TIGER/Line Shapefile, 2015, Series Information for the Address Range-Feature County-based Shapefile

Data.gov (United States)

US Census Bureau, Department of Commerce — The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county...

Synthesis and pharmacological evaluation of thiopyran analogues of the dopamine D-3 receptor-selective agonist (4aR,10bR)-(+)-trans-3,4,4a,10b-tetrahydro-4-n-propyl-2H,5H-[1]benzopyrano[4,3-b]-1,4-oxazin-9-ol (PD 128907)

NARCIS (Netherlands)

van Vliet, LA; Rodenhuis, N; Dijkstra, D; Wikstrom, H; Pugsley, TA; Serpa, KA; Meltzer, LT; Heffner, TG; Wise, LD; Lajiness, ME; Huff, RM; Svensson, K; Sundell, S; Lundmark, M

2000-01-01

Benzopyranoxazine (+)-7 (PD 128907) is the most dopamine (DA) D-3 receptor-selective agonist presently known. The only structural feature which distinguishes 7 from the analogous nonselective naphthoxazines is an oxygen atom in the 6-position. To extend this series of tricyclic DA agonists we used a

Automatic evaluation of intrapartum fetal heart rate recordings: a comprehensive analysis of useful features.

Science.gov (United States)

Chudáček, V; Spilka, J; Janků, P; Koucký, M; Lhotská, L; Huptych, M

2011-08-01

Cardiotocography is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO), used routinely since the 1960s by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes. We assess the features on a large data set (552 records) and unlike in other published papers we use three-class expert evaluation of the records instead of the pH values. We conclude the paper by presenting the best uncorrelated features and their individual rank of importance according to the meta-analysis of three different ranking methods. The number of accelerations and decelerations, interval index, as well as Lempel-Ziv complexity and Higuchi's fractal dimension are among the top five features.

Automatic evaluation of intrapartum fetal heart rate recordings: a comprehensive analysis of useful features

International Nuclear Information System (INIS)

Chudáček, V; Spilka, J; Lhotská, L; Huptych, M; Janků, P; Koucký, M

2011-01-01

Cardiotocography is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO), used routinely since the 1960s by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes. We assess the features on a large data set (552 records) and unlike in other published papers we use three-class expert evaluation of the records instead of the pH values. We conclude the paper by presenting the best uncorrelated features and their individual rank of importance according to the meta-analysis of three different ranking methods. The number of accelerations and decelerations, interval index, as well as Lempel–Ziv complexity and Higuchi's fractal dimension are among the top five features

Historicizing video game series through fan art discourses

Directory of Open Access Journals (Sweden)

Jan Švelch

2016-09-01

Full Text Available In this article, we argue that fannish histories should not be dismissed as mere nostalgia over past experiences of one's own media fandom. Instead they should be understood as complex narratives which combine various historical layers (personal, productional, fictional and influence the future reception of and anticipation for sequels. They also shed light on the personal histories of fans, which are often juxtaposed with extratextual and fictional histories of a video game series. The subjective nature of these historical discourses is not to be seen as a constraint but as a feature of everyday history which points to the prominence of historicizing in fan cultures of video game series. These topics are examined in the selected multimodal material from the site DeviantArt consisting of fan art pieces, authorial captions, and respective comments inspired by two single-player video game series: Tomb Raider and Mass Effect.

Varying ultrasound power level to distinguish surgical instruments and tissue.

Science.gov (United States)

Ren, Hongliang; Anuraj, Banani; Dupont, Pierre E

2018-03-01

We investigate a new framework of surgical instrument detection based on power-varying ultrasound images with simple and efficient pixel-wise intensity processing. Without using complicated feature extraction methods, we identified the instrument with an estimated optimal power level and by comparing pixel values of varying transducer power level images. The proposed framework exploits the physics of ultrasound imaging system by varying the transducer power level to effectively distinguish metallic surgical instruments from tissue. This power-varying image-guidance is motivated from our observations that ultrasound imaging at different power levels exhibit different contrast enhancement capabilities between tissue and instruments in ultrasound-guided robotic beating-heart surgery. Using lower transducer power levels (ranging from 40 to 75% of the rated lowest ultrasound power levels of the two tested ultrasound scanners) can effectively suppress the strong imaging artifacts from metallic instruments and thus, can be utilized together with the images from normal transducer power levels to enhance the separability between instrument and tissue, improving intraoperative instrument tracking accuracy from the acquired noisy ultrasound volumetric images. We performed experiments in phantoms and ex vivo hearts in water tank environments. The proposed multi-level power-varying ultrasound imaging approach can identify robotic instruments of high acoustic impedance from low-signal-to-noise-ratio ultrasound images by power adjustments.

Distinguishing quantum from classical oscillations in a driven phase qubit

International Nuclear Information System (INIS)

Shevchenko, S N; Omelyanchouk, A N; Zagoskin, A M; Savel'ev, S; Nori, Franco

2008-01-01

Rabi oscillations are coherent transitions in a quantum two-level system under the influence of a resonant drive, with a much lower frequency dependent on the perturbation amplitude. These serve as one of the signatures of quantum coherent evolution in mesoscopic systems. It was shown recently (Groenbech-Jensen N and Cirillo M 2005 Phys. Rev. Lett. 95 067001) that in phase qubits (current-biased Josephson junctions) this effect can be mimicked by classical oscillations arising due to the anharmonicity of the effective potential. Nevertheless, we find qualitative differences between the classical and quantum effects. Firstly, while the quantum Rabi oscillations can be produced by the subharmonics of the resonant frequency ω 10 (multiphoton processes), the classical effect also exists when the system is excited at the overtones, nω 10 . Secondly, the shape of the resonance is, in the classical case, characteristically asymmetric, whereas quantum resonances are described by symmetric Lorentzians. Thirdly, the anharmonicity of the potential results in the negative shift of the resonant frequency in the classical case, in contrast to the positive Bloch-Siegert shift in the quantum case. We show that in the relevant range of parameters these features allow us to distinguish confidently the bona fide Rabi oscillations from their classical Doppelgaenger

Is the binding of visual features in working memory resource-demanding?

Science.gov (United States)

Allen, Richard J; Baddeley, Alan D; Hitch, Graham J

2006-05-01

The episodic buffer component of working memory is assumed to play a role in the binding of features into chunks. A series of experiments compared memory for arrays of colors or shapes with memory for bound combinations of these features. Demanding concurrent verbal tasks were used to investigate the role of general attentional processes, producing load effects that were no greater on memory for feature combinations than for the features themselves. However, the binding condition was significantly less accurate with sequential rather than simultaneous presentation, especially for items earlier in the sequence. The findings are interpreted as evidence of a relatively automatic but fragile visual feature binding mechanism in working memory. Implications for the concept of an episodic buffer are discussed. 2006 APA, all rights reserved

Distinguishing advective and powered motion in self-propelled colloids

Science.gov (United States)

Byun, Young-Moo; Lammert, Paul E.; Hong, Yiying; Sen, Ayusman; Crespi, Vincent H.

2017-11-01

Self-powered motion in catalytic colloidal particles provides a compelling example of active matter, i.e. systems that engage in single-particle and collective behavior far from equilibrium. The long-time, long-distance behavior of such systems is of particular interest, since it connects their individual micro-scale behavior to macro-scale phenomena. In such analyses, it is important to distinguish motion due to subtle advective effects—which also has long time scales and length scales—from long-timescale phenomena that derive from intrinsically powered motion. Here, we develop a methodology to analyze the statistical properties of the translational and rotational motions of powered colloids to distinguish, for example, active chemotaxis from passive advection by bulk flow.

Identical Distinguishable Gas Particles in the Real World

Indian Academy of Sciences (India)

IAS Admin

particles, it requires more care to identify a gas of identical distinguishable particles ... properties (such as mass, charge, shape, and spin). Adopt an operational ... [6] which might appear to be a physical realization of the proto- typical system of ...

Is hearing loss a feature of Joubert syndrome, a ciliopathy?

NARCIS (Netherlands)

Kroes, Hester Y.; Van Zanten, Bert G. A.; De Ru, Sander A.; Boon, Maartje; Mancini, Grazia M. S.; Van der Knaap, Marjo S.; Poll-The, Bwee Tien; Lindhout, Dick

Objective To assess if hearing loss is a feature of Joubert syndrome (JBS). one of the ciliopathies and therefore possibly associated with hearing loss Design: Retrospective case series. Setting University Children's Hospital Patients Dutch patients with JBS. Main outcome measures Audiological data.

Is hearing loss a feature of Joubert syndrome, a ciliopathy?

NARCIS (Netherlands)

Kroes, Hester Y.; van Zanten, Bert G. A.; de Ru, Sander A.; Boon, Maartje; Mancini, Grazia M. S.; van der Knaap, Marjo S.; Poll-The, Bwee Tien; Lindhout, Dick

2010-01-01

Objective To assess if hearing loss is a feature of Joubert syndrome (JBS). one of the ciliopathies and therefore possibly associated with hearing loss Design: Retrospective case series. Setting University Children's Hospital Patients Dutch patients with JBS. Main outcome measures Audiological data.

Eccrine Porocarcinoma: Patient Characteristics, Clinical and Histopathologic Features, and Treatment in 7 Cases.

Science.gov (United States)

Gómez-Zubiaur, A; Medina-Montalvo, S; Vélez-Velázquez, M D; Polo-Rodríguez, I

2017-05-01

Eccrine porocarcinoma is a rare, malignant cutaneous adnexal tumor that arises from the ducts of sweat glands. Found mainly in patients of advanced age, this tumor has diverse clinical presentations. Histology confirms the diagnosis, detects features relevant to prognosis, and guides treatment. Growth is slow, but the prognosis is poor if the tumor metastasizes to lymph nodes or visceral organs. We report 7 cases of eccrine porocarcinoma, describing patient characteristics, the clinical and histopathologic features of the tumors, and treatments used. Our observations were similar to those of other published case series. Given the lack of therapeutic algorithms or protocols for this carcinoma, we propose a decision-making schema based on our review of the literature and our experience with this case series. The algorithm centers on sentinel lymph node biopsy and histologic features. Copyright © 2016 AEDV. Publicado por Elsevier España, S.L.U. All rights reserved.

Common dental features and craniofacial development of three siblings with Ter Haar syndrome.

Science.gov (United States)

Parker, K; Pabla, R; Hay, N; Ayliffe, P

2014-02-01

Ter Haar syndrome is a rare genetic syndrome with <30 cases reported worldwide. There is nothing within the published literature regarding the dental development and dental features of these patients. This case series examines three patients with Ter Haar syndrome and tracks their dental development and identifies common dental and skeletal features. All three patients received dental treatment and regular follow-up at Great Ormond Street Hospital Dental Department. These patients have many common dental and craniofacial features which poses the question as to whether these features are due to Ter Haar syndrome.

Methods for deconvolving sparse positive delta function series

International Nuclear Information System (INIS)

Trussell, H.J.; Schwalbe, L.A.

1981-01-01

Sparse delta function series occur as data in many chemical analyses and seismic methods. These original data are often sufficiently degraded by the recording instrument response that the individual delta function peaks are difficult to distinguish and measure. A method, which has been used to measure these peaks, is to fit a parameterized model by a nonlinear least-squares fitting algorithm. The deconvolution approaches described have the advantage of not requiring a parameterized point spread function, nor do they expect a fixed number of peaks. Two new methods are presented. The maximum power technique is reviewed. A maximum a posteriori technique is introduced. Results on both simulated and real data by the two methods are presented. The characteristics of the data can determine which method gives superior results. 5 figures

ALARA/ALARP distinguished

International Nuclear Information System (INIS)

Riley, P.

1992-01-01

In the United Kingdom the term ALARA, ''as low as reasonably achievable'' and the term ALARP ''as low as reasonably practicable'' are used in regulations, in conditions in licenses, in assessment principles and in guidance notes used in the nuclear industry. In fact the ALARA principle is a cornerstone on which much of radiation protection regulation is based. The words ''reasonably practicable'' in ALARP have an established meaning in UK law and are used extensively in statutes and regulations, in particular The Health and Safety Act 1974. The Select Committee of the House of Lords on the European Communities in 1986 concluded that public opinion will play a much larger part in deciding the future of nuclear power than is usual with questions of science and technology. Under the circumstances it is important to industry and the general public for the terms used in legislation to be clear and unambiguous. This paper by distinguishing the terms ALARA/ALARP, sets the scene for a more disciplined use of the terms. (author)

Las series televisivas juveniles: tramas y conflictos en una «teen series» Television Fiction Series Targeted at Young Audience: Plots and Conflicts Portrayed in a Teen Series

Directory of Open Access Journals (Sweden)

Núria García Muñoz

2011-10-01

Full Text Available Se presentan los principales hallazgos de un estudio sobre las «teen series», es decir las series de ficción televisiva protagonizadas por personajes adolescentes y dirigidas expresamente a una audiencia juvenil. El análisis del retrato de los jóvenes representados en productos específicamente dirigidos a un público juvenil tiene un valor muy significativo tanto por la producción de ficción como por la recepción, ya que los consumidores potenciales se encuentran en un momento clave del proceso de construcción de sus identidades. Después de repasar los principales antecedentes en el estudio de la representación de los jóvenes en la ficción televisiva, se describe el marco conceptual relativo a las «teen series» y se discute su relación con el consumo juvenil. Sucesivamente se presenta un estudio de caso que consiste en un análisis de contenido de la serie norteamericana «Dawson’s creek», realizado sobre una muestra representativa de tres temporadas de la serie, para analizar dos grupos de variables: variables relativas a los personajes y variables relativas a las tramas y a los conflictos. Se discuten los resultados relativos al segundo grupo de variables, con particular atención a las características de las tramas y al papel de los personajes en el desarrollo y en la resolución de las mismas. La aceptación de la identidad personal, el amor y la amistad han resultado ser las temáticas más recurrentes. Además, las relaciones sociales entre los personajes han resultado ejercer un papel fundamental en el desarrollo de las tramas y de los conflictos.This paper presents the main findings of a research project on teen series, which are television fiction series featuring teenagers and specifically targeted at a young audience. The analysis of the portrayal of young people in television fictional series specifically targeted at a young audience has a meaningful value both for television production and for audience reception

Soil forensics: How far can soil clay analysis distinguish between soil vestiges?

Science.gov (United States)

Corrêa, R S; Melo, V F; Abreu, G G F; Sousa, M H; Chaker, J A; Gomes, J A

2018-03-01

Soil traces are useful as forensic evidences because they frequently adhere to individuals and objects associated with crimes and can place or discard a suspect at/from a crime scene. Soil is a mixture of organic and inorganic components and among them soil clay contains signatures that make it reliable as forensic evidence. In this study, we hypothesized that soils can be forensically distinguished through the analysis of their clay fraction alone, and that samples of the same soil type can be consistently distinguished according to the distance they were collected from each other. To test these hypotheses 16 Oxisol samples were collected at distances of between 2m and 1.000m, and 16 Inceptisol samples were collected at distances of between 2m and 300m from each other. Clay fractions were extracted from soil samples and analyzed for hyperspectral color reflectance (HSI), X-ray diffraction crystallographic (XRD), and for contents of iron oxides, kaolinite and gibbsite. The dataset was submitted to multivariate analysis and results were from 65% to 100% effective to distinguish between samples from the two soil types. Both soil types could be consistently distinguished for forensic purposes according to the distance that samples were collected from each other: 1000m for Oxisol and 10m for Inceptisol. Clay color and XRD analysis were the most effective techniques to distinguish clay samples, and Inceptisol samples were more easily distinguished than Oxisol samples. Soil forensics seems a promising field for soil scientists as soil clay can be useful as forensic evidence by using routine analytical techniques from soil science. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

Unique features in the ARIES glovebox line

International Nuclear Information System (INIS)

Martinez, H.E.; Brown, W.G.; Flamm, B.; James, C.A.; Laskie, R.; Nelson, T.O.; Wedman, D.E.

