Game-Based Assessments: A Promising Way to Create Idiographic Perspectives

Science.gov (United States)

Walker, A. Adrienne; Engelhard, George, Jr.

2014-01-01

"Game-Based Assessments: A Promising Way to Create Idiographic Perspectives" (Adrienne Walker and George Englehard) comments on: "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Russell G. Almond, Yoon Jeon Kim, Gertrudes Velasquez, and Valerie J. Shute. Here, Walker and Englehard write…

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

Directory of Open Access Journals (Sweden)

Jian Kang

2015-01-01

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

Research on Optimal Observation Scale for Damaged Buildings after Earthquake Based on Optimal Feature Space

Science.gov (United States)

Chen, J.; Chen, W.; Dou, A.; Li, W.; Sun, Y.

2018-04-01

A new information extraction method of damaged buildings rooted in optimal feature space is put forward on the basis of the traditional object-oriented method. In this new method, ESP (estimate of scale parameter) tool is used to optimize the segmentation of image. Then the distance matrix and minimum separation distance of all kinds of surface features are calculated through sample selection to find the optimal feature space, which is finally applied to extract the image of damaged buildings after earthquake. The overall extraction accuracy reaches 83.1 %, the kappa coefficient 0.813. The new information extraction method greatly improves the extraction accuracy and efficiency, compared with the traditional object-oriented method, and owns a good promotional value in the information extraction of damaged buildings. In addition, the new method can be used for the information extraction of different-resolution images of damaged buildings after earthquake, then to seek the optimal observation scale of damaged buildings through accuracy evaluation. It is supposed that the optimal observation scale of damaged buildings is between 1 m and 1.2 m, which provides a reference for future information extraction of damaged buildings.

Fuzzy promises

DEFF Research Database (Denmark)

Anker, Thomas Boysen; Kappel, Klemens; Eadie, Douglas

2012-01-01

as narrative material to communicate self-identity. Finally, (c) we propose that brands deliver fuzzy experiential promises through effectively motivating consumers to adopt and play a social role implicitly suggested and facilitated by the brand. A promise is an inherently ethical concept and the article...... concludes with an in-depth discussion of fuzzy brand promises as two-way ethical commitments that put requirements on both brands and consumers....

Arctic Observing Network Data Management: Current Capabilities and Their Promise for the Future

Science.gov (United States)

Collins, J.; Fetterer, F.; Moore, J. A.

2008-12-01

CADIS (the Cooperative Arctic Data and Information Service) serves as the data management, discovery and delivery component of the Arctic Observing Network (AON). As an International Polar Year (IPY) initiative, AON comprises 34 land, atmosphere and ocean observation sites, and will acquire much of the data coming from the interagency Study of Environmental Arctic Change (SEARCH). CADIS is tasked with ensuring that these observational data are managed for long term use by members of the entire Earth System Science community. Portions of CADIS are either in use by the community or available for testing. We now have an opportunity to evaluate the feedback received from our users, to identify any design shortcomings, and to identify those elements which serve their purpose well and will support future development. This presentation will focus on the nuts-and-bolts of the CADIS development to date, with an eye towards presenting lessons learned and best practices based on our experiences so far. The topics include: - How did we assess our users' needs, and how are those contributions reflected in the end product and its capabilities? - Why did we develop a CADIS metadata profile, and how does it allow CADIS to support preservation and scientific interoperability? - How can we shield the user from metadata complexities (especially those associated with various standards) while still obtaining the metadata needed to support an effective data management system? - How can we bridge the gap between the data storage formats considered convenient by researchers in the field, and those which are necessary to provide data interoperability? - What challenges have been encountered in our efforts to provide access to federated data (data stored outside of the CADIS system)? - What are the data browsing and visualization needs of the AON community, and which tools and technologies are most promising in terms of supporting those needs? A live demonstration of the current

Promising design options for the encapsulated nuclear heat source reactor

International Nuclear Information System (INIS)

Conway, L.; Carelli, M.D.; Dzodzo, M.; Hossain, Q.; Brown, N.W.; Wade, D.C.; Sienick, J.J.; Greenspan, E.; Kastenberg, W.E.; Saphier, D.

2001-01-01

Promising design options for the Encapsulated Nuclear Heat Source (ENHS) liquid-metal cooled fast reactor were identified during the first year of the DOE NERI program sponsored feasibility study. Many opportunities for incorporation of innovations in design and fabrication were identified. Three of the innovations are hereby described: a novel IHX (intermediate heat exchanger) made of a relatively small number of rectangular channels, an ENHS module design featuring 100% natural circulation, and a novel conceptual design of core support and fuelling. As a result of the first year study the ENHS concept appears more practical and more promising than perceived at the outset of this study. (authors)

Promising design options for the encapsulated nuclear heat source reactor

Energy Technology Data Exchange (ETDEWEB)

Conway, L.; Carelli, M.D.; Dzodzo, M. [Westinghouse Science and Technology, Pittsburgh, PA (United States); Hossain, Q.; Brown, N.W. [Lawrence Livermore National Lab., CA (United States); Wade, D.C.; Sienick, J.J. [Argonne National Lab., IL (United States); Greenspan, E.; Kastenberg, W.E.; Saphier, D. [University of California Dept of Nuclear Engineering, Berkeley, CA (United States)

2001-07-01

Promising design options for the Encapsulated Nuclear Heat Source (ENHS) liquid-metal cooled fast reactor were identified during the first year of the DOE NERI program sponsored feasibility study. Many opportunities for incorporation of innovations in design and fabrication were identified. Three of the innovations are hereby described: a novel IHX (intermediate heat exchanger) made of a relatively small number of rectangular channels, an ENHS module design featuring 100% natural circulation, and a novel conceptual design of core support and fuelling. As a result of the first year study the ENHS concept appears more practical and more promising than perceived at the outset of this study. (authors)

Improving inter-observer variability in the evaluation of ultrasonographic features of polycystic ovaries

Directory of Open Access Journals (Sweden)

Leswick David A

2008-07-01

Full Text Available Abstract Background We recently reported poor inter-observer agreement in identifying and quantifying individual ultrasonographic features of polycystic ovaries. Our objective was to determine the effect of a training workshop on reducing inter-observer variation in the ultrasonographic evaluation of polycystic ovaries. Methods Transvaginal ultrasound recordings from thirty women with polycystic ovary syndrome (PCOS were evaluated by three radiologists and three reproductive endocrinologists both before and after an ultrasound workshop. The following endpoints were assessed: 1 follicle number per ovary (FNPO, 2 follicle number per single cross-section (FNPS, 3 largest follicle diameter, 4 ovarian volume, 5 follicle distribution pattern and 6 presence of a corpus luteum (CL. Lin's concordance correlation coefficients (rho and kappa statistics for multiple raters (kappa were used to assess level of inter-observer agreement (>0.80 good, 0.60 – 0.80 moderate/fair, Results Following the workshop, inter-observer agreement improved for the evaluation of FNPS (rho = 0.70, delta rho = +0.11, largest follicle diameter (rho = 0.77, delta rho = +0.10, ovarian volume (rho = 0.84, delta rho = +0.12, follicle distribution pattern (kappa = 0.80, delta kappa = +0.21 and presence of a CL (kappa = 0.87, delta kappa = +0.05. No improvement was evident for FNPO (rho = 0.54, delta rho = -0.01. Both radiologists and reproductive endocrinologists demonstrated improvement in scores (p Conclusion Reliability in evaluating ultrasonographic features of polycystic ovaries can be significantly improved following participation in a training workshop. If ultrasonographic evidence of polycystic ovaries is to be used as an objective measure in the diagnosis of PCOS, then standardized training modules should be implemented to unify the approach to evaluating polycystic ovarian morphology.

Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

Science.gov (United States)

Li, Baopu; Meng, Max Q-H

2012-05-01

Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

Finger vein recognition with personalized feature selection.

Science.gov (United States)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-08-22

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

Finger Vein Recognition with Personalized Feature Selection

Directory of Open Access Journals (Sweden)

Xianjing Meng

2013-08-01

Full Text Available Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG. For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

Online feature selection with streaming features.

Science.gov (United States)

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

2013-05-01

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

Promising Practices in Citywide Afterschool Initiatives. CityWorks: Focus on Infrastructure.

Science.gov (United States)

Hall, Georgia

This brief is the first in a series featuring promising practices in city-wide after-school initiatives, with a focus at the infrastructure level, focusing on the infrastructure representing the underlying elements or framework that hold a system or initiative together. The brief identifies practices to support the public relations function and…

Temporal feature of X-ray laser plasma observed from 3ω0/2, 2ω0 harmonic emission

International Nuclear Information System (INIS)

Li Wenhong; Mei Qiyong; Zhao Xuewei; Chen Yuting; Chunyu Shutai

1995-01-01

Temporal feature of X-ray laser plasma density was observed from 3ω 0 /2, 2ω 0 harmonic emission in the experiments. The temporal feature of 3ω 0 /2 harmonic emission of the germanium film is much different from that of the slab germanium target. The production of x-ray laser is closely related to 3ω 0 /2 harmonic emission in the slab germanium targets

A novel framework for feature extraction in multi-sensor action potential sorting.

Science.gov (United States)

Wu, Shun-Chi; Swindlehurst, A Lee; Nenadic, Zoran

2015-09-30

Extracellular recordings of multi-unit neural activity have become indispensable in neuroscience research. The analysis of the recordings begins with the detection of the action potentials (APs), followed by a classification step where each AP is associated with a given neural source. A feature extraction step is required prior to classification in order to reduce the dimensionality of the data and the impact of noise, allowing source clustering algorithms to work more efficiently. In this paper, we propose a novel framework for multi-sensor AP feature extraction based on the so-called Matched Subspace Detector (MSD), which is shown to be a natural generalization of standard single-sensor algorithms. Clustering using both simulated data and real AP recordings taken in the locust antennal lobe demonstrates that the proposed approach yields features that are discriminatory and lead to promising results. Unlike existing methods, the proposed algorithm finds joint spatio-temporal feature vectors that match the dominant subspace observed in the two-dimensional data without needs for a forward propagation model and AP templates. The proposed MSD approach provides more discriminatory features for unsupervised AP sorting applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Transforming Water Management: an Emerging Promise of Integrated Earth Observations

Science.gov (United States)

Lawford, R. G.

2011-12-01

Throughout its history, civilization has relied on technology to facilitate many of its advances. New innovations and technologies have often provided strategic advantages that have led to transformations in institutions, economies and ultimately societies. Observational and information technologies are leading to significant developments in the water sector. After a brief introduction tracing the role of observational technologies in the areas of hydrology and water cycle science, this talk explores the existing and potential contributions of remote sensing data in water resource management around the world. In particular, it outlines the steps being undertaken by the Group on Earth Observations (GEO) and its Water Task to facilitate capacity building efforts in water management using Earth Observations in Asia, Africa and Latin and Caribbean America. Success stories on the benefits of using Earth Observations and applying GEO principles are provided. While GEO and its capacity building efforts are contributing to the transformation of water management through interoperability, data sharing, and capacity building, the full potential of these contributions has not been fully realized because impediments and challenges still remain.

Do promises matter? An exploration of the role of promises in psychological contract breach.

Science.gov (United States)

Montes, Samantha D; Zweig, David

2009-09-01

Promises are positioned centrally in the study of psychological contract breach and are argued to distinguish psychological contracts from related constructs, such as employee expectations. However, because the effects of promises and delivered inducements are confounded in most research, the role of promises in perceptions of, and reactions to, breach remains unclear. If promises are not an important determinant of employee perceptions, emotions, and behavioral intentions, this would suggest that the psychological contract breach construct might lack utility. To assess the unique role of promises, the authors manipulated promises and delivered inducements separately in hypothetical scenarios in Studies 1 (558 undergraduates) and 2 (441 employees), and they measured them separately (longitudinally) in Study 3 (383 employees). The authors' results indicate that breach perceptions do not represent a discrepancy between what employees believe they were promised and were given. In fact, breach perceptions can exist in the absence of promises. Further, promises play a negligible role in predicting feelings of violation and behavioral intentions. Contrary to the extant literature, the authors' findings suggest that promises may matter little; employees are concerned primarily with what the organization delivers.

Features of everyday life in psychiatric inpatient care for self-harming: an observational study of six women.

Science.gov (United States)

Lindgren, Britt-Marie; Aminoff, Carina; Hällgren Graneheim, Ulla

2015-02-01

This study aimed to describe the features of everyday life in psychiatric inpatient care as experienced by women who self-harm. Participant observations and informal interviews were conducted with six women and were subjected to qualitative content analysis. The major feature of everyday life in psychiatric inpatient care was 'being surrounded by disorder', which consisted of 'living in a confusing environment, being subject to routines and rules that offer safety but lack consistency' and 'waiting both in loneliness and in togetherness'. The nursing staff spent minimal time with the patients and the women turned to each other for support, care and companionship.

M DWARF LUMINOSITY, RADIUS, AND α-ENRICHMENT FROM I-BAND SPECTRAL FEATURES

Energy Technology Data Exchange (ETDEWEB)

Terrien, Ryan C.; Mahadevan, Suvrath; Bender, Chad F.; Deshpande, Rohit; Robertson, Paul, E-mail: rct151@psu.edu [Department of Astronomy and Astrophysics, The Pennsylvania State University, 525 Davey Laboratory, University Park, PA 16802 (United States)

2015-03-20

Despite the ubiquity of M dwarfs and their growing importance to studies of exoplanets, Galactic evolution, and stellar structure, methods for precisely measuring their fundamental stellar properties remain elusive. Existing techniques for measuring M dwarf luminosity, mass, radius, or composition are calibrated over a limited range of stellar parameters or require expensive observations. We find a strong correlation between the K{sub S}-band luminosity (M{sub K}), the observed strength of the I-band sodium doublet absorption feature, and [Fe/H] in M dwarfs without strong Hα emission. We show that the strength of this feature, coupled with [Fe/H] and spectral type, can be used to derive M dwarf M{sub K} and radius without requiring parallax. Additionally, we find promising evidence that the strengths of the I-band sodium doublet and the nearby I-band calcium triplet may jointly indicate α-element enrichment. The use of these I-band features requires only moderate-resolution near-infrared spectroscopy to provide valuable information about the potential habitability of exoplanets around M dwarfs, and surface gravity and distance for M dwarfs throughout the Galaxy. This technique has immediate applicability for both target selection and candidate planet–host system characterization for exoplanet missions such as TESS and K2.

M DWARF LUMINOSITY, RADIUS, AND α-ENRICHMENT FROM I-BAND SPECTRAL FEATURES

International Nuclear Information System (INIS)

Terrien, Ryan C.; Mahadevan, Suvrath; Bender, Chad F.; Deshpande, Rohit; Robertson, Paul

2015-01-01

Despite the ubiquity of M dwarfs and their growing importance to studies of exoplanets, Galactic evolution, and stellar structure, methods for precisely measuring their fundamental stellar properties remain elusive. Existing techniques for measuring M dwarf luminosity, mass, radius, or composition are calibrated over a limited range of stellar parameters or require expensive observations. We find a strong correlation between the K S -band luminosity (M K ), the observed strength of the I-band sodium doublet absorption feature, and [Fe/H] in M dwarfs without strong Hα emission. We show that the strength of this feature, coupled with [Fe/H] and spectral type, can be used to derive M dwarf M K and radius without requiring parallax. Additionally, we find promising evidence that the strengths of the I-band sodium doublet and the nearby I-band calcium triplet may jointly indicate α-element enrichment. The use of these I-band features requires only moderate-resolution near-infrared spectroscopy to provide valuable information about the potential habitability of exoplanets around M dwarfs, and surface gravity and distance for M dwarfs throughout the Galaxy. This technique has immediate applicability for both target selection and candidate planet–host system characterization for exoplanet missions such as TESS and K2

Image cytometric nuclear texture features in inoperable head and neck cancer: a pilot study

International Nuclear Information System (INIS)

Strojan-Flezar, Margareta; Lavrencak, Jaka; Zganec, Mario; Strojan, Primoz

2011-01-01

Image cytometry can measure numerous nuclear features which could be considered a surrogate end-point marker of molecular genetic changes in a nucleus. The aim of the study was to analyze image cytometric nuclear features in paired samples of primary tumor and neck metastasis in patients with inoperable carcinoma of the head and neck. Image cytometric analysis of cell suspensions prepared from primary tumor tissue and fine needle aspiration biopsy cell samples of neck metastases from 21 patients treated with concomitant radiochemotherapy was performed. Nuclear features were correlated with clinical characteristics and response to therapy. Manifestation of distant metastases and new primaries was associated (p<0.05) with several chromatin characteristics from primary tumor cells, whereas the origin of index cancer and disease response in the neck was related to those in the cells from metastases. Many nuclear features of primary tumors and metastases correlated with the TNM stage. A specific pattern of correlation between well-established prognostic indicators and nuclear features of samples from primary tumors and those from neck metastases was observed. Image cytometric nuclear features represent a promising candidate marker for recognition of biologically different tumor subgroups

Elicited vs. voluntary promises

NARCIS (Netherlands)

Ismayilov, H.; Potters, Jan

2017-01-01

We set up an experiment with pre-play communication to study the impact of promise elicitation by trustors from trustees on trust and trustworthiness. When given the opportunity a majority of trustors solicits a promise from the trustee. This drives up the promise making rate by trustees to almost

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

Directory of Open Access Journals (Sweden)

M. Flach

2017-08-01

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

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

Science.gov (United States)

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

2010-01-01

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

Medical big data: promise and challenges.

Science.gov (United States)

Lee, Choong Ho; Yoon, Hyung-Jin

2017-03-01

The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

Medical big data: promise and challenges

Directory of Open Access Journals (Sweden)

Choong Ho Lee

2017-03-01

Full Text Available The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

Features Students Really Expect from Learning Analytics

Science.gov (United States)

Schumacher, Clara; Ifenthaler, Dirk

2016-01-01

In higher education settings more and more learning is facilitated through online learning environments. To support and understand students' learning processes better, learning analytics offers a promising approach. The purpose of this study was to investigate students' expectations toward features of learning analytics systems. In a first…

Keeping the Promise

Science.gov (United States)

Whissemore, Tabitha

2016-01-01

Since its launch in September 2015, Heads Up America has collected information on nearly 125 promise programs across the country, many of which were instituted long before President Barack Obama announced the America's College Promise (ACP) plan in 2015. At least 27 new free community college programs have launched in states, communities, and at…

Earth observations from space: History, promise, and reality. Executive summary

Science.gov (United States)

1995-01-01

In this report the Committee on Earth Studies (CES), a standing committee of the Space Studies Board (SSB) within the National Research Council (NRC), reviews the recent history (nominally from 1981 to 1995) of the U.S. earth observations programs that serve civilian needs. The principal observations programs examined are those of NASA and the National Oceanic and Atmospheric Administration (NOAA). The Air Force' s Defense Meteorological Satellite Program (DMSP) is discussed, but only from the perspective of its relationship to civil needs and the planned merger with the NOAA polar-orbiting system. The report also reviews the interfaces between the earth observations satellite programs and the major national and international environmental monitoring and research programs. The monitoring and research programs discussed are the U.S. Global Change Research Program (USGCRP), the International Geosphere-Biosphere Program (IGBP), the World Climate Research Program (WCRP), related international scientific campaigns, and operational programs for the sharing and application of environmental data. The purpose of this report is to provide a broad historical review and commentary based on the views of the CES members, with particular emphasis on tracing the lengthy record of advisory committee recommendations. Any individual topic could be the subject of an extended report in its own right. Indeed, extensive further reviews are already under way to that end. If the CES has succeeded in the task it has undertaken. This report will serve as a useful starting point for any such more intensive study. The report is divided into eight chapters: ( I ) an introduction, (2) the evolution of the MTPE, (3) its relationship to the USGCRP, (4) applications of earth observations data, (5) the role that smaller satellites can play in research and operational remote sensing, (6) earth system modeling and information systems, (7) a number of associated activities that contribute to the MTPE

Classification of Textures Using Filter Based Local Feature Extraction

Directory of Open Access Journals (Sweden)

Bocekci Veysel Gokhan

2016-01-01

Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

PERICARDIAL FEATURES OF IN-HOSPITAL RHEUMATOLOGY PATIENTS: AN OBSERVATIONAL STUDY.

Science.gov (United States)

Bakalli, Aurora; Rexhepi, Mjellma; Rexhepi, Blerta; Koçinaj, Dardan

Rheumatic disorders can be associated with pericarditis, but severe forms of pericarditis are rare. The aim of this observational study was to evaluate pericardial features in patients with different rheumatic diseases. Thirty-five patients hospitalized at the Clinic of Rheumatology, University Clinical Center of Kosovo, from October 1 to October 21, 2014 were included in the study. Demographic data, history, laboratory, ECG, and echocardiography data, with special emphasis on the analysis of the pericardium, were obtained from each patient. Echocardiography was especially focused on the amount of pericardial fluid and pericardial thickness in the posterior wall of the heart. Mean patient age was 51.5 ± 13.8 years. 65.7% of the patients were women. Out of the patients that we analyzed, 88.6% had an inflammatory rheumatologic disease. 11.3% of the patients had mild symptoms, in 68.7% the symptoms were moderate, and in 20% severe. In all patients, pericardial hyperechogenicity was marked, with a mean pericardial thickness of 4.68 ± 1.66 mm. Pericardial effusion in a small amount was present in 57.1% of patients, with a mean pericardial fluid amount of 3.3 ± 1.9 mm. The severity of rheumatic disease had a positive and significant correlation with the presence of pericardial effusion (r= 0.29, p=0.04) and its amount (r= 0.28, p=0.05). The patients had not been aware of the pericardial involvement and did not have any clinical symptoms. In conclusion, in this short-term small observational study pericardial changes were a frequent finding in the rheumatology patients. In general, the pericarditis was subclinical and with small amounts of effusion. The disease activity of rheumatic disorders can be associated with pericarditis. Further studies with larger samples of patients and of longer duration are needed to further explore this issue.

Feature Import Vector Machine: A General Classifier with Flexible Feature Selection.

Science.gov (United States)

Ghosh, Samiran; Wang, Yazhen

2015-02-01

The support vector machine (SVM) and other reproducing kernel Hilbert space (RKHS) based classifier systems are drawing much attention recently due to its robustness and generalization capability. General theme here is to construct classifiers based on the training data in a high dimensional space by using all available dimensions. The SVM achieves huge data compression by selecting only few observations which lie close to the boundary of the classifier function. However when the number of observations are not very large (small n ) but the number of dimensions/features are large (large p ), then it is not necessary that all available features are of equal importance in the classification context. Possible selection of an useful fraction of the available features may result in huge data compression. In this paper we propose an algorithmic approach by means of which such an optimal set of features could be selected. In short, we reverse the traditional sequential observation selection strategy of SVM to that of sequential feature selection. To achieve this we have modified the solution proposed by Zhu and Hastie (2005) in the context of import vector machine (IVM), to select an optimal sub-dimensional model to build the final classifier with sufficient accuracy.

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives.

Science.gov (United States)

Nichio, Bruno T L; Marchaukoski, Jeroniza Nunes; Raittz, Roberto Tadeu

2017-01-01

Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST "all-against-all" methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives

Directory of Open Access Journals (Sweden)

Bruno T. L. Nichio

2017-10-01

Full Text Available Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST “all-against-all” methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm; or proteinOrtho (which improves the accuracy of ortholog groups; or ReMark (tackling the integration of the pipeline to turn the entry process automatic; or OrthAgogue (using algorithms developed to

Survey of Object-Based Data Reduction Techniques in Observational Astronomy

Directory of Open Access Journals (Sweden)

Łukasik Szymon

2016-01-01

Full Text Available Dealing with astronomical observations represents one of the most challenging areas of big data analytics. Besides huge variety of data types, dynamics related to continuous data flow from multiple sources, handling enormous volumes of data is essential. This paper provides an overview of methods aimed at reducing both the number of features/attributes as well as data instances. It concentrates on data mining approaches not related to instruments and observation tools instead working on processed object-based data. The main goal of this article is to describe existing datasets on which algorithms are frequently tested, to characterize and classify available data reduction algorithms and identify promising solutions capable of addressing present and future challenges in astronomy.

Featureous: infrastructure for feature-centric analysis of object-oriented software

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2010-01-01

The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand how user-observable program features are implemented and how their implementations relate to each other. It is worthwhile to improve this situation, since feature-centric program...... understanding and modification are essential during software evolution and maintenance. In this paper, we present an infrastructure built on top of the NetBeans IDE called Featureous that allows for rapid construction of tools for feature-centric analysis of object-oriented software. Our infrastructure...... encompasses a lightweight feature location mechanism, a number of analytical views and an API allowing for addition of third-party extensions. To form a common conceptual framework for future feature-centric extensions, we propose to structure feature centric analysis along three dimensions: perspective...

Possibilities for direct optical observation of negative hydrogen ions in ion beam plasma sources via Rayleigh or Thomson scattering

International Nuclear Information System (INIS)

Burgess, D.D.

1985-01-01

The possibilities of applying optical scattering techniques to the determination of H - concentrations in plasma sources relevant to negative ion beam generation are considered. Rayleigh scattering measurements for incident wavelengths just below the H - photoionization limit appear to be only just feasible experimentally. A more promising possibility is observation of the modification in a plasma containing negative ions of the collective ion-feature in Thomson scattering. Numerical predictions of the effects of H - concentration on the spectral distribution of the ion-feature are presented. (author)

Promising More Information

Science.gov (United States)

2003-01-01

When NASA needed a real-time, online database system capable of tracking documentation changes in its propulsion test facilities, engineers at Stennis Space Center joined with ECT International, of Brookfield, Wisconsin, to create a solution. Through NASA's Dual-Use Program, ECT developed Exdata, a software program that works within the company's existing Promise software. Exdata not only satisfied NASA s requirements, but also expanded ECT s commercial product line. Promise, ECT s primary product, is an intelligent software program with specialized functions for designing and documenting electrical control systems. An addon to AutoCAD software, Promis e generates control system schematics, panel layouts, bills of material, wire lists, and terminal plans. The drawing functions include symbol libraries, macros, and automatic line breaking. Primary Promise customers include manufacturing companies, utilities, and other organizations with complex processes to control.

Crowding with conjunctions of simple features.

Science.gov (United States)

Põder, Endel; Wagemans, Johan

2007-11-20

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

Finger vein recognition based on the hyperinformation feature

Science.gov (United States)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

2014-01-01

The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

Inter-observer variability in diagnosing radiological features of aneurysmal subarachnoid hemorrhage; a preliminary single centre study comparing observers from different specialties and levels of training.

Science.gov (United States)

Siddiqui, Usman T; Khan, Anjum F; Shamim, Muhammad Shahzad; Hamid, Rana Shoaib; Alam, Muhammad Mehboob; Emaduddin, Muhammad

2014-01-01

A noncontrast computed tomography (CT) scan remains the initial radiological investigation of choice for a patient with suspected aneurysmal subarachnoid hemorrhage (aSAH). This initial scan may be used to derive key information about the underlying aneurysm which may aid in further management. The interpretation, however, is subject to the skill and experience of the interpreting individual. The authors here evaluate the interpretation of such CT scans by different individuals at different levels of training, and in two different specialties (Radiology and Neurosurgery). Initial nonontrast CT scan of 35 patients with aSAH was evaluated independently by four different observers. The observers selected for the study included two from Radiology and two from Neurosurgery at different levels of training; a resident currently in mid training and a resident who had recently graduated from training of each specialty. Measured variables included interpreter's suspicion of presence of subarachnoid blood, side of the subarachnoid hemorrhage, location of the aneurysm, the aneurysm's proximity to vessel bifurcation, number of aneurysm(s), contour of aneurysm(s), presence of intraventricular hemorrhage (IVH), intracerebral hemorrhage (ICH), infarction, hydrocephalus and midline shift. To determine the inter-observer variability (IOV), weighted kappa values were calculated. There was moderate agreement on most of the CT scan findings among all observers. Substantial agreement was found amongst all observers for hydrocephalus, IVH, and ICH. Lowest agreement rates were seen in the location of aneurysm being supra or infra tentorial. There were, however, some noteworthy exceptions. There was substantial to almost perfect agreement between the radiology graduate and radiology resident on most CT findings. The lowest agreement was found between the neurosurgery graduate and the radiology graduate. Our study suggests that although agreements were seen in the interpretation of some of

Loop quantum cosmology: from pre-inflationary dynamics to observations

International Nuclear Information System (INIS)

Ashtekar, Abhay; Barrau, Aurélien

2015-01-01

The Planck collaboration has provided us rich information about the early Universe, and a host of new observational missions will soon shed further light on the ‘anomalies’ that appear to exist on the largest angular scales. From a quantum gravity perspective, it is natural to inquire if one can trace back the origin of such puzzling features to Planck scale physics. Loop quantum cosmology provides a promising avenue to explore this issue because of its natural resolution of the big bang singularity. Thanks to advances over the last decade, the theory has matured sufficiently to allow concrete calculations of the phenomenological consequences of its pre-inflationary dynamics. In this article we summarize the current status of the ensuing two-way dialog between quantum gravity and observations. (paper)

Experimental Observation of Two Features Unexpected from the Classical Theories of Rubber Elasticity

Science.gov (United States)

Nishi, Kengo; Fujii, Kenta; Chung, Ung-il; Shibayama, Mitsuhiro; Sakai, Takamasa

2017-12-01

Although the elastic modulus of a Gaussian chain network is thought to be successfully described by classical theories of rubber elasticity, such as the affine and phantom models, verification experiments are largely lacking owing to difficulties in precisely controlling of the network structure. We prepared well-defined model polymer networks experimentally, and measured the elastic modulus G for a broad range of polymer concentrations and connectivity probabilities, p . In our experiment, we observed two features that were distinct from those predicted by classical theories. First, we observed the critical behavior G ˜|p -pc|1.95 near the sol-gel transition. This scaling law is different from the prediction of classical theories, but can be explained by analogy between the electric conductivity of resistor networks and the elasticity of polymer networks. Here, pc is the sol-gel transition point. Furthermore, we found that the experimental G -p relations in the region above C* did not follow the affine or phantom theories. Instead, all the G /G0-p curves fell onto a single master curve when G was normalized by the elastic modulus at p =1 , G0. We show that the effective medium approximation for Gaussian chain networks explains this master curve.

An observation of distribution features of cobalt rich manganese deposits

Digital Repository Service at National Institute of Oceanography (India)

Yamazaki, T.; Tsurusaki, K.; Handa, K.; Tomishima, Y.; Sharma, R.

Evaluation of seafloor stereo photographs, video data, and large diameter gravity core samples shows a variety of surface features associated with the crusts, nodules, and sediments covering mid Pacific seamounts. A set of deep sea stereo camera...

Passive Safety Features for Small Modular Reactors

International Nuclear Information System (INIS)

Ingersoll, Daniel T.

2010-01-01

The rapid growth in the size and complexity of commercial nuclear power plants in the 1970s spawned an interest in smaller, simpler designs that are inherently or intrinsically safe through the use of passive design features. Several designs were developed, but none were ever built, although some of their passive safety features were incorporated into large commercial plant designs that are being planned or built today. In recent years, several reactor vendors are actively redeveloping small modular reactor (SMR) designs with even greater use of passive features. Several designs incorporate the ultimate in passive safety they completely eliminate specific accident initiators from the design. Other design features help to reduce the likelihood of an accident or help to mitigate the accidents consequences, should one occur. While some passive safety features are common to most SMR designs, irrespective of the coolant technology, other features are specific to water, gas, or liquid-metal cooled SMR designs. The extensive use of passive safety features in SMRs promise to make these plants highly robust, protecting both the general public and the owner/investor. Once demonstrated, these plants should allow nuclear power to be used confidently for a broader range of customers and applications than will be possible with large plants alone.

Model-independent phenotyping of C. elegans locomotion using scale-invariant feature transform.

Directory of Open Access Journals (Sweden)

Yelena Koren

Full Text Available To uncover the genetic basis of behavioral traits in the model organism C. elegans, a common strategy is to study locomotion defects in mutants. Despite efforts to introduce (semi-automated phenotyping strategies, current methods overwhelmingly depend on worm-specific features that must be hand-crafted and as such are not generalizable for phenotyping motility in other animal models. Hence, there is an ongoing need for robust algorithms that can automatically analyze and classify motility phenotypes quantitatively. To this end, we have developed a fully-automated approach to characterize C. elegans' phenotypes that does not require the definition of nematode-specific features. Rather, we make use of the popular computer vision Scale-Invariant Feature Transform (SIFT from which we construct histograms of commonly-observed SIFT features to represent nematode motility. We first evaluated our method on a synthetic dataset simulating a range of nematode crawling gaits. Next, we evaluated our algorithm on two distinct datasets of crawling C. elegans with mutants affecting neuromuscular structure and function. Not only is our algorithm able to detect differences between strains, results capture similarities in locomotory phenotypes that lead to clustering that is consistent with expectations based on genetic relationships. Our proposed approach generalizes directly and should be applicable to other animal models. Such applicability holds promise for computational ethology as more groups collect high-resolution image data of animal behavior.

[INVITED] Evaluation of process observation features for laser metal welding

Science.gov (United States)

Tenner, Felix; Klämpfl, Florian; Nagulin, Konstantin Yu.; Schmidt, Michael

2016-06-01

In the present study we show how fast the fluid dynamics change when changing the laser power for different feed rates during laser metal welding. By the use of two high-speed cameras and a data acquisition system we conclude how fast we have to image the process to measure the fluid dynamics with a very high certainty. Our experiments show that not all process features which can be measured during laser welding do represent the process behavior similarly well. Despite the good visibility of the vapor plume the monitoring of its movement is less suitable as an input signal for a closed-loop control. The features measured inside the keyhole show a good correlation with changes of process parameters. Due to its low noise, the area of the keyhole opening is well suited as an input signal for a closed-loop control of the process.

Incidence and features of eosinophilic esophagitis in dysphagia: a prospective observational study.

Science.gov (United States)

Murray, Iain Alexander; Joyce, Stephne; Palmer, Joanne; Lau, Michael; Schultz, Michael

2016-03-01

The incidence and symptoms associated with eosinophilic esophagitis (EoE) varies with geographic location, present in 7-15% dysphagic European or North American adults. We aimed to determine incidence and features of EoE in a dysphagic New Zealand population. 101 consecutive patients presenting with dysphagia to a New Zealand teaching hospital completed a questionnaire (demographics and history) before upper gastrointestinal endoscopy and esophageal biopsies. The incidence of EoE was 14.1% in those having esophageal biopsies. Patients with EoE were younger (median age 38 years, cohort 58 years: OR 9.2 for age ≤ 40; p dysphagia and history of allergy/atopy occurred with almost identical frequency in those with and without EoE. Classic endoscopic features of EoE had a sensitivity and specificity of 30.6 and 93.2%, respectively. EoE occurs in an adult dysphagic population in New Zealand with similar frequency to that reported in Europe and North America. Demographics and features of history associated with EoE are described and the need to take esophageal biopsies in this population emphasized by the relatively low sensitivity of endoscopic features for the condition.

Gamma-ray astronomy in the nuclear transition region (the promise and the problems)

International Nuclear Information System (INIS)

Chupp, E.L.

1988-01-01

Gamma ray astronomy, γ-ray lines and continuum γ-rays carry unique information about many astrophysical phenomena. The γ-ray observations give insight into the acceleration of particles insolar flares, galactic nucleosynthesis, and the dynamics of an evolving supernovae. Further, we can hope to understand the enigmatic γ-ray bursts and other, yet unknown phenomena. The present list of accomplishments is meager for a field that offers so much promise, yet inspite of the difficulties inherent to the field the promise is even greater today. This is so, because only a few observations have brought forth many insights, as I will discuss. Also many unresolved questions remain concerning the interpretation of the exciting observations of the cosmic 26 Al and the e + --e - annihilation γ lines and as well the γ-ray lines from solar flares. In the following we will review, briefly, some of the conflicts existing at this time on the observational scene and suggest approaches for future developments of the field

Nano features of Al/Au ultrasonic bond interface observed by high resolution transmission electron microscopy

International Nuclear Information System (INIS)

Ji Hongjun; Li Mingyu; Kim, Jong-Myung; Kim, Dae-Won; Wang Chunqing

2008-01-01

Nano-scale interfacial details of ultrasonic AlSi1 wire wedge bonding to a Au/Ni/Cu pad were investigated using high resolution transmission electron microscopy (HRTEM). The intermetallic phase Au 8 Al 3 formed locally due to diffusion and reaction activated by ultrasound at the Al/Au bond interface. Multilayer sub-interfaces roughly parallel to the wire/pad interface were observed among this phase, and interdiffusional features near the Au pad resembled interference patterns, alternately dark and bright bars. Solid-state diffusion theory cannot be used to explain why such a thick compound formed within milliseconds at room temperature. The major formation of metallurgical bonds was attributed to ultrasonic cyclic vibration

Multiscale deep features learning for land-use scene recognition

Science.gov (United States)

Yuan, Baohua; Li, Shijin; Li, Ning

2018-01-01

The features extracted from deep convolutional neural networks (CNNs) have shown their promise as generic descriptors for land-use scene recognition. However, most of the work directly adopts the deep features for the classification of remote sensing images, and does not encode the deep features for improving their discriminative power, which can affect the performance of deep feature representations. To address this issue, we propose an effective framework, LASC-CNN, obtained by locality-constrained affine subspace coding (LASC) pooling of a CNN filter bank. LASC-CNN obtains more discriminative deep features than directly extracted from CNNs. Furthermore, LASC-CNN builds on the top convolutional layers of CNNs, which can incorporate multiscale information and regions of arbitrary resolution and sizes. Our experiments have been conducted using two widely used remote sensing image databases, and the results show that the proposed method significantly improves the performance when compared to other state-of-the-art methods.

Helium Ion Microscopy: A Promising Tool for Probing Biota-Mineral Interfaces

Science.gov (United States)

Lybrand, R.; Zaharescu, D. G.; Gallery, R. E.

2017-12-01

The study of biogeochemical interfaces in soil requires powerful technologies that can enhance our ability to characterize mineral surfaces and interacting organisms at micro- to nanoscale resolutions. We aim to demonstrate potential applications of Helium Ion Microscopy in the earth and ecological sciences using, as an example, samples from a field experiment. We assessed samples deployed for one year along climatic and topographic gradients in two Critical Zone Observatories (CZOs): a desert to mixed conifer forest gradient (Catalina CZO) and a humid hardwood forest (Calhoun CZO). Sterile ground rock (basalt, quartz, and granite; 53-250 µm) was sealed into nylon mesh bags and buried in the surface soils of both CZOs. We employed helium ion and scanning electron microscopies to compare retrieved ground rock samples with sterile unreacted mineral controls in conjunction with the Environmental Molecular Sciences Laboratory at Pacific Northwest National Laboratory, USA. Our work showed early colonization of mesh bag materials by fungal and bacterial organisms from the field systems and identified morphological changes in mineral grains following exposure to the soil environment. Biological specimens observed on grain surfaces exhibited contrasting features depending on mineral type and ecosystem location, including fungal hyphae that varied in length, diameter, and surface morphologies. We also present imagery that provides evidence for incipient stages of mineral transformation at the fungal-mineral interface. Our findings demonstrate that helium ion microscopy can be successfully used to characterize grain features and biological agents of weathering in experimental field samples, representing a promising avenue for research in the biogeosciences. Future directions of this work will couple high resolution imaging with measures of aqueous and solid geochemistry, fungal morphological characterization, and microbial profiling to better understand mineral

Mastering JavaScript promises

CERN Document Server

Hussain, Muzzamil

2015-01-01

This book is for all the software and web engineers wanting to apply the promises paradigm to their next project and get the best outcome from it. This book also acts as a reference for the engineers who are already using promises in their projects and want to improve their current knowledge to reach the next level. To get the most benefit from this book, you should know basic programming concepts, have a familiarity with JavaScript, and a good understanding of HTML.

EVENT-MARKETING – FEATURES OF APPLICATION IN MODERN TOURISM

Directory of Open Access Journals (Sweden)

Oksana Vlasenko

2016-03-01

Full Text Available In the article analyzed the modern features of the development and using of event- marketing. Showed the conditions of the essence and characteristics of event management, its principles and methods of application. Characterized the features and importance of tourism and the benefits of application of event marketing as a promising method of indirect marketing communications. Used examples of practical application of event marketing activity. Determined correlation of event management and marketing and its subordination to the event marketing purposes. Key words: tourism, event-tourism, event-management, event-marketing, socio-cultural sphere. JEL: M 31

C2 emission features in the Red Rectangle : A combined observational laboratory study

NARCIS (Netherlands)

Wehres, N.; Romanzin, C.; Linnartz, H.; van Winckel, H.; Tielens, A. G. G. M.

Context. The Red Rectangle proto-planetary nebula (HD 44179) is known for a number of rather narrow emission features superimposed on a broad extended red emission (ERE) covering the 5000-7500 angstrom regime. The origin of these emission features is unknown. Aims. The aim of the present work is to

Probing features in inflaton potential and reionization history with future CMB space observations

Science.gov (United States)

Hazra, Dhiraj Kumar; Paoletti, Daniela; Ballardini, Mario; Finelli, Fabio; Shafieloo, Arman; Smoot, George F.; Starobinsky, Alexei A.

2018-02-01

We consider the prospects of probing features in the primordial power spectrum with future Cosmic Microwave Background (CMB) polarization measurements. In the scope of the inflationary scenario, such features in the spectrum can be produced by local non-smooth pieces in an inflaton potential (smooth and quasi-flat in general) which in turn may originate from fast phase transitions during inflation in other quantum fields interacting with the inflaton. They can fit some outliers in the CMB temperature power spectrum which are unaddressed within the standard inflationary ΛCDM model. We consider Wiggly Whipped Inflation (WWI) as a theoretical framework leading to improvements in the fit to the Planck 2015 temperature and polarization data in comparison with the standard inflationary models, although not at a statistically significant level. We show that some type of features in the potential within the WWI models, leading to oscillations in the primordial power spectrum that extend to intermediate and small scales can be constrained with high confidence (at 3σ or higher confidence level) by an instrument as the Cosmic ORigins Explorer (CORE). In order to investigate the possible confusion between inflationary features and footprints from the reionization era, we consider an extended reionization history with monotonic increase of free electrons with decrease in redshift. We discuss the present constraints on this model of extended reionization and future predictions with CORE. We also project, to what extent, this extended reionization can create confusion in identifying inflationary features in the data.

Access, Participation, and Supports: The Defining Features of High-Quality Inclusion

Science.gov (United States)

Buysse, Virginia

2011-01-01

This article describes current knowledge about early childhood inclusion, summarizing research and the DEC/NAEYC joint position statement on inclusion. The article also describes effective or promising educational practices that promote access, participation, and supports--the defining features of high-quality inclusion. Future efforts to improve…

Sensitivity to feature displacement in familiar and unfamiliar faces: beyond the internal/external feature distinction.

Science.gov (United States)

Brooks, Kevin R; Kemp, Richard I

2007-01-01

Previous studies of face recognition and of face matching have shown a general improvement for the processing of internal features as a face becomes more familiar to the participant. In this study, we used a psychophysical two-alternative forced-choice paradigm to investigate thresholds for the detection of a displacement of the eyes, nose, mouth, or ears for familiar and unfamiliar faces. No clear division between internal and external features was observed. Rather, for familiar (compared to unfamiliar) faces participants were more sensitive to displacements of internal features such as the eyes or the nose; yet, for our third internal feature-the mouth no such difference was observed. Despite large displacements, many subjects were unable to perform above chance when stimuli involved shifts in the position of the ears. These results are consistent with the proposal that familiarity effects may be mediated by the construction of a robust representation of a face, although the involvement of attention in the encoding of face stimuli cannot be ruled out. Furthermore, these effects are mediated by information from a spatial configuration of features, rather than by purely feature-based information.

Neuromodulation as a cognitive enhancement strategy in healthy older adults: promises and pitfalls.

Science.gov (United States)

Martins, Ana R S; Fregni, Felipe; Simis, Marcel; Almeida, Jorge

2017-03-01

Increases in life expectancy have been followed by an upsurge of age-associated cognitive decline. Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have risen as promising approaches to prevent or delay such cognitive decline. However, consensus has not yet been reached about their efficacy in improving cognitive functioning in healthy older adults. Here we review the effects of TMS and tDCS on cognitive abilities in healthy older adults. Despite considerable variability in the targeted cognitive domains, design features and outcomes, the results generally show an enhancement or uniform benefit across studies. Most studies employed tDCS, suggesting that this technique is particularly well-suited for cognitive enhancement. Further work is required to determine the viability of these techniques as tools for long-term cognitive improvement. Importantly, the combination of TMS/tDCS with other cognitive enhancement strategies may be a promising strategy to alleviate the cognitive decline associated with the healthy aging process.

FEATUREOUS: AN INTEGRATED ENVIRONMENT FOR FEATURE-CENTRIC ANALYSIS AND MODIFICATION OF OBJECT-ORIENTED SOFTWARE

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand the implementations of user-observable program features and their respective interdependencies. As feature-centric program understanding and modification are essential during...... software maintenance and evolution, this situation needs to change. In this paper, we present Featureous, an integrated development environment built on top of the NetBeans IDE that facilitates feature-centric analysis of object-oriented software. Our integrated development environment encompasses...... a lightweight feature location mechanism, a number of reusable analytical views, and necessary APIs for supporting future extensions. The base of the integrated development environment is a conceptual framework comprising of three complementary dimensions of comprehension: perspective, abstraction...

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.

Artificial Intelligence and the Future of Education: Big Promises-Bigger Challenges%Artificial Intelligence and the Future of Education:Big Promises-Bigger Challenges

Institute of Scientific and Technical Information of China (English)

Jonathan Michael Spector; Du Jing

2017-01-01

The history of educational technology in the last 50 years contains few instances of dramatic improvements in learning based on the adoption of a particular technology.An example involving artificial intelligence occurred in the 1990s with the development of intelligent tutoring systems (ITSs).What happened with ITSs was that their success was limited to well-defined and relatively simple declarative and procedural leaming tasks (e.g.,learning how to write a recursive function in LISP;doing multi-column addition),and improvements that were observed tended to be more limited than promised (e.g.,one standard deviation improvement at best rather than the promised standard deviation improvement).Still,there was some progress in terms of how to conceptualize learning.A seldom documented limitation was the notion of only viewing learning from only content and cognitive perspectives (i.e.,in terms of memory limitations,prior knowledge,bug libraries,learning hierarchies and sequences etc.).Little attention was paid to education conceived more broadly than developing specific cognitive skills with highly constrained problems.New technologies offer the potential to create dynamic and multi-dimensional models of a particular leamer,and to track large data sets of learning activities,resources,interventions,and outcomes over a great many leamers.Using those data to personalize learning for a particular leamer developing knowledge,competence and understanding in a specific domain of inquiry is finally a real possibility.While the potential to make significant progress is clearly possible,the reality is less not so promising.There are many as yet unmet challenging some of which will be mentioned in this paper.A persistent worry is that educational technologists and computer scientists will again promise too much,too soon at too little cost and with too little effort and attention to the realities in schools and universities.

Realizing the promises of marine biotechnology

NARCIS (Netherlands)

Luiten, EEM; Akkerman, [No Value; Koulman, A; Kamermans, P; Reith, H; Barbosa, MJ; Sipkema, D; Wijffels, RH

High-quality research in the field of marine biotechnology is one of the key-factors for successful innovation in exploiting the vast diversity of marine life. However, fascinating scientific research with promising results and claims on promising potential applications (e.g. for pharmaceuticals,

Realizing the promises of marine biotechnology

NARCIS (Netherlands)

Luiten, E.E.M.; Akkerman, I.; Koulman, A.; Kamermans, P.; Reith, H.; Barbosa, M.J.; Sipkema, D.; Wijffels, R.H.

2003-01-01

High-quality research in the field of marine biotechnology is one of the key-factors for successful innovation in exploiting the vast diversity of marine life. However, fascinating scientific research with promising results and claims on promising potential applications (e.g. for pharmaceuticals,

Concentric transmon qubit featuring fast tunability and an anisotropic magnetic dipole moment

Energy Technology Data Exchange (ETDEWEB)

Braumueller, Jochen; Schneider, Andre; Schloer, Steffen; Gruenhaupt, Lukas; Rotzinger, Hannes; Marthaler, Michael; Lukashenko, Alexander; Dieter, Amadeus [Karlsruhe Institute of Technology, 76131 Karlsruhe (Germany); Sandberg, Martin; Vissers, Michael R.; Pappas, David P. [National Institute of Standards and Technology, Boulder, Colorado 80305 (United States); Ustinov, Alexey V. [Karlsruhe Institute of Technology, 76131 Karlsruhe (Germany); National University of Science and Technology MISIS, Moscow 119049 (Russian Federation); Weides, Martin [Karlsruhe Institute of Technology, 76131 Karlsruhe (Germany); Johannes Gutenberg University, Mainz, 55128 Mainz (Germany)

2016-07-01

We present a planar qubit design based on a superconducting circuit that we call concentric transmon. While employing a straightforward fabrication process using Al evaporation and lift-off lithography, we observe qubit lifetimes and coherence times in the order of 10 μs. We systematically characterize loss channels such as incoherent dielectric loss, Purcell decay and radiative losses. The implementation of a gradiometric SQUID loop allows for a fast tuning of the qubit transition frequency and therefore for full tomographic control of the quantum circuit. Due to the large loop size, the presented qubit architecture features a strongly increased magnetic dipole moment as compared to conventional transmon designs. This renders the concentric transmon a promising candidate to establish a site-selective passive direct Z coupling between neighboring qubits, being a pending quest in the field of quantum simulation.

Concentric transmon qubit featuring fast tunability and an anisotropic magnetic dipole moment

Science.gov (United States)

Braumüller, Jochen; Sandberg, Martin; Vissers, Michael R.; Schneider, Andre; Schlör, Steffen; Grünhaupt, Lukas; Rotzinger, Hannes; Marthaler, Michael; Lukashenko, Alexander; Dieter, Amadeus; Ustinov, Alexey V.; Weides, Martin; Pappas, David P.

2016-01-01

We present a planar qubit design based on a superconducting circuit that we call concentric transmon. While employing a straightforward fabrication process using Al evaporation and lift-off lithography, we observe qubit lifetimes and coherence times in the order of 10 μ s . We systematically characterize loss channels such as incoherent dielectric loss, Purcell decay and radiative losses. The implementation of a gradiometric SQUID loop allows for a fast tuning of the qubit transition frequency and therefore for full tomographic control of the quantum circuit. Due to the large loop size, the presented qubit architecture features a strongly increased magnetic dipole moment as compared to conventional transmon designs. This renders the concentric transmon a promising candidate to establish a site-selective passive direct Z ̂ coupling between neighboring qubits, being a pending quest in the field of quantum simulation.

Political Reputations and Campaign Promises

OpenAIRE

Aragones, Enriqueta; Palfrey, Thomas R.; Postlewaite, Andrew

2006-01-01

We analyze conditions under which candidates' reputations may affect voters' beliefs over what policy will be implemented by the winning candidate of an election. We develop a model of repeated elections with complete information in which candidates are purely ideological. We analyze an equilibrium in which voters' strategies involve a credible threat to punish candidates who renege on their campaign promises and in which all campaign promises are believed by voters and honored by candidates....

Satellite-observed cold-ring-shaped features atop deep convective clouds

Czech Academy of Sciences Publication Activity Database

Setvák, M.; Lindsey, D. T.; Novák, P.; Wang, P. K.; Radová, Michaela; Kerkmann, J.; Grasso, L.; Su, S.-H.; Rabin, R. M.; Šťástka, J.; Charvát, Z.

2010-01-01

Roč. 97, 1-2 (2010), s. 80-96 ISSN 0169-8095 R&D Projects: GA ČR GA205/07/0905; GA MŠk ME09033 Institutional research plan: CEZ:AV0Z30420517 Keywords : convective storm * storm top * cloud top height * cold-ring shape * cold-U shape * enhanced-V feature * overshooting top * lower stratosphere * Meteosat second generation Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.597, year: 2010 http://www.sciencedirect.com/science/article/pii/S016980951000058X

Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

Directory of Open Access Journals (Sweden)

Mustafa Serter Uzer

2013-01-01

Full Text Available This paper offers a hybrid approach that uses the artificial bee colony (ABC algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.

Statistical and observational research of solar flare for total spectra and geometrical features

Science.gov (United States)

Nishimoto, S.; Watanabe, K.; Imada, S.; Kawate, T.; Lee, K. S.

2017-12-01

Impulsive energy release phenomena such as solar flares, sometimes affect to the solar-terrestrial environment. Usually, we use soft X-ray flux (GOES class) as the index of flare scale. However, the magnitude of effect to the solar-terrestrial environment is not proportional to that scale. To identify the relationship between solar flare phenomena and influence to the solar-terrestrial environment, we need to understand the full spectrum of solar flares. There is the solar flare irradiance model named the Flare Irradiance Spectral Model (FISM) (Chamberlin et al., 2006, 2007, 2008). The FISM can estimate solar flare spectra with high wavelength resolution. However, this model can not express the time evolution of emitted plasma during the solar flare, and has low accuracy on short wavelength that strongly effects and/or controls the total flare spectra. For the purpose of obtaining the time evolution of total solar flare spectra, we are performing statistical analysis of the electromagnetic data of solar flares. In this study, we select solar flare events larger than M-class from the Hinode flare catalogue (Watanabe et al., 2012). First, we focus on the EUV emission observed by the SDO/EVE. We examined the intensities and time evolutions of five EUV lines of 55 flare events. As a result, we found positive correlation between the "soft X-ray flux" and the "EUV peak flux" for all EVU lines. Moreover, we found that hot lines peaked earlier than cool lines of the EUV light curves. We also examined the hard X-ray data obtained by RHESSI. When we analyzed 163 events, we found good correlation between the "hard X-ray intensity" and the "soft X-ray flux". Because it seems that the geometrical features of solar flares effect to those time evolutions, we also looked into flare ribbons observed by SDO/AIA. We examined 21 flare events, and found positive correlation between the "GOES duration" and the "ribbon length". We also found positive correlation between the "ribbon

The Promising Features of New Nano Liquid Metals—Liquid Sodium Containing Titanium Nanoparticles (LSnanop

Directory of Open Access Journals (Sweden)

Toshio Itami

2015-07-01

Full Text Available A new kind of suspension liquid was developed by dispersing Ti nanoparticles (10 nm in liquid Na, which was then determined by TEM (transmission electron microscopy analysis. The volume fraction was estimated to be 0.0088 from the analyzed Ti concentration (2 at. % and the densities of Ti and Na. This suspension liquid, Liquid Sodium containing nanoparticles of titanium (LSnanop, shows, despite only a small addition of Ti nanoparticles, many striking features, namely a negative deviation of 3.9% from the ideal solution for the atomic volume, an increase of 17% in surface tension, a decrease of 11% for the reaction heat to water, and the suppression of chemical reactivity to water and oxygen. The decrease in reaction heat to water seems to be derived from the existence of excess cohesive energy of LSnanop. The excess cohesive energy was discussed based on simple theoretical analyses, with particular emphasis on the screening effect. The suppression of reactivity is discussed with the relation to the decrease of heat of reaction to water or the excess cohesive energy, surface tension, the action as a plug of Ti oxide, negative adsorption on the surface of LSnanop, and percolation.

A redundancy-removing feature selection algorithm for nominal data

Directory of Open Access Journals (Sweden)

Zhihua Li

2015-10-01

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

An image-processing methodology for extracting bloodstain pattern features.

Science.gov (United States)

Arthur, Ravishka M; Humburg, Philomena J; Hoogenboom, Jerry; Baiker, Martin; Taylor, Michael C; de Bruin, Karla G

2017-08-01

There is a growing trend in forensic science to develop methods to make forensic pattern comparison tasks more objective. This has generally involved the application of suitable image-processing methods to provide numerical data for identification or comparison. This paper outlines a unique image-processing methodology that can be utilised by analysts to generate reliable pattern data that will assist them in forming objective conclusions about a pattern. A range of features were defined and extracted from a laboratory-generated impact spatter pattern. These features were based in part on bloodstain properties commonly used in the analysis of spatter bloodstain patterns. The values of these features were consistent with properties reported qualitatively for such patterns. The image-processing method developed shows considerable promise as a way to establish measurable discriminating pattern criteria that are lacking in current bloodstain pattern taxonomies. Copyright © 2017 Elsevier B.V. All rights reserved.

Learning deep features with adaptive triplet loss for person reidentification

Science.gov (United States)

Li, Zhiqiang; Sang, Nong; Chen, Kezhou; Gao, Changxin; Wang, Ruolin

2018-03-01

Person reidentification (re-id) aims to match a specified person across non-overlapping cameras, which remains a very challenging problem. While previous methods mostly focus on feature extraction or metric learning, this paper makes the attempt in jointly learning both the global full-body and local body-parts features of the input persons with a multichannel convolutional neural network (CNN) model, which is trained by an adaptive triplet loss function that serves to minimize the distance between the same person and maximize the distance between different persons. The experimental results show that our approach achieves very promising results on the large-scale Market-1501 and DukeMTMC-reID datasets.

No-reference image quality assessment based on statistics of convolution feature maps

Science.gov (United States)

Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo

2018-04-01

We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.

Texture Feature Extraction and Classification for Iris Diagnosis

Science.gov (United States)

Ma, Lin; Li, Naimin

Appling computer aided techniques in iris image processing, and combining occidental iridology with the traditional Chinese medicine is a challenging research area in digital image processing and artificial intelligence. This paper proposes an iridology model that consists the iris image pre-processing, texture feature analysis and disease classification. To the pre-processing, a 2-step iris localization approach is proposed; a 2-D Gabor filter based texture analysis and a texture fractal dimension estimation method are proposed for pathological feature extraction; and at last support vector machines are constructed to recognize 2 typical diseases such as the alimentary canal disease and the nerve system disease. Experimental results show that the proposed iridology diagnosis model is quite effective and promising for medical diagnosis and health surveillance for both hospital and public use.

Treatment recommendations for DSM-5-defined mixed features.

Science.gov (United States)

Rosenblat, Joshua D; McIntyre, Roger S

2017-04-01

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) mixed features specifier provides a less restrictive definition of mixed mood states, compared to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR), including mood episodes that manifest with subthreshold symptoms of the opposite mood state. A limited number of studies have assessed the efficacy of treatments specifically for DSM-5-defined mixed features in mood disorders. As such, there is currently an inadequate amount of data to appropriately inform evidence-based treatment guidelines of DSM-5 defined mixed features. However, given the high prevalence and morbidity of mixed features, treatment recommendations based on the currently available evidence along with expert opinion may be of benefit. This article serves to provide these interim treatment recommendations while humbly acknowledging the limited amount of evidence currently available. Second-generation antipsychotics (SGAs) appear to have the greatest promise in the treatment of bipolar disorder (BD) with mixed features. Conventional mood stabilizing agents (ie, lithium and divalproex) may also be of benefit; however, they have been inadequately studied. In the treatment of major depressive disorder (MDD) with mixed features, the comparable efficacy of antidepressants versus other treatments, such as SGAs, remains unknown. As such, antidepressants remain first-line treatment of MDD with or without mixed features; however, there are significant safety concerns associated with antidepressant monotherapy when mixed features are present, which merits increased monitoring. Lurasidone is the only SGA monotherapy that has been shown to be efficacious specifically in the treatment of MDD with mixed features. Further research is needed to accurately determine the efficacy, safety, and tolerability of treatments specifically for mood episodes with mixed features to adequately inform

An Expressive Bodily Movement Repertoire for Marimba Performance, Revealed through Observers' Laban Effort-Shape Analyses, and Allied Musical Features: Two Case Studies

Science.gov (United States)

Broughton, Mary C.; Davidson, Jane W.

2016-01-01

Musicians' expressive bodily movements can influence observers' perception of performance. Furthermore, individual differences in observers' music and motor expertise can shape how they perceive and respond to music performance. However, few studies have investigated the bodily movements that different observers of music performance perceive as expressive, in order to understand how they might relate to the music being produced, and the particular instrument type. In this paper, we focus on marimba performance through two case studies—one solo and one collaborative context. This study aims to investigate the existence of a core repertoire of marimba performance expressive bodily movements, identify key music-related features associated with the core repertoire, and explore how observers' perception of expressive bodily movements might vary according to individual differences in their music and motor expertise. Of the six professional musicians who observed and analyzed the marimba performances, three were percussionists and experienced marimba players. Following training, observers implemented the Laban effort-shape movement analysis system to analyze marimba players' bodily movements that they perceived as expressive in audio-visual recordings of performance. Observations that were agreed by all participants as being the same type of action at the same location in the performance recording were examined in each case study, then across the two studies. A small repertoire of bodily movements emerged that the observers perceived as being expressive. Movements were primarily allied to elements of the music structure, technique, and expressive interpretation, however, these elements appeared to be interactive. A type of body sway movement and more localized sound generating actions were perceived as expressive. These movements co-occurred and also appeared separately. Individual participant data revealed slightly more variety in the types and locations of actions

An Expressive Bodily Movement Repertoire for Marimba Performance, Revealed through Observers' Laban Effort-Shape Analyses, and Allied Musical Features: Two Case Studies.

Science.gov (United States)

Broughton, Mary C; Davidson, Jane W

2016-01-01

Musicians' expressive bodily movements can influence observers' perception of performance. Furthermore, individual differences in observers' music and motor expertise can shape how they perceive and respond to music performance. However, few studies have investigated the bodily movements that different observers of music performance perceive as expressive, in order to understand how they might relate to the music being produced, and the particular instrument type. In this paper, we focus on marimba performance through two case studies-one solo and one collaborative context. This study aims to investigate the existence of a core repertoire of marimba performance expressive bodily movements, identify key music-related features associated with the core repertoire, and explore how observers' perception of expressive bodily movements might vary according to individual differences in their music and motor expertise. Of the six professional musicians who observed and analyzed the marimba performances, three were percussionists and experienced marimba players. Following training, observers implemented the Laban effort-shape movement analysis system to analyze marimba players' bodily movements that they perceived as expressive in audio-visual recordings of performance. Observations that were agreed by all participants as being the same type of action at the same location in the performance recording were examined in each case study, then across the two studies. A small repertoire of bodily movements emerged that the observers perceived as being expressive. Movements were primarily allied to elements of the music structure, technique, and expressive interpretation, however, these elements appeared to be interactive. A type of body sway movement and more localized sound generating actions were perceived as expressive. These movements co-occurred and also appeared separately. Individual participant data revealed slightly more variety in the types and locations of actions

Feature-Based Retinal Image Registration Using D-Saddle Feature

Directory of Open Access Journals (Sweden)

Roziana Ramli

2017-01-01

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

Detection of the 3.4 micron emission feature in Comets P/Brorsen-Metcalf and Okazaki-Levy-Rudenko (1989r) and an observational summary

International Nuclear Information System (INIS)

Brooke, T.Y.; Tokunaga, A.T.; Knacke, R.F.

1991-01-01

The 3.4 micron emission feature due to cometary organics was detected in Comets P/Brorsen-Metcalf and Okazaki-Levy-Rudenko (1989r). Features-to-continuum ratios in these two comets were higher than those expected from the trend seen in other comets to date. Three micron spectra of eight comets are reviewed. The 3.4 micron band flux is better correlated with the water production rate than with the dust production rate in this sample of comets. High feature-to-continuum ratios in P/Brorsen-Metcalf and Okazaki-Levy-Rudenko can be explained by the low dust-to-gas ratios of these two comets. The observations to date are consistent with cometary organics being present in all comets (even those for which no 3.4 micron feature was evident) at comparable abundances with respect to water. The emission mechanism and absolute abundance of the organics are not well determined; either gas-phase fluorescence or thermal emission from hot grains is consistent with the heliocentric distance dependence of the 3.4 micron band flux. There is an overall similarity in the spectral profiles of the 3.4 micron feature in comets; however, there are some potentially significant differences in the details of the spectra. 30 refs

Promise Zones for Applicants

Data.gov (United States)

Department of Housing and Urban Development — This tool assists applicants to HUD's Promise Zone initiative prepare data to submit with their application by allowing applicants to draw the exact location of the...

Considerations for Observational Research Using Large Data Sets in Radiation Oncology

Energy Technology Data Exchange (ETDEWEB)

Jagsi, Reshma, E-mail: rjagsi@med.umich.edu [Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan (United States); Bekelman, Justin E. [Departments of Radiation Oncology and Medical Ethics and Health Policy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania (United States); Chen, Aileen [Department of Radiation Oncology, Harvard Medical School, Boston, Massachusetts (United States); Chen, Ronald C. [Department of Radiation Oncology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina (United States); Hoffman, Karen [Department of Radiation Oncology, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Tina Shih, Ya-Chen [Department of Medicine, Section of Hospital Medicine, The University of Chicago, Chicago, Illinois (United States); Smith, Benjamin D. [Department of Radiation Oncology, Division of Radiation Oncology, and Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Yu, James B. [Yale School of Medicine, New Haven, Connecticut (United States)

2014-09-01

The radiation oncology community has witnessed growing interest in observational research conducted using large-scale data sources such as registries and claims-based data sets. With the growing emphasis on observational analyses in health care, the radiation oncology community must possess a sophisticated understanding of the methodological considerations of such studies in order to evaluate evidence appropriately to guide practice and policy. Because observational research has unique features that distinguish it from clinical trials and other forms of traditional radiation oncology research, the International Journal of Radiation Oncology, Biology, Physics assembled a panel of experts in health services research to provide a concise and well-referenced review, intended to be informative for the lay reader, as well as for scholars who wish to embark on such research without prior experience. This review begins by discussing the types of research questions relevant to radiation oncology that large-scale databases may help illuminate. It then describes major potential data sources for such endeavors, including information regarding access and insights regarding the strengths and limitations of each. Finally, it provides guidance regarding the analytical challenges that observational studies must confront, along with discussion of the techniques that have been developed to help minimize the impact of certain common analytical issues in observational analysis. Features characterizing a well-designed observational study include clearly defined research questions, careful selection of an appropriate data source, consultation with investigators with relevant methodological expertise, inclusion of sensitivity analyses, caution not to overinterpret small but significant differences, and recognition of limitations when trying to evaluate causality. This review concludes that carefully designed and executed studies using observational data that possess these qualities hold

Considerations for Observational Research Using Large Data Sets in Radiation Oncology

International Nuclear Information System (INIS)

Jagsi, Reshma; Bekelman, Justin E.; Chen, Aileen; Chen, Ronald C.; Hoffman, Karen; Tina Shih, Ya-Chen; Smith, Benjamin D.; Yu, James B.

2014-01-01

The radiation oncology community has witnessed growing interest in observational research conducted using large-scale data sources such as registries and claims-based data sets. With the growing emphasis on observational analyses in health care, the radiation oncology community must possess a sophisticated understanding of the methodological considerations of such studies in order to evaluate evidence appropriately to guide practice and policy. Because observational research has unique features that distinguish it from clinical trials and other forms of traditional radiation oncology research, the International Journal of Radiation Oncology, Biology, Physics assembled a panel of experts in health services research to provide a concise and well-referenced review, intended to be informative for the lay reader, as well as for scholars who wish to embark on such research without prior experience. This review begins by discussing the types of research questions relevant to radiation oncology that large-scale databases may help illuminate. It then describes major potential data sources for such endeavors, including information regarding access and insights regarding the strengths and limitations of each. Finally, it provides guidance regarding the analytical challenges that observational studies must confront, along with discussion of the techniques that have been developed to help minimize the impact of certain common analytical issues in observational analysis. Features characterizing a well-designed observational study include clearly defined research questions, careful selection of an appropriate data source, consultation with investigators with relevant methodological expertise, inclusion of sensitivity analyses, caution not to overinterpret small but significant differences, and recognition of limitations when trying to evaluate causality. This review concludes that carefully designed and executed studies using observational data that possess these qualities hold

A multi-approach feature extractions for iris recognition

Science.gov (United States)

Sanpachai, H.; Settapong, M.

2014-04-01

Biometrics is a promising technique that is used to identify individual traits and characteristics. Iris recognition is one of the most reliable biometric methods. As iris texture and color is fully developed within a year of birth, it remains unchanged throughout a person's life. Contrary to fingerprint, which can be altered due to several aspects including accidental damage, dry or oily skin and dust. Although iris recognition has been studied for more than a decade, there are limited commercial products available due to its arduous requirement such as camera resolution, hardware size, expensive equipment and computational complexity. However, at the present time, technology has overcome these obstacles. Iris recognition can be done through several sequential steps which include pre-processing, features extractions, post-processing, and matching stage. In this paper, we adopted the directional high-low pass filter for feature extraction. A box-counting fractal dimension and Iris code have been proposed as feature representations. Our approach has been tested on CASIA Iris Image database and the results are considered successful.

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

Science.gov (United States)

King, M. D.

2003-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

The path to fulfilling the promise

Energy Technology Data Exchange (ETDEWEB)

Barrett, J. [Canadian Nuclear Association, Ottawa, ON (Canada)

2014-07-01

'Full text:'Countries work together to develop effective governance and regulation. Canada has made big investments in these areas and it carries a premium for us. The rapid build-out of nuclear technology around the Pacific Rim holds vast promise for our populations in better climate, better air, affordable and reliable electricity, and longer lives. The biggest risk is not another accident: rather, it is the risk of failing to fulfill that promise to our people. Every country that wants the benefits of nuclear must also want to be sure that those benefits are realized and sustained by good governance and regulation. Canada has the people, laws, organizations, public institutions, and relationships that can help our partners fulfill the whole and lasting promise of nuclear technology. (author)

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

International Nuclear Information System (INIS)

Bringmann, Torsten; Calore, Francesca; Weniger, Christoph

2011-06-01

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

Using cell nuclei features to detect colon cancer tissue in hematoxylin and eosin stained slides.

Science.gov (United States)

Jørgensen, Alex Skovsbo; Rasmussen, Anders Munk; Andersen, Niels Kristian Mäkinen; Andersen, Simon Kragh; Emborg, Jonas; Røge, Rasmus; Østergaard, Lasse Riis

2017-08-01

Currently, diagnosis of colon cancer is based on manual examination of histopathological images by a pathologist. This can be time consuming and interpretation of the images is subject to inter- and intra-observer variability. This may be improved by introducing a computer-aided diagnosis (CAD) system for automatic detection of cancer tissue within whole slide hematoxylin and eosin (H&E) stains. Cancer disrupts the normal control mechanisms of cell proliferation and differentiation, affecting the structure and appearance of the cells. Therefore, extracting features from segmented cell nuclei structures may provide useful information to detect cancer tissue. A framework for automatic classification of regions of interest (ROI) containing either benign or cancerous colon tissue extracted from whole slide H&E stained images using cell nuclei features was proposed. A total of 1,596 ROI's were extracted from 87 whole slide H&E stains (44 benign and 43 cancer). A cell nuclei segmentation algorithm consisting of color deconvolution, k-means clustering, local adaptive thresholding, and cell separation was performed within the ROI's to extract cell nuclei features. From the segmented cell nuclei structures a total of 750 texture and intensity-based features were extracted for classification of the ROI's. The nine most discriminative cell nuclei features were used in a random forest classifier to determine if the ROI's contained benign or cancer tissue. The ROI classification obtained an area under the curve (AUC) of 0.96, sensitivity of 0.88, specificity of 0.92, and accuracy of 0.91 using an optimized threshold. The developed framework showed promising results in using cell nuclei features to classify ROIs into containing benign or cancer tissue in H&E stained tissue samples. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Tennessee Promise: A Response to Organizational Change

Science.gov (United States)

Littlepage, Ben; Clark, Teresa; Wilson, Randal; Stout, Logan

2018-01-01

Community colleges in Tennessee, either directly or indirectly, experienced unprecedented change as a result of Tennessee Promise. The present study explored how student support service administrators at three community colleges responded to organizational change as a result of the Tennessee Promise legislation. Investigators selected community…

Promising Cu-Ni-Cr-Si alloy for first wall ITER applications

International Nuclear Information System (INIS)

Ivanov, A.; Abramov, V.; Rodin, M.

1996-01-01

Precipitation-hardened Cu-Ni-Cr-Si alloy, a promising material for ITER applications, is considered. Available commercial products, chemical composition, physical and mechanical properties are presented. Embrittlement of Cu-Ni-Cr-Si alloy at 250-300 C is observed. Mechanical properties of Cu-Ni-Cr-Si alloy neutron irradiated to a dose of ∝0.2 dpa at 293 C are investigated. Embrittlement of Cu-Ni-Cr-Si alloy can be avoided by annealing. (orig.)

Hindi vowel classification using QCN-MFCC features

Directory of Open Access Journals (Sweden)

Shipra Mishra

2016-09-01

Full Text Available In presence of environmental noise, speakers tend to emphasize their vocal effort to improve the audibility of voice. This involuntary adjustment is known as Lombard effect (LE. Due to LE the signal to noise ratio of speech increases, but at the same time the loudness, pitch and duration of phonemes changes. Hence, accuracy of automatic speech recognition systems degrades. In this paper, the effect of unsupervised equalization of Lombard effect is investigated for Hindi vowel classification task using Hindi database designed at TIFR Mumbai, India. Proposed Quantile-based Dynamic Cepstral Normalization MFCC (QCN-MFCC along with baseline MFCC features have been used for vowel classification. Hidden Markov Model (HMM is used as classifier. It is observed that QCN-MFCC features have given a maximum improvement of 5.97% and 5% over MFCC features for context-dependent and context-independent cases respectively. It is also observed that QCN-MFCC features have given improvement of 13% and 11.5% over MFCC features for context-dependent and context-independent classification of mid vowels.

Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images

Directory of Open Access Journals (Sweden)

Sivaramakrishnan Rajaraman

2018-04-01

Full Text Available Malaria is a blood disease caused by the Plasmodium parasites transmitted through the bite of female Anopheles mosquito. Microscopists commonly examine thick and thin blood smears to diagnose disease and compute parasitemia. However, their accuracy depends on smear quality and expertise in classifying and counting parasitized and uninfected cells. Such an examination could be arduous for large-scale diagnoses resulting in poor quality. State-of-the-art image-analysis based computer-aided diagnosis (CADx methods using machine learning (ML techniques, applied to microscopic images of the smears using hand-engineered features demand expertise in analyzing morphological, textural, and positional variations of the region of interest (ROI. In contrast, Convolutional Neural Networks (CNN, a class of deep learning (DL models promise highly scalable and superior results with end-to-end feature extraction and classification. Automated malaria screening using DL techniques could, therefore, serve as an effective diagnostic aid. In this study, we evaluate the performance of pre-trained CNN based DL models as feature extractors toward classifying parasitized and uninfected cells to aid in improved disease screening. We experimentally determine the optimal model layers for feature extraction from the underlying data. Statistical validation of the results demonstrates the use of pre-trained CNNs as a promising tool for feature extraction for this purpose.

ALMA observing strategies

OpenAIRE

Biggs, Andy

2018-01-01

The ALMA Observing Tool (OT) is a Java-based tool used to prepare ALMA observations. In this talk, I highlight the particular features relevant to setting up single dish observations when these are needed to observe sources where the largest angular scale requires the addition of the total power antennas.

ALMA Observing Strategies

Science.gov (United States)

Biggs, Andy

2018-03-01

The ALMA Observing Tool (OT) is a Java-based tool used to prepare ALMA observations. In this talk, I highlight the particular features relevant to setting up single dish observations when these are needed to observe sources where the largest angular scale requires the addition of the total power antennas.

Mutual information based feature selection for medical image retrieval

Science.gov (United States)

Zhi, Lijia; Zhang, Shaomin; Li, Yan

2018-04-01

In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

Classification of Carotid Plaque Echogenicity by Combining Texture Features and Morphologic Characteristics.

Science.gov (United States)

Huang, Xiaowei; Zhang, Yanling; Qian, Ming; Meng, Long; Xiao, Yang; Niu, Lili; Zheng, Rongqin; Zheng, Hairong

2016-10-01

Anechoic carotid plaques on sonography have been used to predict future cardiovascular or cerebrovascular events. The purpose of this study was to investigate whether carotid plaque echogenicity could be assessed objectively by combining texture features extracted by MaZda software (Institute of Electronics, Technical University of Lodz, Lodz, Poland) and morphologic characteristics, which may provide a promising method for early prediction of acute cardiovascular disease. A total of 268 plaque images were collected from 136 volunteers and classified into 85 hyperechoic, 83 intermediate, and 100 anechoic plaques. About 300 texture features were extracted from histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model, and wavelet transform algorithms by MaZda. The morphologic characteristics, including degree of stenosis, maximum plaque intima-media thickness, and maximum plaque length, were measured by B-mode sonography. Statistically significant features were selected by analysis of covariance. The most discriminative features were obtained from statistically significant features by linear discriminant analysis. The K-nearest neighbor classifier was used to classify plaque echogenicity based on statistically significant and most discriminative features. A total of 30 statistically significant features were selected among the plaques, and 2 most discriminative features were obtained from the statistically significant features. The classification accuracy rates for 3 types of plaques based on statistically significant and most discriminative features were 72.03% (κ= 0.571; P MaZda and morphologic characteristics.

Understanding Legacy Features with Featureous

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2011-01-01

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

Promise-based management: the essence of execution.

Science.gov (United States)

Sull, Donald N; Spinosa, Charles

2007-04-01

Critical initiatives stall for a variety of reasons--employee disengagement, a lack of coordination between functions, complex organizational structures that obscure accountability, and so on. To overcome such obstacles, managers must fundamentally rethink how work gets done. Most of the challenges stem from broken or poorly crafted commitments. That's because every company is, at its heart, a dynamic network of promises made between employees and colleagues, customers, outsourcing partners, or other stakeholders. Executives can overcome many problems in the short-term and foster productive, reliable workforces for the long-term by practicing what the authors call "promise-based management," which involves cultivating and coordinating commitments in a systematic way. Good promises share five qualities: They are public, active, voluntary, explicit, and mission based. To develop and execute an effective promise, the "provider" and the "customer" in the deal should go through three phases of conversation. The first, achieving a meeting of minds, entails exploring the fundamental questions of coordinated effort: What do you mean? Do you understand what I mean? What should I do? What will you do? Who else should we talk to? In the next phase, making it happen, the provider executes on the promise. In the final phase, closing the loop, the customer publicly declares that the provider has either delivered the goods or failed to do so. Leaders must weave and manage their webs of promises with great care-encouraging iterative conversation and making sure commitments are fulfilled reliably. If they do, they can enhance coordination and cooperation among colleagues, build the organizational agility required to seize new business opportunities, and tap employees' entrepreneurial energies.

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

Science.gov (United States)

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

2018-02-01

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

Endoscopic ultrasound features of chronic pancreatitis

DEFF Research Database (Denmark)

Rana, Surinder Singh; Vilmann, Peter

2015-01-01

As endoscopic ultrasound (EUS) is the most sensitive imaging modality for diagnosing pancreatic disorders, it can demonstrate subtle alterations in the pancreatic parenchymal and ductal structure even before traditional imaging and functional testing demonstrate any abnormality. In spite...... of this fact and abundant literature, the exact role of EUS in the diagnosis of chronic pancreatitis (CP) is still not established. The EUS features to diagnose CP have evolved over a period from a pure qualitative approach to more advanced and complicated scoring systems incorporating multiple parenchymal...... to define the exact role of these criteria. The measurement of strain ratio using quantitative EUS elastography and thus allowing quantification of pancreatic fibrosis seems to be a promising new technique....