1998-01-01

A series of unique features have been incorporated into the Advanced Recovery and Integrated Extraction System (ARIES) at the Los Alamos National Laboratory, TA-55 Plutonium Facility. The features enhance the material handling in the process of the dismantlement of nuclear weapon primaries in the glovebox line. Incorporated into these features are the various plutonium process module's different ventilation zone requirements that the material handling systems must meet. These features include a conveyor system that consists of a remotely controlled cart that transverses the length of the conveyor glovebox, can be operated from a remote location and can deliver process components to the entrance of any selected module glovebox. Within the modules there exists linear motion material handling systems with lifting hoist, which are controlled via an Allen Bradley control panel or local control panels. To remove the packaged products from the hot process line, the package is processed through an air lock/electrolytic decontamination process that removes the radioactive contamination from the outside of the package container and allows the package to be removed from the process line

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.

Teacher Resource Book for Population Pressure in Indonesia, Problems of Industrialization in Eurasia, Power Blocs in Eurasia. Man on the Earth Series.

Science.gov (United States)

Gunn, Angus

This teacher's resource book is a guide to three intermediate texts about Eurasia entitled Population Pressure in Indonesia, Problems of Industrialization in Eurasia, and Power Blocs in Eurasia. The texts are part of the series, Man on the Earth, which probes broad-based issues confronting mankind. The resource book distinguishes 18 major concepts…

78 FR 12329 - Distinguishing Medical Device Recalls From Product Enhancements; Reporting Requirements; Draft...

Science.gov (United States)

2013-02-22

... medical devices to take timely action to correct violative devices or remove them from the marketplace...] Distinguishing Medical Device Recalls From Product Enhancements; Reporting Requirements; Draft Guidance for... draft guidance entitled ``Distinguishing Medical Device Recalls From Product Enhancements; Reporting...

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

Science.gov (United States)

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

The Risk Return Relationship: Evidence from Index Return and Realised Variance Series

OpenAIRE

Minxian Yang

2014-01-01

The risk return relationship is analysed in bivariate models for return and realised variance(RV) series. Based on daily time series from 21 international market indices for more than 13 years (January 2000 to February 2013), the empirical findings support the arguments of risk return tradeoff, volatility feedback and statistical balance. It is reasoned that the empirical risk return relationship is primarily shaped by two important data features: the negative contemporaneous correlation betw...

MRI features of peripheral traumatic neuromas

Energy Technology Data Exchange (ETDEWEB)

Ahlawat, Shivani [Johns Hopkins University School of Medicine, Musculoskeletal Radiology Section, The Russell H. Morgan Department of Radiology and Radiological Science, Baltimore, MD (United States); Belzberg, Allan J. [The Johns Hopkins Hospital, Department of Neurosurgery, Baltimore, MD (United States); Montgomery, Elizabeth A. [The Johns Hopkins Hospital, Pathology, Oncology and Orthopedic Surgery, Baltimore, MD (United States); Fayad, Laura M. [Department of Orthopedic Surgery, Department of Radiology and Radiological Science, Musculoskeletal Imaging Section Chief, The Johns Hopkins Medical Institutions, Baltimore, MD (United States); The Johns Hopkins Medical Institutions, Department of Orthopedic Surgery, Baltimore, MD (United States)

2016-04-15

To describe the MRI appearance of traumatic neuromas on non-contrast and contrast-enhanced MRI sequences. This IRB-approved, HIPAA-compliant study retrospectively reviewed 13 subjects with 20 neuromas. Two observers reviewed pre-operative MRIs for imaging features of neuroma (size, margin, capsule, signal intensity, heterogeneity, enhancement, neurogenic features and denervation) and the nerve segment distal to the traumatic neuroma. Descriptive statistics were reported. Pearson's correlation was used to examine the relationship between size of neuroma and parent nerve. Of 20 neuromas, 13 were neuromas-in-continuity and seven were end-bulb neuromas. Neuromas had a mean size of 1.5 cm (range 0.6-4.8 cm), 100 % (20/20) had indistinct margins and 0 % (0/20) had a capsule. Eighty-eight percent (7/8) showed enhancement. All 100 % (20/20) had tail sign; 35 % (7/20) demonstrated discontinuity from the parent nerve. None showed a target sign. There was moderate positive correlation (r = 0.68, p = 0.001) with larger neuromas arising from larger parent nerves. MRI evaluation of the nerve segment distal to the neuroma showed increased size (mean size 0.5 cm ± 0.4 cm) compared to the parent nerve (mean size 0.3 cm ± 0.2 cm). Since MRI features of neuromas include enhancement, intravenous contrast medium cannot be used to distinguish neuromas from peripheral nerve sheath tumours. The clinical history of trauma with the lack of a target sign are likely the most useful clues. (orig.)

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

Science.gov (United States)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

Assessment of significance of features acquired from thyroid ultrasonograms in Hashimoto's disease

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Koprowski Robert

2012-08-01

Full Text Available Abstract Introduction This paper concerns the analysis of the features obtained from thyroid ultrasound images in left and right transverse and longitudinal sections. In the image analysis, the thyroid lobe is treated as a texture for healthy subjects and patients with Hashimoto’s disease. The applied methods of analysis and image processing were profiled to obtain 10 features of the image. Then, their significance in the classification was shown. Material In this study, the examined group consisted of 29 healthy subjects aged 18 to 60 and 65 patients with Hashimoto's disease. For each subject, four ultrasound images were taken. They were all in transverse and longitudinal sections of the right and left lobe of the thyroid, which gave 376 images in total. Method 10 different features obtained from each ultrasound image were suggested. The analyzed thyroid lobe was marked automatically or manually with a rectangular element. Results The analysis of 10 features and the creation for each one of them their own decision tree configuration resulted in distinguishing 3 most significant features. The results of the quality of classification show accuracy above 94% for a non-trimmed decision tree.

ACER Mathematics Profile Series: Number Test. (Test Booklet, Answer and Record Sheet, Score Key, and Teachers Handbook).

Science.gov (United States)

Cornish, Greg; Wines, Robin

The Number Test of the ACER Mathematics Profile Series, contains 30 items, for each of three suggested grade levels: 7-8, 8-9, and 9-10. Raw scores on all tests in the ACER Mathematics Profile Series (Number, Operations, Space and Measurement) are converted to a common scale called MAPS, a major feature of the Series. Based on the Rasch Model,…

Joint Markov Blankets in Feature Sets Extracted from Wavelet Packet Decompositions

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Gert Van Dijck

2011-07-01

Full Text Available Since two decades, wavelet packet decompositions have been shown effective as a generic approach to feature extraction from time series and images for the prediction of a target variable. Redundancies exist between the wavelet coefficients and between the energy features that are derived from the wavelet coefficients. We assess these redundancies in wavelet packet decompositions by means of the Markov blanket filtering theory. We introduce the concept of joint Markov blankets. It is shown that joint Markov blankets are a natural extension of Markov blankets, which are defined for single features, to a set of features. We show that these joint Markov blankets exist in feature sets consisting of the wavelet coefficients. Furthermore, we prove that wavelet energy features from the highest frequency resolution level form a joint Markov blanket for all other wavelet energy features. The joint Markov blanket theory indicates that one can expect an increase of classification accuracy with the increase of the frequency resolution level of the energy features.

Mapping Cropland and Crop-type Distribution Using Time Series MODIS Data

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Lu, D.; Chen, Y.; Moran, E. F.; Batistella, M.; Luo, L.; Pokhrel, Y.; Deb, K.

2016-12-01

Mapping regional and global cropland distribution has attracted great attention in the past decade, but the separation of crop types is challenging due to the spectral confusion and cloud cover problems during the growing season in Brazil. The objective of this study is to develop a new approach to identify crop types (including soybean, cotton, maize) and planting patterns (soybean-maize, soybean-cotton, and single crop) in Mato Grosso, Goias and Tocantins States, Brazil. The time series moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) (MOD13Q1) in 2015/2016 were used in this research and field survey data were collected in May 2016. The major steps include: (1) reconstruct time series NDVI data contaminated by noise and clouds using the temporal interpolation algorithm; (2) identify the best periods and develop temporal indices and phenology parameters to distinguish cropland from other land cover types based on time series NDVI data; (3) develop a crop temporal difference index (CTDI) to extract crop types and patterns using time series NDVI data. This research shows that (1) the cropland occupied approximately 16.85% of total land in these three states; (2) soybean-maize and soybean-cotton were two major crop patterns which occupied 54.80% and 19.30% of total cropland area. This research indicates that the proposed approach is promising for accurately and rapidly mapping cropland and crop-type distribution in these three states of Brazil.

Optical computing: introduction by the feature editors.

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Li, Y; Tanida, J; Tooley, F; Wagner, K

1996-03-10

This feature issue of Applied Optics: Information Processing contains 19 papers on Optical Computing. Many of these papers are expanded versions of presentations given at the Optical Society of America's Sixth Topical Meeting on Optical Computing held in Salt Lake City, Utah, in March 1995. This introduction provides a brief historical account of the series of optical computing meetings and a brief review of the papers contained in this special issue.

Integral fast reactor safety features

International Nuclear Information System (INIS)

Cahalan, J.E.; Kramer, J.M.; Marchaterre, J.F.; Mueller, C.J.; Pedersen, D.R.; Sevy, R.H.; Wade, D.C.; Wei, T.Y.C.

1988-01-01

The Integral Fast Reactor (IFR) is an advanced liquid-metal-cooled reactor concept being developed at Argonne National Laboratory. The two major goals of the IFR development effort are improved economics and enhanced safety. In addition to liquid metal cooling, the principal design features that distinguish the IFR are: (1) a pool-type primary system, (2) an advanced ternary alloy metallic fuel, and (3) an integral fuel cycle with on-site fuel reprocessing and fabrication. This paper focuses on the technical aspects of the improved safety margins available in the IFR concept. This increased level of safety is made possible by (1) the liquid metal (sodium) coolant and pool-type primary system layout, which together facilitate passive decay heat removal, and (2) a sodium-bonded metallic fuel pin design with thermal and neutronic properties that provide passive core responses which control and mitigate the consequences of reactor accidents

Distinguishing the communicative functions of gestures

DEFF Research Database (Denmark)

Jokinen, Kristiina; Navarretta, Costanza; Paggio, Patrizia

2008-01-01

This paper deals with the results of a machine learning experiment conducted on annotated gesture data from two case studies (Danish and Estonian). The data concern mainly facial displays, that are annotated with attributes relating to shape and dynamics, as well as communicative function....... The results of the experiments show that the granularity of the attributes used seems appropriate for the task of distinguishing the desired communicative functions. This is a promising result in view of a future automation of the annotation task....

What distinguishes the small fraction of tropical ocean storms with lightning? An examination of the environment, organization, and evolution of radar features over Kwajalein

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Bang, S. D.; Zipser, E. J.

2017-12-01

Lightning over the tropical ocean, though much rarer than over land, is predominantly observed in large, mostly mature convective systems. The implication is that these may require external forcing or organization in order to develop updrafts sufficiently strong to loft and sustain graupel and supercooled water above the freezing level and thereby produce lightning. We examine three years of radar data from the Kwajalein Atoll in the Marshall Islands in the tropical Pacific Ocean, which we subject to the Warning Decisions Support System - Integrated Information (WDSS-II) tracking algorithm in order to create an evolutionary radar feature dataset. In conjunction with ERA-interim reanalysis environmental data and World Wide Lightning Location Network (WWLLN) lightning data, we are able to observe the lifecycles of electrified convection over Kwajalein and examine the characteristics leading up to a lightning flash for radar features throughout the intensity spectrum. We find that lightning over Kwajalein exhibits the same tendency to occur in large, mature radar features, and the probability of lightning increases with increasing size and, to a certain extent, age. However, there is little evidence to support the role of singular environmental parameters in the development into large features. We continue to struggle to find the reasons that may influence or control the evolution of small features into large, organized convective systems, a major issue that has importance well beyond whether the feature is electrified.

Daniel L. Schacter: Award for Distinguished Scientific Contributions

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American Psychologist, 2012

2012-01-01

Presents Daniel L. Schacter as one of the winners of the American Psychological Association's Award for Distinguished Scientific Contributions (2012). Daniel L. Schacter's major theoretical and empirical contributions include groundbreaking research on the psychological and neural foundations of implicit and explicit memory, memory distortions and…

Outlier Detection in Structural Time Series Models

DEFF Research Database (Denmark)

Marczak, Martyna; Proietti, Tommaso

investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality......Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general......–to–specific approach to the detection of structural change, currently implemented in Autometrics via indicator saturation, has proven to be both practical and effective in the context of stationary dynamic regression models and unit–root autoregressions. By focusing on impulse– and step–indicator saturation, we...

Distinguishing Failure to Cure From Complication After Penile Prosthesis Implantation.

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Pineda, Miguel; Burnett, Arthur L

2017-05-01

A successful penile prosthesis implantation (PPI) surgery can be defined by outcomes beyond the absence of complications. To introduce the concept of failure to cure (FTC) in the context of PPI to more accurately gauge postoperative outcomes after PPI. Consecutive patients from our sexual function registry who underwent PPI from January 2011 to December 2013 were analyzed. Demographics, previous treatment of erectile dysfunction, comorbidities, social history, postoperative problems (POPs), and surgical outcomes were tabulated. Patients completed the International Index of Erection Function (IIEF) and the Erectile Dysfunction Inventory of Treatment Satisfaction questionnaires. We defined a complication, according to the Clavien-Dindo classification, as any deviation from the ideal postoperative course that is not inherent in the procedure and does not constitute an FTC. FTC was defined as a POP that was not a complication. The χ 2 tests, t-tests, or Wilcoxon rank-sum tests were used. Patient-reported and objective outcomes after PPI. Our enrollment consisted of 185 patients, and we contacted 124 (67%). Of these, 16 (12.9%) had a POP requiring reoperation. Eight patients developed surgical complications (three infections, four erosions, and one chronic pain). Eight patients had FTC (four malpositions and four malfunctions). Factors that correlated with POPs were previous PPI, body mass index higher than 30 kg/m 2 , and previous treatment with intracorporal injections (P .05 for all comparisons). POPs after PPI surgery can be more accurately categorized using the Clavien-Dindo classification of surgical complications to more clearly distinguish surgical complications from FTC. Limitations of our study include its retrospective approach. Our series included a large proportion of patients treated for prostate cancer, which limits the generalizability of our findings. We also had a relatively short median follow-up time of 27 months. Patient-reported outcome

A Collection of Brain Sections of "Euthanasia" Victims: The Series H of Julius Hallervorden.