Fe/Co doped molybdenum diselenide: a promising two-dimensional intermediate-band photovoltaic material

International Nuclear Information System (INIS)

Zhang, Jiajia; He, Haiyan; Pan, Bicai

2015-01-01

An intermediate-band (IB) photovoltaic material is an important candidate in developing the new-generation solar cell. In this paper, we propose that the Fe-doped or the Co-doped MoSe 2 just meets the required features in IB photovoltaic materials. Our calculations demonstrate that when the concentration of the doped element reaches 11.11%, the doped MoSe 2 shows a high absorptivity for both infrared and visible light, where the photovoltaic efficiency of the doped MoSe 2 is as high as 56%, approaching the upper limit of photovoltaic efficiency of IB materials. So, the Fe- or Co-doped MoSe 2 is a promising two-dimensional photovoltaic material. (paper)

Clustering-based Feature Learning on Variable Stars

Science.gov (United States)

Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

2016-04-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

International Nuclear Information System (INIS)

Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

2016-01-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline

CLUSTERING-BASED FEATURE LEARNING ON VARIABLE STARS

Energy Technology Data Exchange (ETDEWEB)

Mackenzie, Cristóbal; Pichara, Karim [Computer Science Department, Pontificia Universidad Católica de Chile, Santiago (Chile); Protopapas, Pavlos [Institute for Applied Computational Science, Harvard University, Cambridge, MA (United States)

2016-04-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

Deep features for efficient multi-biometric recognition with face and ear images

Science.gov (United States)

Omara, Ibrahim; Xiao, Gang; Amrani, Moussa; Yan, Zifei; Zuo, Wangmeng

2017-07-01

Recently, multimodal biometric systems have received considerable research interest in many applications especially in the fields of security. Multimodal systems can increase the resistance to spoof attacks, provide more details and flexibility, and lead to better performance and lower error rate. In this paper, we present a multimodal biometric system based on face and ear, and propose how to exploit the extracted deep features from Convolutional Neural Networks (CNNs) on the face and ear images to introduce more powerful discriminative features and robust representation ability for them. First, the deep features for face and ear images are extracted based on VGG-M Net. Second, the extracted deep features are fused by using a traditional concatenation and a Discriminant Correlation Analysis (DCA) algorithm. Third, multiclass support vector machine is adopted for matching and classification. The experimental results show that the proposed multimodal system based on deep features is efficient and achieves a promising recognition rate up to 100 % by using face and ear. In addition, the results indicate that the fusion based on DCA is superior to traditional fusion.

Nongaussian Features from Inflationary Particle Production

International Nuclear Information System (INIS)

Barnaby, Neil

2010-01-01

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

Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments

Science.gov (United States)

Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Storrs, Katherine R.; Mur, Marieke

2017-01-01

Recent advances in Deep convolutional Neural Networks (DNNs) have enabled unprecedentedly accurate computational models of brain representations, and present an exciting opportunity to model diverse cognitive functions. State-of-the-art DNNs achieve human-level performance on object categorisation, but it is unclear how well they capture human behavior on complex cognitive tasks. Recent reports suggest that DNNs can explain significant variance in one such task, judging object similarity. Here, we extend these findings by replicating them for a rich set of object images, comparing performance across layers within two DNNs of different depths, and examining how the DNNs’ performance compares to that of non-computational “conceptual” models. Human observers performed similarity judgments for a set of 92 images of real-world objects. Representations of the same images were obtained in each of the layers of two DNNs of different depths (8-layer AlexNet and 16-layer VGG-16). To create conceptual models, other human observers generated visual-feature labels (e.g., “eye”) and category labels (e.g., “animal”) for the same image set. Feature labels were divided into parts, colors, textures and contours, while category labels were divided into subordinate, basic, and superordinate categories. We fitted models derived from the features, categories, and from each layer of each DNN to the similarity judgments, using representational similarity analysis to evaluate model performance. In both DNNs, similarity within the last layer explains most of the explainable variance in human similarity judgments. The last layer outperforms almost all feature-based models. Late and mid-level layers outperform some but not all feature-based models. Importantly, categorical models predict similarity judgments significantly better than any DNN layer. Our results provide further evidence for commonalities between DNNs and brain representations. Models derived from visual features

Promising new vaccine candidates against Campylobacter in broilers.

Directory of Open Access Journals (Sweden)

Marine Meunier

Full Text Available Campylobacter is the leading cause of human bacterial gastroenteritis in the European Union. Birds represent the main reservoir of the bacteria, and human campylobacteriosis mainly occurs after consuming and/or handling poultry meat. Reducing avian intestinal Campylobacter loads should impact the incidence of human diseases. At the primary production level, several measures have been identified to reach this goal, including vaccination of poultry. Despite many studies, however, no efficient vaccine is currently available. We have recently identified new vaccine candidates using the reverse vaccinology strategy. This study assessed the in vivo immune and protective potential of six newly-identified vaccine antigens. Among the candidates tested on Ross broiler chickens, four (YP_001000437.1, YP_001000562.1, YP_999817.1, and YP_999838.1 significantly reduced cecal Campylobacter loads by between 2 and 4.2 log10 CFU/g, with the concomitant development of a specific humoral immune response. In a second trial, cecal load reductions results were not statistically confirmed despite the induction of a strong immune response. These vaccine candidates need to be further investigated since they present promising features.

Young children mostly keep, and expect others to keep, their promises.

Science.gov (United States)

Kanngiesser, Patricia; Köymen, Bahar; Tomasello, Michael

2017-07-01

Promises are speech acts that create an obligation to do the promised action. In three studies, we investigated whether 3- and 5-year-olds (N=278) understand the normative implications of promising in prosocial interactions. In Study 1, children helped a partner who promised to share stickers. When the partner failed to uphold the promise, 3- and 5-year-olds protested and referred to promise norms. In Study 2, when children in this same age range were asked to promise to continue a cleaning task-and they agreed-they persisted longer on the task and mentioned their obligation more frequently than without such a promise. They also persisted longer after a promise than after a cleaning reminder (Study 3). In prosocial interactions, thus, young children feel a normative obligation to keep their promises and expect others to keep their promises as well. Copyright © 2017 Elsevier Inc. All rights reserved.

Feature Selection for Chemical Sensor Arrays Using Mutual Information

Science.gov (United States)

Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.

2014-01-01

We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058

Evaluation of EEG Features in Decoding Individual Finger Movements from One Hand

Directory of Open Access Journals (Sweden)

Ran Xiao

2013-01-01

Full Text Available With the advancements in modern signal processing techniques, the field of brain-computer interface (BCI is progressing fast towards noninvasiveness. One challenge still impeding these developments is the limited number of features, especially movement-related features, available to generate control signals for noninvasive BCIs. A few recent studies investigated several movement-related features, such as spectral features in electrocorticography (ECoG data obtained through a spectral principal component analysis (PCA and direct use of EEG temporal data, and demonstrated the decoding of individual fingers. The present paper evaluated multiple movement-related features under the same task, that is, discriminating individual fingers from one hand using noninvasive EEG. The present results demonstrate the existence of a broadband feature in EEG to discriminate individual fingers, which has only been identified previously in ECoG. It further shows that multiple spectral features obtained from the spectral PCA yield an average decoding accuracy of 45.2%, which is significantly higher than the guess level (P<0.05 and other features investigated (P<0.05, including EEG spectral power changes in alpha and beta bands and EEG temporal data. The decoding of individual fingers using noninvasive EEG is promising to improve number of features for control, which can facilitate the development of noninvasive BCI applications with rich complexity.

ON IRON MONOXIDE NANOPARTICLES AS A CARRIER OF THE MYSTERIOUS 21 μm EMISSION FEATURE IN POST-ASYMPTOTIC GIANT BRANCH STARS

International Nuclear Information System (INIS)

Li, Aigen; Jiang, B. W.; Liu, J. M.

2013-01-01

A prominent mysterious emission feature peaking at ∼20.1 μm—historically known as the '21 μm' feature—is seen in over two dozen Galactic and Magellanic Cloud carbon-rich, post-asymptotic giant branch (post-AGB) stars. The nature of its carrier remains unknown since the first detection of the 21 μm feature in 1989. Over a dozen materials have been suggested as possible carrier candidates. However, none of them has been accepted: they either require too much material (compared to what is available in the circumstellar shells around these post-AGB stars), or exhibit additional emission features that are not seen in these 21 μm sources. Recently, iron monoxide (FeO) nanoparticles seem to be a promising carrier candidate as Fe is an abundant element and FeO emits exclusively at ∼21 μm. In this work, using the proto-typical protoplanetary nebula HD 56126 as a test case, we examine FeO nanoparticles as a carrier for the 21 μm feature by modeling their infrared emission, with FeO being stochastically heated by single stellar photons. We find that FeO emits too broad a 21 μm feature to explain that observed and the Fe abundance required to be locked up in FeO exceeds what is available in HD 56126. We therefore conclude that FeO nanoparticles are not likely to be responsible for the 21 μm feature

Magnetic hydroxyapatite: a promising multifunctional platform for nanomedicine application

Science.gov (United States)

Mondal, Sudip; Manivasagan, Panchanathan; Bharathiraja, Subramaniyan; Santha Moorthy, Madhappan; Kim, Hye Hyun; Seo, Hansu; Lee, Kang Dae; Oh, Junghwan

2017-01-01

In this review, specific attention is paid to the development of nanostructured magnetic hydroxyapatite (MHAp) and its potential application in controlled drug/gene delivery, tissue engineering, magnetic hyperthermia treatment, and the development of contrast agents for magnetic resonance imaging. Both magnetite and hydroxyapatite materials have excellent prospects in nanomedicine with multifunctional therapeutic approaches. To date, many research articles have focused on biomedical applications of nanomaterials because of which it is very difficult to focus on any particular type of nanomaterial. This study is possibly the first effort to emphasize on the comprehensive assessment of MHAp nanostructures for biomedical applications supported with very recent experimental studies. From basic concepts to the real-life applications, the relevant characteristics of magnetic biomaterials are patented which are briefly discussed. The potential therapeutic and diagnostic ability of MHAp-nanostructured materials make them an ideal platform for future nanomedicine. We hope that this advanced review will provide a better understanding of MHAp and its important features to utilize it as a promising material for multifunctional biomedical applications. PMID:29200851

Nanocellulose: a promising nanomaterial for advanced electrochemical energy storage.

Science.gov (United States)

Chen, Wenshuai; Yu, Haipeng; Lee, Sang-Young; Wei, Tong; Li, Jian; Fan, Zhuangjun

2018-04-23

Nanocellulose has emerged as a sustainable and promising nanomaterial owing to its unique structures, superb properties, and natural abundance. Here, we present a comprehensive review of the current research activities that center on the development of nanocellulose for advanced electrochemical energy storage. We begin with a brief introduction of the structural features of cellulose nanofibers within the cell walls of cellulose resources. We then focus on a variety of processes that have been explored to fabricate nanocellulose with various structures and surface chemical properties. Next, we highlight a number of energy storage systems that utilize nanocellulose-derived materials, including supercapacitors, lithium-ion batteries, lithium-sulfur batteries, and sodium-ion batteries. In this section, the main focus is on the integration of nanocellulose with other active materials, developing films/aerogel as flexible substrates, and the pyrolyzation of nanocellulose to carbon materials and their functionalization by activation, heteroatom-doping, and hybridization with other active materials. Finally, we present our perspectives on several issues that need further exploration in this active research field in the future.

Magnetic hydroxyapatite: a promising multifunctional platform for nanomedicine application.

Science.gov (United States)

Mondal, Sudip; Manivasagan, Panchanathan; Bharathiraja, Subramaniyan; Santha Moorthy, Madhappan; Kim, Hye Hyun; Seo, Hansu; Lee, Kang Dae; Oh, Junghwan

2017-01-01

In this review, specific attention is paid to the development of nanostructured magnetic hydroxyapatite (MHAp) and its potential application in controlled drug/gene delivery, tissue engineering, magnetic hyperthermia treatment, and the development of contrast agents for magnetic resonance imaging. Both magnetite and hydroxyapatite materials have excellent prospects in nanomedicine with multifunctional therapeutic approaches. To date, many research articles have focused on biomedical applications of nanomaterials because of which it is very difficult to focus on any particular type of nanomaterial. This study is possibly the first effort to emphasize on the comprehensive assessment of MHAp nanostructures for biomedical applications supported with very recent experimental studies. From basic concepts to the real-life applications, the relevant characteristics of magnetic biomaterials are patented which are briefly discussed. The potential therapeutic and diagnostic ability of MHAp-nanostructured materials make them an ideal platform for future nanomedicine. We hope that this advanced review will provide a better understanding of MHAp and its important features to utilize it as a promising material for multifunctional biomedical applications.

Feature analysis for correlation studies of simultaneous EEG-fMRI data: A proof of concept for neurofeedback approaches.

Science.gov (United States)

Simoes, Simões; Lima, João; Direito, Bruno; Castelhano, João; Ferreira, Carlos; Carvalho, Paulo; Castelo-Branco, Miguel

2015-01-01

The identification and interpretation of facial expressions is an important feature of social cognition. This characteristic is often impaired in various neurodevelopmental disorders. Recent therapeutic approaches to intervene in social communication impairments include neurofeedback (NF). In this study, we present a NF real-time functional Magnetic Resonance Imaging (rt-fMRI), combined with electroencephalography (EEG) to train social communication skills. In this sense, we defined the right Superior Temporal Sulcus as our target region-of-interest. To analyze the correlation between the fMRI regions of interest and the EEG data, we transposed the sources located at the nearest cortical location to the target region. We extracted a set of 75 features from EEG segments and performed a correlation analysis with the brain activations extracted from rt-fMRI in the right pSTS region. The finding of significant correlations of simultaneously measured signals in distinct modalities (EEG and fMRI) is promising. Future studies should address whether the observed correlation levels between local brain activity and scalp measures are sufficient to implement NF approaches.

Promising Compilation to ARMv8 POP

OpenAIRE

Podkopaev, Anton; Lahav, Ori; Vafeiadis, Viktor

2017-01-01

We prove the correctness of compilation of relaxed memory accesses and release-acquire fences from the "promising" semantics of [Kang et al. POPL'17] to the ARMv8 POP machine of [Flur et al. POPL'16]. The proof is highly non-trivial because both the ARMv8 POP and the promising semantics provide some extremely weak consistency guarantees for normal memory accesses; however, they do so in rather different ways. Our proof of compilation correctness to ARMv8 POP strengthens the results of the Kan...

Comparing observer models and feature selection methods for a task-based statistical assessment of digital breast tomsynthesis in reconstruction space

Science.gov (United States)

Park, Subok; Zhang, George Z.; Zeng, Rongping; Myers, Kyle J.

2014-03-01

A task-based assessment of image quality1 for digital breast tomosynthesis (DBT) can be done in either the projected or reconstructed data space. As the choice of observer models and feature selection methods can vary depending on the type of task and data statistics, we previously investigated the performance of two channelized- Hotelling observer models in conjunction with 2D Laguerre-Gauss (LG) and two implementations of partial least squares (PLS) channels along with that of the Hotelling observer in binary detection tasks involving DBT projections.2, 3 The difference in these observers lies in how the spatial correlation in DBT angular projections is incorporated in the observer's strategy to perform the given task. In the current work, we extend our method to the reconstructed data space of DBT. We investigate how various model observers including the aforementioned compare for performing the binary detection of a spherical signal embedded in structured breast phantoms with the use of DBT slices reconstructed via filtered back projection. We explore how well the model observers incorporate the spatial correlation between different numbers of reconstructed DBT slices while varying the number of projections. For this, relatively small and large scan angles (24° and 96°) are used for comparison. Our results indicate that 1) given a particular scan angle, the number of projections needed to achieve the best performance for each observer is similar across all observer/channel combinations, i.e., Np = 25 for scan angle 96° and Np = 13 for scan angle 24°, and 2) given these sufficient numbers of projections, the number of slices for each observer to achieve the best performance differs depending on the channel/observer types, which is more pronounced in the narrow scan angle case.

HST PanCET Program: A Cloudy Atmosphere for the Promising JWST Target WASP-101b

Energy Technology Data Exchange (ETDEWEB)

Wakeford, H. R.; Mandell, A. [Planetary Systems Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Stevenson, K. B.; Lewis, N. K. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Sing, D. K.; Evans, T. [Astrophysics Group, Physics Building, University of Exeter, Stocker Road, Exeter EX4 4QL (United Kingdom); López-Morales, M. [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138 (United States); Marley, M. [NASA Ames Research Center, MS 245-5, Moffett Field, CA 94035 (United States); Kataria, T. [NASA Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Ballester, G. E. [Department of Planetary Sciences and Lunar and Planetary Laboratory, University of Arizona, 1541 E Univ. Boulevard, Tucson, AZ 85721 (United States); Barstow, J. [Physics and Astronomy, University College London, London (United Kingdom); Ben-Jaffel, L. [Institut d’Astrophysique de Paris, CNRS, UMR 7095 and Sorbonne Universités, UPMC Paris 6, 98 bis bd Arago, F-75014 Paris (France); Bourrier, V.; Ehrenreich, D. [Observatoire de l’Université de Genève, 51 chemin des Maillettes, CH-1290 Sauverny (Switzerland); Buchhave, L. A. [Centre for Star and Planet Formation, Niels Bohr Institute and Natural History Museum, University of Copenhagen, Øster Voldgade 5-7, DK-1350 Copenhagen K (Denmark); García Muñoz, A., E-mail: hannah.wakeford@nasa.gov [Zentrum für Astronomie und Astrophysik, Technische Universität Berlin, D-10623 Berlin (Germany); and others

2017-01-20

We present results from the first observations of the Hubble Space Telescope (HST) Panchromatic Comparative Exoplanet Treasury program for WASP-101b, a highly inflated hot Jupiter and one of the community targets proposed for the James Webb Space Telescope ( JWST ) Early Release Science (ERS) program. From a single HST Wide Field Camera 3 observation, we find that the near-infrared transmission spectrum of WASP-101b contains no significant H{sub 2}O absorption features and we rule out a clear atmosphere at 13 σ . Therefore, WASP-101b is not an optimum target for a JWST ERS program aimed at observing strong molecular transmission features. We compare WASP-101b to the well-studied and nearly identical hot Jupiter WASP-31b. These twin planets show similar temperature–pressure profiles and atmospheric features in the near-infrared. We suggest exoplanets in the same parameter space as WASP-101b and WASP-31b will also exhibit cloudy transmission spectral features. For future HST exoplanet studies, our analysis also suggests that a lower count limit needs to be exceeded per pixel on the detector in order to avoid unwanted instrumental systematics.

System for Detecting Vehicle Features from Low Quality Data

Directory of Open Access Journals (Sweden)

Marcin Dominik Bugdol

2018-02-01

Full Text Available The paper presents a system that recognizes the make, colour and type of the vehicle. The classification has been performed using low quality data from real-traffic measurement devices. For detecting vehicles’ specific features three methods have been developed. They employ several image and signal recognition techniques, e.g. Mamdani Fuzzy Inference System for colour recognition or Scale Invariant Features Transform for make identification. The obtained results are very promising, especially because only on-site equipment, not dedicated for such application, has been employed. In case of car type, the proposed system has better performance than commonly used inductive loops. Extensive information about the vehicle can be used in many fields of Intelligent Transport Systems, especially for traffic supervision.

Cloud field classification based on textural features

Science.gov (United States)

Sengupta, Sailes Kumar

1989-01-01

of features. Preliminary results based on the GLDV textural features alone look promising.

The Promise of a College Scholarship Transforms a District

Science.gov (United States)

Ritter, Gary W.; Ash, Jennifer

2016-01-01

Promise programs are place-based scholarships, generally tied to a city or school district, offering near-universal access to all living in the "place." While Promise programs share some characteristics with other scholarship programs, they're unique because they seek to change communities and schools. Underlying such promise programs is…

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

Science.gov (United States)

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

2017-04-01

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

Pulmonary nodule characterization, including computer analysis and quantitative features.

Science.gov (United States)

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

2015-03-01

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

Blue gum gaming machine: an evaluation of responsible gambling features.

Science.gov (United States)

Blaszczynski, Alexander; Gainsbury, Sally; Karlov, Lisa

2014-09-01

Structural characteristics of gaming machines contribute to persistence in play and excessive losses. The purpose of this study was to evaluate the effectiveness of five proposed responsible gaming features: responsible gaming messages; a bank meter quarantining winnings until termination of play; alarm clock facilitating setting time-reminders; demo mode allowing play without money; and a charity donation feature where residual amounts can be donated rather than played to zero credits. A series of ten modified gaming machines were located in five Australian gambling venues. The sample comprised 300 patrons attending the venue and who played the gaming machines. Participants completed a structured interview eliciting gambling and socio-demographic data and information on their perceptions and experience of play on the index machines. Results showed that one-quarter of participants considered that these features would contribute to preventing recreational gamblers from developing problems. Just under half of the participants rated these effects to be at least moderate or significant. The promising results suggest that further refinements to several of these features could represent a modest but effective approach to minimising excessive gambling on gaming machines.

Contact-free palm-vein recognition based on local invariant features.

Directory of Open Access Journals (Sweden)

Wenxiong Kang

Full Text Available Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs, respectively, which demonstrate the effectiveness of the proposed approach.

Contact-free palm-vein recognition based on local invariant features.

Science.gov (United States)

Kang, Wenxiong; Liu, Yang; Wu, Qiuxia; Yue, Xishun

2014-01-01

Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach.

Intra- and inter-observer reproducibility of global and regional magnetic resonance feature tracking derived strain parameters of the left and right ventricle

Energy Technology Data Exchange (ETDEWEB)

Schmidt, Björn, E-mail: bjoernschmidt1989@gmx.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Dick, Anastasia, E-mail: anastasia-dick@web.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Treutlein, Melanie, E-mail: melanie-treutlein@web.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Schiller, Petra, E-mail: petra.schiller@uni-koeln.de [Institute of Medical Statistics, Informatics and Epidemiology, University of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Bunck, Alexander C., E-mail: alexander.bunck@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Maintz, David, E-mail: david.maintz@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany); Baeßler, Bettina, E-mail: bettina.baessler@uk-koeln.de [Department of Radiology, University Hospital of Cologne, Kerpener Str. 62, D-50937, Cologne (Germany)

2017-04-15

Highlights: • Left and right ventricular CMR feature tracking is highly reproducible. • The only exception is radial strain and strain rate. • Sample size estimations are presented as a practical reference for future studies. - Abstract: Objectives: To investigate the reproducibility of regional and global strain and strain rate (SR) parameters of both ventricles and to determine sample sizes for all investigated strain and SR parameters in order to generate a practical reference for future studies. Materials and methods: The study population consisted of 20 healthy individuals and 20 patients with acute myocarditis. Cine sequences in three horizontal long axis views and a stack of short axis views covering the entire left and right ventricle (LV, RV) were retrospectively analysed using a dedicated feature tracking (FT) software algorithm (TOMTEC). For intra-observer analysis, one observer analysed CMR images of all patients and volunteers twice. For inter-observer analysis, three additional blinded observers analysed the same datasets once. Intra- and inter-observer reproducibility were tested in all patients and controls using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation. Results: Intra-observer reproducibility of global LV strain and SR parameters was excellent (range of ICCs: 0.81–1.00), the only exception being global radial SR with a poor reproducibility (ICC 0.23). On a regional level, basal and midventricular strain and SR parameters were more reproducible when compared to apical parameters. Inter-observer reproducibility of all LV parameters was slightly lower than intra-observer reproducibility, yet still good to excellent for all global and regional longitudinal and circumferential strain and SR parameters (range of ICCs: 0.66–0.93). Similar to the LV, all global RV longitudinal and circumferential strain and SR parameters showed an excellent reproducibility, (range of ICCs: 0.75–0

Intra- and inter-observer reproducibility of global and regional magnetic resonance feature tracking derived strain parameters of the left and right ventricle

International Nuclear Information System (INIS)

Schmidt, Björn; Dick, Anastasia; Treutlein, Melanie; Schiller, Petra; Bunck, Alexander C.; Maintz, David; Baeßler, Bettina

2017-01-01

Highlights: • Left and right ventricular CMR feature tracking is highly reproducible. • The only exception is radial strain and strain rate. • Sample size estimations are presented as a practical reference for future studies. - Abstract: Objectives: To investigate the reproducibility of regional and global strain and strain rate (SR) parameters of both ventricles and to determine sample sizes for all investigated strain and SR parameters in order to generate a practical reference for future studies. Materials and methods: The study population consisted of 20 healthy individuals and 20 patients with acute myocarditis. Cine sequences in three horizontal long axis views and a stack of short axis views covering the entire left and right ventricle (LV, RV) were retrospectively analysed using a dedicated feature tracking (FT) software algorithm (TOMTEC). For intra-observer analysis, one observer analysed CMR images of all patients and volunteers twice. For inter-observer analysis, three additional blinded observers analysed the same datasets once. Intra- and inter-observer reproducibility were tested in all patients and controls using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation. Results: Intra-observer reproducibility of global LV strain and SR parameters was excellent (range of ICCs: 0.81–1.00), the only exception being global radial SR with a poor reproducibility (ICC 0.23). On a regional level, basal and midventricular strain and SR parameters were more reproducible when compared to apical parameters. Inter-observer reproducibility of all LV parameters was slightly lower than intra-observer reproducibility, yet still good to excellent for all global and regional longitudinal and circumferential strain and SR parameters (range of ICCs: 0.66–0.93). Similar to the LV, all global RV longitudinal and circumferential strain and SR parameters showed an excellent reproducibility, (range of ICCs: 0.75–0

Small-scale features in the Earth's magnetic field observed by Magsat.

Science.gov (United States)

Cain, J.C.; Schmitz, D.R.; Muth, L.

1984-01-01

A spherical harmonic expansion to degree and order 29 is derived using a selected magnetically quiet sample of Magsat data. Global maps representing the contribution due to terms of the expansion above n = 13 at 400 km altitude are compared with previously published residual anomaly maps and shown to be similar, even in polar regions. An expansion with such a high degree and order displays all but the sharpest features seen by the satellite and gives a more consistent picture of the high-order field structure at a constant altitude than do component maps derived independently. -Authors

Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Internal attention to features in visual short-term memory guides object learning.

Science.gov (United States)

Fan, Judith E; Turk-Browne, Nicholas B

2013-11-01

Attending to objects in the world affects how we perceive and remember them. What are the consequences of attending to an object in mind? In particular, how does reporting the features of a recently seen object guide visual learning? In three experiments, observers were presented with abstract shapes in a particular color, orientation, and location. After viewing each object, observers were cued to report one feature from visual short-term memory (VSTM). In a subsequent test, observers were cued to report features of the same objects from visual long-term memory (VLTM). We tested whether reporting a feature from VSTM: (1) enhances VLTM for just that feature (practice-benefit hypothesis), (2) enhances VLTM for all features (object-based hypothesis), or (3) simultaneously enhances VLTM for that feature and suppresses VLTM for unreported features (feature-competition hypothesis). The results provided support for the feature-competition hypothesis, whereby the representation of an object in VLTM was biased towards features reported from VSTM and away from unreported features (Experiment 1). This bias could not be explained by the amount of sensory exposure or response learning (Experiment 2) and was amplified by the reporting of multiple features (Experiment 3). Taken together, these results suggest that selective internal attention induces competitive dynamics among features during visual learning, flexibly tuning object representations to align with prior mnemonic goals. Copyright © 2013 Elsevier B.V. All rights reserved.

Radial-Velocity Signatures of Magnetic Features on the Sun Observed as a Star

Science.gov (United States)

Palumbo, M. L., III; Haywood, R. D.; Saar, S. H.; Dupree, A. K.; Milbourne, T. W.

2017-12-01

In recent years, the search for Earth-mass planets using radial-velocity measurements has become increasingly limited by signals arising from stellar activity. Individual magnetic features induce localized changes in intensity and velocity, which combine to change the apparent radial velocity of the star. Therefore it is critical to identify an indicator of activity-driven radial-velocity variations on the timescale of stellar rotation periods. We use 617.3 nm photospheric filtergrams, magnetograms, and dopplergrams from SDO/HMI and 170.0 nm chromospheric filtergrams from AIA to identify magnetically-driven solar features and reconstruct the integrated solar radial velocity with six samples per day over the course of 2014. Breaking the solar image up into regions of umbrae, penumbrae, quiet Sun, network, and plages, we find a distinct variation in the center-to-limb intensity-weighted velocity for each region. In agreement with past studies, we find that the suppression of convective blueshift is dominated by plages and network, rather than dark photospheric features. In the future, this work will be highly useful for identifying indicators which correlate with rotationally modulated radial-velocity variations. This will allow us to break the activity barrier that currently precludes the precise characterization of exoplanet properties at the lowest masses. This work was supported by the NSF-REU solar physics program at SAO, grant number AGS-1560313. This work was performed in part under contract with the California Institute of Technology (Caltech)/Jet Propulsion Laboratory (JPL) funded by NASA through the Sagan Fellowship Program executed by the NASA Exoplanet Science Institute.

Standard of Care and Promising New Agents for Triple Negative Metastatic Breast Cancer

Directory of Open Access Journals (Sweden)

Patrizia Mancini

2014-10-01

Full Text Available Triple negative breast cancer (TNBC is a cluster of heterogeneous diseases, all of them sharing the lack of expression of estrogen and progesterone receptors and HER2 protein. They are characterized by different biological, molecular and clinical features, including a poor prognosis despite the increased sensitivity to the current cytotoxic therapies. Several studies have identified important molecular features which enable further subdivision of this type of tumor. We are drawing from genomics, transcription and translation analysis at different levels, to improve our knowledge of the molecular alterations along the pathways which are activated during carcinogenesis and tumor progression. How this information should be used for the rational selection of therapy is an ongoing challenge and the subject of numerous research studies in progress. Currently, the vascular endothelial growth factor (VEGF, poly (ADP-ribose polymerase (PARP, HSP90 and Aurora inhibitors are most used as targeting agents in metastatic setting clinical trials. In this paper we will review the current knowledge about the genetic subtypes of TNBC and their different responses to conventional therapeutic strategies, as well as to some new promising molecular target agents, aimed to achieve more tailored therapies.

Standard of Care and Promising New Agents for Triple Negative Metastatic Breast Cancer

Energy Technology Data Exchange (ETDEWEB)

Mancini, Patrizia, E-mail: patrizia.mancini@uniroma1.it [Department of Experimental Medicine, Sapienza University of Rome, Viale Regina Elena 324, Rome 00161 (Italy); Angeloni, Antonio [Department of Molecular Medicine, Sapienza University of Rome, Viale Regina Elena 324, Rome 00161 (Italy); Risi, Emanuela [Department of Radiology, Oncology and Human Pathology, Sapienza University of Rome, Viale Regina Elena 324, Rome 00161 (Italy); Orsi, Errico [Department of Surgical Science, Sapienza University of Rome, Viale Regina Elena 324, Rome 00161 (Italy); Mezi, Silvia [Department of Radiology, Oncology and Human Pathology, Sapienza University of Rome, Viale Regina Elena 324, Rome 00161 (Italy)

2014-10-24

Triple negative breast cancer (TNBC) is a cluster of heterogeneous diseases, all of them sharing the lack of expression of estrogen and progesterone receptors and HER2 protein. They are characterized by different biological, molecular and clinical features, including a poor prognosis despite the increased sensitivity to the current cytotoxic therapies. Several studies have identified important molecular features which enable further subdivision of this type of tumor. We are drawing from genomics, transcription and translation analysis at different levels, to improve our knowledge of the molecular alterations along the pathways which are activated during carcinogenesis and tumor progression. How this information should be used for the rational selection of therapy is an ongoing challenge and the subject of numerous research studies in progress. Currently, the vascular endothelial growth factor (VEGF), poly (ADP-ribose) polymerase (PARP), HSP90 and Aurora inhibitors are most used as targeting agents in metastatic setting clinical trials. In this paper we will review the current knowledge about the genetic subtypes of TNBC and their different responses to conventional therapeutic strategies, as well as to some new promising molecular target agents, aimed to achieve more tailored therapies.

Use of alarm features in referral of febrile children to the emergency department : an observational study

NARCIS (Netherlands)

van Ierland, Yvette; Elshout, Gijs; Moll, Henritte A.; Nijman, Ruud G.; Vergouwe, Yvonne; van der Lei, Johan; Berger, Marjolein Y.; Oostenbrink, Rianne

Background The diagnostic value of alarm features of serious infections in low prevalence settings is unclear. Aim To explore to what extent alarm features play a role in referral to the emergency department (ED) by GPs who face a febrile child during out-of-hours care. Design and setting

Object-based selection from spatially-invariant representations: evidence from a feature-report task.

Science.gov (United States)

Matsukura, Michi; Vecera, Shaun P

2011-02-01

Attention selects objects as well as locations. When attention selects an object's features, observers identify two features from a single object more accurately than two features from two different objects (object-based effect of attention; e.g., Duncan, Journal of Experimental Psychology: General, 113, 501-517, 1984). Several studies have demonstrated that object-based attention can operate at a late visual processing stage that is independent of objects' spatial information (Awh, Dhaliwal, Christensen, & Matsukura, Psychological Science, 12, 329-334, 2001; Matsukura & Vecera, Psychonomic Bulletin & Review, 16, 529-536, 2009; Vecera, Journal of Experimental Psychology: General, 126, 14-18, 1997; Vecera & Farah, Journal of Experimental Psychology: General, 123, 146-160, 1994). In the present study, we asked two questions regarding this late object-based selection mechanism. In Part I, we investigated how observers' foreknowledge of to-be-reported features allows attention to select objects, as opposed to individual features. Using a feature-report task, a significant object-based effect was observed when to-be-reported features were known in advance but not when this advance knowledge was absent. In Part II, we examined what drives attention to select objects rather than individual features in the absence of observers' foreknowledge of to-be-reported features. Results suggested that, when there was no opportunity for observers to direct their attention to objects that possess to-be-reported features at the time of stimulus presentation, these stimuli must retain strong perceptual cues to establish themselves as separate objects.

Neural Architecture for Feature Binding in Visual Working Memory.

Science.gov (United States)

Schneegans, Sebastian; Bays, Paul M

2017-04-05

Binding refers to the operation that groups different features together into objects. We propose a neural architecture for feature binding in visual working memory that employs populations of neurons with conjunction responses. We tested this model using cued recall tasks, in which subjects had to memorize object arrays composed of simple visual features (color, orientation, and location). After a brief delay, one feature of one item was given as a cue, and the observer had to report, on a continuous scale, one or two other features of the cued item. Binding failure in this task is associated with swap errors, in which observers report an item other than the one indicated by the cue. We observed that the probability of swapping two items strongly correlated with the items' similarity in the cue feature dimension, and found a strong correlation between swap errors occurring in spatial and nonspatial report. The neural model explains both swap errors and response variability as results of decoding noisy neural activity, and can account for the behavioral results in quantitative detail. We then used the model to compare alternative mechanisms for binding nonspatial features. We found the behavioral results fully consistent with a model in which nonspatial features are bound exclusively via their shared location, with no indication of direct binding between color and orientation. These results provide evidence for a special role of location in feature binding, and the model explains how this special role could be realized in the neural system. SIGNIFICANCE STATEMENT The problem of feature binding is of central importance in understanding the mechanisms of working memory. How do we remember not only that we saw a red and a round object, but that these features belong together to a single object rather than to different objects in our environment? Here we present evidence for a neural mechanism for feature binding in working memory, based on encoding of visual

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

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

Science.gov (United States)

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

2016-12-01

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

Origins of the 3.28 μm dust emission feature

International Nuclear Information System (INIS)

Gatley, I.

1984-01-01

Some practical problems encountered in making spectroscopic observations in the 3 - 4 μm wavelength range are discussed. Emphasis is placed on the interpretation of observations of the Galactic center, and their implications for the origins of the 3.28 μm dust emission feature. These observations suggest, in contrast to some previous analyses, that the carrier of the 3.28 μm feature may be a common, non-volatile component of interstellar grains. (author)

Robust classification of motor imagery EEG signals using statistical time–domain features

International Nuclear Information System (INIS)

Khorshidtalab, A; Salami, M J E; Hamedi, M

2013-01-01

The tradeoff between computational complexity and speed, in addition to growing demands for real-time BMI (brain–machine interface) systems, expose the necessity of applying methods with least possible complexity. Willison amplitude (WAMP) and slope sign change (SSC) are two promising time–domain features only if the right threshold value is defined for them. To overcome the drawback of going through trial and error for the determination of a suitable threshold value, modified WAMP and modified SSC are proposed in this paper. Besides, a comprehensive assessment of statistical time–domain features in which their effectiveness is evaluated with a support vector machine (SVM) is presented. To ensure the accuracy of the results obtained by the SVM, the performance of each feature is reassessed with supervised fuzzy C-means. The general assessment shows that every subject had at least one of his performances near or greater than 80%. The obtained results prove that for BMI applications, in which a few errors can be tolerated, these combinations of feature–classifier are suitable. Moreover, features that could perform satisfactorily were selected for feature combination. Combinations of the selected features are evaluated with the SVM, and they could significantly improve the results, in some cases, up to full accuracy. (paper)

Establishing an ISO 10001-based promise in inpatients care.

Science.gov (United States)

Khan, Mohammad Ashiqur Rahman; Karapetrovic, Stanislav

2015-01-01

The purpose of this paper is to explore ISO 10001:2007 in planning, designing and developing a customer satisfaction promise (CSP) intended for inpatients care. Through meetings and interviews with research participants, who included a program manager, unit managers and registered nurses, information about potential promises and their implementation was obtained and analyzed. A number of promises were drafted and one was finally selected to be developed as a CSP. Applying the standard required adaptation and novel interpretation. Additionally, ISO 10002:2004 (Clause 7) was used to design the feedback handling activities. A promise initially chosen for development turned out to be difficult to implement, experience that helped in selecting and developing the final promise. Research participants found the ISO 10001-based method useful and comprehensible. This paper presents a specific health care example of how to adapt a standard's guideline in establishing customer promises. The authors show how a promise can be used in alleviating an existing issue (i.e. communication between carers and patients). The learning can be beneficial in various health care settings. To the knowledge, this paper shows the first example of applying ISO 10001:2007 in a health care case. A few activities suggested by the standard are further detailed, and a new activity is introduced. The integrated use of ISO 10001:2007 and 10002:2004 is presented and how one can be "augmented" by the other is demonstrated.

A TALE OF THREE MYSTERIOUS SPECTRAL FEATURES IN CARBON-RICH EVOLVED STARS: THE 21 μm, 30 μm, AND “UNIDENTIFIED INFRARED” EMISSION FEATURES

Energy Technology Data Exchange (ETDEWEB)

Mishra, Ajay; Li, Aigen [Department of Physics and Astronomy, University of Missouri, Columbia, MO 65211 (United States); Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn [Department of Astronomy, Beijing Normal University, Beijing 100875 (China)

2015-03-20

The mysterious “21 μm” emission feature seen almost exclusively in the short-lived protoplanetary nebula (PPN) phase of stellar evolution remains unidentified since its discovery two decades ago. This feature is always accompanied by the equally mysterious, unidentified “30 μm” feature and the so-called “unidentified infrared” (UIR) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μm which are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. The 30 μm feature is commonly observed in all stages of stellar evolution from the asymptotic giant branch through PPN to the planetary nebula phase. We explore the interrelations among the mysterious 21, 30 μm, and UIR features of the 21 μm sources. We derive the fluxes emitted in the observed UIR, 21, and 30 μm features from published Infrared Space Observatory or Spitzer/IRS spectra. We find that none of these spectral features correlate with each other. This argues against a common carrier (e.g., thiourea) for both the 21 μm feature and the 30 μm feature. This also does not support large PAH clusters as a possible carrier for the 21 μm feature.

Stem cell therapy in spinal cord injury: Hollow promise or promising science?

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Aimee Goel

2016-01-01

Full Text Available Spinal cord injury (SCI remains one of the most physically, psychologically and socially debilitating conditions worldwide. While rehabilitation measures may help limit disability to some extent, there is no effective primary treatment yet available. The efficacy of stem cells as a primary therapeutic option in spinal cord injury is currently an area under much scrutiny and debate. Several laboratory and some primary clinical studies into the use of bone marrow mesenchymal stem cells or embryonic stem cell-derived oligodentrocyte precursor cells have shown some promising results in terms of remyelination and regeneration of damaged spinal nerve tracts. More recently,laboratory and early clinical experiments into the use of Olfactory Ensheathing Cells, a type of glial cell derived from olfactory bulb and mucosa have provided some phenomenal preliminary evidence as to their neuroregenerative and neural bridging capacity. This report compares and evaluates some current research into selected forms of embryonic and mesenchymal stem cell therapy as well as olfactory ensheathing cell therapy in SCI, and also highlights some legal and ethical issues surrounding their use. While early results shows promise, more rigorous large scaleclinical trials are needed to shed light on the safety, efficacy and long term viability of stem cell and cellular transplant techniques in SCI.

SOFIA OBSERVATIONS OF SN 2010jl: ANOTHER NON-DETECTION OF THE 9.7 μm SILICATE DUST FEATURE

International Nuclear Information System (INIS)

Williams, Brian J.; Fox, Ori D.

2015-01-01

We present photometric observations from the Stratospheric Observatory for Infrared Astronomy (SOFIA) at 11.1 μm of the Type IIn supernova (SN IIn) 2010jl. The SN is undetected by SOFIA, but the upper limits obtained, combined with new and archival detections from Spitzer at 3.6 and 4.5 μm, allow us to characterize the composition of the dust present. Dust in other SN IIn has been shown in previous works to reside in a circumstellar shell of material ejected by the progenitor system in the few millenia prior to explosion. Our model fits show that the dust in the system shows no evidence for the strong, ubiquitous 9.7 μm feature from silicate dust, suggesting the presence of carbonaceous grains. The observations are best fit with 0.01–0.05 M ⊙ of carbonaceous dust radiating at a temperature of ∼550–620 K. The dust composition may reveal clues concerning the nature of the progenitor system, which remains ambiguous for this subclass. Most of the single star progenitor systems proposed for SNe IIn, such as luminous blue variables, red supergiants, yellow hypergiants, and B[e] stars, all clearly show silicate dust in their pre-SN outflows. However, this post-SN result is consistent with the small sample of SNe IIn with mid-IR observations, none of which show signs of emission from silicate dust in their IR spectra

SOFIA OBSERVATIONS OF SN 2010jl: ANOTHER NON-DETECTION OF THE 9.7 μm SILICATE DUST FEATURE

Energy Technology Data Exchange (ETDEWEB)

Williams, Brian J. [CRESST and X-ray Astrophysics Laboratory, NASA/GSFC, Code 662, 8800 Greenbelt Road, Greenbelt, MD (United States); Fox, Ori D., E-mail: brian.j.williams@nasa.gov [Department of Astronomy, University of California, Berkeley, CA 94720-3411 (United States)

2015-07-20

We present photometric observations from the Stratospheric Observatory for Infrared Astronomy (SOFIA) at 11.1 μm of the Type IIn supernova (SN IIn) 2010jl. The SN is undetected by SOFIA, but the upper limits obtained, combined with new and archival detections from Spitzer at 3.6 and 4.5 μm, allow us to characterize the composition of the dust present. Dust in other SN IIn has been shown in previous works to reside in a circumstellar shell of material ejected by the progenitor system in the few millenia prior to explosion. Our model fits show that the dust in the system shows no evidence for the strong, ubiquitous 9.7 μm feature from silicate dust, suggesting the presence of carbonaceous grains. The observations are best fit with 0.01–0.05 M{sub ⊙} of carbonaceous dust radiating at a temperature of ∼550–620 K. The dust composition may reveal clues concerning the nature of the progenitor system, which remains ambiguous for this subclass. Most of the single star progenitor systems proposed for SNe IIn, such as luminous blue variables, red supergiants, yellow hypergiants, and B[e] stars, all clearly show silicate dust in their pre-SN outflows. However, this post-SN result is consistent with the small sample of SNe IIn with mid-IR observations, none of which show signs of emission from silicate dust in their IR spectra.

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

Science.gov (United States)

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

2015-07-08

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

Integrated Phoneme Subspace Method for Speech Feature Extraction

Directory of Open Access Journals (Sweden)

Park Hyunsin

2009-01-01

Full Text Available Speech feature extraction has been a key focus in robust speech recognition research. In this work, we discuss data-driven linear feature transformations applied to feature vectors in the logarithmic mel-frequency filter bank domain. Transformations are based on principal component analysis (PCA, independent component analysis (ICA, and linear discriminant analysis (LDA. Furthermore, this paper introduces a new feature extraction technique that collects the correlation information among phoneme subspaces and reconstructs feature space for representing phonemic information efficiently. The proposed speech feature vector is generated by projecting an observed vector onto an integrated phoneme subspace (IPS based on PCA or ICA. The performance of the new feature was evaluated for isolated word speech recognition. The proposed method provided higher recognition accuracy than conventional methods in clean and reverberant environments.

Kernel-based discriminant feature extraction using a representative dataset

Science.gov (United States)

Li, Honglin; Sancho Gomez, Jose-Luis; Ahalt, Stanley C.

2002-07-01

Discriminant Feature Extraction (DFE) is widely recognized as an important pre-processing step in classification applications. Most DFE algorithms are linear and thus can only explore the linear discriminant information among the different classes. Recently, there has been several promising attempts to develop nonlinear DFE algorithms, among which is Kernel-based Feature Extraction (KFE). The efficacy of KFE has been experimentally verified by both synthetic data and real problems. However, KFE has some known limitations. First, KFE does not work well for strongly overlapped data. Second, KFE employs all of the training set samples during the feature extraction phase, which can result in significant computation when applied to very large datasets. Finally, KFE can result in overfitting. In this paper, we propose a substantial improvement to KFE that overcomes the above limitations by using a representative dataset, which consists of critical points that are generated from data-editing techniques and centroid points that are determined by using the Frequency Sensitive Competitive Learning (FSCL) algorithm. Experiments show that this new KFE algorithm performs well on significantly overlapped datasets, and it also reduces computational complexity. Further, by controlling the number of centroids, the overfitting problem can be effectively alleviated.

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

Science.gov (United States)

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

2016-05-01

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

The behavior of the 3.28 μm dust feature in NGC 2024

International Nuclear Information System (INIS)

Brand, P.W.J.L.; Meadows, P.J.; Wolstencroft, R.D.

1984-01-01

Observations of the 3.28 μm unidentified dust emission feature and the hydrogen Brackett alpha line have been made at several spatial positions across the ionization front in the HII region NGC 2024. The hydrogen observations delineate the edge of the ionised region while the 3.3 μm feature is seen to be continuous across the front. The 3.4 μm feature is observed with a constant strength relative to the 3.28 μm feature of 0.3 +- 0.1. Since the 3.28 μm feature is seen outside the ionized region the dust has to be excited by non-ionizing ultra-violet photons from the exciting star in the HII region. (author)

Interplay of multiple synaptic plasticity features in filamentary memristive devices for neuromorphic computing

Science.gov (United States)

La Barbera, Selina; Vincent, Adrien F.; Vuillaume, Dominique; Querlioz, Damien; Alibart, Fabien

2016-12-01

Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.

Service Users perspectives in PROMISE and research.

Science.gov (United States)

Rae, Sarah

2017-09-01

Since its inception in 2013, PROMISE (PROactive Management of Integrated Services and Environments) has been supporting service users and staff at the Cambridgeshire and Peterborough NHS Foundation Trust (CPFT) on a journey to reduce reliance on force. The author's own personal experiences led to the founding of PROMISE and illustrates how individual experiences can influence a patient to lead change. Coproduction is actively embedded in PROMISE. Patients have been meaningfully involved because they are innovators and problem solvers who bring an alternative viewpoint by the very nature of their condition. A patient is more than just a person who needs to be 'fixed' they are individuals with untapped skills and added insight. There have been 2 separate Patient Advisory Groups (PAGs) since the project was first established. The first Patient Advisory Group was recruited to work with the PROMISE researchers on a study which used a participatory qualitative approach. Drawing on their lived experience and different perspectives the PAG was instrumental in shaping the qualitative study, including the research questions. Their active involvement helped to ensure that that the study was sensitively designed, methodologically robust and ethically sound. The 2 nd PAG was formed in 2016 to give the project an overall steer. Patients in this group contributed to the work on the 'No' Audit and reviewed several CPFT policies such as the Seclusion and Segregation policy which has impacted on frontline practice. They also made a significant contribution to the study design for a funding application that was submitted by the PROMISE team to the National Institute for Health Research (NIHR). Both PAGs were supported by funding from East of England Collaboration for Leadership in Applied Health Research and Care (CLAHRC EoE) and were influential in different ways. An evaluation of the 2 nd PAG which was conducted in June 2017 showed very high satisfaction levels. The free text

Flare Seismology from SDO Observations

Science.gov (United States)

Lindsey, Charles; Martinez Oliveros, Juan Carlos; Hudson, Hugh

2011-10-01

Some flares release intense seismic transients into the solar interior. These transients are the sole instance we know of in which the Sun's corona exerts a conspicuous influence on the solar interior through flares. The desire to understand this phenomenon has led to ambitious efforts to model the mechanisms by which energy stored in coronal magnetic fields drives acoustic waves that penetrate deep into the Sun's interior. These mechanisms potentially involve the hydrodynamic response of the chromosphere to thick-target heating by high-energy particles, radiative exchange in the chromosphere and photosphere, and Lorentz-force transients to account for acoustic energies estimated up to at 5X10^27 erg and momenta of order 6X10^19 dyne sec. An understanding of these components of flare mechanics promises more than a powerful diagnostic for local helioseismology. It could give us fundamental new insight into flare mechanics themselves. The key is appropriate observations to match the models. Helioseismic observations have identified the compact sources of transient seismic emission at the foot points of flares. The Solar Dynamics Observatory is now giving us high quality continuum-brightness and Doppler observations of acoustically active flares from HMI concurrent with high-resolution EUV observations from AIA. Supported by HXR observations from RHESSI and a broad variety of other observational resources, the SDO promises a leading role in flare research in solar cycle 24.

Automatic processing of unattended object features by functional connectivity

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Katja Martina Mayer

2013-05-01

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

Statistical Feature Recognition for Multidimensional Solar Imagery

Science.gov (United States)

Turmon, Michael; Jones, Harrison P.; Malanushenko, Olena V.; Pap, Judit M.

2010-04-01

A maximum a posteriori (MAP) technique is developed to identify solar features in cotemporal and cospatial images of line-of-sight magnetic flux, continuum intensity, and equivalent width observed with the NASA/National Solar Observatory (NSO) Spectromagnetograph (SPM). The technique facilitates human understanding of patterns in large data sets and enables systematic studies of feature characteristics for comparison with models and observations of long-term solar activity and variability. The method uses Bayes’ rule to compute the posterior probability of any feature segmentation of a trio of observed images from per-pixel, class-conditional probabilities derived from independently-segmented training images. Simulated annealing is used to find the most likely segmentation. New algorithms for computing class-conditional probabilities from three-dimensional Gaussian mixture models and interpolated histogram densities are described and compared. A new extension to the spatial smoothing in the Bayesian prior model is introduced, which can incorporate a spatial dependence such as center-to-limb variation. How the spatial scale of training segmentations affects the results is discussed, and a new method for statistical separation of quiet Sun and quiet network is presented.

Limits in feature-based attention to multiple colors.

Science.gov (United States)

Liu, Taosheng; Jigo, Michael

2017-11-01

Attention to a feature enhances the sensory representation of that feature. Although much has been learned about the properties of attentional modulation when attending to a single feature, the effectiveness of attending to multiple features is not well understood. We investigated this question in a series of experiments using a color-detection task while varying the number of attended colors in a cueing paradigm. Observers were shown either a single cue, two cues, or no cue (baseline) before detecting a coherent color target. We measured detection threshold by varying the coherence level of the target. Compared to the baseline condition, we found consistent facilitation of detection performance in the one-cue and two-cue conditions, but performance in the two-cue condition was lower than that in the one-cue condition. In the final experiment, we presented a 50% valid cue to emulate the situation in which observers were only able to attend a single color in the two-cue condition, and found equivalent detection thresholds with the standard two-cue condition. These results indicate a limit in attending to two colors and further imply that observers could effectively attend a single color at a time. Such a limit is likely due to an inability to maintain multiple active attentional templates for colors.

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.

The Promised Savior in Pre-Islamic Great Religions

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Mahin Arab

2014-08-01

Full Text Available Since the ancient times the belief in the rise of the Reformer has been a fundamental principle. Many of the holy prophets have announced the advent of new prophet. Moreover in the announcements and indications of predecessors there are always allusions to "the Last Promised" and "the Savior of Last Days" under such titles as "Kalki", "Fifth Buddha", "Soshyans", "Messiah", "The Son of Man" and so on and so forth. Of course there are different types of belief in the last reformer in religions. In one place the Savior is merely a social reformer while in another place he is only after the spiritual salvation of people and even sometimes he undertakes both tasks. On the other hand, the Last Promised is once nationalist and once seeks to save the whole world.    This essay seeks to assay the views of pre-Islamic great religions including Zoroastrianism, Judaism, Christianity, Hinduism and Buddhism as to the Promised Savior. This essay is an analytico-descriptive research which has based itself on the first hand works comprising the sacred scriptures of religions and proceeds through the typological analyses of idea of the Promised in religions.    Zoroastrianism: the idea of the Promised has been tied to the notion of Soshyant. Generally speaking, this notion alludes to a group of people who periodically emerge at the end of every millennium of the last three millennia of world's age so as to uproot evil and renew the world, the last one of these reformers is Soshyans. According to the aforementioned typology, Zoroastrian idea of Last Savior is among the Promised who saves the whole world. Moreover Zoroastrian Promised cannot be declared only a social savior as he is not wholly detached from people's spirituality too. From another point of view, Zoroastrian idea of the Promised represents a universal and not nationalist savior who is relatively a human and not divine entity who emerges in the last millennium of world's age.    Judaism: in the

The Promised Savior in Pre-Islamic Great Religions

Directory of Open Access Journals (Sweden)

Mahin Arab

2014-09-01

Full Text Available Since the ancient times the belief in the rise of the Reformer has been a fundamental principle. Many of the holy prophets have announced the advent of new prophet. Moreover in the announcements and indications of predecessors there are always allusions to "the Last Promised" and "the Savior of Last Days" under such titles as "Kalki", "Fifth Buddha", "Soshyans", "Messiah", "The Son of Man" and so on and so forth. Of course there are different types of belief in the last reformer in religions. In one place the Savior is merely a social reformer while in another place he is only after the spiritual salvation of people and even sometimes he undertakes both tasks. On the other hand, the Last Promised is once nationalist and once seeks to save the whole world.    This essay seeks to assay the views of pre-Islamic great religions including Zoroastrianism, Judaism, Christianity, Hinduism and Buddhism as to the Promised Savior. This essay is an analytico-descriptive research which has based itself on the first hand works comprising the sacred scriptures of religions and proceeds through the typological analyses of idea of the Promised in religions.    Zoroastrianism: the idea of the Promised has been tied to the notion of Soshyant. Generally speaking, this notion alludes to a group of people who periodically emerge at the end of every millennium of the last three millennia of world's age so as to uproot evil and renew the world, the last one of these reformers is Soshyans. According to the aforementioned typology, Zoroastrian idea of Last Savior is among the Promised who saves the whole world. Moreover Zoroastrian Promised cannot be declared only a social savior as he is not wholly detached from people's spirituality too. From another point of view, Zoroastrian idea of the Promised represents a universal and not nationalist savior who is relatively a human and not divine entity who emerges in the last millennium of world's age.    Judaism: in the

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

A Classification-oriented Method of Feature Image Generation for Vehicle-borne Laser Scanning Point Clouds

Directory of Open Access Journals (Sweden)

YANG Bisheng

2016-02-01

Full Text Available An efficient method of feature image generation of point clouds to automatically classify dense point clouds into different categories is proposed, such as terrain points, building points. The method first uses planar projection to sort points into different grids, then calculates the weights and feature values of grids according to the distribution of laser scanning points, and finally generates the feature image of point clouds. Thus, the proposed method adopts contour extraction and tracing means to extract the boundaries and point clouds of man-made objects (e.g. buildings and trees in 3D based on the image generated. Experiments show that the proposed method provides a promising solution for classifying and extracting man-made objects from vehicle-borne laser scanning point clouds.

Heralded noiseless amplification for single-photon entangled state with polarization feature

Science.gov (United States)

Wang, Dan-Dan; Jin, Yu-Yu; Qin, Sheng-Xian; Zu, Hao; Zhou, Lan; Zhong, Wei; Sheng, Yu-Bo

2018-03-01

Heralded noiseless amplification is a promising method to overcome the transmission photon loss in practical noisy quantum channel and can effectively lengthen the quantum communication distance. Single-photon entanglement is an important resource in current quantum communications. Here, we construct two single-photon-assisted heralded noiseless amplification protocols for the single-photon two-mode entangled state and single-photon three-mode W state, respectively, where the single-photon qubit has an arbitrary unknown polarization feature. After the amplification, the fidelity of the single-photon entangled state can be increased, while the polarization feature of the single-photon qubit can be well remained. Both the two protocols only require the linear optical elements, so that they can be realized under current experimental condition. Our protocols may be useful in current and future quantum information processing.

Features for detecting smoke in laparoscopic videos

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Jalal Nour Aldeen

2017-09-01

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

Observing the sun a pocket field guide

CERN Document Server

Jenkins, Jamey L

2013-01-01

A comprehensive solar observing guide for use at the telescope by amateur astronomers at all three levels: beginning, intermediate, and advanced. Users will find invaluable information for identifying features through photos, charts, diagrams in a logical, orderly fashion and then interpreting the observations. Because the Sun is a dynamic celestial body in constant flux, astronomers rarely know for certain what awaits them at the eyepiece. All features of the Sun are transient and sometimes rather fleeting. Given the number of features and the complex life cycles of some solar features, it can be a challenging hobby, and this guide provides all of the guidance necessary to inform observers about the sights and events unfolding before their eyes on the most active and powerful member of our Solar System.

Contextual Multi-armed Bandits under Feature Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nam, Jun Hyun [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Mo, Sangwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Shin, Jinwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of)

2017-03-03

We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined NLinRel, having O(T⁷/₈(log(dT)+K√d)) regret bound for T rounds, K actions, and d-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including NLinRel are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has O(T²/₃√log d)regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case, we also design a practical variant of NLinRel, coined Universal-NLinRel, for arbitrary feature distributions. It first runs NLinRel for finding the ‘true’ coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of Universal-NLinRel on both synthetic and real-world datasets.

Observations to information

Science.gov (United States)

Cox, S. J.

2013-12-01

Observations provide the fundamental constraint on natural science interpretations. Earth science observations originate in many contexts, including in-situ field observations and monitoring, various modes of remote sensing and geophysics, sampling for ex-situ (laboratory) analysis, as well as numerical modelling and simulation which also provide estimates of parameter values. Most investigations require a combination of these, often sourced from multiple initiatives and archives, so data discovery and re-organization can be a significant project burden. The Observations and Measurements (O&M) information model was developed to provide a common vocabulary that can be applied to all these cases, and thus provide a basis for cross-initiative and cross-domain interoperability. O&M was designed in the context of the standards for geographic information from OGC and ISO. It provides a complementary viewpoint to the well-known feature (object oriented) and coverage (property field) views, but prioritizes the property determination process. Nevertheless, use of O&M implies the existence of well defined feature types. In disciplines such as geology and ecosystem sciences the primary complexity is in their model of the world, for which the description of each item requires access to diverse observation sets. On the other hand, geophysics and earth observations work with simpler underlying information items, but in larger quantities over multiple spatio-temporal dimensions, acquired using complex sensor systems. Multiple transformations between the three viewpoints are involved in the data flows in most investigations, from collection through analysis to information and story. The O&M model classifies observations: - from a provider viewpoint: in terms of the sensor or procedure involved; - from a consumer viewpoint: in terms of the property being reported, and the feature with which it is associated. These concerns carry different weights in different applications

Ecoinformatics (Big Data) for Agricultural Entomology: Pitfalls, Progress, and Promise.

Science.gov (United States)

Rosenheim, Jay A; Gratton, Claudio

2017-01-31

Ecoinformatics, as defined in this review, is the use of preexisting data sets to address questions in ecology. We provide the first review of ecoinformatics methods in agricultural entomology. Ecoinformatics methods have been used to address the full range of questions studied by agricultural entomologists, enabled by the special opportunities associated with data sets, nearly all of which have been observational, that are larger and more diverse and that embrace larger spatial and temporal scales than most experimental studies do. We argue that ecoinformatics research methods and traditional, experimental research methods have strengths and weaknesses that are largely complementary. We address the important interpretational challenges associated with observational data sets, highlight common pitfalls, and propose some best practices for researchers using these methods. Ecoinformatics methods hold great promise as a vehicle for capitalizing on the explosion of data emanating from farmers, researchers, and the public, as novel sampling and sensing techniques are developed and digital data sharing becomes more widespread.

A Kinect based sign language recognition system using spatio-temporal features

Science.gov (United States)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

Financial Technology: The Promise of Blockchain

OpenAIRE

Demary, Markus; Demary, Vera

2017-01-01

Digitization affects all sectors of the economy. A new and possibly disruptive digital technology is the blockchain, a decentralized ledger, which seems to offer great promise for many financial and business applications.

Behind every innovative solution lies an obscure feature

Directory of Open Access Journals (Sweden)

Lee Spector (Fellow ISGEC

2012-06-01

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

An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem

Directory of Open Access Journals (Sweden)

Jing Bian

2016-01-01

Full Text Available In the era of big data, feature selection is an essential process in machine learning. Although the class imbalance problem has recently attracted a great deal of attention, little effort has been undertaken to develop feature selection techniques. In addition, most applications involving feature selection focus on classification accuracy but not cost, although costs are important. To cope with imbalance problems, we developed a cost-sensitive feature selection algorithm that adds the cost-based evaluation function of a filter feature selection using a chaos genetic algorithm, referred to as CSFSG. The evaluation function considers both feature-acquiring costs (test costs and misclassification costs in the field of network security, thereby weakening the influence of many instances from the majority of classes in large-scale datasets. The CSFSG algorithm reduces the total cost of feature selection and trades off both factors. The behavior of the CSFSG algorithm is tested on a large-scale dataset of network security, using two kinds of classifiers: C4.5 and k-nearest neighbor (KNN. The results of the experimental research show that the approach is efficient and able to effectively improve classification accuracy and to decrease classification time. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

Use of the discriminant Fourier-derived cepstrum with feature-level post-processing for surface electromyographic signal classification

International Nuclear Information System (INIS)

Chen, Xinpu; Zhu, Xiangyang; Zhang, Dingguo

2009-01-01

Myoelectrical pattern classification is a crucial part in multi-functional prosthesis control. This paper investigates a discriminant Fourier-derived cepstrum (DFC) and feature-level post-processing (FLPP) to discriminate hand and wrist motions using the surface electromyographic signal. The Fourier-derived cepstrum takes advantage of the Fourier magnitude or sub-band power energy of signals directly and provides flexible use of spectral information changing with different motions. Appropriate cepstral coefficients are selected by a proposed separability criterion to construct DFC features. For the post-processing, FLPP which combines features from several analysis windows is used to improve the feature performance further. In this work, two classifiers (a linear discriminant classifier and quadratic discriminant classifier) without hyper-parameter optimization are employed to simplify the training procedure and avoid the possible bias of feature evaluation. Experimental results of the 11-motion problem show that the proposed DFC feature outperforms traditional features such as time-domain statistics and autoregressive-derived cepstrum in terms of the classification accuracy, and it is a promising method for the multi-functionality and high-accuracy control of myoelectric prostheses

SSVEP recognition using common feature analysis in brain-computer interface.

Science.gov (United States)

Zhang, Yu; Zhou, Guoxu; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2015-04-15

Canonical correlation analysis (CCA) has been successfully applied to steady-state visual evoked potential (SSVEP) recognition for brain-computer interface (BCI) application. Although the CCA method outperforms the traditional power spectral density analysis through multi-channel detection, it requires additionally pre-constructed reference signals of sine-cosine waves. It is likely to encounter overfitting in using a short time window since the reference signals include no features from training data. We consider that a group of electroencephalogram (EEG) data trials recorded at a certain stimulus frequency on a same subject should share some common features that may bear the real SSVEP characteristics. This study therefore proposes a common feature analysis (CFA)-based method to exploit the latent common features as natural reference signals in using correlation analysis for SSVEP recognition. Good performance of the CFA method for SSVEP recognition is validated with EEG data recorded from ten healthy subjects, in contrast to CCA and a multiway extension of CCA (MCCA). Experimental results indicate that the CFA method significantly outperformed the CCA and the MCCA methods for SSVEP recognition in using a short time window (i.e., less than 1s). The superiority of the proposed CFA method suggests it is promising for the development of a real-time SSVEP-based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

Immunotherapy and immunochemotherapy in visceral leishmaniasis: promising treatments for this neglected disease

Directory of Open Access Journals (Sweden)

Bruno Mendes Roatt

2014-06-01

Full Text Available Leishmaniasis has several clinical forms: self-healing or chronic cutaneous leishmaniasis or post-kala-azar dermal leishmaniasis; mucosal leishmaniasis; and visceral leishmaniasis, which is fatal if left untreated. The epidemiology and clinical features of VL vary greatly due to the interaction of multiple factors including parasite strains, vectors, host genetics, and the environment. HIV infection, augments the severity of VL increasing the risk of developing active disease by 100 to 2320 times. An effective vaccine for humans is not yet available. Resistance to chemotherapy is a growing problem in many regions, and the costs associated with drug identification and development, make commercial production for leishmaniasis, unattractive. The toxicity of currently drugs, their long treatment course, and limited efficacy are significant concerns. For cutaneous disease, many studies have shown promising results with immunotherapy/immunochemotherapy, aimed to modulate and activate the immune response to obtain a therapeutic cure. Nowadays, the focus of many groups centers on treating canine VL by using vaccines and immunomodulators with or without chemotherapy. In human disease, the use of cytokines like Interferon-γ associated with pentavalent antimonials demonstrated promising results in patients that did not respond to conventional treatment. In mice, immunomodulation based on monoclonal antibodies to remove endogenous immunosuppressive cytokines (interleukin-10 or block their receptors, antigen-pulsed syngeneic dendritic cells, or biological products like Pam3Cys (TLR ligand has already been shown as a prospective treatment of the disease. This review addresses VL treatment, particularly immunotherapy and/or immunochemotherapy as an alternative to conventional drug treatment in experimental models, canine VL, and human disease.

Prediction of Protein Structural Class Based on Gapped-Dipeptides and a Recursive Feature Selection Approach

Directory of Open Access Journals (Sweden)

Taigang Liu

2015-12-01

Full Text Available The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to address this problem, it is still a challenging topic in the field of bioinformatics. The position-specific score matrix (PSSM profile has been shown to provide a useful source of information for improving the prediction performance of protein structural class. However, this information has not been adequately explored. To this end, in this study, we present a feature extraction technique which is based on gapped-dipeptides composition computed directly from PSSM. Then, a careful feature selection technique is performed based on support vector machine-recursive feature elimination (SVM-RFE. These optimal features are selected to construct a final predictor. The results of jackknife tests on four working datasets show that our method obtains satisfactory prediction accuracies by extracting features solely based on PSSM and could serve as a very promising tool to predict protein structural class.

Reliability of radiographic observations recorded on a proforma measured using inter- and intra-observer variation: a preliminary study.

Science.gov (United States)

Saunders, M B; Gulabivala, K; Holt, R; Kahan, R S

2000-05-01

The aim of this preliminary study was to test the reliability of radiographic evaluation of features of endodontic interest using a newly devised data collection system. Twelve endodontic MSc postgraduate students and one specialist endodontist examined sample radiographs derived from a random selection of 42 patients seen previously on an Endodontic New Patient Clinic (EDI). Each student examined a random selection of 8-9 roots on periapical radiographs of single- and multirooted teeth, with and without previous root canal therapy and 3-4 dental panoramic tomograms (DPTs). A total of 100 roots were examined. A proforma was used to record observations on 67 radiographic features using predefined criteria. Intra-observer agreement was tested by asking the students to re-examine the radiographs. The principle investigator and the specialist endodontist examined the same radiographs and devised a Gold Standard using the same criteria. This was compared with the student assessments to determine inter-observer variation. The postgraduates then attended a revision session on the use of the form. Each student subsequently examined 8-9 different roots from the pool of radiographs. A further assessment of inter-observer variation was made by comparing these observations with the Gold Standard. Of the 67 radiographic features, only 25 had sufficient response to allow statistical analysis. Kappa values for intra- and inter-observer variation were estimated. These varied depending on the particular radiographic feature being assessed. Fifteen out of 25 intra-observer recordings showed 'good' or 'very good' Kappa agreement, but only three out of 25 inter-observer observations achieved 'good' or 'very good' values. Inter-observer variation was improved following the revision session with 16 out of 25 observations achieving 'good' or 'very good' Kappa agreement. Modification to the proforma, the criteria used, and training for radiographic assessment were considered necessary to

New infrared telescopic observation of Vesta

Science.gov (United States)

Palomba, E.; D'Aversa, E.; Sato, T.; Longobardo, A.; Aoki, S.; Sindoni, G.; Oliva, F.

2017-09-01

In this work we present new telescopic observations of the Vesta asteroid made at the Subaru Telescope by using the COMICS IR spectrometer. We were able to obtain 5 different observations in 5 day, at two different epochs. The obtained spectra do not exhibit Reststrahlen bands and show only weak features attributable to the Christiansen peak and to the transparency feature compatible with a fine grain size regolith.

The pragmatics of NPP presidential campaign promises in Ghana's ...

African Journals Online (AJOL)

The paper discusses election campaign promises under Commissives, an aspect of Speech Act Theory, and Political Discourse Analysis (PDA). It considers the importance of context and looks at the social settings that are connected with promises. It examines the semantics, pragmatics and the structure of campaign ...

Some Specific Features of the Object of Prosecutorial Supervision over the Observance of Constitutional Rights of the Individual to Work

Directory of Open Access Journals (Sweden)

Daniil S. Tishkov

2017-08-01

Full Text Available The article defines the place of supervision functions within the system of the functions of prosecution bodies of the Russian Federation as one of the priority sectors of prosecutorial supervision. The legal regulation of prosecutorial supervision of the rights and freedoms of Russian Federation citizens is examined. The Author reveals the specific features of the subject of prosecutorial supervision in compliance with the constitutional rights of the individual to work based on the results of the current legislation system analysis. The assumption of the need for changes to the Prosecutor General of the Russian Federation organizational and administrative documents in order to increase the efficiency of prosecutorial supervision over the observance of individual’s constitutional rights to work is expressed.

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.

A novel feature ranking algorithm for biometric recognition with PPG signals.

Science.gov (United States)

Reşit Kavsaoğlu, A; Polat, Kemal; Recep Bozkurt, M

2014-06-01

This study is intended for describing the application of the Photoplethysmography (PPG) signal and the time domain features acquired from its first and second derivatives for biometric identification. For this purpose, a sum of 40 features has been extracted and a feature-ranking algorithm is proposed. This proposed algorithm calculates the contribution of each feature to biometric recognition and collocates the features, the contribution of which is from great to small. While identifying the contribution of the features, the Euclidean distance and absolute distance formulas are used. The efficiency of the proposed algorithms is demonstrated by the results of the k-NN (k-nearest neighbor) classifier applications of the features. During application, each 15-period-PPG signal belonging to two different durations from each of the thirty healthy subjects were used with a PPG data acquisition card. The first PPG signals recorded from the subjects were evaluated as the 1st configuration; the PPG signals recorded later at a different time as the 2nd configuration and the combination of both were evaluated as the 3rd configuration. When the results were evaluated for the k-NN classifier model created along with the proposed algorithm, an identification of 90.44% for the 1st configuration, 94.44% for the 2nd configuration, and 87.22% for the 3rd configuration has successfully been attained. The obtained results showed that both the proposed algorithm and the biometric identification model based on this developed PPG signal are very promising for contactless recognizing the people with the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modulation of neuronal responses during covert search for visual feature conjunctions.

Science.gov (United States)

Buracas, Giedrius T; Albright, Thomas D

2009-09-29

While searching for an object in a visual scene, an observer's attentional focus and eye movements are often guided by information about object features and spatial locations. Both spatial and feature-specific attention are known to modulate neuronal responses in visual cortex, but little is known of the dynamics and interplay of these mechanisms as visual search progresses. To address this issue, we recorded from directionally selective cells in visual area MT of monkeys trained to covertly search for targets defined by a unique conjunction of color and motion features and to signal target detection with an eye movement to the putative target. Two patterns of response modulation were observed. One pattern consisted of enhanced responses to targets presented in the receptive field (RF). These modulations occurred at the end-stage of search and were more potent during correct target identification than during erroneous saccades to a distractor in RF, thus suggesting that this modulation is not a mere presaccadic enhancement. A second pattern of modulation was observed when RF stimuli were nontargets that shared a feature with the target. The latter effect was observed during early stages of search and is consistent with a global feature-specific mechanism. This effect often terminated before target identification, thus suggesting that it interacts with spatial attention. This modulation was exhibited not only for motion but also for color cue, although MT neurons are known to be insensitive to color. Such cue-invariant attentional effects may contribute to a feature binding mechanism acting across visual dimensions.

Candida Biofilms: Threats, Challenges, and Promising Strategies

Directory of Open Access Journals (Sweden)

Mafalda Cavalheiro

2018-02-01

Full Text Available Candida species are fungal pathogens known for their ability to cause superficial and systemic infections in the human host. These pathogens are able to persist inside the host due to the development of pathogenicity and multidrug resistance traits, often leading to the failure of therapeutic strategies. One specific feature of Candida species pathogenicity is their ability to form biofilms, which protects them from external factors such as host immune system defenses and antifungal drugs. This review focuses on the current threats and challenges when dealing with biofilms formed by Candida albicans, Candida glabrata, Candida tropicalis, and Candida parapsilosis, highlighting the differences between the four species. Biofilm characteristics depend on the ability of each species to produce extracellular polymeric substances (EPS and display dimorphic growth, but also on the biofilm substratum, carbon source availability and other factors. Additionally, the transcriptional control over processes like adhesion, biofilm formation, filamentation, and EPS production displays great complexity and diversity within pathogenic yeasts of the Candida genus. These differences not only have implications in the persistence of colonization and infections but also on antifungal resistance typically found in Candida biofilm cells, potentiated by EPS, that functions as a barrier to drug diffusion, and by the overexpression of drug resistance transporters. The ability to interact with different species in in vivo Candida biofilms is also a key factor to consider when dealing with this problem. Despite many challenges, the most promising strategies that are currently available or under development to limit biofilm formation or to eradicate mature biofilms are discussed.

Candida Biofilms: Threats, Challenges, and Promising Strategies.

Science.gov (United States)

Cavalheiro, Mafalda; Teixeira, Miguel Cacho

2018-01-01

Candida species are fungal pathogens known for their ability to cause superficial and systemic infections in the human host. These pathogens are able to persist inside the host due to the development of pathogenicity and multidrug resistance traits, often leading to the failure of therapeutic strategies. One specific feature of Candida species pathogenicity is their ability to form biofilms, which protects them from external factors such as host immune system defenses and antifungal drugs. This review focuses on the current threats and challenges when dealing with biofilms formed by Candida albicans, Candida glabrata, Candida tropicalis , and Candida parapsilosis , highlighting the differences between the four species. Biofilm characteristics depend on the ability of each species to produce extracellular polymeric substances (EPS) and display dimorphic growth, but also on the biofilm substratum, carbon source availability and other factors. Additionally, the transcriptional control over processes like adhesion, biofilm formation, filamentation, and EPS production displays great complexity and diversity within pathogenic yeasts of the Candida genus. These differences not only have implications in the persistence of colonization and infections but also on antifungal resistance typically found in Candida biofilm cells, potentiated by EPS, that functions as a barrier to drug diffusion, and by the overexpression of drug resistance transporters. The ability to interact with different species in in vivo Candida biofilms is also a key factor to consider when dealing with this problem. Despite many challenges, the most promising strategies that are currently available or under development to limit biofilm formation or to eradicate mature biofilms are discussed.

Candida Biofilms: Threats, Challenges, and Promising Strategies

Science.gov (United States)

Cavalheiro, Mafalda; Teixeira, Miguel Cacho

2018-01-01

Candida species are fungal pathogens known for their ability to cause superficial and systemic infections in the human host. These pathogens are able to persist inside the host due to the development of pathogenicity and multidrug resistance traits, often leading to the failure of therapeutic strategies. One specific feature of Candida species pathogenicity is their ability to form biofilms, which protects them from external factors such as host immune system defenses and antifungal drugs. This review focuses on the current threats and challenges when dealing with biofilms formed by Candida albicans, Candida glabrata, Candida tropicalis, and Candida parapsilosis, highlighting the differences between the four species. Biofilm characteristics depend on the ability of each species to produce extracellular polymeric substances (EPS) and display dimorphic growth, but also on the biofilm substratum, carbon source availability and other factors. Additionally, the transcriptional control over processes like adhesion, biofilm formation, filamentation, and EPS production displays great complexity and diversity within pathogenic yeasts of the Candida genus. These differences not only have implications in the persistence of colonization and infections but also on antifungal resistance typically found in Candida biofilm cells, potentiated by EPS, that functions as a barrier to drug diffusion, and by the overexpression of drug resistance transporters. The ability to interact with different species in in vivo Candida biofilms is also a key factor to consider when dealing with this problem. Despite many challenges, the most promising strategies that are currently available or under development to limit biofilm formation or to eradicate mature biofilms are discussed. PMID:29487851

Feature-aware natural texture synthesis

KAUST Repository

Wu, Fuzhang

2014-12-04

This article presents a framework for natural texture synthesis and processing. This framework is motivated by the observation that given examples captured in natural scene, texture synthesis addresses a critical problem, namely, that synthesis quality can be affected adversely if the texture elements in an example display spatially varied patterns, such as perspective distortion, the composition of different sub-textures, and variations in global color pattern as a result of complex illumination. This issue is common in natural textures and is a fundamental challenge for previously developed methods. Thus, we address it from a feature point of view and propose a feature-aware approach to synthesize natural textures. The synthesis process is guided by a feature map that represents the visual characteristics of the input texture. Moreover, we present a novel adaptive initialization algorithm that can effectively avoid the repeat and verbatim copying artifacts. Our approach improves texture synthesis in many images that cannot be handled effectively with traditional technologies.

The semiology of febrile seizures: Focal features are frequent.

Science.gov (United States)

Takasu, Michihiko; Kubota, Tetsuo; Tsuji, Takeshi; Kurahashi, Hirokazu; Numoto, Shingo; Watanabe, Kazuyoshi; Okumura, Akihisa

2017-08-01

To clarify the semiology of febrile seizures (FS) and to determine the frequency of FS with symptoms suggestive of focal onset. FS symptoms in children were reported within 24h of seizure onset by the parents using a structured questionnaire consisting principally of closed-ended questions. We focused on events at seizure commencement, including changes in behavior and facial expression, and ocular and oral symptoms. We also investigated the autonomic and motor symptoms developing during seizures. The presence or absence of focal and limbic features was determined for each patient. The associations of certain focal and limbic features with patient characteristics were assessed. Information was obtained on FS in 106 children. Various events were recorded at seizure commencement. Behavioral changes were observed in 35 children, changes in facial expression in 53, ocular symptoms in 78, and oral symptoms in 90. In terms of events during seizures, autonomic symptoms were recognized in 78, and convulsive motor symptoms were recognized in 68 children. Focal features were evident in 81 children; 38 children had two or more such features. Limbic features were observed in 44 children, 9 of whom had two or more such features. There was no significant relationship between any patient characteristic and the numbers of focal or limbic features. The semiology of FS varied widely among children, and symptoms suggestive of focal onset were frequent. FS of focal onset may be more common than is generally thought. Copyright © 2017 Elsevier Inc. All rights reserved.