Science.gov (United States)

Wässle, Heinz

2017-12-01

Julius Hallervorden, a distinguished German neuropathologist, admitted on several occasions that he had received some five hundred brains of "euthanasia" victims from the Nazi killing centres for the insane. He investigated the brains in the summer of 1942; however, their traces were subsequently lost. The present study shows, that the Series H, which was part of the Hallervorden collection of brain sections in the Max Planck Institute for Brain Research, comprises the brain sections of the above mentioned five hundred euthanasia victims. The provenance of 105 patients could be reconstructed and 84 are for sure euthanasia victims. Most of them were killed in Bernburg or in Sonnenstein-Pirna. Hallervorden used the brain sections of Series H until 1956 for his studies and never publicly regretted this abuse of the brains of euthanasia victims. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distinction of neurons, glia and endothelial cells in the cerebral cortex: an algorithm based on cytological features

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Miguel Ángel García-Cabezas

2016-11-01

Full Text Available The estimation of the number or density of neurons and types of glial cells and their relative proportions in different brain areas are at the core of rigorous quantitative neuroanatomical studies. Unfortunately, the lack of detailed, updated, systematic, and well-illustrated descriptions of the cytology of neurons and glial cell types, especially in the primate brain, makes such studies especially demanding, often limiting their scope and broad use. Here, following extensive analysis of histological materials and the review of current and classical literature, we compile a list of precise morphological criteria that can facilitate and standardize identification of cells in stained sections examined under the microscope. We describe systematically and in detail the cytological features of neurons and glial cell types in the cerebral cortex of the macaque monkey and the human using semithin and thick sections stained for Nissl. We used this classical staining technique because it labels all cells in the brain in distinct ways. In addition, we corroborate key distinguishing characteristics of different cell types in sections immunolabeled for specific markers counterstained for Nissl and in ultrathin sections processed for electron microscopy. Finally, we summarize the core features that distinguish each cell type in easy-to-use tables and sketches, and structure these key features in an algorithm that can be used to systematically distinguish cellular types in the cerebral cortex. Moreover, we report high inter-observer algorithm reliability, which is a crucial test for obtaining consistent and reproducible cell counts in unbiased stereological studies. This protocol establishes a consistent framework that can be used to reliably identify and quantify cells in the cerebral cortex of primates as well as other mammalian species in health and disease.

Distinction of Neurons, Glia and Endothelial Cells in the Cerebral Cortex: An Algorithm Based on Cytological Features

Science.gov (United States)

García-Cabezas, Miguel Á.; John, Yohan J.; Barbas, Helen; Zikopoulos, Basilis

2016-01-01

The estimation of the number or density of neurons and types of glial cells and their relative proportions in different brain areas are at the core of rigorous quantitative neuroanatomical studies. Unfortunately, the lack of detailed, updated, systematic and well-illustrated descriptions of the cytology of neurons and glial cell types, especially in the primate brain, makes such studies especially demanding, often limiting their scope and broad use. Here, following an extensive analysis of histological materials and the review of current and classical literature, we compile a list of precise morphological criteria that can facilitate and standardize identification of cells in stained sections examined under the microscope. We describe systematically and in detail the cytological features of neurons and glial cell types in the cerebral cortex of the macaque monkey and the human using semithin and thick sections stained for Nissl. We used this classical staining technique because it labels all cells in the brain in distinct ways. In addition, we corroborate key distinguishing characteristics of different cell types in sections immunolabeled for specific markers counterstained for Nissl and in ultrathin sections processed for electron microscopy. Finally, we summarize the core features that distinguish each cell type in easy-to-use tables and sketches, and structure these key features in an algorithm that can be used to systematically distinguish cellular types in the cerebral cortex. Moreover, we report high inter-observer algorithm reliability, which is a crucial test for obtaining consistent and reproducible cell counts in unbiased stereological studies. This protocol establishes a consistent framework that can be used to reliably identify and quantify cells in the cerebral cortex of primates as well as other mammalian species in health and disease. PMID:27847469

Method of identifying features in indexed data

Science.gov (United States)

Jarman, Kristin H [Richland, WA; Daly, Don Simone [Richland, WA; Anderson, Kevin K [Richland, WA; Wahl, Karen L [Richland, WA

2001-06-26

The present invention is a method of identifying features in indexed data, especially useful for distinguishing signal from noise in data provided as a plurality of ordered pairs. Each of the plurality of ordered pairs has an index and a response. The method has the steps of: (a) providing an index window having a first window end located on a first index and extending across a plurality of indices to a second window end; (b) selecting responses corresponding to the plurality of indices within the index window and computing a measure of dispersion of the responses; and (c) comparing the measure of dispersion to a dispersion critical value. Advantages of the present invention include minimizing signal to noise ratio, signal drift, varying baseline signal and combinations thereof.

Nonlinear time series analysis with R

CERN Document Server

Huffaker, Ray; Rosa, Rodolfo

2017-01-01

In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjec...

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

Science.gov (United States)

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

Breast cancer molecular subtype classification using deep features: preliminary results

Science.gov (United States)

Zhu, Zhe; Albadawy, Ehab; Saha, Ashirbani; Zhang, Jun; Harowicz, Michael R.; Mazurowski, Maciej A.

2018-02-01

Radiogenomics is a field of investigation that attempts to examine the relationship between imaging characteris- tics of cancerous lesions and their genomic composition. This could offer a noninvasive alternative to establishing genomic characteristics of tumors and aid cancer treatment planning. While deep learning has shown its supe- riority in many detection and classification tasks, breast cancer radiogenomic data suffers from a very limited number of training examples, which renders the training of the neural network for this problem directly and with no pretraining a very difficult task. In this study, we investigated an alternative deep learning approach referred to as deep features or off-the-shelf network approach to classify breast cancer molecular subtypes using breast dynamic contrast enhanced MRIs. We used the feature maps of different convolution layers and fully connected layers as features and trained support vector machines using these features for prediction. For the feature maps that have multiple layers, max-pooling was performed along each channel. We focused on distinguishing the Luminal A subtype from other subtypes. To evaluate the models, 10 fold cross-validation was performed and the final AUC was obtained by averaging the performance of all the folds. The highest average AUC obtained was 0.64 (0.95 CI: 0.57-0.71), using the feature maps of the last fully connected layer. This indicates the promise of using this approach to predict the breast cancer molecular subtypes. Since the best performance appears in the last fully connected layer, it also implies that breast cancer molecular subtypes may relate to high level image features

PyEEG: an open source Python module for EEG/MEG feature extraction.

Science.gov (United States)

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

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Zhijie eBian

2014-02-01

Full Text Available Objective: Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI from normal cognitive function in type 2 diabetes. Materials and Methods: In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well. Results: The main findings of this study were that: 1 compared with the control group, the ratios of power in theta band (P(theta versus power in alpha band (P(alpha (P(theta/P(alpha in the frontal region and left temporal region were significantly higher for aMCI, and 2 for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC and left posterior-right posterior (LP-RP regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT region were increased. Conclusion: The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

32 CFR 22.205 - Distinguishing assistance from procurement.

Science.gov (United States)

2010-07-01

... procurement contract, is the appropriate instrument, based on the following: (a) Purpose. (1) The grants... purpose is acquisition, then the grants officer shall judge that a procurement contract is the appropriate... 32 National Defense 1 2010-07-01 2010-07-01 false Distinguishing assistance from procurement. 22...

Supporting the material control and accountancy system with physical protection system features

International Nuclear Information System (INIS)

Miyoshi, D.S.; Olson, C.E.; Caskey, D.L.

1984-01-01

Most physical security functions can be accomplished by a range of alternative features. Careful design can provide comparable levels of security regardless of which option is chosen, albeit with possible differences in cost and efficiency. However, the effectiveness and especially the cost and efficiency of the material control and accounting system may be strongly influenced by the selection of a particular design approach to physical security. In this paper, a series of examples are cited to illustrate the effects that particular physical protection design choices may have. The examples have been chosen from several systems engineering projects at facilities within the DOE nuclear community. These examples are generalized, and a series of design principles are proposed for integrating physical security with material control and accounting by appropriate selection of alternative features. 2 references, 6 figures

Supporting the material control and accountancy system with physical protection system features

International Nuclear Information System (INIS)

Miyoshi, D.S.; Caskey, D.L.; Olson, C.E.

1984-01-01

Most physical security functions can be accomplished by a range of alternative features. Careful design can provide comparable levels of security regardless of which option is chosen, albeit with possible differences in cost and efficiency. However, the effectiveness and especially the cost and efficiency of the material control and accounting system may be strongly influenced by the selection of a particular design approach to physical security. In this paper, a series of examples are cited to illustrate the effects that particular physical protection design choices may have. The examples have been chosen from several systems engineering projects at facilities within the DOE nuclear community. These examples are generalized, and a series of design principles are proposed for integrating physical security with MC and A by appropriate selection of alternative features

Edge enhancement and noise suppression for infrared image based on feature analysis

Science.gov (United States)

Jiang, Meng

2018-06-01

Infrared images are often suffering from background noise, blurred edges, few details and low signal-to-noise ratios. To improve infrared image quality, it is essential to suppress noise and enhance edges simultaneously. To realize it in this paper, we propose a novel algorithm based on feature analysis in shearlet domain. Firstly, as one of multi-scale geometric analysis (MGA), we introduce the theory and superiority of shearlet transform. Secondly, after analyzing the defects of traditional thresholding technique to suppress noise, we propose a novel feature extraction distinguishing image structures from noise well and use it to improve the traditional thresholding technique. Thirdly, with computing the correlations between neighboring shearlet coefficients, the feature attribute maps identifying the weak detail and strong edges are completed to improve the generalized unsharped masking (GUM). At last, experiment results with infrared images captured in different scenes demonstrate that the proposed algorithm suppresses noise efficiently and enhances image edges adaptively.

Non-linear time series extreme events and integer value problems

CERN Document Server

Turkman, Kamil Feridun; Zea Bermudez, Patrícia

2014-01-01

This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time ...

Forged Signature Distinction Using Convolutional Neural Network for Feature Extraction

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Seungsoo Nam

2018-01-01

Full Text Available This paper proposes a dynamic verification scheme for finger-drawn signatures in smartphones. As a dynamic feature, the movement of a smartphone is recorded with accelerometer sensors in the smartphone, in addition to the moving coordinates of the signature. To extract high-level longitudinal and topological features, the proposed scheme uses a convolution neural network (CNN for feature extraction, and not as a conventional classifier. We assume that a CNN trained with forged signatures can extract effective features (called S-vector, which are common in forging activities such as hesitation and delay before drawing the complicated part. The proposed scheme also exploits an autoencoder (AE as a classifier, and the S-vector is used as the input vector to the AE. An AE has high accuracy for the one-class distinction problem such as signature verification, and is also greatly dependent on the accuracy of input data. S-vector is valuable as the input of AE, and, consequently, could lead to improved verification accuracy especially for distinguishing forged signatures. Compared to the previous work, i.e., the MLP-based finger-drawn signature verification scheme, the proposed scheme decreases the equal error rate by 13.7%, specifically, from 18.1% to 4.4%, for discriminating forged signatures.

Optimizing the coefficients of the leading terms of the Born Series: FWI+MVA+more

KAUST Repository

Alkhalifah, Tariq Ali

2017-05-26

The scattering series theoretically utilizes a model perturbation framework to explain the difference between the seismic modeled data corresponding to a background model and those measured in the field corresponding to the real Earth. These perturbations include short wavelength features like those predicted by full waveform inversion (FWI) gradients, and long wavelength features often constrained by migration velocity analysis (MVA) objectives. The Born series, however, is not a convergent series. If the perturbations are large, we probably will not be able to explain the data difference. Thus, using the leading terms of the Born in an iterative process, in which they are scaled properly, allows us to avoid such limitations and update the short and long wavelength components of the velocity model. In fact, the FWI update is manifested in the first term of the Born series, and the MVA update is represented by the transmission (first Fresnel zone) part of the second term. In this case, FWI and MVA are code names for dividing the optimized update to reflectivity based portions and those adequate for the background, respectively. Examples on synthetic and real data demonstrate this logic.

Biological time series analysis using a context free language: applicability to pulsatile hormone data.

Directory of Open Access Journals (Sweden)

Dennis A Dean

Full Text Available We present a novel approach for analyzing biological time-series data using a context-free language (CFL representation that allows the extraction and quantification of important features from the time-series. This representation results in Hierarchically AdaPtive (HAP analysis, a suite of multiple complementary techniques that enable rapid analysis of data and does not require the user to set parameters. HAP analysis generates hierarchically organized parameter distributions that allow multi-scale components of the time-series to be quantified and includes a data analysis pipeline that applies recursive analyses to generate hierarchically organized results that extend traditional outcome measures such as pharmacokinetics and inter-pulse interval. Pulsicons, a novel text-based time-series representation also derived from the CFL approach, are introduced as an objective qualitative comparison nomenclature. We apply HAP to the analysis of 24 hours of frequently sampled pulsatile cortisol hormone data, which has known analysis challenges, from 14 healthy women. HAP analysis generated results in seconds and produced dozens of figures for each participant. The results quantify the observed qualitative features of cortisol data as a series of pulse clusters, each consisting of one or more embedded pulses, and identify two ultradian phenotypes in this dataset. HAP analysis is designed to be robust to individual differences and to missing data and may be applied to other pulsatile hormones. Future work can extend HAP analysis to other time-series data types, including oscillatory and other periodic physiological signals.

Kearns–Sayre syndrome: a case series of 35 adults and children

Directory of Open Access Journals (Sweden)

Khambatta S

2014-07-01

Full Text Available Sherezade Khambatta, Douglas L Nguyen, Thomas J Beckman, Christopher M Wittich Division of General Internal Medicine, Mayo Clinic, Rochester, MN, USA Background: Kearns–Sayre syndrome (KSS is a rare mitochondrial cytopathy, first described at Mayo Clinic in 1958. Aims: We aimed to define patient and disease characteristics in a large group of adult and pediatric patients with KSS. Methods: We retrospectively searched the Mayo Clinic medical index patient database for the records of patients with KSS between 1976 and 2009. The 35 patients identified with KSS were analyzed in terms of demographic characteristics, presenting signs and symptoms, diagnostic features, clinical evolution, and associations between disease features and the development of disability. Results: The mean (standard [SD] age at KSS presentation was 17 (10 years, but the mean age at diagnosis was 26 (15 years. Ophthalmologic symptoms developed in all patients, and neurologic and cardiac involvement was common. Only four patients (11% in the series died, but all deaths were from sudden cardiac events. The development of physical disability was significantly associated with cognitive decline (P=0.004 but not with other clinical features, such as sex or sudden cardiac death. Conclusion: We report the largest case series to date of patients with KSS from a single institution. In addition to the conduction system abnormalities identified in previous series, our cohort included patients with syncope and sudden cardiac death. This underscores the need to consider formal electrophysiologic studies and prophylactic defibrillators in patients with KSS. Keywords: heart block, mitochondrial diseases, ophthalmoplegia, retinitis pigmentosa

Fourier series

CERN Document Server

Tolstov, Georgi P

1962-01-01

Richard A. Silverman's series of translations of outstanding Russian textbooks and monographs is well-known to people in the fields of mathematics, physics, and engineering. The present book is another excellent text from this series, a valuable addition to the English-language literature on Fourier series.This edition is organized into nine well-defined chapters: Trigonometric Fourier Series, Orthogonal Systems, Convergence of Trigonometric Fourier Series, Trigonometric Series with Decreasing Coefficients, Operations on Fourier Series, Summation of Trigonometric Fourier Series, Double Fourie

Realistic Free-Spins Features Increase Preference for Slot Machines.

Science.gov (United States)

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

2017-06-01

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

Problems of Software Detection of Periodic Features in a Time ...

African Journals Online (AJOL)

Problems arise when attempts are made to extract automatically, visually obvious periodic features indicative of defects in a vibration time series for diagnosis using computers. Such problems may be interpretational in nature arising either from insufficient knowledge of the mechanism, or the convolution of the source signal ...

Distinguishing infected from noninfected abdominal fluid collections after surgery: an imaging, clinical, and laboratory-based scoring system.

Science.gov (United States)

Gnannt, Ralph; Fischer, Michael A; Baechler, Thomas; Clavien, Pierre-Alain; Karlo, Christoph; Seifert, Burkhardt; Lesurtel, Mickael; Alkadhi, Hatem

2015-01-01

Mortality from abdominal abscesses ranges from 30% in treated cases up to 80% to 100% in patients with undrained or nonoperated abscesses. Various computed tomographic (CT) imaging features have been suggested to indicate infection of postoperative abdominal fluid collections; however, features are nonspecific and substantial overlap between infected and noninfected collections exists. The purpose of this study was to develop and validate a scoring system on the basis of CT imaging findings as well as laboratory and clinical parameters for distinguishing infected from noninfected abdominal fluid collections after surgery. The score developmental cohort included 100 consecutive patients (69 men, 31 women; mean age, 58 ± 17 years) who underwent portal-venous phase CT within 24 hours before CT-guided intervention of postoperative abdominal fluid collections. Imaging features included attenuation (Hounsfield unit [HU]), volume, wall enhancement and thickness, fat stranding, as well as entrapped gas of fluid collections. Laboratory and clinical parameters included diabetes, intake of immunosuppressive drugs, body temperature, C-reactive protein, and leukocyte blood cell count. The score was validated in a separate cohort of 30 consecutive patients (17 men, 13 women; mean age, 51 ± 15 years) with postoperative abdominal fluid collections. Microbiologic analysis from fluid samples served as the standard of reference. Diabetes, body temperature, C-reactive protein, attenuation of the fluid collection (in HUs), wall enhancement and thickness of the wall, adjacent fat stranding, as well as entrapped gas within the fluid collection were significantly different between infected and noninfected collections (P collection (in HUs), as well as entrapped gas as significant independent predictors of infection (P collection, ≥ 20 HU: 4 points; entrapped gas: 3 points). The model was well calibrated (Hosmer-Lemeshow test, P = 0.36). In the validation cohort, scores of 2 or lower

A comparative analysis of image features between weave embroidered Thangka and piles embroidered Thangka

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Li, Zhenjiang; Wang, Weilan

2018-04-01

Thangka is a treasure of Tibetan culture. In its digital protection, most of the current research focuses on the content of Thangka images, not the fabrication process. For silk embroidered Thangka of "Guo Tang", there are two craft methods, namely, weave embroidered and piles embroidered. The local texture of weave embroidered Thangka is rough, and that of piles embroidered Thangka is more smooth. In order to distinguish these two kinds of fabrication processes from images, a effectively segmentation algorithm of color blocks is designed firstly, and the obtained color blocks contain the local texture patterns of Thangka image; Secondly, the local texture features of the color block are extracted and screened; Finally, the selected features are analyzed experimentally. The experimental analysis shows that the proposed features can well reflect the difference between methods of weave embroidered and piles embroidered.

Imaging features of rosette-forming glioneuronal tumours (RGNTs): A series of seven cases

Energy Technology Data Exchange (ETDEWEB)

Medhi, Gorky; Prasad, Chandrajit; Saini, Jitender; Pendharkar, Hima; Bhat, Maya Dattatraya [National Institute of Mental Health and Neurosciences, Department of Neuroimaging and Interventional Radiology, Bangalore (India); Pandey, Paritosh [National Institute of Mental Health and Neurosciences, Department of Neurosurgery, Bangalore (India); Muthane, Yasha [National Institute of Mental Health and Neurosciences, Department of Neuropathology, Bangalore (India)

2016-01-15

Rosette-forming glioneuronal tumours (RGNTs) are a recently described, rare, distinct nosological entity of the glioneuronal family. We describe imaging findings (CT and MRI) in seven patients with RGNTs. This retrospective study includes seven RGNT patients (4 male, 3 female; age range: 7-42 years; mean age: 25 years) diagnosed and treated at our institute. MR studies were performed on 3 T and 1.5-T clinical MR systems. All patients were reviewed by two experienced neuroradiologists and imaging findings were tabulated. Five tumours were located in the posterior fossa, and two were in the pineal region. One of the tumours demonstrated multiple satellite lesions, which involved the midbrain, pons, medulla as well as the cervical cord. Tumours located in the pineal region compressed the 3rd ventricle/aqueduct and extended below the tentorium cerebelli. All the tumours demonstrated enhancement, and susceptibility was evident in six of the seven patients. CSF dissemination was present in two patients. RGNTs are usually solid-cystic tumours and frequently demonstrate peripheral/heterogeneous enhancement upon post-contrast study. Haemorrhage is a common feature which may not be evident on CT. Cerebrospinal fluid (CSF) dissemination is a feature and appropriate imaging should be performed whenever an RGNT is suspected. (orig.)

Imaging features of rosette-forming glioneuronal tumours (RGNTs): A series of seven cases

International Nuclear Information System (INIS)

Medhi, Gorky; Prasad, Chandrajit; Saini, Jitender; Pendharkar, Hima; Bhat, Maya Dattatraya; Pandey, Paritosh; Muthane, Yasha

2016-01-01

Rosette-forming glioneuronal tumours (RGNTs) are a recently described, rare, distinct nosological entity of the glioneuronal family. We describe imaging findings (CT and MRI) in seven patients with RGNTs. This retrospective study includes seven RGNT patients (4 male, 3 female; age range: 7-42 years; mean age: 25 years) diagnosed and treated at our institute. MR studies were performed on 3 T and 1.5-T clinical MR systems. All patients were reviewed by two experienced neuroradiologists and imaging findings were tabulated. Five tumours were located in the posterior fossa, and two were in the pineal region. One of the tumours demonstrated multiple satellite lesions, which involved the midbrain, pons, medulla as well as the cervical cord. Tumours located in the pineal region compressed the 3rd ventricle/aqueduct and extended below the tentorium cerebelli. All the tumours demonstrated enhancement, and susceptibility was evident in six of the seven patients. CSF dissemination was present in two patients. RGNTs are usually solid-cystic tumours and frequently demonstrate peripheral/heterogeneous enhancement upon post-contrast study. Haemorrhage is a common feature which may not be evident on CT. Cerebrospinal fluid (CSF) dissemination is a feature and appropriate imaging should be performed whenever an RGNT is suspected. (orig.)

Fingerprints of primordial universe paradigms as features in density perturbations

International Nuclear Information System (INIS)

Chen Xingang

2011-01-01

Experimentally distinguishing different primordial universe paradigms that lead to the Big Bang model is an outstanding challenge in modern cosmology and astrophysics. We show that a generic type of signals that exist in primordial universe models can be used for such purpose. These signals are induced by tiny oscillations of massive fields and manifest as features in primordial density perturbations. They are capable of recording the time-dependence of the scale factor of the primordial universe, and therefore provide direct evidence for specific paradigm. These signals present special opportunities and challenges for experiments and data analyses.

MgH Rydberg series: Transition energies from electron propagator theory and oscillator strengths from the molecular quantum defect orbital method

Science.gov (United States)

Corzo, H. H.; Velasco, A. M.; Lavín, C.; Ortiz, J. V.

2018-02-01

Vertical excitation energies belonging to several Rydberg series of MgH have been inferred from 3+ electron-propagator calculations of the electron affinities of MgH+ and are in close agreement with experiment. Many electronically excited states with n > 3 are reported for the first time and new insight is given on the assignment of several Rydberg series. Valence and Rydberg excited states of MgH are distinguished respectively by high and low pole strengths corresponding to Dyson orbitals of electron attachment to the cation. By applying the Molecular Quantum Defect Orbital method, oscillator strengths for electronic transitions involving Rydberg states also have been determined.

Award for Distinguished Scientific Contributions: Steven F. Maier

Science.gov (United States)

American Psychologist, 2009

2009-01-01

Steven F. Maier, winner of the Award for Distinguished Scientific Contributions, is cited for his work in the fields of learned helplessness; cytokines, depressed mood, and cognitive interference; and the brain structures that produce and counteract learned helplessness. In addition to the citation, a biography and selected bibliography of Maier's…

Observation of higher-order diffraction features in self-assembled photonic crystals

International Nuclear Information System (INIS)

Nair, Rajesh V.; Vijaya, R.

2007-01-01

The optical response of high quality three dimensionally (3D) ordered photonic crystals is analyzed in the high energy region. By tuning the reflectance with the angle of incidence of light, the peaks in the reflection spectrum that correspond to the first, second, and third order photonic stop bands and the van Hove singular point in the photon density of states are clearly distinguished. The high energy features have been observed for photonic crystals made from colloids of different diameters, having different index contrast and fabricated by two different self-assembly routes. The observation of van Hove singularity at near-normal incidence of light and its presence even in low index-contrast photonic crystals provide conclusive evidence that these high energy features are due to the perfect periodic ordering present in the photonic crystals with less defects and disorder

Brief Report: Major Depressive Disorder with Psychotic Features in Williams Syndrome--A Case Series

Science.gov (United States)

Valdes, Francisca; Keary, Christopher J.; Mullett, Jennifer E.; Palumbo, Michelle L.; Waxler, Jessica L.; Pober, Barbara R.; McDougle, Christopher J.

2018-01-01

Descriptions of individuals with Williams syndrome (WS) and co-morbid major depressive disorder (MDD) with psychotic features have not appeared in the literature. In addition to reviewing previous reports of psychotic symptoms in persons with WS, this paper introduces clinical histories and therapeutic management strategies for three previously…

Perception Of "Features" And "Objects": Applications To The Design Of Instrument Panel Displays

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Poynter, Douglas; Czarnomski, Alan J.

1988-10-01

An experiment was conducted to determine whether socalled feature displays allow for faster and more accurate processing compared to object displays. Previous psychological studies indicate that features can be processed in parallel across the visual field, whereas objects must be processed one at a time with the aid of attentional focus. Numbers and letters are examples of objects; line orientation and color are examples of features. In this experiment, subjects were asked to search displays composed of up to 16 elements for the presence of specific elements. The ability to detect, localize, and identify targets was influenced by display format. Digital errors increased with the number of elements, the number of targets, and the distance of the target from the fixation point. Line orientation errors increased only with the number of targets. Several other display types were evaluated, and each produced a pattern of errors similar to either digital or line orientation format. Results of the study were discussed in terms of Feature Integration Theory, which distinguishes between elements that are processed with parallel versus serial mechanisms.

New significance test methods for Fourier analysis of geophysical time series

Directory of Open Access Journals (Sweden)

Z. Zhang

2011-09-01

Full Text Available When one applies the discrete Fourier transform to analyze finite-length time series, discontinuities at the data boundaries will distort its Fourier power spectrum. In this paper, based on a rigid statistics framework, we present a new significance test method which can extract the intrinsic feature of a geophysical time series very well. We show the difference in significance level compared with traditional Fourier tests by analyzing the Arctic Oscillation (AO and the Nino3.4 time series. In the AO, we find significant peaks at about 2.8, 4.3, and 5.7 yr periods and in Nino3.4 at about 12 yr period in tests against red noise. These peaks are not significant in traditional tests.

Production design and location in the Danish television drama series Arvingerne

DEFF Research Database (Denmark)

Ion Wille, Jakob; Waade, Anne Marit

2016-01-01

Television fiction is most often referred to as the writer’s medium, whereas feature film is generally perceived as the vision and work of the director. In this article we turn our focus to the role and function of the production design and locations in developing and conceptualising a television...... drama series. We use the drama series Arvingerne (The Legacy, DR, 2014-2015) to illustrate how design ideas can be developed at an early stage, in pre-pre-production, as part of a collective, creative process that includes the scriptwriter, the production designer and the producer. Our empirical study...... of the series draws on an analysis of in-house design/concept documents [1], interviews with the production designer Mia Stensgaard [2], and promotional material made for the series [3]. The paper also draws on visual analysis of the finished production. Our overall argument is that the importance of location...

What does the structure of its visibility graph tell us about the nature of the time series?

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Franke, Jasper G.; Donner, Reik V.

2017-04-01

Visibility graphs are a recently introduced method to construct complex network representations based upon univariate time series in order to study their dynamical characteristics [1]. In the last years, this approach has been successfully applied to studying a considerable variety of geoscientific research questions and data sets, including non-trivial temporal patterns in complex earthquake catalogs [2] or time-reversibility in climate time series [3]. It has been shown that several characteristic features of the thus constructed networks differ between stochastic and deterministic (possibly chaotic) processes, which is, however, relatively hard to exploit in the case of real-world applications. In this study, we propose studying two new measures related with the network complexity of visibility graphs constructed from time series, one being a special type of network entropy [4] and the other a recently introduced measure of the heterogeneity of the network's degree distribution [5]. For paradigmatic model systems exhibiting bifurcation sequences between regular and chaotic dynamics, both properties clearly trace the transitions between both types of regimes and exhibit marked quantitative differences for regular and chaotic dynamics. Moreover, for dynamical systems with a small amount of additive noise, the considered properties demonstrate gradual changes prior to the bifurcation point. This finding appears closely related to the subsequent loss of stability of the current state known to lead to a critical slowing down as the transition point is approaches. In this spirit, both considered visibility graph characteristics provide alternative tracers of dynamical early warning signals consistent with classical indicators. Our results demonstrate that measures of visibility graph complexity (i) provide a potentially useful means to tracing changes in the dynamical patterns encoded in a univariate time series that originate from increasing autocorrelation and (ii

Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

Science.gov (United States)

Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

2018-01-01

Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM

Distinguishing between Realistic and Fantastical Figures in Iran

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Davoodi, Telli; Corriveau, Kathleen H.; Harris, Paul L.

2016-01-01

Children in the United States come to distinguish historical from fictional story figures between the ages of 3 and 5 years, guided by the plausibility of the story events surrounding the figure (Corriveau, Kim, Schwalen, & Harris, 2009; Woolley & Cox, 2007). However, U.S. children vary in their reactions to stories that include…

Transcranial magnetic stimulation distinguishes Alzheimer disease from frontotemporal dementia.

Science.gov (United States)

Benussi, Alberto; Di Lorenzo, Francesco; Dell'Era, Valentina; Cosseddu, Maura; Alberici, Antonella; Caratozzolo, Salvatore; Cotelli, Maria Sofia; Micheli, Anna; Rozzini, Luca; Depari, Alessandro; Flammini, Alessandra; Ponzo, Viviana; Martorana, Alessandro; Caltagirone, Carlo; Padovani, Alessandro; Koch, Giacomo; Borroni, Barbara

2017-08-15

To determine whether a transcranial magnetic stimulation (TMS) multiparadigm approach can be used to distinguish Alzheimer disease (AD) from frontotemporal dementia (FTD). Paired-pulse TMS was used to investigate short-interval intracortical inhibition (SICI) and facilitation (ICF), long-interval intracortical inhibition, and short-latency afferent inhibition (SAI) to measure the activity of different intracortical circuits in patients with AD, patients with FTD, and healthy controls (HC). The primary outcome measures were sensitivity and specificity of TMS measures, derived from receiver operating curve analysis. A total of 175 participants met the inclusion criteria. We diagnosed 79 patients with AD, 64 patients with FTD, and 32 HC. We found that while patients with AD are characterized by a specific impairment of SAI, FTD shows a remarkable dysfunction of SICI-ICF intracortical circuits. With the use of the best indexes, TMS differentiated FTD from AD with a sensitivity of 91.8% and specificity of 88.6%, AD from HC with a sensitivity of 84.8% and specificity of 90.6%, and FTD from HC with a sensitivity of 90.2% and specificity of 78.1%. These results were confirmed in patients with mild disease. TMS is a noninvasive procedure that reliably distinguishes AD from FTD and HC and, if these findings are replicated in larger studies, could represent a useful additional diagnostic tool for clinical practice. This study provides Class III evidence that TMS measures can distinguish patients with AD from those with FTD. © 2017 American Academy of Neurology.