Edge Detection and Feature Line Tracing in 3D-Point Clouds by Analyzing Geometric Properties of Neighborhoods

Directory of Open Access Journals (Sweden)

Huan Ni

2016-09-01

Full Text Available This paper presents an automated and effective method for detecting 3D edges and tracing feature lines from 3D-point clouds. This method is named Analysis of Geometric Properties of Neighborhoods (AGPN, and it includes two main steps: edge detection and feature line tracing. In the edge detection step, AGPN analyzes geometric properties of each query point’s neighborhood, and then combines RANdom SAmple Consensus (RANSAC and angular gap metric to detect edges. In the feature line tracing step, feature lines are traced by a hybrid method based on region growing and model fitting in the detected edges. Our approach is experimentally validated on complex man-made objects and large-scale urban scenes with millions of points. Comparative studies with state-of-the-art methods demonstrate that our method obtains a promising, reliable, and high performance in detecting edges and tracing feature lines in 3D-point clouds. Moreover, AGPN is insensitive to the point density of the input data.

Nanoparticles for cancer imaging: The good, the bad, and the promise

Science.gov (United States)

Chapman, Sandra; Dobrovolskaia, Marina; Farahani, Keyvan; Goodwin, Andrew; Joshi, Amit; Lee, Hakho; Meade, Thomas; Pomper, Martin; Ptak, Krzysztof; Rao, Jianghong; Singh, Ravi; Sridhar, Srinivas; Stern, Stephan; Wang, Andrew; Weaver, John B.; Woloschak, Gayle; Yang, Lily

2014-01-01

Summary Recent advances in molecular imaging and nanotechnology are providing new opportunities for biomedical imaging with great promise for the development of novel imaging agents. The unique optical, magnetic, and chemical properties of materials at the scale of nanometers allow the creation of imaging probes with better contrast enhancement, increased sensitivity, controlled biodistribution, better spatial and temporal information, multi-functionality and multi-modal imaging across MRI, PET, SPECT, and ultrasound. These features could ultimately translate to clinical advantages such as earlier detection, real time assessment of disease progression and personalized medicine. However, several years of investigation into the application of these materials to cancer research has revealed challenges that have delayed the successful application of these agents to the field of biomedical imaging. Understanding these challenges is critical to take full advantage of the benefits offered by nano-sized imaging agents. Therefore, this article presents the lessons learned and challenges encountered by a group of leading researchers in this field, and suggests ways forward to develop nanoparticle probes for cancer imaging. Published by Elsevier Ltd. PMID:25419228

Heuristic algorithms for feature selection under Bayesian models with block-diagonal covariance structure.

Science.gov (United States)

Foroughi Pour, Ali; Dalton, Lori A

2018-03-21

Many bioinformatics studies aim to identify markers, or features, that can be used to discriminate between distinct groups. In problems where strong individual markers are not available, or where interactions between gene products are of primary interest, it may be necessary to consider combinations of features as a marker family. To this end, recent work proposes a hierarchical Bayesian framework for feature selection that places a prior on the set of features we wish to select and on the label-conditioned feature distribution. While an analytical posterior under Gaussian models with block covariance structures is available, the optimal feature selection algorithm for this model remains intractable since it requires evaluating the posterior over the space of all possible covariance block structures and feature-block assignments. To address this computational barrier, in prior work we proposed a simple suboptimal algorithm, 2MNC-Robust, with robust performance across the space of block structures. Here, we present three new heuristic feature selection algorithms. The proposed algorithms outperform 2MNC-Robust and many other popular feature selection algorithms on synthetic data. In addition, enrichment analysis on real breast cancer, colon cancer, and Leukemia data indicates they also output many of the genes and pathways linked to the cancers under study. Bayesian feature selection is a promising framework for small-sample high-dimensional data, in particular biomarker discovery applications. When applied to cancer data these algorithms outputted many genes already shown to be involved in cancer as well as potentially new biomarkers. Furthermore, one of the proposed algorithms, SPM, outputs blocks of heavily correlated genes, particularly useful for studying gene interactions and gene networks.

Remote sensing of coastal sea-surface features off northern British Columbia

International Nuclear Information System (INIS)

Jardine, I.D.; Thomson, K.A.; LeBlond, P.H.; Foreman, M.G.

1993-01-01

This article presents an overview of surface oceanographic features identified by AVHRR imagery in Hecate Strait and adjacent waters surrounding the Queen Charlotte Islands, Canada, an area still poor in in situ observations. The observed features and their temporal variability are interpreted in terms of meteorological and hydrological forcing. The effects of tidal mixing are discussed through the application of a finite element numerical model

ON THE 10 μm SILICATE FEATURE IN ACTIVE GALACTIC NUCLEI

International Nuclear Information System (INIS)

Nikutta, Robert; Elitzur, Moshe; Lacy, Mark

2009-01-01

The 10 μm silicate feature observed with Spitzer in active galactic nuclei (AGNs) reveals some puzzling behavior. It (1) has been detected in emission in type 2 sources, (2) shows broad, flat-topped emission peaks shifted toward long wavelengths in several type 1 sources, and (3) is not seen in deep absorption in any source observed so far. We solve all three puzzles with our clumpy dust radiative transfer formalism. Addressing (1), we present the spectral energy distribution (SED) of SST1721+6012, the first type 2 quasar observed to show a clear 10 μm silicate feature in emission. Such emission arises in models of the AGN torus easily when its clumpy nature is taken into account. We constructed a large database of clumpy torus models and performed extensive fitting of the observed SED. We find that the cloud radial distribution varies as r -1.5 and the torus contains 2-4 clouds along radial equatorial rays, each with optical depth at visual ∼60-80. The source bolometric luminosity is ∼3 x 10 12 L sun . Our modeling suggests that ∼<35% of objects with tori sharing these characteristics and geometry would have their central engines obscured. This relatively low obscuration probability can explain the clear appearance of the 10 μm emission feature in SST1721+6012 together with its rarity among other QSO2. Investigating (2), we also fitted the SED of PG1211+143, one of the first type 1 QSOs with a 10 μm silicate feature detected in emission. Together with other similar sources, this QSO appears to display an unusually broadened feature whose peak is shifted toward longer wavelengths. Although this led to suggestions of non-standard dust chemistry in these sources, our analysis fits such SEDs with standard galactic dust; the apparent peak shifts arise from simple radiative transfer effects. Regarding (3), we find additionally that the distribution of silicate feature strengths among clumpy torus models closely resembles the observed distribution, and the

On the 10 μm Silicate Feature in Active Galactic Nuclei

Science.gov (United States)

Nikutta, Robert; Elitzur, Moshe; Lacy, Mark

2009-12-01

The 10 μm silicate feature observed with Spitzer in active galactic nuclei (AGNs) reveals some puzzling behavior. It (1) has been detected in emission in type 2 sources, (2) shows broad, flat-topped emission peaks shifted toward long wavelengths in several type 1 sources, and (3) is not seen in deep absorption in any source observed so far. We solve all three puzzles with our clumpy dust radiative transfer formalism. Addressing (1), we present the spectral energy distribution (SED) of SST1721+6012, the first type 2 quasar observed to show a clear 10 μm silicate feature in emission. Such emission arises in models of the AGN torus easily when its clumpy nature is taken into account. We constructed a large database of clumpy torus models and performed extensive fitting of the observed SED. We find that the cloud radial distribution varies as r -1.5 and the torus contains 2-4 clouds along radial equatorial rays, each with optical depth at visual ~60-80. The source bolometric luminosity is ~3 × 1012 Lsun. Our modeling suggests that lsim35% of objects with tori sharing these characteristics and geometry would have their central engines obscured. This relatively low obscuration probability can explain the clear appearance of the 10 μm emission feature in SST1721+6012 together with its rarity among other QSO2. Investigating (2), we also fitted the SED of PG1211+143, one of the first type 1 QSOs with a 10 μm silicate feature detected in emission. Together with other similar sources, this QSO appears to display an unusually broadened feature whose peak is shifted toward longer wavelengths. Although this led to suggestions of non-standard dust chemistry in these sources, our analysis fits such SEDs with standard galactic dust; the apparent peak shifts arise from simple radiative transfer effects. Regarding (3), we find additionally that the distribution of silicate feature strengths among clumpy torus models closely resembles the observed distribution, and the feature

Feature-Based versus Category-Based Induction with Uncertain Categories

Science.gov (United States)

Griffiths, Oren; Hayes, Brett K.; Newell, Ben R.

2012-01-01

Previous research has suggested that when feature inferences have to be made about an instance whose category membership is uncertain, feature-based inductive reasoning is used to the exclusion of category-based induction. These results contrast with the observation that people can and do use category-based induction when category membership is…

Feature Extraction and Classification on Esophageal X-Ray Images of Xinjiang Kazak Nationality

Directory of Open Access Journals (Sweden)

Fang Yang

2017-01-01

Full Text Available Esophageal cancer is one of the fastest rising types of cancers in China. The Kazak nationality is the highest-risk group in Xinjiang. In this work, an effective computer-aided diagnostic system is developed to assist physicians in interpreting digital X-ray image features and improving the quality of diagnosis. The modules of the proposed system include image preprocessing, feature extraction, feature selection, image classification, and performance evaluation. 300 original esophageal X-ray images were resized to a region of interest and then enhanced by the median filter and histogram equalization method. 37 features from textural, frequency, and complexity domains were extracted. Both sequential forward selection and principal component analysis methods were employed to select the discriminative features for classification. Then, support vector machine and K-nearest neighbors were applied to classify the esophageal cancer images with respect to their specific types. The classification performance was evaluated in terms of the area under the receiver operating characteristic curve, accuracy, precision, and recall, respectively. Experimental results show that the classification performance of the proposed system outperforms the conventional visual inspection approaches in terms of diagnostic quality and processing time. Therefore, the proposed computer-aided diagnostic system is promising for the diagnostics of esophageal cancer.

Physical model for the 2175 A interstellar extinction feature

International Nuclear Information System (INIS)

Hecht, J.H.

1986-01-01

Recent IUE observations have shown that the 2175 A interstellar extinction feature is constant in wavelength but varies in width. A model has been constructed to explain these results. It is proposed that the 2175 A feature will only be seen when there is extinction due to carbon grains which have lost their hydrogen. In particular, the feature is caused by a separate population of small (less than 50 A radius), hydrogen-free carbon grains. The variations in width would be due to differences in either their temperature, size distribution, or impurity content. All other carbon grains retain hydrogen, which causes the feature to be suppressed. If this model is correct, then it implies that the grains responsible for the unidentified IR emission features would not generally cause the 2175 A feature. 53 references

Discrete Feature Model (DFM) User Documentation

Energy Technology Data Exchange (ETDEWEB)

Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))

2008-06-15

This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this

Discrete Feature Model (DFM) User Documentation

International Nuclear Information System (INIS)

Geier, Joel

2008-06-01

This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this software, the

Wolf-Hirschhorn syndrome (WHS) - literature review on the features of the syndrome.

Science.gov (United States)

Paradowska-Stolarz, Anna M

2014-01-01

Wolf-Hirschhorn syndrome (WHS) is a congenital disorder associated with 4 chromosome microdeletion. The patients suffer from various deformities. Among them, mental and growth retardation, even in the fetus, are observed. Most of the characteristics concern facial features. The "Greek warrior helmet appearance" is the most characteristic feature and refers to the facial view with prominent glabella, high arched eyebrow, broad nasal bridge and hypertelorism. Another characteristic feature is microcephalia with micrognathia. The features are more pronounced in infants. Clefts of lip and/or palate are observed in almost half of the cases. The characteristic thing is that the more genetic material is missing, the more pronounced are the dimorphic features of the syndrome. Mostly, the dental status does not differ much from that of the healthy individuals. It had been proven though that WHS-patients are more prone to anomalies in dental structures. Cone-shaped and taurodontic teeth were observed. Multiple tooth agenesis (mainly at premolars and molars) with over-retained deciduous dentition might be associated with MSX1-gene impairment.

Cycling hypoxia: A key feature of the tumor microenvironment.

Science.gov (United States)

Michiels, Carine; Tellier, Céline; Feron, Olivier

2016-08-01

A compelling body of evidence indicates that most human solid tumors contain hypoxic areas. Hypoxia is the consequence not only of the chaotic proliferation of cancer cells that places them at distance from the nearest capillary but also of the abnormal structure of the new vasculature network resulting in transient blood flow. Hence two types of hypoxia are observed in tumors: chronic and cycling (intermittent) hypoxia. Most of the current work aims at understanding the role of chronic hypoxia in tumor growth, response to treatment and metastasis. Only recently, cycling hypoxia, with spatial and temporal fluctuations in oxygen levels, has emerged as another key feature of the tumor environment that triggers different responses in comparison to chronic hypoxia. Either type of hypoxia is associated with distinct effects not only in cancer cells but also in stromal cells. In particular, cycling hypoxia has been demonstrated to favor, to a higher extent than chronic hypoxia, angiogenesis, resistance to anti-cancer treatments, intratumoral inflammation and tumor metastasis. These review details these effects as well as the signaling pathway it triggers to switch on specific transcriptomic programs. Understanding the signaling pathways through which cycling hypoxia induces these processes that support the development of an aggressive cancer could convey to the emergence of promising new cancer treatments. Copyright © 2016 Elsevier B.V. All rights reserved.

Simulated cosmic microwave background maps at 0.5 deg resolution: Unresolved features

Science.gov (United States)

Kogut, A.; Hinshaw, G.; Bennett, C. L.

1995-01-01

High-contrast peaks in the cosmic microwave background (CMB) anisotropy can appear as unresolved sources to observers. We fit simluated CMB maps generated with a cold dark matter model to a set of unresolved features at instrumental resolution 0.5 deg-1.5 deg to derive the integral number density per steradian n (greater than absolute value of T) of features brighter than threshold temperature absolute value of T and compare the results to recent experiments. A typical medium-scale experiment observing 0.001 sr at 0.5 deg resolution would expect to observe one feature brighter than 85 micro-K after convolution with the beam profile, with less than 5% probability to observe a source brighter than 150 micro-K. Increasing the power-law index of primordial density perturbations n from 1 to 1.5 raises these temperature limits absolute value of T by a factor of 2. The MSAM features are in agreement with standard cold dark matter models and are not necessarily evidence for processes beyond the standard model.

Unary probabilistic and quantum automata on promise problems

OpenAIRE

Gainutdinova, Aida; Yakaryilmaz, Abuzer

2015-01-01

We continue the systematic investigation of probabilistic and quantum finite automata (PFAs and QFAs) on promise problems by focusing on unary languages. We show that bounded-error QFAs are more powerful than PFAs. But, in contrary to the binary problems, the computational powers of Las-Vegas QFAs and bounded-error PFAs are equivalent to deterministic finite automata (DFAs). Lastly, we present a new family of unary promise problems with two parameters such that when fixing one parameter QFAs ...

HBC-Evo: predicting human breast cancer by exploiting amino acid sequence-based feature spaces and evolutionary ensemble system.

Science.gov (United States)

Majid, Abdul; Ali, Safdar

2015-01-01

We developed genetic programming (GP)-based evolutionary ensemble system for the early diagnosis, prognosis and prediction of human breast cancer. This system has effectively exploited the diversity in feature and decision spaces. First, individual learners are trained in different feature spaces using physicochemical properties of protein amino acids. Their predictions are then stacked to develop the best solution during GP evolution process. Finally, results for HBC-Evo system are obtained with optimal threshold, which is computed using particle swarm optimization. Our novel approach has demonstrated promising results compared to state of the art approaches.

Measuring how typical and atypical minds read other's intentions. Comment on "Seeing mental states: An experimental strategy for measuring the observability of other minds" by Cristina Becchio et al.

Science.gov (United States)

Parma, Valentina; Sartori, Luisa; Castiello, Umberto

2018-03-01

Becchio et al. [1] propose a model to render other's minds observable against the Unobservability Principle. Such model develops over four, distinct steps. First, it provides experimental evidence indicating that mental states (i.e., intentions) can be encoded in behavioral patterns (e.g., movement kinematics). Second, it provides strategies to test the efficiency of the quantification of such intention-related behavioral manifestations (i.e., resolution of the uncertainty between two intentions based on different patterns of accumulation of kinematic parameters). Third, it indicates specific features of the observed behavior that viewers use to detect different intentions (i.e., a series of decision rules based on kinematic features through which intention categorization occurs). Fourth, it proposes a manner to manipulate such specific behavioral features so that an observer can detect different intentions, based on how informative such behavioral features are. We see in this operational/experimental approach a significant contribution to the theoretical debate on the possibility to observe mental states, allowing the direct testing of the unobservability principle and therefore providing falsifiable hypotheses. Besides this already central aspect, we believe this approach holds promise to the elucidation of clinical open questions, such as those posed by autism spectrum disorders (ASD). Indeed, experimentally evaluating the ability to observe and manipulate other's intentions allow us to quantify with high accuracy the deficits in the representation of other people's minds that so chiefly characterize ASD as well as the outcomes of treatment options focusing on this aspect. Here we suggest a few clarifications and extensions of the proposed model which will make it possibly tailored for clinical applications.

Seaweed: Promising plant of the millennium

Digital Repository Service at National Institute of Oceanography (India)

Dhargalkar, V.K.; Pereira, N.

Seaweeds, one of the important marine living resources could be termed as the futuristically promising plants. These plants have been a source of food, feed and medicine in the orient as well as in the west, since ancient times. Although, seaweeds...

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach.

Science.gov (United States)

Nasir, Muhammad; Attique Khan, Muhammad; Sharif, Muhammad; Lali, Ikram Ullah; Saba, Tanzila; Iqbal, Tassawar

2018-02-21

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F-score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods. © 2018 Wiley Periodicals, Inc.

Automatic lip reading by using multimodal visual features

Science.gov (United States)

Takahashi, Shohei; Ohya, Jun

2013-12-01

Since long time ago, speech recognition has been researched, though it does not work well in noisy places such as in the car or in the train. In addition, people with hearing-impaired or difficulties in hearing cannot receive benefits from speech recognition. To recognize the speech automatically, visual information is also important. People understand speeches from not only audio information, but also visual information such as temporal changes in the lip shape. A vision based speech recognition method could work well in noisy places, and could be useful also for people with hearing disabilities. In this paper, we propose an automatic lip-reading method for recognizing the speech by using multimodal visual information without using any audio information such as speech recognition. First, the ASM (Active Shape Model) is used to track and detect the face and lip in a video sequence. Second, the shape, optical flow and spatial frequencies of the lip features are extracted from the lip detected by ASM. Next, the extracted multimodal features are ordered chronologically so that Support Vector Machine is performed in order to learn and classify the spoken words. Experiments for classifying several words show promising results of this proposed method.

iFER: facial expression recognition using automatically selected geometric eye and eyebrow features

Science.gov (United States)

Oztel, Ismail; Yolcu, Gozde; Oz, Cemil; Kazan, Serap; Bunyak, Filiz

2018-03-01

Facial expressions have an important role in interpersonal communications and estimation of emotional states or intentions. Automatic recognition of facial expressions has led to many practical applications and became one of the important topics in computer vision. We present a facial expression recognition system that relies on geometry-based features extracted from eye and eyebrow regions of the face. The proposed system detects keypoints on frontal face images and forms a feature set using geometric relationships among groups of detected keypoints. Obtained feature set is refined and reduced using the sequential forward selection (SFS) algorithm and fed to a support vector machine classifier to recognize five facial expression classes. The proposed system, iFER (eye-eyebrow only facial expression recognition), is robust to lower face occlusions that may be caused by beards, mustaches, scarves, etc. and lower face motion during speech production. Preliminary experiments on benchmark datasets produced promising results outperforming previous facial expression recognition studies using partial face features, and comparable results to studies using whole face information, only slightly lower by ˜ 2.5 % compared to the best whole face facial recognition system while using only ˜ 1 / 3 of the facial region.

Spectroscopy of the 3.3 ad 3.4 micron dust emission features

International Nuclear Information System (INIS)

Geballe, T.R.

1984-01-01

Various unidentified infrared features which have been observed in the interstellar grain medium are thought to be emitted or absorbed by molecules within dust grains. In order to correctly identify these molecules accurate high spectral resolution measurements of the features must be obtained. In order to obtain more accurate profiles, the 3.3 and 3.4 micron features have been observed in the planetary nebula NGC 7027 and in the HII region S106, during June and July 1983, using UKIRT and its 7-channel cooled grating spectrometer. (author)

Guilt by Association: The 13 Micron Dust Emission Feature and Its Correlation to Other Gas and Dust Features

Science.gov (United States)

Sloan, G. C.; Kraemer, Kathleen E.; Goebel, J. H.; Price, Stephan D.

2003-09-01

A study of all full-scan spectra of optically thin oxygen-rich circumstellar dust shells in the database produced by the Short Wavelength Spectrometer on ISO reveals that the strength of several infrared spectral features correlates with the strength of the 13 μm dust feature. These correlated features include dust features at 19.8 and 28.1 μm and the bands produced by warm carbon dioxide molecules (the strongest of which are at 13.9, 15.0, and 16.2 μm). The database does not provide any evidence for a correlation of the 13 μm feature with a dust feature at 32 μm, and it is more likely that a weak emission feature at 16.8 μm arises from carbon dioxide gas rather than dust. The correlated dust features at 13, 20, and 28 μm tend to be stronger with respect to the total dust emission in semiregular and irregular variables associated with the asymptotic giant branch than in Mira variables or supergiants. This family of dust features also tends to be stronger in systems with lower infrared excesses and thus lower mass-loss rates. We hypothesize that the dust features arise from crystalline forms of alumina (13 μm) and silicates (20 and 28 μm). Based on observations with the ISO, a European Space Agency (ESA) project with instruments funded by ESA member states (especially the Principal Investigator countries: France, Germany, the Netherlands, and the United Kingdom) and with the participation of the Institute of Space and Astronautical Science (ISAS) and the National Aeronautics and Space Administration (NASA).

The development of cones and associated features on ion bombarded copper

International Nuclear Information System (INIS)

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

1977-01-01

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

The development of cones and associated features on ion bombarded copper

International Nuclear Information System (INIS)

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

1977-01-01

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

A prototype feature system for feature retrieval using relationships

Science.gov (United States)

Choi, J.; Usery, E.L.

2009-01-01

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

No Effect of Featural Attention on Body Size Aftereffects.

Science.gov (United States)

Stephen, Ian D; Bickersteth, Chloe; Mond, Jonathan; Stevenson, Richard J; Brooks, Kevin R

2016-01-01

Prolonged exposure to images of narrow bodies has been shown to induce a perceptual aftereffect, such that observers' point of subjective normality (PSN) for bodies shifts toward narrower bodies. The converse effect is shown for adaptation to wide bodies. In low-level stimuli, object attention (attention directed to the object) and spatial attention (attention directed to the location of the object) have been shown to increase the magnitude of visual aftereffects, while object-based attention enhances the adaptation effect in faces. It is not known whether featural attention (attention directed to a specific aspect of the object) affects the magnitude of adaptation effects in body stimuli. Here, we manipulate the attention of Caucasian observers to different featural information in body images, by asking them to rate the fatness or sex typicality of male and female bodies manipulated to appear fatter or thinner than average. PSNs for body fatness were taken at baseline and after adaptation, and a change in PSN (ΔPSN) was calculated. A body size adaptation effect was found, with observers who viewed fat bodies showing an increased PSN, and those exposed to thin bodies showing a reduced PSN. However, manipulations of featural attention to body fatness or sex typicality produced equivalent results, suggesting that featural attention may not affect the strength of the body size aftereffect.

Freedom: A Promise of Possibility.

Science.gov (United States)

Bunkers, Sandra Schmidt

2015-10-01

The idea of freedom as a promise of possibility is explored in this column. The core concepts from a research study on considering tomorrow (Bunkers, 1998) coupled with humanbecoming community change processes (Parse, 2003) are used to illuminate this notion. The importance of intentionality in human freedom is discussed from both a human science and a natural science perspective. © The Author(s) 2015.

Low-Dimensional Feature Representation for Instrument Identification

Science.gov (United States)

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

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

Information Processing Features Can Detect Behavioral Regimes of Dynamical Systems

Directory of Open Access Journals (Sweden)

Rick Quax

2018-01-01

Full Text Available In dynamical systems, local interactions between dynamical units generate correlations which are stored and transmitted throughout the system, generating the macroscopic behavior. However a framework to quantify exactly how these correlations are stored, transmitted, and combined at the microscopic scale is missing. Here we propose to characterize the notion of “information processing” based on all possible Shannon mutual information quantities between a future state and all possible sets of initial states. We apply it to the 256 elementary cellular automata (ECA, which are the simplest possible dynamical systems exhibiting behaviors ranging from simple to complex. Our main finding is that only a few information features are needed for full predictability of the systemic behavior and that the “information synergy” feature is always most predictive. Finally we apply the idea to foreign exchange (FX and interest-rate swap (IRS time-series data. We find an effective “slowing down” leading indicator in all three markets for the 2008 financial crisis when applied to the information features, as opposed to using the data itself directly. Our work suggests that the proposed characterization of the local information processing of units may be a promising direction for predicting emergent systemic behaviors.

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

Science.gov (United States)

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

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

Impact of load-related neural processes on feature binding in visuospatial working memory.

Directory of Open Access Journals (Sweden)

Nicole A Kochan

Full Text Available BACKGROUND: The capacity of visual working memory (WM is substantially limited and only a fraction of what we see is maintained as a temporary trace. The process of binding visual features has been proposed as an adaptive means of minimising information demands on WM. However the neural mechanisms underlying this process, and its modulation by task and load effects, are not well understood. OBJECTIVE: To investigate the neural correlates of feature binding and its modulation by WM load during the sequential phases of encoding, maintenance and retrieval. METHODS AND FINDINGS: 18 young healthy participants performed a visuospatial WM task with independent factors of load and feature conjunction (object identity and position in an event-related functional MRI study. During stimulus encoding, load-invariant conjunction-related activity was observed in left prefrontal cortex and left hippocampus. During maintenance, greater activity for task demands of feature conjunction versus single features, and for increased load was observed in left-sided regions of the superior occipital cortex, precuneus and superior frontal cortex. Where these effects were expressed in overlapping cortical regions, their combined effect was additive. During retrieval, however, an interaction of load and feature conjunction was observed. This modulation of feature conjunction activity under increased load was expressed through greater deactivation in medial structures identified as part of the default mode network. CONCLUSIONS AND SIGNIFICANCE: The relationship between memory load and feature binding qualitatively differed through each phase of the WM task. Of particular interest was the interaction of these factors observed within regions of the default mode network during retrieval which we interpret as suggesting that at low loads, binding processes may be 'automatic' but at higher loads it becomes a resource-intensive process leading to disengagement of activity in this

OBSERVATIONS OF TYPE Ia SUPERNOVA 2014J WITH FLITECAM ON SOFIA

Energy Technology Data Exchange (ETDEWEB)

Vacca, William D.; Hamilton, Ryan T.; Savage, Maureen; Shenoy, Sachindev; Becklin, E. E.; Helton, L. A. [SOFIA-USRA, NASA Ames Research Center, Mail Stop N232-12, Moffet Field, CA 94035-1000 (United States); McLean, Ian S.; Logsdon, Sarah E. [Department of Physics and Astronomy, UCLA, Los Angeles, CA 90095-1562 (United States); Marion, G. H. [University of Texas at Austin, 1 University Station C1400, Austin, TX 78712-0259 (United States); Ashok, N. M.; Banerjee, D. P. K. [Physical Research Laboratory, Ahmedabad 380009 (India); Evans, A. [Astrophysics Group, Keele University, Keele, Staffordshire, ST5 5BG (United Kingdom); Fox, O. D. [Department of Astronomy, University of California, Berkeley, CA 94720-3411 (United States); Garnavich, P. [University of Notre Dame, 225 Nieuwland Science Ctr, Notre Dame, IN 46556-5670 (United States); Gehrz, R. D. [Minnesota Institute for Astrophysics, University of Minnesota, 116 Church St. SE, Minneapolis, MN 55455-0149 (United States); Greenhouse, M. [NASA Goddard Space Flight Center, Code 665, Greenbelt, MD 20771 (United States); Kirshner, R. P. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Shenoy, D. [Minnesota Institute for Astrophysics, School of Physics and Astronomy, University of Minnesota, 116 Church Street, S. E., Minneapolis, MN 55455 (United States); Smith, Nathan [Steward Observatory, 933 N. Cherry Avenue, Tucson, AZ 85719 (United States); Spyromilio, J., E-mail: wvacca@sofia.usra.edu [European Southern Observatory, Karl-Schwarzschild-Strasse 2, Garching, D-85748 (Germany); and others

2015-05-01

We present medium-resolution near-infrared (NIR) spectra, covering 1.1–3.4 μm, of the normal Type Ia supernova (SN Ia) SN 2014J in M82 obtained with the FLITECAM instrument on board Stratospheric Observatory for Infrared Astronomy (SOFIA) between 17 and 26 days after maximum B light. Our 2.8–3.4 μm spectra may be the first ∼3 μm spectra of an SN Ia ever published. The spectra spanning the 1.5–2.7 μm range are characterized by a strong emission feature at ∼1.77 μm with a FWHM of ∼11,000–13,000 km s{sup −1}. We compare the observed FLITECAM spectra to the recent non-LTE delayed detonation models of Dessart et al. and find that the models agree with the spectra remarkably well in the 1.5–2.7 μm wavelength range. Based on this comparison we identify the ∼1.77 μm emission peak as a blend of permitted lines of Co ii. Other features seen in the 2.0–2.5 μm spectra are also identified as emission from permitted transitions of Co ii. However, the models are not as successful at reproducing the spectra in the 1.1–1.4 μm range or between 2.8 and 3.4 μm. These observations demonstrate the promise of SOFIA, which allows access to wavelength regions inaccessible from the ground, and serve to draw attention to the usefulness of the regions between the standard ground-based NIR passbands for constraining SN models.

OBSERVATIONS OF TYPE Ia SUPERNOVA 2014J WITH FLITECAM ON SOFIA

International Nuclear Information System (INIS)

Vacca, William D.; Hamilton, Ryan T.; Savage, Maureen; Shenoy, Sachindev; Becklin, E. E.; Helton, L. A.; McLean, Ian S.; Logsdon, Sarah E.; Marion, G. H.; Ashok, N. M.; Banerjee, D. P. K.; Evans, A.; Fox, O. D.; Garnavich, P.; Gehrz, R. D.; Greenhouse, M.; Kirshner, R. P.; Shenoy, D.; Smith, Nathan; Spyromilio, J.

2015-01-01

We present medium-resolution near-infrared (NIR) spectra, covering 1.1–3.4 μm, of the normal Type Ia supernova (SN Ia) SN 2014J in M82 obtained with the FLITECAM instrument on board Stratospheric Observatory for Infrared Astronomy (SOFIA) between 17 and 26 days after maximum B light. Our 2.8–3.4 μm spectra may be the first ∼3 μm spectra of an SN Ia ever published. The spectra spanning the 1.5–2.7 μm range are characterized by a strong emission feature at ∼1.77 μm with a FWHM of ∼11,000–13,000 km s −1 . We compare the observed FLITECAM spectra to the recent non-LTE delayed detonation models of Dessart et al. and find that the models agree with the spectra remarkably well in the 1.5–2.7 μm wavelength range. Based on this comparison we identify the ∼1.77 μm emission peak as a blend of permitted lines of Co ii. Other features seen in the 2.0–2.5 μm spectra are also identified as emission from permitted transitions of Co ii. However, the models are not as successful at reproducing the spectra in the 1.1–1.4 μm range or between 2.8 and 3.4 μm. These observations demonstrate the promise of SOFIA, which allows access to wavelength regions inaccessible from the ground, and serve to draw attention to the usefulness of the regions between the standard ground-based NIR passbands for constraining SN models

Design features of HTMR-hybrid toroidal magnet tokamak reactor

International Nuclear Information System (INIS)

Rosatelli, F.; Avanzini, P.G.; Derchi, D.; Magnasco, M.; Grattarola, M.; Peluffo, M.; Raia, G.; Brunelli, B.; Zampaglione, V.

1984-01-01

The HTMR (Hybrid Toroidal Magnet Tokamak Reactor) conceptual design is aimed to demonstrate the feasibility of a Tokamak reactor which could fulfil the scientific and technological objectives expected from next generation devices with size and costs as small as possible. A hybrid toroidal field magnet, made up by copper and superconducting coils, seems to be a promising solution, allowing a considerable flexibility in machine performances, so as to gain useful margins in front of the uncertainties in confinement time scaling laws and beta and plasma density limits. The optimization procedure for the hybrid magnet, configuration, the main design features of HTMR and the preliminary mechanical calculations of the superconducting toroidal coils are described. (author)

Copenhagen's climate finance promise: six key questions

Energy Technology Data Exchange (ETDEWEB)

Roberts, J. Timmons [Brown University (United States); Stadelmann, Martin [University of Zurich (Switzerland); Huq, Saleemul

2010-02-15

One clear promise emerged from the confusion of the 2009 climate talks in Copenhagen. This was to provide short- and long-term 'climate finance' to help developing countries – especially the most vulnerable – adapt to climate impacts. The promise seemed simple enough: wealthier nations would pledge US$10 billion a year from 2010-2012, ramping up to US$100 billion a year starting in 2020. This was also touted as a way to help developing countries avoid high-carbon pathways of development by adopting lower-emitting power sources such as solar or natural gas. But a closer look at the Copenhagen promise unearths at least six big questions – any one of which could seriously challenge the trust these funds were designed to build.

Laboratory simulation of infrared astrophysical features

International Nuclear Information System (INIS)

Rose, L.A.

1979-01-01

Laboratory infrared emission and absorption spectra have been taken of terrestrial silicates, meteorites and lunar soils in the form of micrometer and sub-micrometer grains. The emission spectra were taken in a way that imitates telescopic observations. The purpose was to see which materials best simulate the 10 μm astrophysical feature. The emission spectra of dunite, fayalite and Allende give a good fit to the 10 μm broadband emission feature of comets Bennett and Kohoutek. A study of the effect of grain size on the presence of the 10 μm emission features of dunite shows that for particles larger than 37 μm no feature is seen. The emission spectrum of the Murray meteorite, a Type 2 carbonaceous chondrite, is quite similar to the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Hydrous silicates or amorphous magnesium silicates in combination with high-temperature condensates, such as olivine or anorthite, would yield spectra that match the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Glassy olivine and glassy anorthite in approximately equal proportions would also give a spectrum that is a good fit to the cometary 10 μm feature. (Auth.)

Clinical Electrocardiographic and Echocardiographic Features of ...

African Journals Online (AJOL)

Clinical Electrocardiographic and Echocardiographic Features of Atrial Fibrillation in Nigerians: An Analysis of 39 Patients Seen at the Lagos University Teaching Hospital. ... Congestive cardiac failure was present in 74% of the subjects with a mean NYHA class of about III. Embolic phenomenon was observed in 15% of the ...

76 FR 13152 - Promise Neighborhoods Program

Science.gov (United States)

2011-03-10

... comprehensive education reforms that are linked to improved educational outcomes for children and youth in... parents or family members who report talking with their child about the importance of college and career... DEPARTMENT OF EDUCATION RIN 1855-ZA07 Promise Neighborhoods Program Catalog of Federal Domestic...

Final Validation of the ProMisE Molecular Classifier for Endometrial Carcinoma in a Large Population-based Case Series.

Science.gov (United States)

Kommoss, S; McConechy, M K; Kommoss, F; Leung, S; Bunz, A; Magrill, J; Britton, H; Kommoss, F; Grevenkamp, F; Karnezis, A; Yang, W; Lum, A; Krämer, B; Taran, F; Staebler, A; Lax, S; Brucker, S Y; Huntsman, D G; Gilks, C B; McAlpine, J N; Talhouk, A

2018-02-07

Based on The Cancer Genome Atlas, we previously developed and confirmed a pragmatic molecular classifier for endometrial cancers; ProMisE (Proactive Molecular Risk Classifier for Endometrial Cancer). ProMisE identifies four prognostically distinct molecular subtypes, and can be applied to diagnostic specimens (biopsy/curettings), enabling earlier informed decision-making. We have strictly adhered to the Institute of Medicine (IOM) guidelines for the development of genomic biomarkers, and herein present the final validation step of a locked-down classifier prior to clinical application. We assessed a retrospective cohort of women from the Tübingen University Women's Hospital treated for endometrial carcinoma between 2003-13. Primary outcomes of overall, disease-specific and progression-free survival were evaluated for clinical, pathological, and molecular features. Complete clinical and molecular data were evaluable from 452 women. Patient age ranged from 29 - 93 (median 65) years, and 87.8% cases were endometrioid histotype. Grade distribution included 282 (62.4%) G1, 75 (16.6%) G2, and 95 (21.0%) G3 tumors. 276 (61.1%) patients had stage IA disease, with the remaining stage IB (89 (19.7%)), stage II (26 (5.8%)), and stage III/IV (61 (13.5%)). ProMisE molecular classification yielded 127 (28.1%) MMR-D, 42 (9.3%) POLE, 55 (12.2%) p53abn, and 228 (50.4%) p53wt. ProMisE was a prognostic marker for progression-free (P=0.001) and disease-specific (P=0.03) survival even after adjusting for known risk factors. Concordance between diagnostic and surgical specimens was highly favorable; accuracy 0.91, kappa 0.88. We have developed, confirmed and now validated a pragmatic molecular classification tool (ProMisE) that provides consistent categorization of tumors and identifies four distinct prognostic molecular subtypes. ProMisE can be applied to diagnostic samples and thus could be used to inform surgical procedure(s) and/or need for adjuvant therapy. Based on the IOM

Serious Games and Gamification for Mental Health: Current Status and Promising Directions.

Science.gov (United States)

Fleming, Theresa M; Bavin, Lynda; Stasiak, Karolina; Hermansson-Webb, Eve; Merry, Sally N; Cheek, Colleen; Lucassen, Mathijs; Lau, Ho Ming; Pollmuller, Britta; Hetrick, Sarah

2016-01-01

Computer games are ubiquitous and can be utilized for serious purposes such as health and education. "Applied games" including serious games (in brief, computerized games for serious purposes) and gamification (gaming elements used outside of games) have the potential to increase the impact of mental health internet interventions via three processes. First, by extending the reach of online programs to those who might not otherwise use them. Second, by improving engagement through both game-based and "serious" motivational dynamics. Third, by utilizing varied mechanisms for change, including therapeutic processes and gaming features. In this scoping review, we aim to advance the field by exploring the potential and opportunities available in this area. We review engagement factors which may be exploited and demonstrate that there is promising evidence of effectiveness for serious games for depression from contemporary systematic reviews. We illustrate six major categories of tested applied games for mental health (exergames, virtual reality, cognitive behavior therapy-based games, entertainment games, biofeedback, and cognitive training games) and demonstrate that it is feasible to translate traditional evidence-based interventions into computer gaming formats and to exploit features of computer games for therapeutic change. Applied games have considerable potential for increasing the impact of online interventions for mental health. However, there are few independent trials, and direct comparisons of game-based and non-game-based interventions are lacking. Further research, faster iterations, rapid testing, non-traditional collaborations, and user-centered approaches are needed to respond to diverse user needs and preferences in rapidly changing environments.