Time domain series system definition and gear set reliability modeling

International Nuclear Information System (INIS)

Xie, Liyang; Wu, Ningxiang; Qian, Wenxue

2016-01-01

Time-dependent multi-configuration is a typical feature for mechanical systems such as gear trains and chain drives. As a series system, a gear train is distinct from a traditional series system, such as a chain, in load transmission path, system-component relationship, system functioning manner, as well as time-dependent system configuration. Firstly, the present paper defines time-domain series system to which the traditional series system reliability model is not adequate. Then, system specific reliability modeling technique is proposed for gear sets, including component (tooth) and subsystem (tooth-pair) load history description, material priori/posterior strength expression, time-dependent and system specific load-strength interference analysis, as well as statistically dependent failure events treatment. Consequently, several system reliability models are developed for gear sets with different tooth numbers in the scenario of tooth root material ultimate tensile strength failure. The application of the models is discussed in the last part, and the differences between the system specific reliability model and the traditional series system reliability model are illustrated by virtue of several numerical examples. - Highlights: • A new type of series system, i.e. time-domain multi-configuration series system is defined, that is of great significance to reliability modeling. • Multi-level statistical analysis based reliability modeling method is presented for gear transmission system. • Several system specific reliability models are established for gear set reliability estimation. • The differences between the traditional series system reliability model and the new model are illustrated.

`Indoor` series vending machines; `Indoor` series jido hanbaiki

Energy Technology Data Exchange (ETDEWEB)

Gensui, T.; Kida, A. [Fuji Electric Co. Ltd., Tokyo (Japan); Okumura, H. [Fuji Denki Reiki Co. Ltd., Tokyo (Japan)

1996-07-10

This paper introduces three series of vending machines that were designed to match the interior of an office building. The three series are vending machines for cups, paper packs, cans, and tobacco. Among the three series, `Interior` series has a symmetric design that was coated in a grain pattern. The inside of the `Interior` series is coated by laser satin to ensure a sense of superior quality and a refined style. The push-button used for product selection is hot-stamped on the plastic surface to ensure the hair-line luster. `Interior Phase II` series has a bay window design with a sense of superior quality and lightness. The inside of the `Interior Phase II` series is coated by laser satin. `Interior 21` series is integrated with the wall except the sales operation panel. The upper and lower dress panels can be detached and attached. The door lock is a wire-type structure with high operativity. The operation block is coated by titanium color. The dimensions of three series are standardized. 6 figs., 1 tab.

A Reception Analysis on the Youth Audiences of TV Series in Marivan

Directory of Open Access Journals (Sweden)

Omid Karimi

2014-03-01

Full Text Available The aim of this article is to describe the role of foreign media as the agitators of popular culture. For that with reception analysis it’s pay to describe decoding of youth audiences about this series. Globalization theory and Reception in Communication theory are formed the theoretical system of current article. The methodology in this research is qualitative one, and two techniques as in-depth interview and observation are used for data collection. The results show different people based on individual features, social and cultural backgrounds have inclination toward special characters and identify with them. This inclination so far the audience fallow the series because of his/her favorite character. Also there is a great compatibility between audience backgrounds and their receptions. A number of audience have criticized the series and point out the negative consequences on its society. However, seeing the series continue; really they prefer watching series enjoying to risks of it.

Time series analysis methods and applications for flight data

CERN Document Server

Zhang, Jianye

2017-01-01

This book focuses on different facets of flight data analysis, including the basic goals, methods, and implementation techniques. As mass flight data possesses the typical characteristics of time series, the time series analysis methods and their application for flight data have been illustrated from several aspects, such as data filtering, data extension, feature optimization, similarity search, trend monitoring, fault diagnosis, and parameter prediction, etc. An intelligent information-processing platform for flight data has been established to assist in aircraft condition monitoring, training evaluation and scientific maintenance. The book will serve as a reference resource for people working in aviation management and maintenance, as well as researchers and engineers in the fields of data analysis and data mining.

Investigation of Soil Salinity to Distinguish Boundary Line between ...

African Journals Online (AJOL)

ADOWIE PERE

Investigation of Soil Salinity to Distinguish Boundary Line between Saline and ... Setting 4 dSm-1 as the limit between saline and non-saline soils in kriging algorithms resulted in a .... number of sample points within the search window,.

Award for Distinguished Scientific Contributions: Alice H. Eagly

Science.gov (United States)

American Psychologist, 2009

2009-01-01

Alice H. Eagly, winner of the Award for Distinguished Scientific Contributions, is cited for her work in the field of social psychology, the psychology of gender, and the use of meta-analytic techniques. She envisions a psychology that extends from individual cognitions to societal structures. In addition to the citation, a biography and selected…

Knuckle-walking anteater: a convergence test of adaptation for purported knuckle-walking features of African Hominidae.

Science.gov (United States)

Orr, Caley M

2005-11-01

Appeals to synapomorphic features of the wrist and hand in African apes, early hominins, and modern humans as evidence of knuckle-walking ancestry for the hominin lineage rely on accurate interpretations of those features as adaptations to knuckle-walking locomotion. Because Gorilla, Pan, and Homo share a relatively close common ancestor, the interpretation of such features is confounded somewhat by phylogeny. The study presented here examines the evolution of a similar locomotor regime in New World anteaters (order Xenarthra, family Myrmecophagidae) and uses the terrestrial giant anteater (Myrmecophaga tridactyla) as a convergence test of adaptation for purported knuckle-walking features of the Hominidae. During the stance phase of locomotion, Myrmecophaga transmits loads through flexed digits and a vertical manus, with hyperextension occurring at the metacarpophalangeal joints of the weight-bearing rays. This differs from the locomotion of smaller, arboreal anteaters of outgroup genera Tamandua and Cyclopes that employ extended wrist postures during above-branch quadrupedality. A number of features shared by Myrmecophaga and Pan and Gorilla facilitate load transmission or limit extension, thereby stabilizing the wrist and hand during knuckle-walking, and distinguish these taxa from their respective outgroups. These traits are a distally extended dorsal ridge of the distal radius, proximal expansion of the nonarticular surface of the dorsal capitate, a pronounced articular ridge on the dorsal aspects of the load-bearing metacarpal heads, and metacarpal heads that are wider dorsally than volarly. Only the proximal expansion of the nonarticular area of the dorsal capitate distinguishes knuckle-walkers from digitigrade cercopithecids, but features shared with digitigrade primates might be adaptive to the use of a vertical manus of some sort in the stance phase of terrestrial locomotion. The appearance of capitate nonarticular expansion and the dorsal ridge of the

Diagnostic value of chemical shift artifact in distinguishing benign lymphadenopathy

Energy Technology Data Exchange (ETDEWEB)

Farshchian, Nazanin, E-mail: farshchian.n@gmail.com [Department of Radiology, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Tamari, Saghar; Farshchian, Negin [Department of Radiology, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Madani, Hamid [Department of Pathology, Imam-Reza Hospital, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Rezaie, Mansour [Department of Biostatistics, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of); Mohammadi-Motlagh, Hamid-Reza, E-mail: mohammadimotlagh@gmail.com [Medical Biology Research Center, Kermanshah University of Medical Sciences, Kermanshah (Iran, Islamic Republic of)

2011-11-15

Purpose: Today, distinguishing metastatic lymph nodes from secondary benign inflammatory ones via using non-invasive methods is increasingly favorable. In this study, the diagnostic value of chemical shift artifact (CSA) in magnetic resonance imaging (MRI) was evaluated to distinguish benign lymphadenopathy. Subjects and methods: A prospective intraindividual internal review board-approved study was carried out on 15 men and 15 women having lymphadenopathic lesions in different locations of the body who underwent contrast-enhanced dynamic MR imaging at 1.5 T. Then, the imaging findings were compared with pathology reports, using the statistics analyses. Results: Due to the findings of the CSA existence in MRI, a total of 56.7% of the studied lesions (17 of 30) were identified as benign lesions and the rest were malignant, whereas the pathology reports distinguished twelve malignant and eighteen benign cases. Furthermore, the CSA findings comparing the pathology reports indicated that CSA, with confidence of 79.5%, has a significant diagnostic value to differentiate benign lesions from malignant ones. Conclusion: Our study demonstrated that CSA in MR imaging has a suitable diagnostic potential nearing readiness for clinical trials. Furthermore, CSA seems to be a feasible tool to differentiate benign lymph nodes from malignant ones; however, further studies including larger numbers of patients are required to confirm our results.

Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.

Science.gov (United States)

Shan, Juan; Alam, S Kaisar; Garra, Brian; Zhang, Yingtao; Ahmed, Tahira

2016-04-01

This work identifies effective computable features from the Breast Imaging Reporting and Data System (BI-RADS), to develop a computer-aided diagnosis (CAD) system for breast ultrasound. Computerized features corresponding to ultrasound BI-RADs categories were designed and tested using a database of 283 pathology-proven benign and malignant lesions. Features were selected based on classification performance using a "bottom-up" approach for different machine learning methods, including decision tree, artificial neural network, random forest and support vector machine. Using 10-fold cross-validation on the database of 283 cases, the highest area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 from a support vector machine with 77.7% overall accuracy; the highest overall accuracy, 78.5%, was from a random forest with the AUC 0.83. Lesion margin and orientation were optimum features common to all of the different machine learning methods. These features can be used in CAD systems to help distinguish benign from worrisome lesions. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. All rights reserved.

Complexation of amidocarbamoyl phosphine oxides with Ln+3 (Ln = La, Nd, Pm, Sm and Eu) cation series: structural and thermodynamical features

International Nuclear Information System (INIS)

Hosseinnejad, Tayebeh; Kazemi, Tayebeh

2016-01-01

In the present study, we have mainly investigated the nature of interactions in Ln 3+ (Ln = La, Nd, Pm, Sm, Eu) complexes with amidocarbamoyl methyl phosphine oxide (CMPO) and amidocarbamoyl propyl phosphine oxide (CPPO) ligands based on density functional theory (DFT) approaches. In the first step, thermodynamical properties for complexation of CMPO and CPPO ligands with Ln 3+ cation series have been determined in the gas phase and with the presence of three solvents: n-hexane, chloroform and toluene, via polarized continuum model (PCM) computations. The trend of metal-ligand interaction strength has been analyzed and compared with the trend of ionic hardness within the series of lanthanide cations and different size of alkyl chain of amidocarbamoyl phosphine oxide ligand. The calculated thermochemical results in the gas and solution phases reveals that there is a consistency between increasing trend in the hardness of Ln 3+ cation series and also electron-donating property of alkyl chain with increasing in thermodynamical stability of [Ln-CMPO] 3+ and [Ln-CPPO] 3+ complex series. We have also demonstrated that in the complexation reaction of all complex series, using n-hexane as solvent is more favorable thermodynamically than chloroform and toluene. It should be stated that this issue has been observed in many experiments. Finally, analysis of calculated deformation energies and also the variation in bond order of some selected key bonds in CMPO and CPPO ligands and their corresponded Ln 3+ complexes series show a similar trend with increasing in the hardness of Ln 3+ cation series and electron-donating of alkyl chain of amidocarbamoyl phosphine oxide ligand.

Hydralazine-induced pauci-immune glomerulonephritis: intriguing case series with misleading diagnoses

Directory of Open Access Journals (Sweden)

Faizan Babar

2016-04-01

Full Text Available Hydralazine has been used since the 1950s for the management of hypertension. Evidence for hydralazine-associated vasculitis dates to pre-ANCA (antineutrophil cytoplasmic antibodies era. This abstract describes two cases of ANCA-positive pauci-immune glomerulonephritis (GN in challenging scenarios where diagnosis was misconstrued. A comprehensive literature review was done to understand the pathogenesis of drug-induced pauci-immune GN. We have described key diagnostic features that are helpful in distinguishing idiopathic ANCA vasculitis from drug-induced vasculitis. Additionally, we have also described different treatments meant to provide therapy options with the least side effects.

Imaging features of intracerebral hemorrhage with cerebral amyloid angiopathy: Systematic review and meta-analysis.

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Neshika Samarasekera

Full Text Available We sought to summarize Computed Tomography (CT/Magnetic Resonance Imaging (MRI features of intracerebral hemorrhage (ICH associated with cerebral amyloid angiopathy (CAA in published observational radio-pathological studies.In November 2016, two authors searched OVID Medline (1946-, Embase (1974- and relevant bibliographies for studies of imaging features of lobar or cerebellar ICH with pathologically proven CAA ("CAA-associated ICH". Two authors assessed studies' diagnostic test accuracy methodology and independently extracted data.We identified 22 studies (21 cases series and one cross-sectional study with controls of CT features in 297 adults, two cross-sectional studies of MRI features in 81 adults and one study which reported both CT and MRI features in 22 adults. Methods of CAA assessment varied, and rating of imaging features was not masked to pathology. The most frequently reported CT features of CAA-associated ICH in 21 case series were: subarachnoid extension (pooled proportion 82%, 95% CI 69-93%, I2 = 51%, 12 studies and an irregular ICH border (64%, 95% CI 32-91%, I2 = 85%, five studies. CAA-associated ICH was more likely to be multiple on CT than non-CAA ICH in one cross-sectional study (CAA-associated ICH 7/41 vs. non-CAA ICH 0/42; χ2 = 7.8, p = 0.005. Superficial siderosis on MRI was present in 52% of CAA-associated ICH (95% CI 39-65%, I2 = 35%, 3 studies.Subarachnoid extension and an irregular ICH border are common imaging features of CAA-associated ICH, but methodologically rigorous diagnostic test accuracy studies are required to determine the sensitivity and specificity of these features.

Sensorineural Deafness, Distinctive Facial Features and Abnormal Cranial Bones

Science.gov (United States)

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

2008-01-01

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

Use of liquefaction-induced features for paleoseismic analysis - An overview of how seismic liquefaction features can be distinguished from other features and how their regional distribution and properties of source sediment can be used to infer the location and strength of Holocene paleo-earthquakes

Science.gov (United States)

Obermeier, S.F.

1996-01-01

Liquefaction features can be used in many field settings to estimate the recurrence interval and magnitude of strong earthquakes through much of the Holocene. These features include dikes, craters, vented sand, sills, and laterally spreading landslides. The relatively high seismic shaking level required for their formation makes them particularly valuable as records of strong paleo-earthquakes. This state-of-the-art summary for using liquefaction-induced features for paleoseismic interpretation and analysis takes into account both geological and geotechnical engineering perspectives. The driving mechanism for formation of the features is primarily the increased pore-water pressure associated with liquefaction of sand-rich sediment. The role of this mechanism is often supplemented greatly by the direct action of seismic shaking at the ground surface, which strains and breaks the clay-rich cap that lies immediately above the sediment that liquefied. Discussed in the text are the processes involved in formation of the features, as well as their morphology and characteristics in field settings. Whether liquefaction occurs is controlled mainly by sediment grain size, sediment packing, depth to the water table, and strength and duration of seismic shaking. Formation of recognizable features in the field generally requires a low-permeability cap above the sediment that liquefied. Field manifestations are controlled largely by the severity of liquefaction and the thickness and properties of the low-permeability cap. Criteria are presented for determining whether observed sediment deformation in the field originated by seismically induced liquefaction. These criteria have been developed mainly by observing historic effects of liquefaction in varied field settings. The most important criterion is that a seismic liquefaction origin requires widespread, regional development of features around a core area where the effects are most severe. In addition, the features must have a

Tribal Science 2017 Webinar Series: Harmful Algal Blooms (HABs): Research, Collaborations, and Other Activities

Science.gov (United States)

The Tribal Science Webinar Series provides a forum for discussion of the complex environmental issues facing many tribal and indigenous communities, and features a wide variety of expert guest speakers from government,.....

Fast region-based object detection and tracking using correlation of features

CSIR Research Space (South Africa)

Senekal, F

2010-11-01

Full Text Available and track a target object (or objects) over a series of digital images. Visual target tracking can be accomplished by feature-based or region-based approaches. In feature-based approaches, interest points are calculated in a digital image, and a local...-time performance based on the computational power that is available on a specific platform. To further reduce the computational requirements, process- ing is restricted to the region of interest (ROI). The region of interest is provided as an input parameter...