Serious Games and Gamification for Mental Health: Current Status and Promising Directions

Science.gov (United States)

Fleming, Theresa M.; Bavin, Lynda; Stasiak, Karolina; Hermansson-Webb, Eve; Merry, Sally N.; Cheek, Colleen; Lucassen, Mathijs; Lau, Ho Ming; Pollmuller, Britta; Hetrick, Sarah

2017-01-01

Computer games are ubiquitous and can be utilized for serious purposes such as health and education. “Applied games” including serious games (in brief, computerized games for serious purposes) and gamification (gaming elements used outside of games) have the potential to increase the impact of mental health internet interventions via three processes. First, by extending the reach of online programs to those who might not otherwise use them. Second, by improving engagement through both game-based and “serious” motivational dynamics. Third, by utilizing varied mechanisms for change, including therapeutic processes and gaming features. In this scoping review, we aim to advance the field by exploring the potential and opportunities available in this area. We review engagement factors which may be exploited and demonstrate that there is promising evidence of effectiveness for serious games for depression from contemporary systematic reviews. We illustrate six major categories of tested applied games for mental health (exergames, virtual reality, cognitive behavior therapy-based games, entertainment games, biofeedback, and cognitive training games) and demonstrate that it is feasible to translate traditional evidence-based interventions into computer gaming formats and to exploit features of computer games for therapeutic change. Applied games have considerable potential for increasing the impact of online interventions for mental health. However, there are few independent trials, and direct comparisons of game-based and non-game-based interventions are lacking. Further research, faster iterations, rapid testing, non-traditional collaborations, and user-centered approaches are needed to respond to diverse user needs and preferences in rapidly changing environments. PMID:28119636

Enhancing facial features by using clear facial features

Science.gov (United States)

Rofoo, Fanar Fareed Hanna

2017-09-01

The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

Automatic building extraction from LiDAR data fusion of point and grid-based features

Science.gov (United States)

Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang

2017-08-01

This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.

Spatial features register: toward standardization of spatial features

Science.gov (United States)

Cascio, Janette

1994-01-01

As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 2.

Singular value decomposition based feature extraction technique for physiological signal analysis.

Science.gov (United States)

Chang, Cheng-Ding; Wang, Chien-Chih; Jiang, Bernard C

2012-06-01

Multiscale entropy (MSE) is one of the popular techniques to calculate and describe the complexity of the physiological signal. Many studies use this approach to detect changes in the physiological conditions in the human body. However, MSE results are easily affected by noise and trends, leading to incorrect estimation of MSE values. In this paper, singular value decomposition (SVD) is adopted to replace MSE to extract the features of physiological signals, and adopt the support vector machine (SVM) to classify the different physiological states. A test data set based on the PhysioNet website was used, and the classification results showed that using SVD to extract features of the physiological signal could attain a classification accuracy rate of 89.157%, which is higher than that using the MSE value (71.084%). The results show the proposed analysis procedure is effective and appropriate for distinguishing different physiological states. This promising result could be used as a reference for doctors in diagnosis of congestive heart failure (CHF) disease.

The effective field theory of inflation models with sharp features

International Nuclear Information System (INIS)

Bartolo, Nicola; Cannone, Dario; Matarrese, Sabino

2013-01-01

We describe models of single-field inflation with small and sharp step features in the potential (and sound speed) of the inflaton field, in the context of the Effective Field Theory of Inflation. This approach allows us to study the effects of features in the power-spectrum and in the bispectrum of curvature perturbations, from a model-independent point of view, by parametrizing the features directly with modified ''slow-roll'' parameters. We can obtain a self-consistent power-spectrum, together with enhanced non-Gaussianity, which grows with a quantity β that parametrizes the sharpness of the step. With this treatment it is straightforward to generalize and include features in other coefficients of the effective action of the inflaton field fluctuations. Our conclusion in this case is that, excluding extrinsic curvature terms, the only interesting effects at the level of the bispectrum could arise from features in the first slow-roll parameter ε or in the speed of sound c s . Finally, we derive an upper bound on the parameter β from the consistency of the perturbative expansion of the action for inflaton perturbations. This constraint can be used for an estimation of the signal-to-noise ratio, to show that the observable which is most sensitive to features is the power-spectrum. This conclusion would change if we consider the contemporary presence of a feature and a speed of sound c s < 1, as, in such a case, contributions from an oscillating folded configuration can potentially make the bispectrum the leading observable for feature models

An explorative childhood pneumonia analysis based on ultrasonic imaging texture features

Science.gov (United States)

Zenteno, Omar; Diaz, Kristians; Lavarello, Roberto; Zimic, Mirko; Correa, Malena; Mayta, Holger; Anticona, Cynthia; Pajuelo, Monica; Oberhelman, Richard; Checkley, William; Gilman, Robert H.; Figueroa, Dante; Castañeda, Benjamín.

2015-12-01

According to World Health Organization, pneumonia is the respiratory disease with the highest pediatric mortality rate accounting for 15% of all deaths of children under 5 years old worldwide. The diagnosis of pneumonia is commonly made by clinical criteria with support from ancillary studies and also laboratory findings. Chest imaging is commonly done with chest X-rays and occasionally with a chest CT scan. Lung ultrasound is a promising alternative for chest imaging; however, interpretation is subjective and requires adequate training. In the present work, a two-class classification algorithm based on four Gray-level co-occurrence matrix texture features (i.e., Contrast, Correlation, Energy and Homogeneity) extracted from lung ultrasound images from children aged between six months and five years is presented. Ultrasound data was collected using a L14-5/38 linear transducer. The data consisted of 22 positive- and 68 negative-diagnosed B-mode cine-loops selected by a medical expert and captured in the facilities of the Instituto Nacional de Salud del Niño (Lima, Peru), for a total number of 90 videos obtained from twelve children diagnosed with pneumonia. The classification capacity of each feature was explored independently and the optimal threshold was selected by a receiver operator characteristic (ROC) curve analysis. In addition, a principal component analysis was performed to evaluate the combined performance of all the features. Contrast and correlation resulted the two more significant features. The classification performance of these two features by principal components was evaluated. The results revealed 82% sensitivity, 76% specificity, 78% accuracy and 0.85 area under the ROC.

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

Directory of Open Access Journals (Sweden)

Ketan Jhunjhunwala

2014-08-01

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

A Fast, Open EEG Classification Framework Based on Feature Compression and Channel Ranking

Directory of Open Access Journals (Sweden)

Jiuqi Han

2018-04-01

Full Text Available Superior feature extraction, channel selection and classification methods are essential for designing electroencephalography (EEG classification frameworks. However, the performance of most frameworks is limited by their improper channel selection methods and too specifical design, leading to high computational complexity, non-convergent procedure and narrow expansibility. In this paper, to remedy these drawbacks, we propose a fast, open EEG classification framework centralized by EEG feature compression, low-dimensional representation, and convergent iterative channel ranking. First, to reduce the complexity, we use data clustering to compress the EEG features channel-wise, packing the high-dimensional EEG signal, and endowing them with numerical signatures. Second, to provide easy access to alternative superior methods, we structurally represent each EEG trial in a feature vector with its corresponding numerical signature. Thus, the recorded signals of many trials shrink to a low-dimensional structural matrix compatible with most pattern recognition methods. Third, a series of effective iterative feature selection approaches with theoretical convergence is introduced to rank the EEG channels and remove redundant ones, further accelerating the EEG classification process and ensuring its stability. Finally, a classical linear discriminant analysis (LDA model is employed to classify a single EEG trial with selected channels. Experimental results on two real world brain-computer interface (BCI competition datasets demonstrate the promising performance of the proposed framework over state-of-the-art methods.

An Approach to Assess Observation Impact Based on Observation-Minus-Forecast Residuals

Science.gov (United States)

Todling, Ricardo

2009-01-01

Langland and Baker (2004) introduced an approach to assess the impact of observations on the forecasts. In that, a state-space aspect of the forecast is defined and a procedure is derived that relates changes in the aspect with changes in the initial conditions associated with the assimilation of observations) ultimately providing information about the impact of individual observations on the forecast. Some features of the approach are to be noted. The typical choice of forecast aspect employed in related works is rather arbitrary and leads to an incomplete assessment of the observing system. Furthermore, the state-space forecast aspect requires availability of a verification state that should ideally be uncorrelated with the forecast but in practice is not. Lastly, the approach involves the adjoint operator of the entire data assimilation system and as such it is constrained by the validity of this operator. In this presentation, an observation-space metric is used that, for a relatively time-homogeneous observing system, allows inferring observation impact on the forecast without some of the limitations above. Specifically, using observation-minus-forecast residuals leads to an approach with the following features: (i) it suggests a rather natural choice of forecast aspect, directly linked to the analysis system and providing full assessment of the observations; (ii) it naturally avoids introducing undesirable correlations in the forecast aspect by verifying against the observations; and (iii) it does not involve linearization and use of adjoints; therefore being applicable to any length of forecast. The state and observation-space approaches might be complementary to some degree, and involve different limitations and complexities. Illustrations are given using the NASA GEOS-5 data.

Nuclear energy: obstacles and promises

International Nuclear Information System (INIS)

Bacher, P.

2003-01-01

Nuclear energy has distinctive merits (sustainable resources, low costs, no greenhouse gases) but its development must overcome serious hurdles (fear of accidents, radio-phobia, waste management). The large unit size of present-day reactors is compatible only with large electrical grids, and involves a high capital cost. Taking into account these different factors, the paper outlines how nuclear energy may contribute to the reduction of greenhouse gases, and which are the most promising developments. (author)

Solutions for Failing High Schools: Converging Visions and Promising Models.

Science.gov (United States)

Legters, Nettie; Balfanz, Robert; McPartland, James

Promising solutions to the failings of traditional comprehensive high schools were reviewed to identify basic principles and strategies for improving high schools nationwide. Selected research studies, policy documents, and promising high school programs were reviewed. The review revealed the following principles for helping high schools better…

The role of strategic position in brand promise: Evidence from LG Company

Directory of Open Access Journals (Sweden)

A. Eilaghi Karvandi

2016-08-01

Full Text Available This paper presents an empirical investigation to study the effects of different strategies including attribute, advantage, application, consumer, competitive advantage, pricing/quality and category on brand promise for products of LG Company in city of Tehran, Iran. The study designs two questionnaires, one for strategic positioning and the other for brand promise in Likert scale. Cronbach alphas for brand promise and strategic positioning are 0.81 and 0.79, respectively. The questionnaires are distributed among 385 randomly selected regular users of LG products and using Spearman correlation as well as Stepwise regression techniques, the effects of various strategies on brand promise are examined. The results of the implementation of Spearman correlation have indicated that there were positive and meaningful relationships between different strategies and brand promise. In addition, the results of Stepwise regression have indicated that three strategies of price/quality, consumer and application were the most important predictors of brand promise.

Liquid Core ARROW Waveguides: A Promising Photonic Structure for Integrated Optofluidic Microsensors

Directory of Open Access Journals (Sweden)

Genni Testa

2016-03-01

Full Text Available In this paper, we introduce a liquid core antiresonant reflecting optical waveguide (ARROW as a novel optofluidic device that can be used to create innovative and highly functional microsensors. Liquid core ARROWs, with their dual ability to guide the light and the fluids in the same microchannel, have shown great potential as an optofluidic tool for quantitative spectroscopic analysis. ARROWs feature a planar architecture and, hence, are particularly attractive for chip scale integrated system. Step by step, several improvements have been made in recent years towards the implementation of these waveguides in a complete on-chip system for highly-sensitive detection down to the single molecule level. We review applications of liquid ARROWs for fluids sensing and discuss recent results and trends in the developments and applications of liquid ARROW in biomedical and biochemical research. The results outlined show that the strong light matter interaction occurring in the optofluidic channel of an ARROW and the versatility offered by the fabrication methods makes these waveguides a very promising building block for optofluidic sensor development.

Problems of Formation of Diagnostic Features in the Diagnosis of Aircraft Engines

Directory of Open Access Journals (Sweden)

Pronyakin V.I.

2017-01-01

Full Text Available The article is devoted to the evaluation of current technical condition of aircraft engines. Deals with the choice of the detection method of diagnostic features required for degradation assessment, emergency protection and detection of incipient defects on the example of cyclic machines and mechanisms. For the formation of diagnostic features in the diagnosis of aircraft engines use different physical effects (vibration, shock, heat radiation, electrodynamic and thermal processes, wear debris in oil, etc.. Classification of defects and requirements for the development of diagnostics systems is formed based on them. The article describes the requirements for diagnostic signs. The article provides a promising phase method that allows obtaining stable diagnostic characters in exploitation. The result of applying the method is shown. Diagnostic signs are formed. In mathematical modeling it was used the traditional theory of the description of rotary mechanisms. The data obtained are compared with experimental data.

FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

Directory of Open Access Journals (Sweden)

Ratri Enggar Pawening

2016-06-01

Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

Local and global trust based on the concept of promises

NARCIS (Netherlands)

Bergstra, J.; Burgess, M.

2009-01-01

We use the notion of a promise to define local trust between agents possessing autonomous decision-making. An agent is trustworthy if it is expected that it will keep a promise. This definition satisfies most commonplace meanings of trust. Reputation is then an estimation of this expectation value

Permutation importance: a corrected feature importance measure.

Science.gov (United States)

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

2010-05-15

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

A Bayesian Approach to Multistage Fitting of the Variation of the Skeletal Age Features

Directory of Open Access Journals (Sweden)

Dong Hua

2009-01-01

Full Text Available Accurate assessment of skeletal maturity is important clinically. Skeletal age assessment is usually based on features encoded in ossification centers. Therefore, it is critical to design a mechanism to capture as much as possible characteristics of features. We have observed that given a feature, there exist stages of the skeletal age such that the variation pattern of the feature differs in these stages. Based on this observation, we propose a Bayesian cut fitting to describe features in response to the skeletal age. With our approach, appropriate positions for stage separation are determined automatically by a Bayesian approach, and a model is used to fit the variation of a feature within each stage. Our experimental results show that the proposed method surpasses the traditional fitting using only one line or one curve not only in the efficiency and accuracy of fitting but also in global and local feature characterization.

Using probabilistic model as feature descriptor on a smartphone device for autonomous navigation of unmanned ground vehicles

Science.gov (United States)

Desai, Alok; Lee, Dah-Jye

2013-12-01

There has been significant research on the development of feature descriptors in the past few years. Most of them do not emphasize real-time applications. This paper presents the development of an affine invariant feature descriptor for low resource applications such as UAV and UGV that are equipped with an embedded system with a small microprocessor, a field programmable gate array (FPGA), or a smart phone device. UAV and UGV have proven suitable for many promising applications such as unknown environment exploration, search and rescue operations. These applications required on board image processing for obstacle detection, avoidance and navigation. All these real-time vision applications require a camera to grab images and match features using a feature descriptor. A good feature descriptor will uniquely describe a feature point thus allowing it to be correctly identified and matched with its corresponding feature point in another image. A few feature description algorithms are available for a resource limited system. They either require too much of the device's resource or too much simplification on the algorithm, which results in reduction in performance. This research is aimed at meeting the needs of these systems without sacrificing accuracy. This paper introduces a new feature descriptor called PRObabilistic model (PRO) for UGV navigation applications. It is a compact and efficient binary descriptor that is hardware-friendly and easy for implementation.

Big data analytics in healthcare: promise and potential.

Science.gov (United States)

Raghupathi, Wullianallur; Raghupathi, Viju

2014-01-01

To describe the promise and potential of big data analytics in healthcare. The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.

Observation and simulation of the ionosphere disturbance waves triggered by rocket exhausts

Science.gov (United States)

Lin, Charles C. H.; Chen, Chia-Hung; Matsumura, Mitsuru; Lin, Jia-Ting; Kakinami, Yoshihiro

2017-08-01

Observations and theoretical modeling of the ionospheric disturbance waves generated by rocket launches are investigated. During the rocket passage, time rate change of total electron content (rTEC) enhancement with the V-shape shock wave signature is commonly observed, followed by acoustic wave disturbances and region of negative rTEC centered along the trajectory. Ten to fifteen min after the rocket passage, delayed disturbance waves appeared and propagated along direction normal to the V-shape wavefronts. These observation features appeared most prominently in the 2016 North Korea rocket launch showing a very distinct V-shape rTEC enhancement over enormous areas along the southeast flight trajectory despite that it was also appeared in the 2009 North Korea rocket launch with the eastward flight trajectory. Numerical simulations using the physical-based nonlinear and nonhydrostatic coupled model of neutral atmosphere and ionosphere reproduce promised results in qualitative agreement with the characteristics of ionospheric disturbance waves observed in the 2009 event by considering the released energy of the rocket exhaust as the disturbance source. Simulations reproduce the shock wave signature of electron density enhancement, acoustic wave disturbances, the electron density depletion due to the rocket-induced pressure bulge, and the delayed disturbance waves. The pressure bulge results in outward neutral wind flows carrying neutrals and plasma away from it and leading to electron density depletions. Simulations further show, for the first time, that the delayed disturbance waves are produced by the surface reflection of the earlier arrival acoustic wave disturbances.

Self-Synchronization: Splendid Promise or Dangerous Delusion

National Research Council Canada - National Science Library

Hatter, Steven

2000-01-01

... with extraordinary efficiency and precision. Proponents of Network-Centric Warfare build upon the optimism in JV 2010 by offering a war-fighting paradigm that promises "an information superiority enabled concept of operations that generates...

Storage of features, conjunctions and objects in visual working memory.

Science.gov (United States)

Vogel, E K; Woodman, G F; Luck, S J

2001-02-01

Working memory can be divided into separate subsystems for verbal and visual information. Although the verbal system has been well characterized, the storage capacity of visual working memory has not yet been established for simple features or for conjunctions of features. The authors demonstrate that it is possible to retain information about only 3-4 colors or orientations in visual working memory at one time. Observers are also able to retain both the color and the orientation of 3-4 objects, indicating that visual working memory stores integrated objects rather than individual features. Indeed, objects defined by a conjunction of four features can be retained in working memory just as well as single-feature objects, allowing many individual features to be retained when distributed across a small number of objects. Thus, the capacity of visual working memory must be understood in terms of integrated objects rather than individual features.

The deepwater Gulf of Mexico : promises delivered?

International Nuclear Information System (INIS)

Pickering, D.R.

1999-01-01

A summary review of deepwater Gulf of Mexico (GOM) oil production was presented for the years 1989 to 1998. Trends and prospects in deepwater GOM production and leasing were assessed. Promises and forecasts made in the early 1990s were compared with what actually happened since then. Forecasts in the early 1990s promised deeper, faster and cheaper developments in the deepwater Gulf. Results of the comparison showed that the prognosticators were correct on all three counts. Regarding the future of the Gulf, one can be justified in being optimistic in so far as more experience, robust economics, more and cheaper rigs can be taken as reliable indicators of optimism. In contrast, there are certain negatives to consider, such as low commodity prices, budget constraints, lease expirations, technical challenges and increased competition. . 12 figs

The promise of cyborg intelligence.

Science.gov (United States)

Brown, Michael F; Brown, Alexander A

2017-03-01

Yu et al. (2016) demonstrated that algorithms designed to find efficient routes in standard mazes can be integrated with the natural processes controlling rat navigation and spatial choices, and they pointed out the promise of such "cyborg intelligence" for biorobotic applications. Here, we briefly describe Yu et al.'s work, explore its relevance to the study of comparative cognition, and indicate how work involving cyborg intelligence would benefit from interdisciplinary collaboration between behavioral scientists and engineers.

Sarcoma Spheroids and Organoids—Promising Tools in the Era of Personalized Medicine

Directory of Open Access Journals (Sweden)

Gianluca Colella

2018-02-01

Full Text Available Cancer treatment is rapidly evolving toward personalized medicine, which takes into account the individual molecular and genetic variability of tumors. Sophisticated new in vitro disease models, such as three-dimensional cell cultures, may provide a tool for genetic, epigenetic, biomedical, and pharmacological research, and help determine the most promising individual treatment. Sarcomas, malignant neoplasms originating from mesenchymal cells, may have a multitude of genomic aberrations that give rise to more than 70 different histopathological subtypes. Their low incidence and high level of histopathological heterogeneity have greatly limited progress in their treatment, and trials of clinical sarcoma are less frequent than trials of other carcinomas. The main advantage of 3D cultures from tumor cells or biopsy is that they provide patient-specific models of solid tumors, and they overcome some limitations of traditional 2D monolayer cultures by reflecting cell heterogeneity, native histologic architectures, and cell–extracellular matrix interactions. Recent advances promise that these models can help bridge the gap between preclinical and clinical research by providing a relevant in vitro model of human cancer useful for drug testing and studying metastatic and dormancy mechanisms. However, additional improvements of 3D models are expected in the future, specifically the inclusion of tumor vasculature and the immune system, to enhance their full ability to capture the biological features of native tumors in high-throughput screening. Here, we summarize recent advances and future perspectives of spheroid and organoid in vitro models of rare sarcomas that can be used to investigate individual molecular biology and predict clinical responses. We also highlight how spheroid and organoid culture models could facilitate the personalization of sarcoma treatment, provide specific clinical scenarios, and discuss the relative strengths and limitations

Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

Directory of Open Access Journals (Sweden)

Dane Brown

2017-07-01

Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

Design features of HTMR-Hybrid Toroidal Magnet Tokamak Reactor

International Nuclear Information System (INIS)

Rosatelli, F.; Avanzini, P.G.; Brunelli, B.; Derchi, D.; Magnasco, M.; Grattarola, M.; Peluffo, M.; Raia, G.; Zampaglione, V.

1985-01-01

The HTMR (Hybrid Toroidal Magnet Tokamak Reactor) conceptual design is aimed to demonstrate the feasibility of a Tokamak reactor which could fulfill the scientific and technological objectives expected from next generation devices (e.g. INTOR-NET) with size and costs as small as possible. An hybrid toroidal field magnet, made up by copper and superconducting coils, seems to be a promising solution, allowing a considerable flexibility in machine performances, so as to gain useful margins in front of the uncertainties in confinement time scaling laws and beta and plasma density limits. In this paper the authors describe the optimization procedure for the hybrid magnet configuration, the main design features of HTMR and the preliminary mechanical calculations of the superconducting toroidal coils

Templates for Rejection: Configuring Attention to Ignore Task-Irrelevant Features

Science.gov (United States)

Arita, Jason T.; Carlisle, Nancy B.; Woodman, Geoffrey F.

2012-01-01

Theories of attention are compatible with the idea that we can bias attention to avoid selecting objects that have known nontarget features. Although this may underlie several existing phenomena, the explicit guidance of attention away from known nontargets has yet to be demonstrated. Here we show that observers can use feature cues (i.e., color)…

Identifying significant environmental features using feature recognition.

Science.gov (United States)

2015-10-01

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

Adaptive weighted local textural features for illumination, expression, and occlusion invariant face recognition

Science.gov (United States)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image

Mathematical Profiles and Problem Solving Abilities of Mathematically Promising Students

Science.gov (United States)

Budak, Ibrahim

2012-01-01

Mathematically promising students are defined as those who have the potential to become the leaders and problem solvers of the future. The purpose of this research is to reveal what problem solving abilities mathematically promising students show in solving non-routine problems and type of profiles they present in the classroom and during problem…

Digital amateur observations of Venus at 0.9μm

Science.gov (United States)

Kardasis, E.

2017-09-01

Venus atmosphere is extremely dynamic, though it is very difficult to observe any features on it in the visible and even in the near-IR range. Digital observations with planetary cameras in recent years routinely produce high-quality images, especially in the near-infrared (0.7-1μm), since IR wavelengths are less influenced by Earth's atmosphere and Venus's atmosphere is partially transparent in this spectral region. Continuous observations over a few hours may track dark atmospheric features in the dayside and determine their motion. In this work we will present such observations and some dark-feature motion measurements at 0.9μm. Ground-based observations at this wavelength are rare and are complementary to in situ observations by JAXA's Akatsuki orbiter, that studies the atmospheric dynamics of Venus also in this band with the IR1 camera.

The Promise of Zoomable User Interfaces

Science.gov (United States)

Bederson, Benjamin B.

2011-01-01

Zoomable user interfaces (ZUIs) have received a significant amount of attention in the 18 years since they were introduced. They have enjoyed some success, and elements of ZUIs are widely used in computers today, although the grand vision of a zoomable desktop has not materialised. This paper describes the premise and promise of ZUIs along with…

Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

Directory of Open Access Journals (Sweden)

Yuchou Chang

2008-02-01

Full Text Available Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

Unsupervised Video Shot Detection Using Clustering Ensemble with a Color Global Scale-Invariant Feature Transform Descriptor

Directory of Open Access Journals (Sweden)

Hong Yi

2008-01-01

Full Text Available Abstract Scale-invariant feature transform (SIFT transforms a grayscale image into scale-invariant coordinates of local features that are invariant to image scale, rotation, and changing viewpoints. Because of its scale-invariant properties, SIFT has been successfully used for object recognition and content-based image retrieval. The biggest drawback of SIFT is that it uses only grayscale information and misses important visual information regarding color. In this paper, we present the development of a novel color feature extraction algorithm that addresses this problem, and we also propose a new clustering strategy using clustering ensembles for video shot detection. Based on Fibonacci lattice-quantization, we develop a novel color global scale-invariant feature transform (CGSIFT for better description of color contents in video frames for video shot detection. CGSIFT first quantizes a color image, representing it with a small number of color indices, and then uses SIFT to extract features from the quantized color index image. We also develop a new space description method using small image regions to represent global color features as the second step of CGSIFT. Clustering ensembles focusing on knowledge reuse are then applied to obtain better clustering results than using single clustering methods for video shot detection. Evaluation of the proposed feature extraction algorithm and the new clustering strategy using clustering ensembles reveals very promising results for video shot detection.

Chitin fulfilling a biomaterials promise

CERN Document Server

Khor, Eugene

2001-01-01

The second edition of Chitin underscores the important factors for standardizing chitin processing and characterization. It captures the essential interplay between chitin's assets and limitations as a biomaterial, placing the past promises of chitin in perspective, addressing its present realities and offering insight into what is required to realize chitin's destiny (including its derivative, chitosan) as a biomaterial of the twenty-first century. This book is an ideal guide for both industrialists and researchers with a vested interest in commercializing chitin.An upd

Immature truncated O-glycophenotype of cancer directly induces oncogenic features

DEFF Research Database (Denmark)

Radhakrishnan, Prakash; Dabelsteen, Sally; Madsen, Frey Brus

2014-01-01

Aberrant expression of immature truncated O-glycans is a characteristic feature observed on virtually all epithelial cancer cells, and a very high frequency is observed in early epithelial premalignant lesions that precede the development of adenocarcinomas. Expression of the truncated O-glycan s...

The features of sporadic hyperbolic meteors observed by television techniques in the period of 2007-2009

Science.gov (United States)

Guliyev, Ayyub; Nabiyev, Shaig

2015-12-01

The features of 238 hyperbolic meteors observed within the framework of the Japanese program SonotaCo in the period of 2007-2009 are investigated in this paper. Irregularity of the eccentricities, explicitly dominance of retrograde orbits over direct ones, absence of domination of perihelia closes the ecliptic, irregular distribution of angular elements for these bodies' orbits were noticed. The values of eccentricities are distributed in the interval from 1 up to 1.31. The significant concentration of these particles perihelia closes the anti-apex of the Sun's peculiarity movements in the Galaxy was noticed. Distribution of elements of orbits in the galactic system of coordinates was considered also, however it was not possible to find the appreciable regularities. The distributions of the distant nodes and MOID-Minimum Orbit Intersection Distance of the hyperbolic meteors relatively to the orbits of the planets-giants were investigated as well. However it was not possible to prove, that the majority of the particles could receive the hyperbolic excess of speed due to the gravitational influence of the planets-giants. The statistics of relation of the hyperbolic meteors with 14 known trans-Neptunian planetary bodies brighter 3m.5 is considered. Testing of the distant nodes and MOID values only for 2003 MW12, 2007 OR10 and Qaoaor have the positive results. In the next stage we have made analogical calculations for the 78 TNO having absolute brightness 5m.5 also and obtained the reasonable results for 9 of them.

CDS, UX, and System Redesign - Promising Techniques and Tools to Bridge the Evidence Gap.

Science.gov (United States)

McGinn, Thomas

2015-01-01

In this special issue of eGEMs, we explore the struggles related to bringing evidence into day-to-day practice, what I define as the "evidence gap." We are all aware of high quality evidence in the form of guidelines, randomized clinical trials for treatments and diagnostic tests, and clinical prediction rules, which are all readily available online. We also know that electronic health records (EHRs) are now ubiquitous in health care and in most practices across the country. How we marry this high quality evidence and the practice of medicine through effective decision support is a major challenge. All of the articles in this issue explore, in some fashion, CDS systems and how we can best bring providers and their work environment to the evidence. We are at the very early stages of the science of usability. Much more research and funding is needed in this area if we hope to improve the dissemination and implementation of evidence in practice. While the featured examples, techniques, and tools in the special issue are a promising start to improving usability and CDS, many of the papers highlight current gaps in knowledge and a great need for generalizable approaches. The great promise is for "learning" approaches to generate new evidence and to integrate this evidence in reliable, patient-centered ways at scale using new technology. Closing the evidence gap is a real possibility, but only if the community works together to innovate and invest in research on the best ways to disseminate, communicate, and implement evidence in practice.

Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

Science.gov (United States)

Kim, Soyeon; Baladandayuthapani, Veerabhadran; Lee, J Jack

2017-06-01

In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results. However, selecting the right amount of penalization is critical to simultaneously achieving these two goals. Standard approaches based on cross-validation (CV) typically provide high prediction accuracy with high true positive rates but at the cost of too many false positives. Alternatively, stability selection (SS) controls the number of false positives, but at the cost of yielding too few true positives. To circumvent these issues, we propose prediction-oriented marker selection (PROMISE), which combines SS with CV to conflate the advantages of both methods. Our application of PROMISE with the lasso and elastic net in data analysis shows that, compared to CV, PROMISE produces sparse solutions, few false positives, and small type I + type II error, and maintains good prediction accuracy, with a marginal decrease in the true positive rates. Compared to SS, PROMISE offers better prediction accuracy and true positive rates. In summary, PROMISE can be applied in many fields to select regularization parameters when the goals are to minimize false positives and maximize prediction accuracy.

The observational analysis of performance in the handball ´s throwing of the Spanish promises selection

Directory of Open Access Journals (Sweden)

Pablo Blanco García

2012-06-01

Full Text Available This work has as objective to analyze the efficiency of the handball´s throwings. For it, there were analyzed five matches that the lower level spanish selection disputed in an european championship. This process was realized by an observational methodology, where were evaluated different parameters related to the handball´s throwing: the model of the throw, distance, position and opposition with regard to the variable goal-no goal. The results found that the variables distance and opposition have an influence in the throwing´s efficiency, so that training of these parameters must be taken into account in the game.Key Words: Observational methodology, Spanish selection, Handball, Throwing,  Efficiency.

Observing nebulae

CERN Document Server

Griffiths, Martin

2016-01-01

This book enables anyone with suitable instruments to undertake an examination of nebulae and see or photograph them in detail. Nebulae, ethereal clouds of gas and dust, are among the most beautiful objects to view in the night sky. These star-forming regions are a common target for observers and photographers. Griffiths describes many of the brightest and best nebulae and includes some challenges for the more experienced observer. Readers learn the many interesting astrophysical properties of these clouds, which are an important subject of study in astronomy and astrobiology. Non-mathematical in approach, the text is easily accessible to anyone with an interest in the subject. A special feature is the inclusion of an observational guide to 70 objects personally observed or imaged by the author. The guide also includes photographs of each object for ease of identification along with their celestial coordinates, magnitudes and other pertinent information. Observing Nebulae provides a ready resource to allow an...

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

Directory of Open Access Journals (Sweden)

Pachet François

2009-01-01

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

A FRAMEWORK OF CHANGE DETECTION BASED ON COMBINED MORPHOLOGICA FEATURES AND MULTI-INDEX CLASSIFICATION

Directory of Open Access Journals (Sweden)

S. Li

2017-09-01

Full Text Available Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI, the differential water index (NDWI are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

Science.gov (United States)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

How to Observe the Sun Safely

CERN Document Server

Macdonald, Lee

2012-01-01

How to Observe the Sun Safely, Second Edition gives all the basic information and advice the amateur astronomer needs to get started in observing our own ever-fascinating star. Unlike many other astronomical objects, you do not need a large telescope or expensive equipment to observe the Sun. And it is possible to take excellent pictures of the Sun with today's low-cost digital cameras! This book surveys what is visible on the Sun and then describes how to record solar features and measure solar activity levels. There is also an account of how to use H-alpha and Calcium-K filters to observe and record prominences and other features of the solar chromosphere, the Sun's inner atmosphere. Because we are just entering a period of high activity on the Sun, following a long, quiet period, this is a great time to get involved with solar observing. Still emphasizing safety first, this Second Edition reflects recent and exciting advances in solar observing equipment. Chapters 6 through 8 have been completely revised ...

Onychomatricoma with misleading features.

Science.gov (United States)

Fayol, J; Baran, R; Perrin, C; Labrousse, F

2000-01-01

Onychomatricoma is a rare tumour of the nail matrix with peculiar clinical and histological features and electron microscopic findings. We report on 5 cases with appearances which were misleading. Three presented as longitudinal melanonychia, a previously unreported observation. One case had the appearance of a cutaneous horn. In 3 of the 5 cases the tumour was associated with an onychomycosis and this may thus have been a predisposing factor in the secondary fungal infestation. Onychomatricoma appears as a multi-faceted tumour which can be mimicked by longitudinal melanonychia and/or onychomycosis.

Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

International Nuclear Information System (INIS)

Khalvati, Farzad; Wong, Alexander; Haider, Masoom A.

2015-01-01

Prostate cancer is the most common form of cancer and the second leading cause of cancer death in North America. Auto-detection of prostate cancer can play a major role in early detection of prostate cancer, which has a significant impact on patient survival rates. While multi-parametric magnetic resonance imaging (MP-MRI) has shown promise in diagnosis of prostate cancer, the existing auto-detection algorithms do not take advantage of abundance of data available in MP-MRI to improve detection accuracy. The goal of this research was to design a radiomics-based auto-detection method for prostate cancer via utilizing MP-MRI data. In this work, we present new MP-MRI texture feature models for radiomics-driven detection of prostate cancer. In addition to commonly used non-invasive imaging sequences in conventional MP-MRI, namely T2-weighted MRI (T2w) and diffusion-weighted imaging (DWI), our proposed MP-MRI texture feature models incorporate computed high-b DWI (CHB-DWI) and a new diffusion imaging modality called correlated diffusion imaging (CDI). Moreover, the proposed texture feature models incorporate features from individual b-value images. A comprehensive set of texture features was calculated for both the conventional MP-MRI and new MP-MRI texture feature models. We performed feature selection analysis for each individual modality and then combined best features from each modality to construct the optimized texture feature models. The performance of the proposed MP-MRI texture feature models was evaluated via leave-one-patient-out cross-validation using a support vector machine (SVM) classifier trained on 40,975 cancerous and healthy tissue samples obtained from real clinical MP-MRI datasets. The proposed MP-MRI texture feature models outperformed the conventional model (i.e., T2w+DWI) with regard to cancer detection accuracy. Comprehensive texture feature models were developed for improved radiomics-driven detection of prostate cancer using MP-MRI. Using a

Results from Joint Observations of Jupiter's Atmosphere by Juno and a Network of Earth-Based Observing Stations

Science.gov (United States)

Orton, G. S.; Bolton, S. J.; Levin, S.; Hansen, C. J.; Janssen, M. A.; Adriani, A.; Gladstone, R.; Bagenal, F.; Ingersoll, A. P.; Momary, T.; Payne, A.

2016-12-01

The Juno mission has promoted and coordinated a network of Earth-based observations, including both space- and ground-based facilities, to extend and enhance observations made by the Juno mission. The spectral region and timeline of all of these observations are summarized in the web site: https://www.missionjuno.swri.edu/planned-observations. Among the earliest of these were observation of Jovian auroral phenomena at X-ray, ultraviolet and infrared wavelengths and measurements of Jovian synchrotron radiation from the Earth simultaneously with the measurement of properties of the upstream solar wind described elsewhere in this meeting. Other observations of significance to the magnetosphere measured the mass loading from Io by tracking its observed volcanic activity and the opacity of its torus. Observations of Jupiter's neutral atmosphere included observations of reflected sunlight from the near-ultraviolet through the near-infrared and thermal emission from 5 microns through the radio region. The point of these measurements is to relate properties of the deep atmosphere that are the focus of Juno's mission to the state of the "weather layer" at much higher atmospheric levels. These observations cover spectral regions not included in Juno's instrumentation, provide spatial context for Juno's often spatially limited coverage of Jupiter, and they describe the evolution of atmospheric features in time that are measured only once by Juno. We will summarize the results of measurements during the approach phase of the mission that characterized the state of the atmosphere, as well as observations made by Juno and the supporting campaign during Juno's perijoves 1 (August 27), 2 (October 19), 3 (November 2), 4 (November 15), and 5 (November 30). The Juno mission also benefited from the enlistment of a network of dedicated amateur astronomers who, besides providing input needed for public operation of the JunoCam visible camera, tracked the evolution of features in Jupiter

Archeomagnetic Intensity Spikes: Global or Regional Geomagnetic Field Features?

Directory of Open Access Journals (Sweden)

Monika Korte

2018-03-01

Full Text Available Variations of the geomagnetic field prior to direct observations are inferred from archeo- and paleomagnetic experiments. Seemingly unusual variations not seen in the present-day and historical field are of particular interest to constrain the full range of core dynamics. Recently, archeomagnetic intensity spikes, characterized by very high field values that appear to be associated with rapid secular variation rates, have been reported from several parts of the world. They were first noted in data from the Levant at around 900 BCE. A recent re-assessment of previous and new Levantine data, involving a rigorous quality assessment, interprets the observations as an extreme local geomagnetic high with at least two intensity spikes between the 11th and 8th centuries BCE. Subsequent reports of similar features from Asia, the Canary Islands and Texas raise the question of whether such features might be common occurrences, or whether they might even be part of a global magnetic field feature. Here we use spherical harmonic modeling to test two hypotheses: firstly, whether the Levantine and other potential spikes might be associated with higher dipole field intensity than shown by existing global field models around 1,000 BCE, and secondly, whether the observations from different parts of the world are compatible with a westward drifting intense flux patch. Our results suggest that the spikes originate from intense flux patches growing and decaying mostly in situ, combined with stronger and more variable dipole moment than shown by previous global field models. Axial dipole variations no more than 60% higher than observed in the present field, probably within the range of normal geodynamo behavior, seem sufficient to explain the observations.

A Broad 22 Micron Emission Feature in the Carina Nebula H ii Region.

Science.gov (United States)

Chan; Onaka

2000-04-10

We report the detection of a broad 22 µm emission feature in the Carina Nebula H ii region by the Infrared Space Observatory (ISO) short-wavelength spectrometer. The feature shape is similar to that of the 22 µm emission feature of newly synthesized dust observed in the Cassiopeia A supernova remnant. This finding suggests that both of the features are arising from the same carrier and that supernovae are probably the dominant production sources of this new interstellar grain. A similar broad emission dust feature is also found in the spectra of two starburst galaxies from the ISO archival data. This new dust grain could be an abundant component of interstellar grains and can be used to trace the supernova rate or star formation rate in external galaxies. The existence of the broad 22 µm emission feature complicates the dust model for starburst galaxies and must be taken into account correctly in the derivation of dust color temperature. Mg protosilicate has been suggested as the carrier of the 22 µm emission dust feature observed in Cassiopeia A. The present results provide useful information in studies on the chemical composition and emission mechanism of the carrier.

Learning representative features for facial images based on a modified principal component analysis

Science.gov (United States)

Averkin, Anton; Potapov, Alexey

2013-05-01

The paper is devoted to facial image analysis and particularly deals with the problem of automatic evaluation of the attractiveness of human faces. We propose a new approach for automatic construction of feature space based on a modified principal component analysis. Input data sets for the algorithm are the learning data sets of facial images, which are rated by one person. The proposed approach allows one to extract features of the individual subjective face beauty perception and to predict attractiveness values for new facial images, which were not included into a learning data set. The Pearson correlation coefficient between values predicted by our method for new facial images and personal attractiveness estimation values equals to 0.89. This means that the new approach proposed is promising and can be used for predicting subjective face attractiveness values in real systems of the facial images analysis.

Perpendicular recording: the promise and the problems

International Nuclear Information System (INIS)

Wood, Roger; Sonobe, Yoshiaki; Jin Zhen; Wilson, Bruce

2001-01-01

Perpendicular recording has long been advocated as a means of achieving the highest areal densities. In particular, in the context of the 'superparamagnetic limit', perpendicular recording with a soft underlayer promises several key advantages. These advantages include a higher coercivity, thicker media that should permit smaller diameter grains and higher signal-to-noise ratio. Also, the sharper edge-writing will facilitate recording at very high track densities (lower bit aspect ratio). Recent demonstrations of the technology have shown densities comparable with the highest densities reported for longitudinal recording. This paper further examines the promise that perpendicular recording will deliver an increase in areal density two to eight times higher than that achievable with longitudinal recording. There are a number of outstanding issues but the key challenge is to create a low-noise medium with a coercivity that is high and is much larger than the remanent magnetization

Human mesenchymal stem cells and biomaterials interaction: a promising synergy to improve spine fusion.

Science.gov (United States)

Barbanti Brodano, G; Mazzoni, E; Tognon, M; Griffoni, C; Manfrini, M

2012-05-01

Spine fusion is the gold standard treatment in degenerative and traumatic spine diseases. The bone regenerative medicine needs (i) in vitro functionally active osteoblasts, and/or (ii) the in vivo induction of the tissue. The bone tissue engineering seems to be a very promising approach for the effectiveness of orthopedic surgical procedures, clinical applications are often hampered by the limited availability of bone allograft or substitutes. New biomaterials have been recently developed for the orthopedic applications. The main characteristics of these scaffolds are the ability to induce the bone tissue formation by generating an appropriate environment for (i) the cell growth and (ii) recruiting precursor bone cells for the proliferation and differentiation. A new prototype of biomaterials known as "bioceramics" may own these features. Bioceramics are bone substitutes mainly composed of calcium and phosphate complex salt derivatives. In this study, the characteristics bioceramics bone substitutes have been tested with human mesenchymal stem cells obtained from the bone marrow of adult orthopedic patients. These cellular models can be employed to characterize in vitro the behavior of different biomaterials, which are used as bone void fillers or three-dimensional scaffolds. Human mesenchymal stem cells in combination with biomaterials seem to be good alternative to the autologous or allogenic bone fusion in spine surgery. The cellular model used in our study is a useful tool for investigating cytocompatibility and biological features of HA-derived scaffolds.

Promising features of Moringa oleifera oil: recent updates and perspectives.

Science.gov (United States)

Nadeem, Muhammad; Imran, Muhammad

2016-12-08

Lipids are the concentrated source of energy, fat soluble vitamins, essential fatty acids, carriers of flavours and many bio-active compounds with important role in maintaining physiological functions of biological body. Moringa oleifera is native to Himalaya and widely grown in many Asian and African countries with seed oil content range from 35-40%. Moringa oleifera oil (MOO) has light yellow colour with mild nutty flavour and fatty acids composition suggests that MOO is highly suitable for both edible and non-edible applications. MOO is extremely resistant to autoxidation which can be used as an antioxidant for the long term stabilization of commercial edible oils. Thermal stability of MOO is greater than soybean, sunflower, canola and cottonseed oils. High oleic contents of MOO are believed to have the capability of increasing beneficial HDL cholesterol and decreased the serum cholesterol and triglycerides. MOO applications have also been explored in cosmetics, folk medicines and skin care formulations. Overall, this review focuses on commercial production status, food applications, antioxidant characteristics, health benefits, thermal stability, fractionation, cholesterol contents, medicinal, nutraceutical action, toxicological evaluation, biodiesel production, personal care formulations and future perspectives of the MOO for the stake holders to process and utilize MOO as a new source of edible oil for industrial purpose.

Promises in intelligent plant control systems

International Nuclear Information System (INIS)

Otaduy, P.J.

1987-01-01

The control system is the brain of a power plant. The traditional goal of control systems has been productivity. However, in nuclear power plants the potential for disaster requires safety to be the dominant concern, and the worldwide political climate demands trustworthiness for nuclear power plants. To keep nuclear generation as a viable option for power in the future, trust is the essential critical goal which encompasses all others. In most of today's nuclear plants the control system is a hybrid of analog, digital, and human components that focuses on productivity and operates under the protective umbrella of an independent engineered safety system. Operation of the plant is complex, and frequent challenges to the safety system occur which impact on their trustworthiness. Advances in nuclear reactor design, computer sciences, and control theory, and in related technological areas such as electronics and communications as well as in data storage, retrieval, display, and analysis have opened a promise for control systems with more acceptable human brain-like capabilities to pursue the required goals. This paper elaborates on the promise of futuristic nuclear power plants with intelligent control systems and addresses design requirements and implementation approaches

Utilizing Multi-Field Text Features for Efficient Email Spam Filtering

Directory of Open Access Journals (Sweden)

Wuying Liu

2012-06-01

Full Text Available Large-scale spam emails cause a serious waste of time and resources. This paper investigates the text features of email documents and the feature noises among multi-field texts, resulting in an observation of a power law distribution of feature strings within each text field. According to the observation, we propose an efficient filtering approach including a compound weight method and a lightweight field text classification algorithm. The compound weight method considers both the historical classifying ability of each field classifier and the classifying contribution of each text field in the current classified email. The lightweight field text classification algorithm straightforwardly calculates the arithmetical average of multiple conditional probabilities predicted from feature strings according to a string-frequency index for labeled emails storing. The string-frequency index structure has a random-sampling-based compressible property owing to the power law distribution and can largely reduce the storage space. The experimental results in the TREC spam track show that the proposed approach can complete the filtering task in low space cost and high speed, whose overall performance 1-ROCA exceeds the best one among the participators at the trec07p evaluation.

Attention improves encoding of task-relevant features in the human visual cortex

Science.gov (United States)

Jehee, Janneke F.M.; Brady, Devin K.; Tong, Frank

2011-01-01

When spatial attention is directed towards a particular stimulus, increased activity is commonly observed in corresponding locations of the visual cortex. Does this attentional increase in activity indicate improved processing of all features contained within the attended stimulus, or might spatial attention selectively enhance the features relevant to the observer’s task? We used fMRI decoding methods to measure the strength of orientation-selective activity patterns in the human visual cortex while subjects performed either an orientation or contrast discrimination task, involving one of two laterally presented gratings. Greater overall BOLD activation with spatial attention was observed in areas V1-V4 for both tasks. However, multivariate pattern analysis revealed that orientation-selective responses were enhanced by attention only when orientation was the task-relevant feature, and not when the grating’s contrast had to be attended. In a second experiment, observers discriminated the orientation or color of a specific lateral grating. Here, orientation-selective responses were enhanced in both tasks but color-selective responses were enhanced only when color was task-relevant. In both experiments, task-specific enhancement of feature-selective activity was not confined to the attended stimulus location, but instead spread to other locations in the visual field, suggesting the concurrent involvement of a global feature-based attentional mechanism. These results suggest that attention can be remarkably selective in its ability to enhance particular task-relevant features, and further reveal that increases in overall BOLD amplitude are not necessarily accompanied by improved processing of stimulus information. PMID:21632942

Prostatic adenocarcinoma with glomeruloid features.

Science.gov (United States)

Pacelli, A; Lopez-Beltran, A; Egan, A J; Bostwick, D G

1998-05-01

A wide variety of architectural patterns of adenocarcinoma may be seen in the prostate. We have recently encountered a hitherto-undescribed pattern of growth characterized by intraluminal ball-like clusters of cancer cells reminiscent of renal glomeruli, which we refer to as prostatic adenocarcinoma with glomeruloid features. To define the architectural features, frequency, and distribution of prostatic adenocarcinoma with glomeruloid features, we reviewed 202 totally embedded radical prostatectomy specimens obtained between October 1992 and April 1994 from the files of the Mayo Clinic. This series was supplemented by 100 consecutive needle biopsies with prostatic cancer from January to February 1996. Prostatic adenocarcinoma with glomeruloid features was characterized by round to oval epithelial tufts growing within malignant acini, often supported by a fibrovascular core. The epithelial cells were sometimes arranged in semicircular concentric rows separated by clefted spaces. In the radical prostatectomy specimens, nine cases (4.5%) had glomeruloid features. The glomeruloid pattern constituted 5% to 20% of each cancer (mean, 8.33%) and was usually located at the apex or in the peripheral zone of the prostate. Seven cases were associated with a high Gleason score (7 or 8), one with a score of 6, and one with a score of 5. All cases were associated with high-grade prostatic intraepithelial neoplasia and extensive perineural invasion. Pathological stages included T2c (three cases), T3b (four cases), and T3c (two cases); one of the T3b cases had lymph node metastases (N1). Three (3%) of 100 consecutive routine needle biopsy specimens with cancer showed glomeruloid features, and this pattern constituted 5% to 10% of each cancer (mean, 6.7%). The Gleason score was 6 for two cases and 8 for one case. Two cases were associated with high-grade prostatic intraepithelial neoplasia, and one case had perineural invasion. Glomeruloid features were not observed in any benign or

77 FR 4550 - Promising and Practical Strategies to Increase Postsecondary Success

Science.gov (United States)

2012-01-30

... education providers, researchers, and institutional faculty and staff, or consortia of such entities, to... providers, researchers, and institutional faculty and staff who can offer information about promising and... intervention. [cir] The theory of action that provides the basis for the promising and practical strategy. [cir...

Large datasets: Segmentation, feature extraction, and compression

Energy Technology Data Exchange (ETDEWEB)

Downing, D.J.; Fedorov, V.; Lawkins, W.F.; Morris, M.D.; Ostrouchov, G.

1996-07-01

Large data sets with more than several mission multivariate observations (tens of megabytes or gigabytes of stored information) are difficult or impossible to analyze with traditional software. The amount of output which must be scanned quickly dilutes the ability of the investigator to confidently identify all the meaningful patterns and trends which may be present. The purpose of this project is to develop both a theoretical foundation and a collection of tools for automated feature extraction that can be easily customized to specific applications. Cluster analysis techniques are applied as a final step in the feature extraction process, which helps make data surveying simple and effective.

An efficient fractal image coding algorithm using unified feature and DCT

International Nuclear Information System (INIS)

Zhou Yiming; Zhang Chao; Zhang Zengke

2009-01-01

Fractal image compression is a promising technique to improve the efficiency of image storage and image transmission with high compression ratio, however, the huge time consumption for the fractal image coding is a great obstacle to the practical applications. In order to improve the fractal image coding, efficient fractal image coding algorithms using a special unified feature and a DCT coder are proposed in this paper. Firstly, based on a necessary condition to the best matching search rule during fractal image coding, the fast algorithm using a special unified feature (UFC) is addressed, and it can reduce the search space obviously and exclude most inappropriate matching subblocks before the best matching search. Secondly, on the basis of UFC algorithm, in order to improve the quality of the reconstructed image, a DCT coder is combined to construct a hybrid fractal image algorithm (DUFC). Experimental results show that the proposed algorithms can obtain good quality of the reconstructed images and need much less time than the baseline fractal coding algorithm.

Interpretation of fingerprint image quality features extracted by self-organizing maps

Science.gov (United States)

Danov, Ivan; Olsen, Martin A.; Busch, Christoph

2014-05-01

Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

Word-level recognition of multifont Arabic text using a feature vector matching approach

Science.gov (United States)

Erlandson, Erik J.; Trenkle, John M.; Vogt, Robert C., III

1996-03-01

Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. An alternative approach is to recognize text imagery at the word level, without analyzing individual characters. This approach avoids the problem of individual character segmentation, and can overcome local errors in character recognition. A word-level recognition system for machine-printed Arabic text has been implemented. Arabic is a script language, and is therefore difficult to segment at the character level. Character segmentation has been avoided by recognizing text imagery of complete words. The Arabic recognition system computes a vector of image-morphological features on a query word image. This vector is matched against a precomputed database of vectors from a lexicon of Arabic words. Vectors from the database with the highest match score are returned as hypotheses for the unknown image. Several feature vectors may be stored for each word in the database. Database feature vectors generated using multiple fonts and noise models allow the system to be tuned to its input stream. Used in conjunction with database pruning techniques, this Arabic recognition system has obtained promising word recognition rates on low-quality multifont text imagery.

Melanoma Vaccines: Mixed Past, Promising Future

Science.gov (United States)

Ozao-Choy, Junko; Lee, Delphine J.; Faries, Mark B.

2014-01-01

Synopsis Cancer vaccines were one of the earliest forms of immunotherapy to be investigated. Past attempts to vaccinate against cancer, including melanoma, have mixed results, revealing the complexity of what was thought to be a simple concept. However, several recent successes and the combination of improved knowledge of tumor immunology and the advent of new immunomodulators make vaccination a promising strategy for the future. PMID:25245965

Feature Article

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. Feature Article. Articles in Resonance – Journal of Science Education. Volume 1 Issue 1 January 1996 pp 80-85 Feature Article. What's New in Computers Windows 95 · Vijnan Shastri · More Details Fulltext PDF. Volume 1 Issue 1 January 1996 pp 86-89 Feature ...

Featureous: A Tool for Feature-Centric Analysis of Java Software

DEFF Research Database (Denmark)

Olszak, Andrzej; Jørgensen, Bo Nørregaard

2010-01-01

Feature-centric comprehension of source code is necessary for incorporating user-requested modifications during software evolution and maintenance. However, such comprehension is difficult to achieve in case of large object-oriented programs due to the size, complexity, and implicit character...... of mappings between features and source code. To support programmers in overcoming these difficulties, we present a feature-centric analysis tool, Featureous. Our tool extends the NetBeans IDE with mechanisms for efficient location of feature implementations in legacy source code, and an extensive analysis...

Interpretation of coronal synoptic observations

International Nuclear Information System (INIS)

Munro, R.H.; Fisher, R.R.

1986-01-01

Three-dimensional reconstruction techniques used to determine coronal density distributions from synoptic data are complicated and time consuming to employ. Current techniques also assume time invariant structures and thus mix both temporal and spatial variations present in the coronal data. The observed distribution of polarized brightness, pB, and brightness, B, of coronal features observed either at eclipses or with coronagraphs depends upon both the three-dimensional distribution of electron density within the structure and the location of the feature with respect to the plane-of-the-sky. By theoretically studying the signature of various coronal structures as they would appear during a limb transit, it is possible to recognize these patterns in real synoptic data as well as estimate temporal evolutionary effects

Computer aided detection of masses in mammography using subregion Hotelling observers

International Nuclear Information System (INIS)

Baydush, Alan H.; Catarious, David M.; Abbey, Craig K.; Floyd, Carey E.

2003-01-01

We propose to investigate the use of the subregion Hotelling observer for the basis of a computer aided detection scheme for masses in mammography. A database of 1320 regions of interest (ROIs) was selected from the DDSM database collected by the University of South Florida using the Lumisys scanner cases. The breakdown of the cases was as follows: 656 normal ROIs, 307 benign ROIs, and 357 cancer ROIs. Each ROI was extracted at a size of 1024x1024 pixels and subsampled to 128x128 pixels. For the detection task, cancer and benign cases were considered positive and normal was considered negative. All positive cases had the lesion centered in the ROI. We chose to investigate the subregion Hotelling observer as a classifier to detect masses. The Hotelling observer incorporates information about the signal, the background, and the noise correlation for prediction of positive and negative and is the optimal detector when these are known. For our study, 225 subregion Hotelling observers were set up in a 15x15 grid across the center of the ROIs. Each separate observer was designed to 'observe', or discriminate, an 8x8 pixel area of the image. A leave one out training and testing methodology was used to generate 225 'features', where each feature is the output of the individual observers. The 225 features derived from separate Hotelling observers were then narrowed down by using forward searching linear discriminants (LDs). The reduced set of features was then analyzed using an additional LD with receiver operating characteristic (ROC) analysis. The 225 Hotelling observer features were searched by the forward searching LD, which selected a subset of 37 features. This subset of 37 features was then analyzed using an additional LD, which gave a ROC area under the curve of 0.9412+/-0.006 and a partial area of 0.6728. Additionally, at 98% sensitivity the overall classifier had a specificity of 55.9% and a positive predictive value of 69.3%. Preliminary results suggest that

Decoding stimulus features in primate somatosensory cortex during perceptual categorization

Science.gov (United States)

Alvarez, Manuel; Zainos, Antonio; Romo, Ranulfo

2015-01-01

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

High-level intuitive features (HLIFs) for intuitive skin lesion description.

Science.gov (United States)

Amelard, Robert; Glaister, Jeffrey; Wong, Alexander; Clausi, David A

2015-03-01

A set of high-level intuitive features (HLIFs) is proposed to quantitatively describe melanoma in standard camera images. Melanoma is the deadliest form of skin cancer. With rising incidence rates and subjectivity in current clinical detection methods, there is a need for melanoma decision support systems. Feature extraction is a critical step in melanoma decision support systems. Existing feature sets for analyzing standard camera images are comprised of low-level features, which exist in high-dimensional feature spaces and limit the system's ability to convey intuitive diagnostic rationale. The proposed HLIFs were designed to model the ABCD criteria commonly used by dermatologists such that each HLIF represents a human-observable characteristic. As such, intuitive diagnostic rationale can be conveyed to the user. Experimental results show that concatenating the proposed HLIFs with a full low-level feature set increased classification accuracy, and that HLIFs were able to separate the data better than low-level features with statistical significance. An example of a graphical interface for providing intuitive rationale is given.

CMB anomalies and the effects of local features of the inflaton potential

Energy Technology Data Exchange (ETDEWEB)

Cadavid, Alexander Gallego [Kyoto University, Yukawa Institute for Theoretical Physics, Kyoto (Japan); ICRANet, Pescara (Italy); Universidad de Antioquia, Instituto de Fisica, Medellin (Colombia); Romano, Antonio Enea [Kyoto University, Yukawa Institute for Theoretical Physics, Kyoto (Japan); University of Torino, Department of Physics, Turin (Italy); Universidad de Antioquia, Instituto de Fisica, Medellin (Colombia); Gariazzo, Stefano [University of Torino, Department of Physics, Turin (Italy); INFN, Sezione di Torino, Turin (Italy); Instituto de Fisica Corpuscular (CSIC-Universitat de Valencia), Paterna, Valencia (Spain)

2017-04-15

Recent analysis of the WMAP and Planck data have shown the presence of a dip and a bump in the spectrum of primordial perturbations at the scales k = 0.002 Mpc{sup -1}, respectively. We analyze for the first time the effects of a local feature in the inflaton potential to explain the observed deviations from scale invariance in the primordial spectrum. We perform a best-fit analysis of the cosmic microwave background (CMB) radiation temperature and polarization data. The effects of the features can improve the agreement with observational data respect to the featureless model. The best-fit local feature affects the primordial curvature spectrum mainly in the region of the bump, leaving the spectrum unaffected on other scales. (orig.)

Promise and deceit: pharmakos, drug replacement therapy, and the perils of experience.

Science.gov (United States)

Meyers, Todd

2014-06-01

The problem of lying as a feature of medication compliance has been well documented in anthropological and clinical literatures. Yet the role of the lie-its destabilizing effects on the continuity of drug treatment and therapy, as a technology of drug misuse, or as a way to understand the neuro-chemical processes of treatment (pharmacotherapy "tricking" or lying to the brain)-has been less considered, particularly in the context of opioid replacement therapy. The following paper is set against the backdrop of a three-year study of adolescents receiving a relatively new drug (buprenorphine) for the treatment of opiate dependency inside and outside of highly monitored treatment environments in the United States. Lies give order not only to the experience of addiction but also to the experience of therapy as well. In order to better understand this ordering of experience, the paper puts the widely discussed conceptual duality of the pharmakon (healing and poison) in conversation with a perilously overlooked subject in the critical study of pharmacotherapy, namely the pharmakos or the personification of sacrifice. The paper demonstrates how the patient-subject comes to represent therapeutic promise by allowing for the possibility of (and often performing) deceit.

Diagnostic Biomarkers for Posttraumatic Stress Disorder: Promising Horizons from Translational Neuroscience Research.

Science.gov (United States)

Michopoulos, Vasiliki; Norrholm, Seth Davin; Jovanovic, Tanja

2015-09-01

Posttraumatic stress disorder (PTSD) is a heterogeneous disorder that affects individuals exposed to trauma (e.g., combat, interpersonal violence, and natural disasters). Although its diagnostic features have been recently reclassified with the emergence of the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition, the disorder remains characterized by hyperarousal, intrusive reminders of the trauma, avoidance of trauma-related cues, and negative cognition and mood. This heterogeneity indicates the presence of multiple neurobiological mechanisms underlying the etiology and maintenance of PTSD. Translational research spanning the past few decades has revealed several potential avenues for the identification of diagnostic biomarkers for PTSD. These include, but are not limited to, monoaminergic transmitter systems, the hypothalamic-pituitary-adrenal axis, metabolic hormonal pathways, inflammatory mechanisms, psychophysiological reactivity, and neural circuits. The current review provides an update to the literature with regard to the most promising putative PTSD biomarkers, with specific emphasis on the interaction between neurobiological influences on disease risk and symptom progression. Such biomarkers will most likely be identified by multi-dimensional models derived from comprehensive descriptions of molecular, neurobiological, behavioral, and clinical phenotypes. Copyright © 2015 Society of Biological Psychiatry. All rights reserved.

Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

Directory of Open Access Journals (Sweden)

Junbao Zheng

2012-03-01

Full Text Available Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into the classification performance of a bionic olfactory model with the increase of the dimensions of input feature vector (outer factor as well as its parallel channels (inner factor. The principal component analysis technique was applied for feature selection and dimension reduction. Two data sets of three classes of wine derived from different cultivars and five classes of green tea derived from five different provinces of China were used for experiments. In the former case the results showed that the average correct classification rate increased as more principal components were put in to feature vector. In the latter case the results showed that sufficient parallel channels should be reserved in the model to avoid pattern space crowding. We concluded that 6~8 channels of the model with principal component feature vector values of at least 90% cumulative variance is adequate for a classification task of 3~5 pattern classes considering the trade-off between time consumption and classification rate.

A multilevel-ROI-features-based machine learning method for detection of morphometric biomarkers in Parkinson's disease.

Science.gov (United States)

Peng, Bo; Wang, Suhong; Zhou, Zhiyong; Liu, Yan; Tong, Baotong; Zhang, Tao; Dai, Yakang

2017-06-09

Machine learning methods have been widely used in recent years for detection of neuroimaging biomarkers in regions of interest (ROIs) and assisting diagnosis of neurodegenerative diseases. The innovation of this study is to use multilevel-ROI-features-based machine learning method to detect sensitive morphometric biomarkers in Parkinson's disease (PD). Specifically, the low-level ROI features (gray matter volume, cortical thickness, etc.) and high-level correlative features (connectivity between ROIs) are integrated to construct the multilevel ROI features. Filter- and wrapper- based feature selection method and multi-kernel support vector machine (SVM) are used in the classification algorithm. T1-weighted brain magnetic resonance (MR) images of 69 PD patients and 103 normal controls from the Parkinson's Progression Markers Initiative (PPMI) dataset are included in the study. The machine learning method performs well in classification between PD patients and normal controls with an accuracy of 85.78%, a specificity of 87.79%, and a sensitivity of 87.64%. The most sensitive biomarkers between PD patients and normal controls are mainly distributed in frontal lobe, parental lobe, limbic lobe, temporal lobe, and central region. The classification performance of our method with multilevel ROI features is significantly improved comparing with other classification methods using single-level features. The proposed method shows promising identification ability for detecting morphometric biomarkers in PD, thus confirming the potentiality of our method in assisting diagnosis of the disease. Copyright © 2017 Elsevier B.V. All rights reserved.

Sexual dimorphism in medulloblastoma features.

Science.gov (United States)

Zannoni, Gian Franco; Ciucci, Alessandra; Marucci, Gianluca; Travaglia, Daniele; Stigliano, Egidio; Foschini, Maria Pia; Scambia, Giovanni; Gallo, Daniela

2016-03-01

Male sex is a risk factor for medulloblastoma (MB), and is also a negative predictor for clinical outcome. The aim of this study was to assess sex differences in tumour biological features and hormone receptor profiles in a cohort of MB patients. Sixty-four MBs and five normal cerebella were included in the study. Cell proliferation (Ki67), apoptosis (cleaved caspase-3) and microvessel density (CD31) were evaluated in tumours by immunohistochemistry. Tissues were analysed for oestrogen receptor (ER)α, ERβ1, ERβ2, ERβ5 and androgen receptor (AR) expression. The results demonstrated sex-specific features in MBs, with tumours from females showing a higher apoptosis/proliferation ratio and less tumour vascularization than tumours from males. MBs were negative for ERα and AR, but expressed ERβ isoforms at similar levels between the sexes. Altogether, these findings indicate that signalling mechanisms that control cell turnover and angiogenesis operate more efficiently in females than in males. The lack of sex differences in the hormone receptor profiles suggests that circulating oestrogens could be the major determinants of the sexual dimorphism observed in MB features. Here, we provide molecular support for epidemiological data showing sex differences in MB incidence and outcome, completely defining the hormone receptor profile of the tumours. © 2015 John Wiley & Sons Ltd.

Elementary epistemological features of machine intelligence

OpenAIRE

Horvat, Marko

2008-01-01

Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of in...

Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy.

Science.gov (United States)

Ranjith, G; Parvathy, R; Vikas, V; Chandrasekharan, Kesavadas; Nair, Suresh

2015-04-01

With the advent of new imaging modalities, radiologists are faced with handling increasing volumes of data for diagnosis and treatment planning. The use of automated and intelligent systems is becoming essential in such a scenario. Machine learning, a branch of artificial intelligence, is increasingly being used in medical image analysis applications such as image segmentation, registration and computer-aided diagnosis and detection. Histopathological analysis is currently the gold standard for classification of brain tumors. The use of machine learning algorithms along with extraction of relevant features from magnetic resonance imaging (MRI) holds promise of replacing conventional invasive methods of tumor classification. The aim of the study is to classify gliomas into benign and malignant types using MRI data. Retrospective data from 28 patients who were diagnosed with glioma were used for the analysis. WHO Grade II (low-grade astrocytoma) was classified as benign while Grade III (anaplastic astrocytoma) and Grade IV (glioblastoma multiforme) were classified as malignant. Features were extracted from MR spectroscopy. The classification was done using four machine learning algorithms: multilayer perceptrons, support vector machine, random forest and locally weighted learning. Three of the four machine learning algorithms gave an area under ROC curve in excess of 0.80. Random forest gave the best performance in terms of AUC (0.911) while sensitivity was best for locally weighted learning (86.1%). The performance of different machine learning algorithms in the classification of gliomas is promising. An even better performance may be expected by integrating features extracted from other MR sequences. © The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

No Effect of Featural Attention on Body Size Aftereffects

Directory of Open Access Journals (Sweden)

Ian David Stephen

2016-08-01

Full Text Available Prolonged exposure to images of narrow bodies has been shown to induce a perceptual aftereffect, such that observers’ point of subjective normality (PSN for bodies shifts towards narrower bodies. The converse effect is shown for adaptation to wide bodies. In low-level stimuli, object attention (attention directed to the object and spatial attention (attention directed to the location of the object have been shown to increase the magnitude of visual aftereffects, while object-based attention enhances the adaptation effect in faces. It is not known whether featural attention (attention directed to a specific aspect of the object affects the magnitude of adaptation effects in body stimuli. Here, we manipulate the attention of Caucasian observers to different featural information in body images, by asking them to rate the fatness or sex typicality of male and female bodies manipulated to appear fatter or thinner than average. PSNs for body fatness were taken at baseline and after adaptation, and a change in PSN (ΔPSN was calculated. A body size adaptation effect was found, with observers who viewed fat bodies showing an increased PSN, and those exposed to thin bodies showing a reduced PSN. However, manipulations of featural attention to body fatness or sex typicality produced equivalent results, suggesting that featural attention may not affect the strength of the body size aftereffect.

Improving Classroom Learning by Collaboratively Observing Human Tutoring Videos while Problem Solving

Science.gov (United States)

Craig, Scotty D.; Chi, Michelene T. H.; VanLehn, Kurt

2009-01-01

Collaboratively observing tutoring is a promising method for observational learning (also referred to as vicarious learning). This method was tested in the Pittsburgh Science of Learning Center's Physics LearnLab, where students were introduced to physics topics by observing videos while problem solving in Andes, a physics tutoring system.…

The role of entry into regional markets in fulfilling brand promise

Directory of Open Access Journals (Sweden)

Ali Ghasemi

2014-12-01

Full Text Available This paper presents an empirical investigation to study the role of entry into regional markets in fulfilling brand promise. The study designs two questionnaires, one for measuring brand promise and the other for measuring export capabilities, in Likert scale and distributes it among 250 randomly selected producers who were involved in production and development of various products in city of Esfahan, Iran. Cronbach alphas were calculated for brand promise and export capabilities as 0.856 and 0.812, respectively. Using structural equation modeling, the study has detected seven factors including product development, public advocacy, strategic orientation, customer satisfaction, competitive pressures, organizational capabilities and distribution strategies.

Divided spatial attention and feature-mixing errors.

Science.gov (United States)

Golomb, Julie D

2015-11-01

Spatial attention is thought to play a critical role in feature binding. However, often multiple objects or locations are of interest in our environment, and we need to shift or split attention between them. Recent evidence has demonstrated that shifting and splitting spatial attention results in different types of feature-binding errors. In particular, when two locations are simultaneously sharing attentional resources, subjects are susceptible to feature-mixing errors; that is, they tend to report a color that is a subtle blend of the target color and the color at the other attended location. The present study was designed to test whether these feature-mixing errors are influenced by target-distractor similarity. Subjects were cued to split attention across two different spatial locations, and were subsequently presented with an array of colored stimuli, followed by a postcue indicating which color to report. Target-distractor similarity was manipulated by varying the distance in color space between the two attended stimuli. Probabilistic modeling in all cases revealed shifts in the response distribution consistent with feature-mixing errors; however, the patterns differed considerably across target-distractor color distances. With large differences in color, the findings replicated the mixing result, but with small color differences, repulsion was instead observed, with the reported target color shifted away from the other attended color.

On the Origin of the 3.3 μ m Unidentified Infrared Emission Feature

Energy Technology Data Exchange (ETDEWEB)

Sadjadi, Seyedabdolreza; Zhang, Yong; Kwok, Sun, E-mail: sunkwok@hku.hk [Laboratory for Space Research, Faculty of Science, The University of Hong Kong, Pokfulam Road, Hong Kong (China)

2017-08-20

The 3.3 μ m unidentified infrared emission feature is commonly attributed to the C–H stretching band of aromatic molecules. Astronomical observations have shown that this feature is composed of two separate bands at 3.28 and 3.30 μ m, and the origin of these two bands is unclear. In this paper, we perform vibrational analyses based on quantum mechanical calculations of 153 organic molecules, including both pure aromatic molecules and molecules with mixed aromatic/olefinic/aliphatic hydridizations. We find that many of the C–H stretching vibrational modes in polycyclic aromatic hydrocarbon (PAH) molecules are coupled. Even considering the uncoupled modes only, the correlation between the band intensity ratios and the structure of the PAH molecule is not observed, and the 3.28 and 3.30 μ m features cannot be directly interpreted in the PAH model. Based on these results, the possible aromatic, olefinic, and aliphatic origins of the 3.3 μ m feature are discussed. We suggest that the 3.28 μ m feature is assigned to aromatic C–H stretch whereas the 3.30 μ m feature is olefinic. From the ratio of these two features, the relative olefinic to aromatic content of the carrier can be determined.

Machine learning spatial geometry from entanglement features

Science.gov (United States)

You, Yi-Zhuang; Yang, Zhao; Qi, Xiao-Liang

2018-02-01

Motivated by the close relations of the renormalization group with both the holography duality and the deep learning, we propose that the holographic geometry can emerge from deep learning the entanglement feature of a quantum many-body state. We develop a concrete algorithm, call the entanglement feature learning (EFL), based on the random tensor network (RTN) model for the tensor network holography. We show that each RTN can be mapped to a Boltzmann machine, trained by the entanglement entropies over all subregions of a given quantum many-body state. The goal is to construct the optimal RTN that best reproduce the entanglement feature. The RTN geometry can then be interpreted as the emergent holographic geometry. We demonstrate the EFL algorithm on a 1D free fermion system and observe the emergence of the hyperbolic geometry (AdS3 spatial geometry) as we tune the fermion system towards the gapless critical point (CFT2 point).

[11C]NS8880, a promising PET radiotracer targeting the norepinephrine transporter

DEFF Research Database (Denmark)

Vase, Karina Højrup; Peters, Dan; Nielsen, Elsebeth Ø

2014-01-01

-azabicyclo[3.2.1]octane (NS8880), targeting NET. NS8880 has an in vitro binding profile comparable to desipramine and is structurally not related to reboxetine. METHODS: Labeling of NS8880 with [11C] was achieved by a non-conventional technique: substitution of pyridinyl fluorine with [11C]methanolate...... yields with high purity. The PET in vivo evaluation in pig and rat revealed a rapid brain uptake of [11C]NS8880 and fast obtaining of equilibrium. Highest binding was observed in thalamic and hypothalamic regions. Pretreatment with desipramine efficiently reduced binding of [11C]NS8880. CONCLUSION: Based...... on the pre-clinical results obtained so far [11C]NS8880 displays promising properties for PET imaging of NET....

Carnosol: a promising anti-cancer and anti-inflammatory agent.

Science.gov (United States)

Johnson, Jeremy J

2011-06-01

The Mediterranean diet and more specifically certain meats, fruits, vegetables, and olive oil found in certain parts of the Mediterranean region have been associated with a decreased cardiovascular and diabetes risk. More recently, several population based studies have observed with these lifestyle choices have reported an overall reduced risk for several cancers. One study in particular observed an inverse relationship between consumption of Mediterranean herbs such as rosemary, sage, parsley, and oregano with lung cancer. In light of these findings there is a need to explore and identify the anti-cancer properties of these medicinal herbs and to identify the phytochemicals therein. One agent in particular, carnosol, has been evaluated for anti-cancer property in prostate, breast, skin, leukemia, and colon cancer with promising results. These studies have provided evidence that carnosol targets multiple deregulated pathways associated with inflammation and cancer that include nuclear factor kappa B (NFκB), apoptotic related proteins, phosphatidylinositol-3-kinase (PI3 K)/Akt, androgen and estrogen receptors, as well as molecular targets. In addition, carnosol appears to be well tolerated in that it has a selective toxicity towards cancer cells versus non-tumorigenic cells and is well tolerated when administered to animals. This mini-review reports on the pre-clinical studies that have been performed to date with carnosol describing mechanistic, efficacy, and safety/tolerability studies as a cancer chemoprevention and anti-cancer agent. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Comparative study on the performance of textural image features for active contour segmentation.

Science.gov (United States)

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

PRE-ERUPTION OSCILLATIONS IN THIN AND LONG FEATURES IN A QUIESCENT FILAMENT

International Nuclear Information System (INIS)

Joshi, Anand D.; Hanaoka, Yoichiro; Suematsu, Yoshinori; Morita, Satoshi; Yurchyshyn, Vasyl; Cho, Kyung-Suk

2016-01-01

We investigate the eruption of a quiescent filament located close to an active region. Large-scale activation was observed in only half of the filament in the form of pre-eruption oscillations. Consequently only this half erupted nearly 30 hr after the oscillations commenced. Time-slice diagrams of 171 Å images from the Atmospheric Imaging Assembly were used to study the oscillations. These were observed in several thin and long features connecting the filament spine to the chromosphere below. This study traces the origin of such features and proposes their possible interpretation. Small-scale magnetic flux cancellation accompanied by a brightening was observed at the footpoint of the features shortly before their appearance, in images recorded by the Helioseismic and Magnetic Imager. A slow rise of the filament was detected in addition to the oscillations, indicating a gradual loss of equilibrium. Our analysis indicates that a change in magnetic field connectivity between two neighbouring active regions and the quiescent filament resulted in a weakening of the overlying arcade of the filament, leading to its eruption. It is also suggested that the oscillating features are filament barbs, and the oscillations are a manifestation during the pre-eruption phase of the filaments.

PRE-ERUPTION OSCILLATIONS IN THIN AND LONG FEATURES IN A QUIESCENT FILAMENT

Energy Technology Data Exchange (ETDEWEB)

Joshi, Anand D.; Hanaoka, Yoichiro; Suematsu, Yoshinori; Morita, Satoshi [National Astronomical Observatory of Japan, Mitaka, Tokyo 181-8588 (Japan); Yurchyshyn, Vasyl; Cho, Kyung-Suk, E-mail: anand.joshi@nao.ac.jp [Korea Astronomy and Space Science Institute, Daejeon 34055 (Korea, Republic of)

2016-12-20

We investigate the eruption of a quiescent filament located close to an active region. Large-scale activation was observed in only half of the filament in the form of pre-eruption oscillations. Consequently only this half erupted nearly 30 hr after the oscillations commenced. Time-slice diagrams of 171 Å images from the Atmospheric Imaging Assembly were used to study the oscillations. These were observed in several thin and long features connecting the filament spine to the chromosphere below. This study traces the origin of such features and proposes their possible interpretation. Small-scale magnetic flux cancellation accompanied by a brightening was observed at the footpoint of the features shortly before their appearance, in images recorded by the Helioseismic and Magnetic Imager. A slow rise of the filament was detected in addition to the oscillations, indicating a gradual loss of equilibrium. Our analysis indicates that a change in magnetic field connectivity between two neighbouring active regions and the quiescent filament resulted in a weakening of the overlying arcade of the filament, leading to its eruption. It is also suggested that the oscillating features are filament barbs, and the oscillations are a manifestation during the pre-eruption phase of the filaments.

Complexity of Propositional Proofs Under a Promise

Czech Academy of Sciences Publication Activity Database

Dershowitz, N.; Tzameret, Iddo

2010-01-01

Roč. 11, č. 3 (2010), s. 1-29 ISSN 1529-3785 Institutional research plan: CEZ:AV0Z10190503 Keywords : theory * promise problems * propositional proof complexity * random 3CNF * resolution Subject RIV: BA - General Mathematics Impact factor: 1.391, year: 2010 http://dl.acm.org/ citation .cfm?doid=1740582.1740586

Complexity of Propositional Proofs Under a Promise

Czech Academy of Sciences Publication Activity Database

Dershowitz, N.; Tzameret, Iddo

2010-01-01

Roč. 11, č. 3 (2010), s. 1-29 ISSN 1529-3785 Institutional research plan: CEZ:AV0Z10190503 Keywords : theory * promise problems * propositional proof complexity * random 3CNF * resolution Subject RIV: BA - General Mathematics Impact factor: 1.391, year: 2010 http://dl.acm.org/citation.cfm?doid=1740582.1740586

Promising carbons for supercapacitors derived from fungi

Energy Technology Data Exchange (ETDEWEB)

Zhu, Hui; Wang, Xiaolei; Yang, Fan; Yang, Xiurong [State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022 (China)

2011-06-24

Activated carbons with promising performance in capacitors are produced from fungi via a hydrothermal assistant pyrolysis approach. This study introduces a facile strategy to discover carbonaceous materials and triggers interest in exploring fungi for material science applications. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Coordinated Mapping of Sea Ice Deformation Features with Autonomous Vehicles

Science.gov (United States)

Maksym, T.; Williams, G. D.; Singh, H.; Weissling, B.; Anderson, J.; Maki, T.; Ackley, S. F.