Dynamical analysis and visualization of tornadoes time series.

Directory of Open Access Journals (Sweden)

António M Lopes

Full Text Available In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Dynamical analysis and visualization of tornadoes time series.

Science.gov (United States)

Lopes, António M; Tenreiro Machado, J A

2015-01-01

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

"Observation Obscurer" - Time Series Viewer, Editor and Processor

Science.gov (United States)

Andronov, I. L.

The program is described, which contains a set of subroutines suitable for East viewing and interactive filtering and processing of regularly and irregularly spaced time series. Being a 32-bit DOS application, it may be used as a default fast viewer/editor of time series in any compute shell ("commander") or in Windows. It allows to view the data in the "time" or "phase" mode, to remove ("obscure") or filter outstanding bad points; to make scale transformations and smoothing using few methods (e.g. mean with phase binning, determination of the statistically opti- mal number of phase bins; "running parabola" (Andronov, 1997, As. Ap. Suppl, 125, 207) fit and to make time series analysis using some methods, e.g. correlation, autocorrelation and histogram analysis: determination of extrema etc. Some features have been developed specially for variable star observers, e.g. the barycentric correction, the creation and fast analysis of "OC" diagrams etc. The manual for "hot keys" is presented. The computer code was compiled with a 32-bit Free Pascal (www.freepascal.org).

A Data-Driven Modeling Strategy for Smart Grid Power Quality Coupling Assessment Based on Time Series Pattern Matching

Directory of Open Access Journals (Sweden)

Hao Yu

2018-01-01

Full Text Available This study introduces a data-driven modeling strategy for smart grid power quality (PQ coupling assessment based on time series pattern matching to quantify the influence of single and integrated disturbance among nodes in different pollution patterns. Periodic and random PQ patterns are constructed by using multidimensional frequency-domain decomposition for all disturbances. A multidimensional piecewise linear representation based on local extreme points is proposed to extract the patterns features of single and integrated disturbance in consideration of disturbance variation trend and severity. A feature distance of pattern (FDP is developed to implement pattern matching on univariate PQ time series (UPQTS and multivariate PQ time series (MPQTS to quantify the influence of single and integrated disturbance among nodes in the pollution patterns. Case studies on a 14-bus distribution system are performed and analyzed; the accuracy and applicability of the FDP in the smart grid PQ coupling assessment are verified by comparing with other time series pattern matching methods.

Development and application of a modified dynamic time warping algorithm (DTW-S to analyses of primate brain expression time series

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Vingron Martin

2011-08-01

Full Text Available Abstract Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

The Identification of Conductor-Distinguished Functions of Conducting

Science.gov (United States)

Gumm, Alan J.; Battersby, Sharyn L.; Simon, Kathryn L.; Shankles, Andrew E.

2011-01-01

The purpose of the present study was to identify whether conductors distinguish functions of conducting similarly to functions implied in previous research. A sample of 84 conductors with a full range of experience levels (M = 9.8) and of a full range of large ensemble types and ensemble age levels rated how much they pay attention to 82…

Time irreversibility and intrinsics revealing of series with complex network approach

Science.gov (United States)

Xiong, Hui; Shang, Pengjian; Xia, Jianan; Wang, Jing

2018-06-01

In this work, we analyze time series on the basis of the visibility graph algorithm that maps the original series into a graph. By taking into account the all-round information carried by the signals, the time irreversibility and fractal behavior of series are evaluated from a complex network perspective, and considered signals are further classified from different aspects. The reliability of the proposed analysis is supported by numerical simulations on synthesized uncorrelated random noise, short-term correlated chaotic systems and long-term correlated fractal processes, and by the empirical analysis on daily closing prices of eleven worldwide stock indices. Obtained results suggest that finite size has a significant effect on the evaluation, and that there might be no direct relation between the time irreversibility and long-range correlation of series. Similarity and dissimilarity between stock indices are also indicated from respective regional and global perspectives, showing the existence of multiple features of underlying systems.

Extending GIS Technology to Study Karst Features of Southeastern Minnesota

Science.gov (United States)

Gao, Y.; Tipping, R. G.; Alexander, E. C.; Alexander, S. C.

2001-12-01

This paper summarizes ongoing research on karst feature distribution of southeastern Minnesota. The main goals of this interdisciplinary research are: 1) to look for large-scale patterns in the rate and distribution of sinkhole development; 2) to conduct statistical tests of hypotheses about the formation of sinkholes; 3) to create management tools for land-use managers and planners; and 4) to deliver geomorphic and hydrogeologic criteria for making scientifically valid land-use policies and ethical decisions in karst areas of southeastern Minnesota. Existing county and sub-county karst feature datasets of southeastern Minnesota have been assembled into a large GIS-based database capable of analyzing the entire data set. The central database management system (DBMS) is a relational GIS-based system interacting with three modules: GIS, statistical and hydrogeologic modules. ArcInfo and ArcView were used to generate a series of 2D and 3D maps depicting karst feature distributions in southeastern Minnesota. IRIS ExplorerTM was used to produce satisfying 3D maps and animations using data exported from GIS-based database. Nearest-neighbor analysis has been used to test sinkhole distributions in different topographic and geologic settings. All current nearest-neighbor analyses testify that sinkholes in southeastern Minnesota are not evenly distributed in this area (i.e., they tend to be clustered). More detailed statistical methods such as cluster analysis, histograms, probability estimation, correlation and regression have been used to study the spatial distributions of some mapped karst features of southeastern Minnesota. A sinkhole probability map for Goodhue County has been constructed based on sinkhole distribution, bedrock geology, depth to bedrock, GIS buffer analysis and nearest-neighbor analysis. A series of karst features for Winona County including sinkholes, springs, seeps, stream sinks and outcrop has been mapped and entered into the Karst Feature Database

An Incremental Classification Algorithm for Mining Data with Feature Space Heterogeneity

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Yu Wang

2014-01-01

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

Time Series Analysis Using Geometric Template Matching.

Science.gov (United States)

Frank, Jordan; Mannor, Shie; Pineau, Joelle; Precup, Doina

2013-03-01

We present a novel framework for analyzing univariate time series data. At the heart of the approach is a versatile algorithm for measuring the similarity of two segments of time series called geometric template matching (GeTeM). First, we use GeTeM to compute a similarity measure for clustering and nearest-neighbor classification. Next, we present a semi-supervised learning algorithm that uses the similarity measure with hierarchical clustering in order to improve classification performance when unlabeled training data are available. Finally, we present a boosting framework called TDEBOOST, which uses an ensemble of GeTeM classifiers. TDEBOOST augments the traditional boosting approach with an additional step in which the features used as inputs to the classifier are adapted at each step to improve the training error. We empirically evaluate the proposed approaches on several datasets, such as accelerometer data collected from wearable sensors and ECG data.

Distinguishing bias from sensitivity effects in multialternative detection tasks.

Science.gov (United States)

Sridharan, Devarajan; Steinmetz, Nicholas A; Moore, Tirin; Knudsen, Eric I

2014-08-21

Studies investigating the neural bases of cognitive phenomena increasingly employ multialternative detection tasks that seek to measure the ability to detect a target stimulus or changes in some target feature (e.g., orientation or direction of motion) that could occur at one of many locations. In such tasks, it is essential to distinguish the behavioral and neural correlates of enhanced perceptual sensitivity from those of increased bias for a particular location or choice (choice bias). However, making such a distinction is not possible with established approaches. We present a new signal detection model that decouples the behavioral effects of choice bias from those of perceptual sensitivity in multialternative (change) detection tasks. By formulating the perceptual decision in a multidimensional decision space, our model quantifies the respective contributions of bias and sensitivity to multialternative behavioral choices. With a combination of analytical and numerical approaches, we demonstrate an optimal, one-to-one mapping between model parameters and choice probabilities even for tasks involving arbitrarily large numbers of alternatives. We validated the model with published data from two ternary choice experiments: a target-detection experiment and a length-discrimination experiment. The results of this validation provided novel insights into perceptual processes (sensory noise and competitive interactions) that can accurately and parsimoniously account for observers' behavior in each task. The model will find important application in identifying and interpreting the effects of behavioral manipulations (e.g., cueing attention) or neural perturbations (e.g., stimulation or inactivation) in a variety of multialternative tasks of perception, attention, and decision-making. © 2014 ARVO.

General Vertex-Distinguishing Total Coloring of Graphs

Directory of Open Access Journals (Sweden)

Chanjuan Liu

2014-01-01

Full Text Available The general vertex-distinguishing total chromatic number of a graph G is the minimum integer k, for which the vertices and edges of G are colored using k colors such that any two vertices have distinct sets of colors of them and their incident edges. In this paper, we figure out the exact value of this chromatic number of some special graphs and propose a conjecture on the upper bound of this chromatic number.

Sparse Bayesian classification and feature selection for biological expression data with high correlations.

Directory of Open Access Journals (Sweden)

Xian Yang

Full Text Available Classification models built on biological expression data are increasingly used to predict distinct disease subtypes. Selected features that separate sample groups can be the candidates of biomarkers, helping us to discover biological functions/pathways. However, three challenges are associated with building a robust classification and feature selection model: 1 the number of significant biomarkers is much smaller than that of measured features for which the search will be exhaustive; 2 current biological expression data are big in both sample size and feature size which will worsen the scalability of any search algorithms; and 3 expression profiles of certain features are typically highly correlated which may prevent to distinguish the predominant features. Unfortunately, most of the existing algorithms are partially addressing part of these challenges but not as a whole. In this paper, we propose a unified framework to address the above challenges. The classification and feature selection problem is first formulated as a nonconvex optimisation problem. Then the problem is relaxed and solved iteratively by a sequence of convex optimisation procedures which can be distributed computed and therefore allows the efficient implementation on advanced infrastructures. To illustrate the competence of our method over others, we first analyse a randomly generated simulation dataset under various conditions. We then analyse a real gene expression dataset on embryonal tumour. Further downstream analysis, such as functional annotation and pathway analysis, are performed on the selected features which elucidate several biological findings.

Whole-genome phylogeny of Escherichia coli/Shigella group by feature frequency profiles (FFPs)

Science.gov (United States)

Sims, Gregory E.; Kim, Sung-Hou

2011-01-01

A whole-genome phylogeny of the Escherichia coli/Shigella group was constructed by using the feature frequency profile (FFP) method. This alignment-free approach uses the frequencies of l-mer features of whole genomes to infer phylogenic distances. We present two phylogenies that accentuate different aspects of E. coli/Shigella genomic evolution: (i) one based on the compositions of all possible features of length l = 24 (∼8.4 million features), which are likely to reveal the phenetic grouping and relationship among the organisms and (ii) the other based on the compositions of core features with low frequency and low variability (∼0.56 million features), which account for ∼69% of all commonly shared features among 38 taxa examined and are likely to have genome-wide lineal evolutionary signal. Shigella appears as a single clade when all possible features are used without filtering of noncore features. However, results using core features show that Shigella consists of at least two distantly related subclades, implying that the subclades evolved into a single clade because of a high degree of convergence influenced by mobile genetic elements and niche adaptation. In both FFP trees, the basal group of the E. coli/Shigella phylogeny is the B2 phylogroup, which contains primarily uropathogenic strains, suggesting that the E. coli/Shigella ancestor was likely a facultative or opportunistic pathogen. The extant commensal strains diverged relatively late and appear to be the result of reductive evolution of genomes. We also identify clade distinguishing features and their associated genomic regions within each phylogroup. Such features may provide useful information for understanding evolution of the groups and for quick diagnostic identification of each phylogroup. PMID:21536867

A composite method based on formal grammar and DNA structural features in detecting human polymerase II promoter region.

Directory of Open Access Journals (Sweden)

Sutapa Datta

Full Text Available An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques.

A Composite Method Based on Formal Grammar and DNA Structural Features in Detecting Human Polymerase II Promoter Region

Science.gov (United States)

Datta, Sutapa; Mukhopadhyay, Subhasis

2013-01-01

An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG) can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques. PMID:23437045

Distinguishing Biologically Relevant Hexoses by Water Adduction to the Lithium-Cationized Molecule.

Science.gov (United States)

Campbell, Matthew T; Chen, Dazhe; Wallbillich, Nicholas J; Glish, Gary L

2017-10-03

A method to distinguish the four most common biologically relevant underivatized hexoses, d-glucose, d-galactose, d-mannose, and d-fructose, using only mass spectrometry with no prior separation/derivatization step has been developed. Electrospray of a solution containing hexose and a lithium salt generates [Hexose+Li] + . The lithium-cationized hexoses adduct water in a quadrupole ion trap. The rate of this water adduction reaction can be used to distinguish the four hexoses. Additionally, for each hexose, multiple lithiation sites are possible, allowing for multiple structures of [Hexose+Li] + . Electrospray produces at least one structure that reacts with water and at least one that does not. The ratio of unreactive lithium-cationized hexose to total lithium-cationized hexose is unique for the four hexoses studied, providing a second method for distinguishing the isomers. Use of the water adduction reaction rate or the unreactive ratio provides two separate methods for confidently (p ≤ 0.02) distinguishing the most common biologically relevant hexoses using only femtomoles of hexose. Additionally, binary mixtures of glucose and fructose were studied. A calibration curve was created by measuring the reaction rate of various samples with different ratios of fructose and glucose. The calibration curve was used to accurately measure the percentage of fructose in three samples of high fructose corn syrup (<4% error).

Characteristics of the co-fluctuation matrix transmission network based on financial multi-time series

OpenAIRE

Huajiao Li; Haizhong An; Xiangyun Gao; Wei Fang

2015-01-01

The co-fluctuation of two time series has often been studied by analysing the correlation coefficient over a selected period. However, in both domestic and global financial markets, there are more than two active time series that fluctuate constantly as a result of various factors, including geographic locations, information communications and so on. In addition to correlation relationships over longer periods, daily co-fluctuation relationships and their transmission features are also import...

Radiological features of subependymoma with emphasis on computed tomography

International Nuclear Information System (INIS)

Stevens, J.M.; Kendall, B.E.; Love, S.

1984-01-01

The features of 17 symptomatic subependymomas on X-ray computed tomography are described. Thirteen were reviewed from isolated case reports and 4 were original material. Over half were entirely intraventricular, 6 extended into brain substance and 2 into subarachnoidal cisterns. Twelve were isodense, 15 showed diffuse but irregular enhancement, and 5 contained nodular calcification. Large low density cysts, intratumoural haemorrhage and brain oedema were found almost exclusively in lesions extending into brain substance. It is concluded that subependymomas resemble ependymomas too closely on CT to be distinguished radiographically from them as a separate group. However subependymomas contain calcification slightly less frequently, and usually appear as mainly intraventicular lesions even when they occur above the tentorium. (orig.)

Spatio-temporal features for tracking and quadruped/biped discrimination

Science.gov (United States)

Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

2012-05-01

Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Energy Technology Data Exchange (ETDEWEB)

Lutaif, N.A. [Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, SP (Brazil); Palazzo, R. Jr [Departamento de Telemática, Faculdade de Engenharia Elétrica e Computação, Universidade Estadual de Campinas, Campinas, SP (Brazil); Gontijo, J.A.R. [Departamento de Clínica Médica, Faculdade de Ciências Médicas, Universidade Estadual de Campinas, Campinas, SP (Brazil)

2014-01-17

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

International Nuclear Information System (INIS)

Lutaif, N.A.; Palazzo, R. Jr; Gontijo, J.A.R.

2014-01-01

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile

Cerebral oligodendroglioma: MR features indicating anaplastic changes

Energy Technology Data Exchange (ETDEWEB)

Choi, Choong Gon; Chang, Kee Hyun; Han, Moon Hee; Chi, Je Geun [Seoul National Univ., Seoul (Korea, Republic of); Yoon, Hyun Ki [Ulsan Univ., Seoul (Korea, Republic of)

1995-10-15

The purpose of this study is to find helpful MR findings for predicting anaplastic oligodendrogliomas. Retrospective analysis of 46 MR images and 37 CT scans was performed for 46 patients with pathologically-proven cerebral oligodendrogliomas. A neuropathologist graded the tumors as one of low-grade (n = 16), intermediate-grade (n = 12), or anaplastic oligodendroglioma (n 18). MR imaging features were retrospectively analysed with respect to histologic grading of the tumors. Contrast enhancement was observed always in anaplastic group (17/17), in a portion of intermediate-grade group (4/10) but not in low-grade group (0/4). Peritumoral edema was observed infrequently in anaplastic group (4/18) or intermediate-grade group (1/12). Cystic changes (25/46) or calcifications on CT Scans (14/37) were not related with histologic grading. Grossly identifiable hemorrhage was rare in this series (2/46). Among the various imaging features, only tumor enhancement and peritumoral edema were statistically significant for trend test ({rho} < 0.05). When considering the diagnosis of oligodendrogliomas, the presence of contrast enhancement or peritumoral edema is a helpful features suggesting anaplastic oligodendrogliomas.

Using Tractography to Distinguish SWEDD from Parkinson’s Disease Patients Based on Connectivity

Directory of Open Access Journals (Sweden)

Mansu Kim

2016-01-01

Full Text Available Background. It is critical to distinguish between Parkinson’s disease (PD and scans without evidence of dopaminergic deficit (SWEDD, because the two groups are different and require different therapeutic approaches. Objective. The aim of this study was to distinguish SWEDD patients from PD patients using connectivity information derived from diffusion tensor imaging tractography. Methods. Diffusion magnetic resonance images of SWEDD (n=37 and PD (n=40 were obtained from a research database. Tractography, the process of obtaining neural fiber information, was performed using custom software. Group-wise differences between PD and SWEDD patients were quantified using the number of connected fibers between two regions, and correlation analyses were performed based on clinical scores. A support vector machine classifier (SVM was applied to distinguish PD and SWEDD based on group-wise differences. Results. Four connections showed significant group-wise differences and correlated with the Unified Parkinson’s Disease Rating Scale sponsored by the Movement Disorder Society. The SVM classifier attained 77.92% accuracy in distinguishing between SWEDD and PD using these identified connections. Conclusions. The connections and regions identified represent candidates for future research investigations.

Voltage-Gated Sodium Channels: Evolutionary History and Distinctive Sequence Features.

Science.gov (United States)

Kasimova, M A; Granata, D; Carnevale, V

2016-01-01

Voltage-gated sodium channels (Nav) are responsible for the rising phase of the action potential. Their role in electrical signal transmission is so relevant that their emergence is believed to be one of the crucial factors enabling development of nervous system. The presence of voltage-gated sodium-selective channels in bacteria (BacNav) has raised questions concerning the evolutionary history of the ones in animals. Here we review some of the milestones in the field of Nav phylogenetic analysis and discuss some of the most important sequence features that distinguish these channels from voltage-gated potassium channels and transient receptor potential channels. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural Indices of Semantic Processing in Early Childhood Distinguish Eventual Stuttering Persistence and Recovery

Science.gov (United States)

Kreidler, Kathryn; Wray, Amanda Hampton; Usler, Evan; Weber, Christine

2017-01-01

Purpose: Maturation of neural processes for language may lag in some children who stutter (CWS), and event-related potentials (ERPs) distinguish CWS who have recovered from those who have persisted. The current study explores whether ERPs indexing semantic processing may distinguish children who will eventually persist in stuttering…

Distinguishing the elements of a full product basis set needs only projective measurements and classical communication

International Nuclear Information System (INIS)

Chen Pingxing; Li Chengzu

2004-01-01

Nonlocality without entanglement is an interesting field. A manifestation of quantum nonlocality without entanglement is the possible local indistinguishability of orthogonal product states. In this paper we analyze the character of operators to distinguish the elements of a full product basis set in a multipartite system, and show that distinguishing perfectly these product bases needs only local projective measurements and classical communication, and these measurements cannot damage each product basis. Employing these conclusions one can discuss local distinguishability of the elements of any full product basis set easily. Finally we discuss the generalization of these results to the locally distinguishability of the elements of incomplete product basis set

The Diagnostic Drawing Series and the Tree Rating Scale: An Isomorphic Representation of Multiple Personality Disorder, Major Depression, and Schizophrenic Populations.

Science.gov (United States)

Morris, Maureen Batza

1995-01-01

The tree drawings of 80 subjects, who were diagnosed with either multiple personality disorder, schizophrenia, or major depression, and a control group, were rated. Patterns were examined and graphs were used to depict results. Certain features were found to distinguish each category. The descriptive statistical findings were both consistent and…

Markerless client-server augmented reality system with natural features

Science.gov (United States)

Ning, Shuangning; Sang, Xinzhu; Chen, Duo

2017-10-01

A markerless client-server augmented reality system is presented. In this research, the more extensive and mature virtual reality head-mounted display is adopted to assist the implementation of augmented reality. The viewer is provided an image in front of their eyes with the head-mounted display. The front-facing camera is used to capture video signals into the workstation. The generated virtual scene is merged with the outside world information received from the camera. The integrated video is sent to the helmet display system. The distinguishing feature and novelty is to realize the augmented reality with natural features instead of marker, which address the limitations of the marker, such as only black and white, the inapplicability of different environment conditions, and particularly cannot work when the marker is partially blocked. Further, 3D stereoscopic perception of virtual animation model is achieved. The high-speed and stable socket native communication method is adopted for transmission of the key video stream data, which can reduce the calculation burden of the system.

Feature issue of digital holography and 3D imaging (DH) introduction.

Science.gov (United States)

Hayasaki, Yoshio; Zhou, Changhe; Popescu, Gabriel; Onural, Levent

2014-11-17

The OSA Topical Meeting "Digital Holography and 3D Imaging (DH)," was held in Seattle, Washington, July 13-17, 2014. Feature issues based on the DH meeting series have been released by Applied Optics (AO) since 2007. This year Optics Express (OE) and AO jointly decided to have one such feature issue in each journal. The DH meeting will continue in the future, as expected, and the next meeting is scheduled to be held on 24 - 28 May 2015, in Shanghai Institute of Optics and Fine Mechanics, Shanghai, China.

Depth-based human activity recognition: A comparative perspective study on feature extraction

Directory of Open Access Journals (Sweden)

Heba Hamdy Ali

2018-06-01

Full Text Available Depth Maps-based Human Activity Recognition is the process of categorizing depth sequences with a particular activity. In this problem, some applications represent robust solutions in domains such as surveillance system, computer vision applications, and video retrieval systems. The task is challenging due to variations inside one class and distinguishes between activities of various classes and video recording settings. In this study, we introduce a detailed study of current advances in the depth maps-based image representations and feature extraction process. Moreover, we discuss the state of art datasets and subsequent classification procedure. Also, a comparative study of some of the more popular depth-map approaches has provided in greater detail. The proposed methods are evaluated on three depth-based datasets “MSR Action 3D”, “MSR Hand Gesture”, and “MSR Daily Activity 3D”. Experimental results achieved 100%, 95.83%, and 96.55% respectively. While combining depth and color features on “RGBD-HuDaAct” Dataset, achieved 89.1%. Keywords: Activity recognition, Depth, Feature extraction, Video, Human body detection, Hand gesture

Extracting foreground ensemble features to detect abnormal crowd behavior in intelligent video-surveillance systems

Science.gov (United States)

Chan, Yi-Tung; Wang, Shuenn-Jyi; Tsai, Chung-Hsien

2017-09-01

Public safety is a matter of national security and people's livelihoods. In recent years, intelligent video-surveillance systems have become important active-protection systems. A surveillance system that provides early detection and threat assessment could protect people from crowd-related disasters and ensure public safety. Image processing is commonly used to extract features, e.g., people, from a surveillance video. However, little research has been conducted on the relationship between foreground detection and feature extraction. Most current video-surveillance research has been developed for restricted environments, in which the extracted features are limited by having information from a single foreground; they do not effectively represent the diversity of crowd behavior. This paper presents a general framework based on extracting ensemble features from the foreground of a surveillance video to analyze a crowd. The proposed method can flexibly integrate different foreground-detection technologies to adapt to various monitored environments. Furthermore, the extractable representative features depend on the heterogeneous foreground data. Finally, a classification algorithm is applied to these features to automatically model crowd behavior and distinguish an abnormal event from normal patterns. The experimental results demonstrate that the proposed method's performance is both comparable to that of state-of-the-art methods and satisfies the requirements of real-time applications.

Complete nucleotide sequence of the Oenothera elata plastid chromosome, representing plastome I of the five distinguishable euoenothera plastomes.

Science.gov (United States)

Hupfer, H; Swiatek, M; Hornung, S; Herrmann, R G; Maier, R M; Chiu, W L; Sears, B

2000-05-01

We describe the 159,443-bp [corrected] sequence of the plastid chromosome of Oenothera elata (evening primrose). The Oe. elata plastid chromosome represents type I of the five genetically distinguishable basic plastomes found in the subsection Euoenothera. The genus Oenothera provides an ideal system in which to address fundamental questions regarding the functional integration of the compartmentalised genetic system characteristic of the eukaryotic cell. Its highly developed taxonomy and genetics, together with a favourable combination of features in its genetic structure (interspecific fertility, stable heterozygous progeny, biparental transmission of organelles, and the phenomenon of complex heterozygosity), allow facile exchanges of nuclei, plastids and mitochondria, as well as individual chromosome pairs, between species. The resulting hybrids or cybrids are usually viable and fertile, but can display various forms of developmental disturbance.

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

OpenAIRE

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting ...

Quantum-Secret-Sharing Scheme Based on Local Distinguishability of Orthogonal Seven-Qudit Entangled States

Science.gov (United States)

Liu, Cheng-Ji; Li, Zhi-Hui; Bai, Chen-Ming; Si, Meng-Meng

2018-02-01

The concept of judgment space was proposed by Wang et al. (Phys. Rev. A 95, 022320, 2017), which was used to study some important properties of quantum entangled states based on local distinguishability. In this study, we construct 15 kinds of seven-qudit quantum entangled states in the sense of permutation, calculate their judgment space and propose a distinguishability rule to make the judgment space more clearly. Based on this rule, we study the local distinguishability of the 15 kinds of seven-qudit quantum entangled states and then propose a ( k, n) threshold quantum secret sharing scheme. Finally, we analyze the security of the scheme.

Distinguishing benign from malignant gallbladder wall thickening using FDG-PET

International Nuclear Information System (INIS)

Oe, Ai; Kawabe, Joji; Torii, Kenji

2006-01-01

Because thickening of the gallbladder wall is observed not only in patients with gallbladder cancer but also in those with benign diseases such as chronic cholecystitis and gallbladder adenomyosis, it is difficult to distinguish between benign and malignant gallbladder wall thickening by conventional techniques of diagnostic imaging such as computed tomography (CT), magnetic resonance imaging (MRI), and abdominal ultrasonography (US). In the present study, we attempted to distinguish between benign and malignant gallbladder wall thickening by means of fluorine-18-fluorodeoxyglucose (FDG)-Positron emission tomography (PET). FDG-PET was performed in 12 patients with gallbladder wall thickening detected by CT or US, to determine whether it was benign or malignant. Emission scans were taken, beginning 45 minutes after intravenous administration of FDG, and standardized uptake value (SUV) was calculated as an indicator of glucose metabolism. Of the 12 patients, 4 showed positive uptake of FDG in the gallbladder wall. Of these 4 patients, 3 had gallbladder cancer. The remaining one, who had chronic cholecystitis, had false-positive findings. The other 8 patients had negative uptake of FDG in the gallbladder wall. Two of these 8 underwent surgical resection, which yielded a diagnosis of chronic cholecystitis. The other 6 patients exhibited no sign of gallbladder malignancy and have been followed without active treatment. FDG-PET appears able to distinguish between benign and malignant gallbladder wall thickening. (author)

What goes through the gate? Exploring interference with visual feature binding.

Science.gov (United States)

Ueno, Taiji; Mate, Judit; Allen, Richard J; Hitch, Graham J; Baddeley, Alan D

2011-05-01

A series of experiments explored the mechanisms determining the encoding and storage of features and objects in visual working memory. We contrasted the effects of three types of visual suffix on cued recall of a display of colored shapes. The suffix was presented after the display and before the recall cue. The latter was either the color or shape of one of the objects and signaled recall of the object's other feature. In Experiments 1 and 2, we found a larger effect of 'plausible' suffixes comprising features (color and shape) drawn from the experimental set, relative to the effect of 'implausible' suffixes comprising features outside the experimental set. Experiment 3 extended this pattern by showing that 'semi-plausible' suffixes containing only one feature (either color or shape) from the experimental set had an equivalent effect to those with both features from the set. Reduction in accuracy was mainly due to an increase in recall of suffix features, rather than within-display confusions. The findings suggest a feature-based filtering process in visual working memory, with any stimuli that pass through this filter serving to directly overwrite existing object representations. Copyright © 2011 Elsevier Ltd. All rights reserved.

Chest x-ray in Q-fever pneumonia: a series of 71 cases; La radiografia de torax en la neumonia por fiebre-Q. Serie de 71 casos

Energy Technology Data Exchange (ETDEWEB)

Encinas, B; Cerezal, L F; Fidalgo, I; Bustamente, M; Lopez Calderon, M [Hospital Universitario Marques de valdecilla, Santander (Spain)

1995-11-01

Chest X ray features of 71 cases of Q-fever serologically confirmed and with clinical manifestations of acute respiratory disease were retrospectively assessed in order to evaluate the radiographic features. In 68 cases (96%) The X-ray films were abnormal. Segmental consolidation, sometimes multiple and bilateral were tue most usual findings. Nodular opacities were found in 6 cases (9%) and can mimic a tumor. Cavitacion , a very unusual findings, was found in two nodular consolidations(two patients). Laminar atelectasis was less common than proviously reported. As in other series, total resolution or with minimal scars occurs within 3 months 15 refs.

Distinguishing between Poor/Dysfunctional Parenting and Child Emotional Maltreatment

Science.gov (United States)

Wolfe, David A.; McIsaac, Caroline

2011-01-01

Objective: This paper was intended to distinguish between poor parenting and child emotional maltreatment (CEM), to inform child welfare and public health policymakers of the need for differentiated responses. Methods: Scientific literature was integrated with current practice and assumptions relating to poor/dysfunctional parenting and child…

Distinguishing hyperhidrosis and normal physiological sweat production

DEFF Research Database (Denmark)

Thorlacius, Linnea; Gyldenløve, Mette; Zachariae, Claus

2015-01-01

of this study was to establish reference intervals for normal physiological axillary and palmar sweat production. METHODS: Gravimetric testing was performed in 75 healthy control subjects. Subsequently, these results were compared with findings in a cohort of patients with hyperhidrosis and with the results...... 100 mg/5 min. CONCLUSIONS: A sweat production rate of 100 mg/5 min as measured by gravimetric testing may be a reasonable cut-off value for distinguishing axillary and palmar hyperhidrosis from normal physiological sweat production....

Laboratory test variables useful for distinguishing upper from lower gastrointestinal bleeding.

Science.gov (United States)

Tomizawa, Minoru; Shinozaki, Fuminobu; Hasegawa, Rumiko; Shirai, Yoshinori; Motoyoshi, Yasufumi; Sugiyama, Takao; Yamamoto, Shigenori; Ishige, Naoki

2015-05-28

To distinguish upper from lower gastrointestinal (GI) bleeding. Patient records between April 2011 and March 2014 were analyzed retrospectively (3296 upper endoscopy, and 1520 colonoscopy). Seventy-six patients had upper GI bleeding (Upper group) and 65 had lower GI bleeding (Lower group). Variables were compared between the groups using one-way analysis of variance. Logistic regression was performed to identify variables significantly associated with the diagnosis of upper vs lower GI bleeding. Receiver-operator characteristic (ROC) analysis was performed to determine the threshold value that could distinguish upper from lower GI bleeding. Hemoglobin (P = 0.023), total protein (P = 0.0002), and lactate dehydrogenase (P = 0.009) were significantly lower in the Upper group than in the Lower group. Blood urea nitrogen (BUN) was higher in the Upper group than in the Lower group (P = 0.0065). Logistic regression analysis revealed that BUN was most strongly associated with the diagnosis of upper vs lower GI bleeding. ROC analysis revealed a threshold BUN value of 21.0 mg/dL, with a specificity of 93.0%. The threshold BUN value for distinguishing upper from lower GI bleeding was 21.0 mg/dL.

A technique for filling gaps in time series with complicated power spectra

International Nuclear Information System (INIS)

Brown, T.M.

1984-01-01

Fahlman and Ulrych (1982) describe a method for estimating the power and phase spectra of gapped time series, using a maximum-entropy reconstruction of the data in the gaps. It has proved difficult to apply this technique to solar oscillations data, because of the great complexity of the solar oscillations spectrum. We describe a means for avoiding this difficulty, and report the results of a series of blind tests of the modified technique. The main results of these tests are: 1. Gap-filling gives good results, provided that the signal-to-noise ration in the original data is large enough, and provided the gaps are short enough. For low-noise data, the duty cycle of the observations should not be less than about 50%. 2. The frequencies and widths of narrow spectrum features are well reproduced by the technique. 3. The technique systematically reduces the apparent amplitudes of small features in the spectrum relative to large ones. (orig.)

Feature-Based Nonlocal Polarimetric SAR Filtering

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Xiaoli Xing

2017-10-01

Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

Forecasting air quality time series using deep learning.

Science.gov (United States)

Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

2018-04-13

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution

Viability in holder of irradiated cells: distinguish between repair and cell multiplication

International Nuclear Information System (INIS)

Araujo, A.C. de.

1980-01-01

In experiments in which liquid holding recovery (LHR) was measured, the majority of cellular population is formed by non-viable cells and cell multiplication may be important for LHR expression. In order to distinguish between recuperation of viability (true LHR) and cell multiplication, it was necessary to employ improved plating techniques and a fluctuation test based on Poisson distribution. Our results are an indication that this fluctuation test, used together with the traditional method, is a good tool to distinguish repair from cell multiplication. (author)

Entropy and Compression Capture Different Complexity Features: The Case of Fetal Heart Rate

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João Monteiro-Santos

2017-12-01

Full Text Available Entropy and compression have been used to distinguish fetuses at risk of hypoxia from their healthy counterparts through the analysis of Fetal Heart Rate (FHR. Low correlation that was observed between these two approaches suggests that they capture different complexity features. This study aims at characterizing the complexity of FHR features captured by entropy and compression, using as reference international guidelines. Single and multi-scale approaches were considered in the computation of entropy and compression. The following physiologic-based features were considered: FHR baseline; percentage of abnormal long (%abLTV and short (%abSTV term variability; average short term variability; and, number of acceleration and decelerations. All of the features were computed on a set of 68 intrapartum FHR tracings, divided as normal, mildly, and moderately-severely acidemic born fetuses. The correlation between entropy/compression features and the physiologic-based features was assessed. There were correlations between compressions and accelerations and decelerations, but neither accelerations nor decelerations were significantly correlated with entropies. The %abSTV was significantly correlated with entropies (ranging between −0.54 and −0.62, and to a higher extent with compression (ranging between −0.80 and −0.94. Distinction between groups was clearer in the lower scales using entropy and in the higher scales using compression. Entropy and compression are complementary complexity measures.

Significant Histological Features Differentiating Cellular Fibroadenoma from Phyllodes Tumor on Core Needle Biopsies

Science.gov (United States)

Yasir, Saba; Gamez, Roberto; Jenkins, Sarah; Visscher, Daniel W.; Nassar, Aziza

2015-01-01

Objectives Cellular fibroepithelial lesions (CFEL) are a heterogeneous group of tumors encompassing cellular fibroadenoma (CFA) and phyllodes tumor (PT). Distinction between the two is challenging on core needle biopsy (CNB). The objective of this study was to evaluate histological features that can help distinguish PT from CFA on CNB. Methods Records of all patients diagnosed with CFEL on CNB with follow-up excision between 2002 and 2012 were retrieved. Histopathological stromal features were evaluated on CNB including mitoses per 10 HPF, overgrowth, increased cellularity, fragmentation, adipose tissue infiltration, heterogeneity, subepithelial condensation, and nuclear pleomorphism. Results Twenty-seven of 64 (42.2%) were diagnosed as PT (24 BPT, 3 borderline PT) and 37 (57.8%) as CFA on excision. All features except for increased stromal cellularity were statistically significant. The average number of histologic features seen in PT and CFA was 3.9 and 1.4, respectively (OR 7.27; 95% CI: 2.44, 21.69; p= 0.0004). The average mitoses per 10 HPF was 3.0 for PT as compared to 0.8 for CFA (OR 2.14; 95% CI: 1.18, 3.86; p= 0.01). Conclusions The presence of mitosis (3 or more) and/or total histologic features of 3 or more on CNB were most helpful features in predicting PT on excision. PMID:25125627

Sonographic features of neonatal mastitis and breast abscess.

Science.gov (United States)

Borders, Heather; Mychaliska, George; Gebarski, K Stiennon

2009-09-01

Neonatal mastitis and neonatal breast abscess are uncommon. Although well described in the pediatric and surgical literature, there is a paucity of reports describing their sonographic features. To describe and illustrate the sonographic features of neonatal mastitis and neonatal breast abscess. We reviewed the medical database of a large children's health-care center from 2000 through 2008 for patients presenting in the first 8 weeks of life with mastitis. The findings were correlated with clinical presentation and course, laboratory findings and clinical outcome. Four neonates (three girls and one boy) presented with mastitis. They all had prominent breast buds on the affected side with poorly defined margins, slightly more echogenic focally or diffusely compared to normal with hyperemia on color flow Doppler US. The surrounding subcutaneous tissue was thick and echogenic. Two abscesses presented as avascular areas without color flow on Doppler US, subtly increased through-transmission and surrounding hyperemia. One abscess was of increased echogenicity while the other was anechoic. Neonatal mastitis and breast abscess are unusual diseases that should be appropriately treated with antibiotics and drainage to avoid generalized sepsis, breast hypoplasia, and scarring. US is useful in distinguishing mastitis from breast abscess and guiding treatment options.

Consistent two-dimensional visualization of protein-ligand complex series

Directory of Open Access Journals (Sweden)

Stierand Katrin

2011-06-01

Full Text Available Abstract Background The comparative two-dimensional graphical representation of protein-ligand complex series featuring different ligands bound to the same active site offers a quick insight in their binding mode differences. In comparison to arbitrary orientations of the residue molecules in the individual complex depictions a consistent placement improves the legibility and comparability within the series. The automatic generation of such consistent layouts offers the possibility to apply it to large data sets originating from computer-aided drug design methods. Results We developed a new approach, which automatically generates a consistent layout of interacting residues for a given series of complexes. Based on the structural three-dimensional input information, a global two-dimensional layout for all residues of the complex ensemble is computed. The algorithm incorporates the three-dimensional adjacencies of the active site residues in order to find an universally valid circular arrangement of the residues around the ligand. Subsequent to a two-dimensional ligand superimposition step, a global placement for each residue is derived from the set of already placed ligands. The method generates high-quality layouts, showing mostly overlap-free solutions with molecules which are displayed as structure diagrams providing interaction information in atomic detail. Application examples document an improved legibility compared to series of diagrams whose layouts are calculated independently from each other. Conclusions The presented method extends the field of complex series visualizations. A series of molecules binding to the same protein active site is drawn in a graphically consistent way. Compared to existing approaches these drawings substantially simplify the visual analysis of large compound series.

Repetitive nerve stimulation as a diagnostic aid for distinguishing cervical spondylotic amyotrophy from amyotrophic lateral sclerosis.

Science.gov (United States)

Zheng, Chaojun; Jin, Xiang; Zhu, Yu; Lu, Feizhou; Jiang, Jianyuan; Xia, Xinlei

2017-07-01

To identify and compare the features of compound muscle action potential (CMAP) decrements in repetitive nerve stimulation (RNS) in patients with cervical spondylotic amyotrophy (CSA) and in patients with amyotrophic lateral sclerosis (ALS). The cohort consisted of 43 CSA (distal-type to proximal-type ratio: 27-16) and 35 ALS patients. Five muscles, including abductor pollicis brevis (APB), abductor digiti minimi (ADM), biceps brachii (BB), middle deltoid (Del), and upper trapezius (Trap), were tested by 3-Hz RNS. Decrements greater than cutoff values (APB > 5.8%; ADM > 4.8%; BB > 5.2%; Del > 6%; Trap > 5.1%) determined using receiver operating characteristic (ROC) curves were defined as abnormal, and the conventional criterion (≥10%) was also considered. A significant CMAP decrement (>cutoff values) was recorded from at least one tested muscle in 91.4% of ALS patients, and was most common in the proximal muscle, a finding that differed significantly from CSA patients (32.6%, P  0.05). The application of RNS, especially in proximal muscles, may provide a simple accurate and noninvasive supplementary test for distinguishing CSA from ALS, even in the early stage of these diseases. A combination of RNS, needle EMG, clinical features and cervical magnetic resonance imaging may yield sufficient diagnostic information to differentiate CSA and ALS.

Studies to distinguish between human and animal faecal pollution ...

African Journals Online (AJOL)

Human enteric viral infections are considered to be predominantly associated with human wastes, as opposed to animal wastes, and a distinction between these has benefits for water quality control and risk assessment. A variety of techniques have been described to distinguish between human and animal faecal pollution ...

Iris-based medical analysis by geometric deformation features.

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Ma, Lin; Zhang, D; Li, Naimin; Cai, Yan; Zuo, Wangmeng; Wang, Kuanguan

2013-01-01

Iris analysis studies the relationship between human health and changes in the anatomy of the iris. Apart from the fact that iris recognition focuses on modeling the overall structure of the iris, iris diagnosis emphasizes the detecting and analyzing of local variations in the characteristics of irises. This paper focuses on studying the geometrical structure changes in irises that are caused by gastrointestinal diseases, and on measuring the observable deformations in the geometrical structures of irises that are related to roundness, diameter and other geometric forms of the pupil and the collarette. Pupil and collarette based features are defined and extracted. A series of experiments are implemented on our experimental pathological iris database, including manual clustering of both normal and pathological iris images, manual classification by non-specialists, manual classification by individuals with a medical background, classification ability verification for the proposed features, and disease recognition by applying the proposed features. The results prove the effectiveness and clinical diagnostic significance of the proposed features and a reliable recognition performance for automatic disease diagnosis. Our research results offer a novel systematic perspective for iridology studies and promote the progress of both theoretical and practical work in iris diagnosis.

The role of interpersonal harm in distinguishing regret from guilt.

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Zeelenberg, Marcel; Breugelmans, Seger M

2008-10-01

Regret and guilt are emotions that are produced by negative outcomes for which one is responsible. Both emotions have received ample attention in the psychological literature; however, it is still unclear to what extent regret and guilt represent distinct psychological processes. We examined the extent to which the distinction between interpersonal harm (negative outcomes for others) and intrapersonal harm (negative outcomes for self) is crucial in differentiating these two emotions. In a series of 3 studies we found that guilt is predominantly felt in situations of interpersonal harm, whereas regret is felt in both situations of interpersonal harm and intrapersonal harm. Moreover, the results show that in situations of interpersonal harm the phenomenology of regret shares many, but not all features with the phenomenology of guilt. We conclude that the emotion processes resulting from interpersonal and intrapersonal harm are clearly distinct, but that regret as an emotion label is applied to both types of processes whereas the emotion label guilt is primarily used to refer to experiences of interpersonal harm. Implications for emotion research are discussed. (c) 2008 APA, all rights reserved

Analysis of JET ELMy time series

International Nuclear Information System (INIS)

Zvejnieks, G.; Kuzovkov, V.N.

2005-01-01

Full text: Achievement of the planned operational regime in the next generation tokamaks (such as ITER) still faces principal problems. One of the main challenges is obtaining the control of edge localized modes (ELMs), which should lead to both long plasma pulse times and reasonable divertor life time. In order to control ELMs the hypothesis was proposed by Degeling [1] that ELMs exhibit features of chaotic dynamics and thus a standard chaos control methods might be applicable. However, our findings which are based on the nonlinear autoregressive (NAR) model contradict this hypothesis for JET ELMy time-series. In turn, it means that ELM behavior is of a relaxation or random type. These conclusions coincide with our previous results obtained for ASDEX Upgrade time series [2]. [1] A.W. Degeling, Y.R. Martin, P.E. Bak, J. B.Lister, and X. Llobet, Plasma Phys. Control. Fusion 43, 1671 (2001). [2] G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm, Physics of Plasmas 11, 5658 (2004)

Ultrasonographic Features of Papillary Thyroid Carcinomas According to Their Subtypes

Directory of Open Access Journals (Sweden)

Hye Jin Baek

2018-05-01

Full Text Available BackgroundThe ultrasonographic characteristics and difference for various subtypes of papillary thyroid carcinoma (PTC are still unclear. The aim of this study was to compare the ultrasonographic features of PTC according to its subtype in patients undergoing thyroid surgery.MethodsIn total, 140 patients who underwent preoperative thyroid ultrasonography (US and thyroid surgery between January 2016 and December 2016 were included. The ultrasonographic features and the Korean Thyroid Imaging Reporting and Data System (K-TIRADS category of each thyroid nodule were retrospectively evaluated by a single radiologist, and differences in ultrasonographic features according to the PTC subtype were assessed.ResultsAccording to histopathological analyses, there were 97 classic PTCs (62.2%, 34 follicular variants (21.8%, 5 tall cell variants (3.2%, 2 oncocytic variants (1.3%, 1 Warthin-like variant (0.6%, and 1 diffuse sclerosing variant (0.6%. Most PTCs were classified under K-TIRADS category 5. Among the ultrasonographic features, the nodule margin and the presence of calcification were significantly different among the PTC subtypes. A spiculated/microlobulated margin was the most common type of margin, regardless of the PTC subtype. In particular, all tall cell variants exhibited a spiculated/microlobulated margin. The classic PTC group exhibited the highest prevalence of intranodular calcification, with microcalcification being the most common. The prevalence of multiplicity and nodal metastasis was high in the tall cell variant group.ConclusionThe majority of PTCs in the present study belonged to K-TIRADS category 5, regardless of the subtype. Our findings suggest that ultrasonographic features are not useful for distinguishing PTC subtypes.

On Sums of Numerical Series and Fourier Series

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Pavao, H. Germano; de Oliveira, E. Capelas

2008-01-01

We discuss a class of trigonometric functions whose corresponding Fourier series, on a conveniently chosen interval, can be used to calculate several numerical series. Particular cases are presented and two recent results involving numerical series are recovered. (Contains 1 note.)

Binding of intrinsic and extrinsic features in working memory.

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

2013-02-01

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

Online feature selection with streaming features.

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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.