2016-12-01

Decreases in summer sea ice extent in the Beaufort and Chukchi Seas has lead to a transition from a largely perennial ice cover, to a seasonal ice cover. This drives shifts in sea ice production, dynamics, ice types, and thickness distribution. To examine how the processes driving ice advance might also impact the morphology of the ice cover, a coordinated ice mapping effort was undertaken during a field campaign in the Beaufort Sea in October, 2015. Here, we present observations of sea ice draft topography from six missions of an Autonomous Underwater Vehicle run under different ice types and deformation features observed during autumn freeze-up. Ice surface features were also mapped during coordinated drone photogrammetric missions over each site. We present preliminary results of a comparison between sea ice surface topography and ice underside morphology for a range of sample ice types, including hummocked multiyear ice, rubble fields, young ice ridges and rafts, and consolidated pancake ice. These data are compared to prior observations of ice morphological features from deformed Antarctic sea ice. Such data will be useful for improving parameterizations of sea ice redistribution during deformation, and for better constraining estimates of airborne or satellite sea ice thickness.

Radar observations of Mercury

International Nuclear Information System (INIS)

Harmon, J.K.; Campbell, D.B.

1988-01-01

Some of the radar altimetry profiles of Mercury obtained on the basis of data from the Arecibo Observatory are presented. In these measurements, the delay-Doppler method was used to measure altitudes along the Doppler equator, rather than to map radar reflectivity. The profiles, derived from observations made over a 6-yr period, provide extensive coverage over a restricted equatorial band and permit the identification of radar signatures for features as small as 50-km diameter craters and 1-km-high arcuate scarps. The data allowed identification of large-scale topographic features such as smooth plains subsidence zones and major highland regions

Surgical trauma induces overgrowth in lower limb gigantism: regulation with use of rapamycin is promising.

Science.gov (United States)

Pinto, Rohan Sebastian; Harrison, William David; Graham, Kenneth; Nayagam, Durai

2018-01-04

We describe an unclassified overgrowth syndrome characterised by unregulated growth of dermal fibroblasts in the lower limbs of a 35-year-old woman. A PIK3CA gene mutation resulted in lower limb gigantism. Below the waist, she weighed 117 kg with each leg measuring over 100 cm in circumference. Her total adiposity was 50% accounted for by her legs mainly. Liposuction and surgical debulking were performed to reduce the size of the limbs but had exacerbated the overgrowth in her lower limbs. Systemic sepsis from an infected foot ulcer necessitated treatment by an above-knee amputation. Postoperatively, the stump increased in size by 19 kg. A trial of rapamycin to reverse the growth of the stump has shown promise. We discuss the clinical and genetic features of this previously unclassified disorder and the orthopaedic considerations involved. © BMJ Publishing Group Ltd (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

Science.gov (United States)

Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.;

Definitions of engineered safety features and related features for nuclear power plants

International Nuclear Information System (INIS)

1986-01-01

In light water moderated, light water cooled nuclear power plants, definitions are given of engineered safety features which are designed to suppress or prevent dispersion of radioactive materials due to damage etc. of fuel at the times of power plant failures, and of related features which are designed to actuate or operate the engineered safety features. Contents are the following: scope of engineered safety features and of related features; classification of engineered safety features (direct systems and indirect systems) and of related features (auxiliaries, emergency power supply, and protective means). (Mori, K.)

Feature extraction using convolutional neural network for classifying breast density in mammographic images

Science.gov (United States)

Thomaz, Ricardo L.; Carneiro, Pedro C.; Patrocinio, Ana C.

2017-03-01

Breast cancer is the leading cause of death for women in most countries. The high levels of mortality relate mostly to late diagnosis and to the direct proportionally relationship between breast density and breast cancer development. Therefore, the correct assessment of breast density is important to provide better screening for higher risk patients. However, in modern digital mammography the discrimination among breast densities is highly complex due to increased contrast and visual information for all densities. Thus, a computational system for classifying breast density might be a useful tool for aiding medical staff. Several machine-learning algorithms are already capable of classifying small number of classes with good accuracy. However, machinelearning algorithms main constraint relates to the set of features extracted and used for classification. Although well-known feature extraction techniques might provide a good set of features, it is a complex task to select an initial set during design of a classifier. Thus, we propose feature extraction using a Convolutional Neural Network (CNN) for classifying breast density by a usual machine-learning classifier. We used 307 mammographic images downsampled to 260x200 pixels to train a CNN and extract features from a deep layer. After training, the activation of 8 neurons from a deep fully connected layer are extracted and used as features. Then, these features are feedforward to a single hidden layer neural network that is cross-validated using 10-folds to classify among four classes of breast density. The global accuracy of this method is 98.4%, presenting only 1.6% of misclassification. However, the small set of samples and memory constraints required the reuse of data in both CNN and MLP-NN, therefore overfitting might have influenced the results even though we cross-validated the network. Thus, although we presented a promising method for extracting features and classifying breast density, a greater database is

Hard X-ray observations of the Her X-1 line feature

International Nuclear Information System (INIS)

Manchanda, R.K.; Vialetto, G.; Bazzano, A.; La Padula, C.; Polcaro, V.F.; Ubertini, P.

1982-01-01

We have carried out two observations separated by a year in 1980 and 1981 during the mid-on phase of Her X-1, by using xenon filled multi-wire proportional chambers. This paper presents the time-averaged spectral results of Her X-1 in the 15-150 keV energy range. The possible case of the line centroid variability seen during 1980 experiment is also discussed. (orig./WL)

Interplay of static and dynamic features in biomimetic smart ears.

Science.gov (United States)

Pannala, Mittu; Meymand, Sajjad Zeinoddini; Müller, Rolf

2013-06-01

Horseshoe bats (family Rhinolophidae) have sophisticated biosonar systems with outer ears (pinnae) that are characterized by static local shape features as well as dynamic non-rigid changes to their overall shapes. Here, biomimetic prototypes fabricated from elastic rubber sheets have been used to study the impact of these static and dynamic features on the acoustic device characteristics. The basic shape of the prototypes was an obliquely truncated horn augmented with three static local shape features: vertical ridge, pinna-rim incision and frontal flap (antitragus). The prototype shape was deformed dynamically using a one-point actuation mechanism to produce a biomimetic bending of the prototype's tip. In isolation, the local shape features had little impact on the device beampattern. However, strong interactions were observed between these features and the overall deformation. The further the prototype tip was bent down, the stronger the beampatterns associated with combinations of multiple features differed from the upright configuration in the prominence of sidelobes. This behavior was qualitatively similar to numerical predictions for horseshoe bats. Hence, the interplay between static and dynamic features could be a bioinspired principle for affecting large changes through the dynamic manipulations of interactions that are sensitive to small geometrical changes.

Dynamic Moss Observed with Hi-C

Science.gov (United States)

Alexander, Caroline; Winebarger, Amy; Morton, Richard; Savage, Sabrina

2014-01-01

The High-resolution Coronal Imager (Hi-C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi-C imaged a large active region (AR11520) with 0.2-0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi-C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi-C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Synthesis of o-Alkenylated 2-Arylbenzoxazoles via Rh-Catalyzed Oxidative Olefination of 2-Arylbenzoxazoles: Scope Investigation, Structural Features, and Mechanism Studies.

Science.gov (United States)

Zhou, Quan; Zhang, Jing-Fan; Cao, Hui; Zhong, Rui; Hou, Xiu-Feng

2016-12-16

2-Arylbenzazoles are promising molecules for potential applications in medicine and material areas. Efficient protocols for direct regioselective functionalization of 2-arylbenzoxazoles are in high demand. Herein, we disclose a general method for selective ortho-olefination of 2-arylbenzo[d]oxazoles with alkenes enabled by versatile Cp*Rh(III) in high yields. This protocol features broad functional group tolerance and high regioselectivity. Intermolecular competition studies and kinetic isotope effect experiments imply that the oxidative olefination process occurs via an electrophilic C-H activation pathway. The molecular structure of the m-fluoro-substituted olefination product confirms regioselective C-H activation/olefination at the more hindered site in cases where the meta F atom or heteroatom substituent existed. Apparent torsion angles were observed in the structures of mono- and bis-olefination products, which resulted in distinct different chemical shifts of olefinic protons. Additionally, two gram-scale reactions and further transformation experiments demonstrate that this method is practical for synthesis of ortho-alkenylated 2-arylbenzoxazole derivatives.

Evaluating Observation Influence on Regional Water Budgets in Reanalyses

Science.gov (United States)

Bosilovich, Michael G.; Chern, Jiun-Dar; Mocko, David; Robertson, Franklin R.; daSilva, Arlindo M.

2014-01-01

The assimilation of observations in reanalyses incurs the potential for the physical terms of budgets to be balanced by a term relating the fit of the observations relative to a forecast first guess analysis. This may indicate a limitation in the physical processes of the background model, or perhaps inconsistencies in the observing system and its assimilation. In the MERRA reanalysis, an area of long term moisture flux divergence over land has been identified over the Central United States. Here, we evaluate the water vapor budget in this region, taking advantage of two unique features of the MERRA diagnostic output; 1) a closed water budget that includes the analysis increment and 2) a gridded diagnostic output data set of the assimilated observations and their innovations (e.g. forecast departures). In the Central United States, an anomaly occurs where the analysis adds water to the region, while precipitation decreases and moisture flux divergence increases. This is related more to a change in the observing system than to a deficiency in the model physical processes. MERRAs Gridded Innovations and Observations (GIO) data narrow the observations that influence this feature to the ATOVS and Aqua satellites during the 06Z and 18Z analysis cycles. Observing system experiments further narrow the instruments that affect the anomalous feature to AMSUA (mainly window channels) and AIRS. This effort also shows the complexities of the observing system, and the reactions of the regional water budgets in reanalyses to the assimilated observations.

Promising change, delivering continuity

DEFF Research Database (Denmark)

Lund, Jens Friis; Sungusia, Eliezeri; Mabele, Mathew Bukhi

2017-01-01

REDD+ is an ambition to reduce carbon emissions from deforestation and forest degradation in the Global South. This ambition has generated unprecedented commitment of political support and financial funds for the forest-development sector. Many academics and people-centered advocacy organizations...... have conceptualized REDD+ as an example of ‘‘green grabbing” and have voiced fears of a potential global rush for land and trees. In this paper we argue that, in practice and up until now, REDD+ resembles longstanding dynamics of the development and conservation industry, where the promise of change...... becomes a discursive commodity that is constantly reproduced and used to generate value and appropriate financial resources. We thus argue for a re-conceptualization of REDD+ as a conservation fad within the broader political economy of development and conservation. We derive this argument from a study...

Recognition of grasp types through principal components of DWT based EMG features.

Science.gov (United States)

Kakoty, Nayan M; Hazarika, Shyamanta M

2011-01-01

With the advancement in machine learning and signal processing techniques, electromyogram (EMG) signals have increasingly gained importance in man-machine interaction. Multifingered hand prostheses using surface EMG for control has appeared in the market. However, EMG based control is still rudimentary, being limited to a few hand postures based on higher number of EMG channels. Moreover, control is non-intuitive, in the sense that the user is required to learn to associate muscle remnants actions to unrelated posture of the prosthesis. Herein lies the promise of a low channel EMG based grasp classification architecture for development of an embedded intelligent prosthetic controller. This paper reports classification of six grasp types used during 70% of daily living activities based on two channel forearm EMG. A feature vector through principal component analysis of discrete wavelet transform coefficients based features of the EMG signal is derived. Classification is through radial basis function kernel based support vector machine following preprocessing and maximum voluntary contraction normalization of EMG signals. 10-fold cross validation is done. We have achieved an average recognition rate of 97.5%. © 2011 IEEE

Running of featureful primordial power spectra

Science.gov (United States)

Gariazzo, Stefano; Mena, Olga; Miralles, Victor; Ramírez, Héctor; Boubekeur, Lotfi

2017-06-01

Current measurements of the temperature and polarization anisotropy power spectra of the cosmic microwave background (CMB) seem to indicate that the naive expectation for the slow-roll hierarchy within the most simple inflationary paradigm may not be respected in nature. We show that a primordial power spectrum with localized features could in principle give rise to the observed slow-roll anarchy when fitted to a featureless power spectrum. From a model comparison perspective, and assuming that nature has chosen a featureless primordial power spectrum, we find that, while with mock Planck data there is only weak evidence against a model with localized features, upcoming CMB missions may provide compelling evidence against such a nonstandard primordial power spectrum. This evidence could be reinforced if a featureless primordial power spectrum is independently confirmed from bispectrum and/or galaxy clustering measurements.

Mid-Infrared Silicate Dust Features in Seyfert 1 Spectra

Science.gov (United States)

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.

Odontogenic keratocyst radiographic features

International Nuclear Information System (INIS)

Nartey, N. O.; Saini, T.

1990-01-01

The clinical features often patients with odontogenic keratocysts were studied. One patient had Gorlin-GoJtz syndrome. A total of fourteen radiolucent lesions were observed on radiographic examination. All the fourteen lesions were diagnosed as odontogenic keratocyst after histopathclogical examination of biopsied tissue from the patients. The age at diagnosis ranged from 25-72 years with a mean age of 37.6 years. The male : female ratio was 2.3:1. Thirteen of these lesions occurred in the mandible, nine involved the mandibular third molar region. Involvement of the ramus of the mandible produced a sausage-shaped radiolucency. Cystic lesions which have been present for long periods of time showed scalloped margins, due to the regional resorption of the surrounding bone. The bony ledges present on the cortical bones simulated multilocular appearance in such cases. It was also observed that the lesions in older individuals perforated the cortical plates rather than eliciting a periostally induced bony expansion. (author)

Classification of Alzheimer's disease patients with hippocampal shape wrapper-based feature selection and support vector machine

Science.gov (United States)

Young, Jonathan; Ridgway, Gerard; Leung, Kelvin; Ourselin, Sebastien

2012-02-01

It is well known that hippocampal atrophy is a marker of the onset of Alzheimer's disease (AD) and as a result hippocampal volumetry has been used in a number of studies to provide early diagnosis of AD and predict conversion of mild cognitive impairment patients to AD. However, rates of atrophy are not uniform across the hippocampus making shape analysis a potentially more accurate biomarker. This study studies the hippocampi from 226 healthy controls, 148 AD patients and 330 MCI patients obtained from T1 weighted structural MRI images from the ADNI database. The hippocampi are anatomically segmented using the MAPS multi-atlas segmentation method, and the resulting binary images are then processed with SPHARM software to decompose their shapes as a weighted sum of spherical harmonic basis functions. The resulting parameterizations are then used as feature vectors in Support Vector Machine (SVM) classification. A wrapper based feature selection method was used as this considers the utility of features in discriminating classes in combination, fully exploiting the multivariate nature of the data and optimizing the selected set of features for the type of classifier that is used. The leave-one-out cross validated accuracy obtained on training data is 88.6% for classifying AD vs controls and 74% for classifying MCI-converters vs MCI-stable with very compact feature sets, showing that this is a highly promising method. There is currently a considerable fall in accuracy on unseen data indicating that the feature selection is sensitive to the data used, however feature ensemble methods may overcome this.

Congestion Service Facilities Location Problem with Promise of Response Time

Directory of Open Access Journals (Sweden)

Dandan Hu

2013-01-01

Full Text Available In many services, promise of specific response time is advertised as a commitment by the service providers for the customer satisfaction. Congestion on service facilities could delay the delivery of the services and hurts the overall satisfaction. In this paper, congestion service facilities location problem with promise of response time is studied, and a mixed integer nonlinear programming model is presented with budget constrained. The facilities are modeled as M/M/c queues. The decision variables of the model are the locations of the service facilities and the number of servers at each facility. The objective function is to maximize the demands served within specific response time promised by the service provider. To solve this problem, we propose an algorithm that combines greedy and genetic algorithms. In order to verify the proposed algorithm, a lot of computational experiments are tested. And the results demonstrate that response time has a significant impact on location decision.

Luminescent features of sol–gel derived rare-earth multi-doped oxyfluoride nano-structured phosphors for white LED application

International Nuclear Information System (INIS)

Gouveia-Neto, A.S.; Silva, A.F. da; Bueno, L.A.; Costa, E.B. da

2012-01-01

Rare-earth doped oxyfluoride 75SiO 2 :25PbF 2 nano-structured phosphors for white-light-emitting diodes were synthesized by thermal treatment of precursor sol–gel derived glasses. Room temperature luminescence features of Eu 3+ , Sm 3+ , Tb 3+ , Eu 3+ /Tb 3+ , and Sm 3+ /Tb 3+ ions incorporated into low-phonon-energy PbF 2 nanocrystals dispersed in the aluminosilicate glass matrix and excited with UV light emitting diode were investigated. The luminescence spectra exhibited strong emission signals in the red (600, 610, 625, and 646 nm), green (548 and 560 nm), and blue (485 nm) wavelength regions. White-light emission was observed in Sm/Tb and Eu/Tb double-doped activated phosphors employing UV-LED excitation at 395 nm. The dependence of the luminescence emission intensities upon annealing temperature and rare-earth concentration was also examined. The results indicated that there exist optimum annealing temperature and activator ion concentration in order to obtain intense visible emission light with high color rendering index. The study suggests that the nanocomposite phosphor based upon 75SiO 2 :25PbF 2 host herein reported is a promising contender for white-light LED applications. - Highlights: ► White-light emission in double-doped activated phosphors employing UV-LED excitation. ► Luminescent features of europium, samarium, and terbium in nanocrystals dispersed in aluminosilicate glass. ► New nanocomposite phosphor host for white-light LED applications.

Suppressing epidemics on networks by exploiting observer nodes.

Science.gov (United States)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Suppressing epidemics on networks by exploiting observer nodes

Science.gov (United States)

Takaguchi, Taro; Hasegawa, Takehisa; Yoshida, Yuichi

2014-07-01

To control infection spreading on networks, we investigate the effect of observer nodes that recognize infection in a neighboring node and make the rest of the neighbor nodes immune. We numerically show that random placement of observer nodes works better on networks with clustering than on locally treelike networks, implying that our model is promising for realistic social networks. The efficiency of several heuristic schemes for observer placement is also examined for synthetic and empirical networks. In parallel with numerical simulations of epidemic dynamics, we also show that the effect of observer placement can be assessed by the size of the largest connected component of networks remaining after removing observer nodes and links between their neighboring nodes.

Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching.

Science.gov (United States)

Machado, Inês; Toews, Matthew; Luo, Jie; Unadkat, Prashin; Essayed, Walid; George, Elizabeth; Teodoro, Pedro; Carvalho, Herculano; Martins, Jorge; Golland, Polina; Pieper, Steve; Frisken, Sarah; Golby, Alexandra; Wells, William

2018-06-04

The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.

Stennis observes Women's History Month

Science.gov (United States)

2010-01-01

NASA John C. Stennis Space Center employees observed Women's History Month on March 17 with a panel discussion that featured accomplished women of the facility. The gathering featured (l to r): Pam Covington, manager of the NASA Office of External Affairs at Stennis; Mary Jones, assistant chief of staff with the Navy Meterology & Oceanography Command; and Lauren Underwood, senior research scientist with Science Systems and Applications, Inc. In addition to the panel discussion, the Stennis Diversity Council and Patriot Technologies also hosted a pair of 'lunch-and-learn' sessions focused on women's issues and history. The luncheons featured videos on Sally Hemings, the slave widely recognized as the mistress of President Thomas Jefferson; and several mothers of U.S. presidents.

Radiographic Features of Acute Patellar Tendon Rupture.

Science.gov (United States)

Fazal, Muhammad Ali; Moonot, Pradeep; Haddad, Fares

2015-11-01

The purpose of our study was to assess soft tissue features of acute patellar tendon rupture on lateral knee radiograph that would facilitate early diagnosis. The participants were divided into two groups of 35 patients each. There were 28 men and seven women with a mean age of 46 years in the control group and 26 men and nine women with a mean age of 47 years in the rupture group. The lateral knee radiograph of each patient was evaluated for Insall-Salvati ratio for patella alta, increased density of the infrapatellar fat pad, appearance of the soft tissue margin of the patellar tendon and bony avulsions. In the rupture group there were three consistent soft tissue radiographic features in addition to patellar alta. These were increased density of infrapatellar fat pad; loss of sharp, well-defined linear margins of the patellar tendon and angulated wavy margin of the patellar tendon while in the control group these features were not observed. The soft tissue radiographic features described in the rupture group are consistent and reliable. When coupled with careful clinical assessment, these will aid in early diagnosis and further imaging will be seldom required. © 2015 Chinese Orthopaedic Association and Wiley Publishing Asia Pty Ltd.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

Science.gov (United States)

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

JCE Feature Columns

Science.gov (United States)

Holmes, Jon L.

1999-05-01

The Features area of JCE Online is now readily accessible through a single click from our home page. In the Features area each column is linked to its own home page. These column home pages also have links to them from the online Journal Table of Contents pages or from any article published as part of that feature column. Using these links you can easily find abstracts of additional articles that are related by topic. Of course, JCE Online+ subscribers are then just one click away from the entire article. Finding related articles is easy because each feature column "site" contains links to the online abstracts of all the articles that have appeared in the column. In addition, you can find the mission statement for the column and the email link to the column editor that I mentioned above. At the discretion of its editor, a feature column site may contain additional resources. As an example, the Chemical Information Instructor column edited by Arleen Somerville will have a periodically updated bibliography of resources for teaching and using chemical information. Due to the increase in the number of these resources available on the WWW, it only makes sense to publish this information online so that you can get to these resources with a simple click of the mouse. We expect that there will soon be additional information and resources at several other feature column sites. Following in the footsteps of the Chemical Information Instructor, up-to-date bibliographies and links to related online resources can be made available. We hope to extend the online component of our feature columns with moderated online discussion forums. If you have a suggestion for an online resource you would like to see included, let the feature editor or JCE Online (jceonline@chem.wisc.edu) know about it. JCE Internet Features JCE Internet also has several feature columns: Chemical Education Resource Shelf, Conceptual Questions and Challenge Problems, Equipment Buyers Guide, Hal's Picks, Mathcad

Cooking with Active Oxygen and Solid Alkali: A Promising Alternative Approach for Lignocellulosic Biorefineries.

Science.gov (United States)

Jiang, Yetao; Zeng, Xianhai; Luque, Rafael; Tang, Xing; Sun, Yong; Lei, Tingzhou; Liu, Shijie; Lin, Lu

2017-10-23

Lignocellulosic biomass, a matrix of biopolymers including cellulose, hemicellulose, and lignin, has gathered increasing attention in recent years for the production of chemicals, fuels, and materials through biorefinery processes owing to its renewability and availability. The fractionation of lignocellulose is considered to be the fundamental step to establish an economical and sustainable lignocellulosic biorefinery. In this Minireview, we summarize a newly developed oxygen delignification for lignocellulose fractionation called cooking with active oxygen and solid alkali (CAOSA), which can fractionate lignocellulose into its constituents and maintain its processable form. In the CAOSA approach, environmentally friendly chemicals are applied instead of undesirable chemicals such as strong alkalis and sulfides. Notably, the alkali recovery for this process promises to be relatively simple and does not require causticizing or sintering. These features make the CAOSA process an alternative for both lignocellulose fractionation and biomass pretreatment. The advantages and challenges of CAOSA are also discussed to provide a comprehensive perspective with respect to existing strategies. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

Directory of Open Access Journals (Sweden)

Lijun Wang

2013-01-01

Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.

Fault Diagnosis in Dynamic Systems Using Fuzzy Interacting Observers

Directory of Open Access Journals (Sweden)

N. V. Kolesov

2013-01-01

Full Text Available A method of fault diagnosis in dynamic systems based on a fuzzy approach is proposed. The new method possesses two basic specific features which distinguish it from the other known fuzzy methods based on the application of fuzzy logic and a bank of state observers. First, this method uses a bank of interacting observers instead of traditional independent observers. The second specific feature of the proposed method is the assumption that there is no strict boundary between the serviceable and disabled technical states of the system, which makes it possible to specify a decision making rule for fault diagnosis.

Promising oncolytic agents for metastatic breast cancer treatment

Directory of Open Access Journals (Sweden)

Cody JJ

2015-06-01

Full Text Available James J Cody,1 Douglas R Hurst2 1ImQuest BioSciences, Frederick, MD, 2Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, USA Abstract: New therapies for metastatic breast cancer patients are urgently needed. The long-term survival rates remain unacceptably low for patients with recurrent disease or disseminated metastases. In addition, existing therapies often cause a variety of debilitating side effects that severely impact quality of life. Oncolytic viruses constitute a developing therapeutic modality in which interest continues to build due to their ability to spare normal tissue while selectively destroying tumor cells. A number of different viruses have been used to develop oncolytic agents for breast cancer, including herpes simplex virus, adenovirus, vaccinia virus, measles virus, reovirus, and others. In general, clinical trials for several cancers have demonstrated excellent safety records and evidence of efficacy. However, the impressive tumor responses often observed in preclinical studies have yet to be realized in the clinic. In order for the promise of oncolytic virotherapy to be fully realized for breast cancer patients, effectiveness must be demonstrated in metastatic disease. This review provides a summary of oncolytic virotherapy strategies being developed to target metastatic breast cancer. Keywords: oncolytic virus, virotherapy, breast cancer, metastasis 

A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus.

Science.gov (United States)

Ekins, Sean; Freundlich, Joel S; Coffee, Megan

2014-01-01

We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a common features pharmacophore. This ligand-based pharmacophore implicates a possible common target or mechanism that could be further explored. A recent structure based design project yielded nine co-crystal structures of pyrrolidinone inhibitors bound to the viral protein 35 (VP35). When receptor-ligand pharmacophores based on the analogs of these molecules and the protein structures were constructed, the molecular features partially overlapped with the common features of solely ligand-based pharmacophore models based on FDA approved drugs. These previously identified FDA approved drugs with activity against Ebola were therefore docked into this protein. The antimalarials chloroquine and amodiaquine docked favorably in VP35. We propose that these drugs identified to date as inhibitors of the Ebola virus may be targeting VP35. These computational models may provide preliminary insights into the molecular features that are responsible for their activity against Ebola virus in vitro and in vivo and we propose that this hypothesis could be readily tested.

Rosai-Dorfman Disease with Epidural and Spinal Bone Marrow Involvement: Magnetic Resonance Imaging and Diffusion-Weighted Imaging Features

International Nuclear Information System (INIS)

Oner, A.Y.; Akpek, S.; Tali, T.

2007-01-01

Sinus histiocytosis with massive lymphadenopathy (SHML), or Rosai-Dorfman disease, is a rare histiocytic disorder that typically presents with chronic, self-limiting cervical lymphadenopathy. Although this disease mainly affects histiocytes, there are a few reports of bone marrow infiltration. Diffusion-weighted imaging (DWI) is a promising technology in differentiating between various bone marrow pathologies. We here present conventional magnetic resonance imaging and DWI features of a patient with SHML and bone marrow involvement

Rosai-Dorfman Disease with Epidural and Spinal Bone Marrow Involvement: Magnetic Resonance Imaging and Diffusion-Weighted Imaging Features

Energy Technology Data Exchange (ETDEWEB)

Oner, A.Y.; Akpek, S.; Tali, T. [Dept. of Radiology, Gazi Univ. School of Medicine. Besevler-Ankara (Turkey)

2007-04-15

Sinus histiocytosis with massive lymphadenopathy (SHML), or Rosai-Dorfman disease, is a rare histiocytic disorder that typically presents with chronic, self-limiting cervical lymphadenopathy. Although this disease mainly affects histiocytes, there are a few reports of bone marrow infiltration. Diffusion-weighted imaging (DWI) is a promising technology in differentiating between various bone marrow pathologies. We here present conventional magnetic resonance imaging and DWI features of a patient with SHML and bone marrow involvement.

Discovery and fusion of salient multimodal features toward news story segmentation

Science.gov (United States)

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

2003-12-01

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

The correlation between the ultraviolet lambda 220 feature and the diffuse lambda 4430 band

International Nuclear Information System (INIS)

Nandy, K.; Thompson, G.I.

1975-01-01

Observations of the ultraviolet feature which occurs close to 2200 A are presented for over 60 stars for which interstellar lambda 4430 data are available in the literature. Observational material used here is obtained from the ultraviolet spectra taken with the Sky Survey telescope (S2/68) in the ESRO TD1 satellite. The equivalent widths of the lambda 2200 feature have been determined from ultraviolet extinction at 2190 and 2500 A, and the relation between the equivalent width of the ultraviolet feature and the central depth of the lambda 4430 band has been determined. It is found that they are well correlated and the correlation coefficient, including allowance for errors, is greater than 0.9; this indicates that the carriers for the lambda 2200 feature and diffuse band lambda 4430 coexist in the interstellar medium. (author)

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.

Predictive Validity of an Empirical Approach for Selecting Promising Message Topics: A Randomized-Controlled Study

Science.gov (United States)

Lee, Stella Juhyun; Brennan, Emily; Gibson, Laura Anne; Tan, Andy S. L.; Kybert-Momjian, Ani; Liu, Jiaying; Hornik, Robert

2016-01-01

Several message topic selection approaches propose that messages based on beliefs pretested and found to be more strongly associated with intentions will be more effective in changing population intentions and behaviors when used in a campaign. This study aimed to validate the underlying causal assumption of these approaches which rely on cross-sectional belief–intention associations. We experimentally tested whether messages addressing promising themes as identified by the above criterion were more persuasive than messages addressing less promising themes. Contrary to expectations, all messages increased intentions. Interestingly, mediation analyses showed that while messages deemed promising affected intentions through changes in targeted promising beliefs, messages deemed less promising also achieved persuasion by influencing nontargeted promising beliefs. Implications for message topic selection are discussed. PMID:27867218

Fuelling expectations: A policy-promise lock-in of UK biofuel policy

International Nuclear Information System (INIS)

Berti, Pietro; Levidow, Les

2014-01-01

Controversy over EU-wide biofuel policy resonated within the UK, fuelling policy disagreements among UK public authorities. They disagreed over how to protect a space for future second-generation biofuels, which were expected to overcome harm from first-generation biofuels. The UK government defended rising targets for available biofuels as a necessary stimulus for industry to help fulfil the UK's EU obligations and eventually develop second-generation biofuels. By contrast, Parliamentary Select Committees opposed biofuel targets on grounds that these would instead lock-in first-generation biofuels, thus delaying or pre-empting second-generation biofuels. Those disagreements can be explained by different institutional responsibilities and reputational stakes towards ‘promise-requirement cycles’, whereby techno-optimistic promises generate future requirements for the actors involved. The UK government's stance illustrates a ‘policy-promise lock-in’, a dilemma whereby promised support is a requirement for credibility towards technology innovators and thus technoscientific development – but may delay the redirection of support from incumbent to preferable emerging technologies. Thus the sociology of expectations – previously applied to technological expectations from technology innovators – can be extended to analyse public authorities. - Highlights: • Controversy over EU-wide biofuel policy resonated within the UK. • At issue was how to stimulate future 2nd-generation biofuels. • The government defended targets for 1st-generation as necessary to stimulate industry. • Parliamentary Committees opposed biofuel targets as locking in 1st-generation. • The UK government′s stance illustrates a ‘policy-promise lock-in’

In vivo Immunomodulatory Effect and Histopathological Features of ...

African Journals Online (AJOL)

HP

The morphological features of liver and kidney were observed with light microscope and then compared with the liver and kidney of control group. ... Department of Biology, Faculty of Pharmacy,. Gadjah Mada University, Yogyakarta, ... A total of 100 µL macrophage cell culture, that have been incubated overnight, were put ...

Dysplastic naevus: histological criteria and their inter-observer reproducibility.

Science.gov (United States)

Hastrup, N; Clemmensen, O J; Spaun, E; Søndergaard, K

1994-06-01

Forty melanocytic lesions were examined in a pilot study, which was followed by a final series of 100 consecutive melanocytic lesions, in order to evaluate the inter-observer reproducibility of the histological criteria proposed for the dysplastic naevus. The specimens were examined in a blind fashion by four observers. Analysis by kappa statistics showed poor reproducibility of nuclear features, while reproducibility of architectural features was acceptable, improving in the final series. Consequently, we cannot apply the combined criteria of cytological and architectural features with any confidence in the diagnosis of dysplastic naevus, and, until further studies have documented that architectural criteria alone will suffice in the diagnosis of dysplastic naevus, we, as pathologists, shall avoid this term.

Diagnostic Biomarkers for Posttraumatic Stress Disorder (PTSD): Promising Horizons from Translational Neuroscience Research

Science.gov (United States)

Michopoulos, Vasiliki; Norrholm, Seth Davin; Jovanovic, Tanja

2015-01-01

Posttraumatic stress disorder (PTSD) is a heterogeneous disorder that affects individuals exposed to trauma (e.g., combat, interpersonal violence, and natural disasters). Although its diagnostic features have been recently re-classified with the emergence of the Diagnostic and Statistical Manual for Mental Disorders, Fifth Edition (DSM-5), the disorder remains characterized by hyperarousal, intrusive reminders of the trauma, avoidance of trauma-related cues, and negative cognition and mood. This heterogeneity indicates the presence of multiple neurobiological mechanisms underlying the etiology and maintenance of PTSD. Translational research spanning the past few decades has revealed several potential avenues for the identification of diagnostic biomarkers for PTSD. These include, but are not limited to, monoaminergic transmitter systems, the hypothalamic-pituitary-adrenal (HPA) axis, metabolic hormonal pathways, inflammatory mechanisms, psychophysiological reactivity, and neural circuits. The current review provides an update to the literature with regard to the most promising putative PTSD biomarkers with specific emphasis on the interaction between neurobiological influences on disease risk and symptom progression. Such biomarkers will most likely be identified by multi-dimensional models derived from comprehensive descriptions of molecular, neurobiological, behavioral, and clinical phenotypes. PMID:25727177

Applications of Satellite Observations of Tropospheric Composition

Science.gov (United States)

Monks, Paul S.; Beirle, Steffen

A striking feature of the field of tropospheric composition is the sheer number of chemical species that have been detected and measured with satellite instruments. The measurements have found application both in atmospheric chemistry itself, providing evidence, for example, of unexpected cryochemistry in the Arctic regions, and also in environmental monitoring with, for example, the observed growth in NO2 emissions over eastern Asia. Chapter 8 gives an overview of the utility of satellite observations for measuring tropospheric composition, dealing with each of the many compounds seen in detail. A comprehensive compound by compound table of the many studies performed is a most useful feature.

A CNN-Based Fusion Method for Feature Extraction from Sentinel Data

Directory of Open Access Journals (Sweden)

Giuseppe Scarpa

2018-02-01

Full Text Available Sensitivity to weather conditions, and specially to clouds, is a severe limiting factor to the use of optical remote sensing for Earth monitoring applications. A possible alternative is to benefit from weather-insensitive synthetic aperture radar (SAR images. In many real-world applications, critical decisions are made based on some informative optical or radar features related to items such as water, vegetation or soil. Under cloudy conditions, however, optical-based features are not available, and they are commonly reconstructed through linear interpolation between data available at temporally-close time instants. In this work, we propose to estimate missing optical features through data fusion and deep-learning. Several sources of information are taken into account—optical sequences, SAR sequences, digital elevation model—so as to exploit both temporal and cross-sensor dependencies. Based on these data and a tiny cloud-free fraction of the target image, a compact convolutional neural network (CNN is trained to perform the desired estimation. To validate the proposed approach, we focus on the estimation of the normalized difference vegetation index (NDVI, using coupled Sentinel-1 and Sentinel-2 time-series acquired over an agricultural region of Burkina Faso from May–November 2016. Several fusion schemes are considered, causal and non-causal, single-sensor or joint-sensor, corresponding to different operating conditions. Experimental results are very promising, showing a significant gain over baseline methods according to all performance indicators.

High-cadence observations of spicular-type events on the Sun

Science.gov (United States)

Shetye, J.; Doyle, J. G.; Scullion, E.; Nelson, C. J.; Kuridze, D.; Henriques, V.; Woeger, F.; Ray, T.

2016-05-01

Context. Chromospheric observations taken at high-cadence and high-spatial resolution show a range of spicule-like features, including Type-I, Type-II (as well as rapid blue-shifted excursions (RBEs) and rapid red-shifted excursions (RREs) which are thought to be on-disk counterparts of Type-II spicules) and those which seem to appear within a few seconds, which if interpreted as flows would imply mass flow velocities in excess of 1000 km s-1. Aims: This article seeks to quantify and study rapidly appearing spicular-type events. We also compare the multi-object multi-frame blind deconvolution (MOMFBD) and speckle reconstruction techniques to understand if these spicules are more favourably observed using a particular technique. Methods: We use spectral imaging observations taken with the CRisp Imaging SpectroPolarimeter (CRISP) on the Swedish 1-m Solar Telescope. Data was sampled at multiple positions within the Hα line profile for both an on-disk and limb location. Results: The data is host to numerous rapidly appearing features which are observed at different locations within the Hα line profile. The feature's durations vary between 10-20 s and lengths around 3500 km. Sometimes, a time delay in their appearance between the blue and red wings of 3-5 s is evident, whereas, sometimes they are near simultaneous. In some instances, features are observed to fade and then re-emerge at the same location several tens of seconds later. Conclusions: We provide the first statistical analysis of these spicules and suggest that these observations can be interpreted as the line-of-sight (LOS) movement of highly dynamic spicules moving in and out of the narrow 60 mÅ transmission filter that is used to observe in different parts of the Hα line profile. The LOS velocity component of the observed fast chromospheric features, manifested as Doppler shifts, are responsible for their appearance in the red and blue wings of Hα line. Additional work involving data at other

Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

Directory of Open Access Journals (Sweden)

Xiaoming Xi

2013-07-01

Full Text Available Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT, which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

Ultrastructural hepatocellular features associated with severe hepatic lipidosis in cats.

Science.gov (United States)

Center, S A; Guida, L; Zanelli, M J; Dougherty, E; Cummings, J; King, J

1993-05-01

In this study, we compared hepatic ultrastructure in healthy cats, in cats with severe hepatic lipidosis, and in cats with experimentally induced, chronic, extrahepatic bile duct occlusion. Ultrastructural features unique to the lipidosis syndrome included an apparent reduction in number of peroxisomes and alteration in their morphologic features. The quantity of endoplasmic reticulum, Golgi complexes, and lysosomes was subjectively reduced, and paucity of cytosolic glycogen was observed. Bile canaliculi appeared collapsed because of cytosolic distention with lipid. Mitochondria were reduced in number and were markedly pleomorphic. Cristae assumed a variety of shapes, lengths, and orientations. Ultrastructural features of bile duct occlusion were similar to those described in other species and differed from those in cats with hepatic lipidosis.

The Radical Promise of Reformist Zeal: What Makes "Inquiry for Equity" Plausible?

Science.gov (United States)

Lashaw, Amanda

2010-01-01

Education reform movements often promise more than they deliver. Why are such promises plausible in light of seemingly perpetual education reform? Drawing on ethnographic fieldwork based in a nonprofit education reform organization, this article explores the appeal of popular notions about "using data to close the racial achievement…

THE MORPHOLOGICAL PYRAMID AND ITS APPLICATIONS TO REMOTE SENSING: MULTIRESOLUTION DATA ANALYSIS AND FEATURES EXTRACTION

Directory of Open Access Journals (Sweden)

Laporterie Florence

2011-05-01

Full Text Available In remote sensing, sensors are more and more numerous, and their spatial resolution is higher and higher. Thus, the availability of a quick and accurate characterisation of the increasing amount of data is now a quite important issue. This paper deals with an approach combining a pyramidal algorithm and mathematical morphology to study the physiographic characteristics of terrestrial ecosystems. Our pyramidal strategy involves first morphological filters, then extraction at each level of resolution of well-known landscapes features. The approach is applied to a digitised aerial photograph representing an heterogeneous landscape of orchards and forests along the Garonne river (France. This example, simulating very high spatial resolution imagery, highlights the influence of the parameters of the pyramid according to the spatial properties of the studied patterns. It is shown that, the morphological pyramid approach is a promising attempt for multi-level features extraction by modelling geometrical relevant parameters.

Efficient feature for classification of eye movements using electrooculography signals

Directory of Open Access Journals (Sweden)

Phukpattaranont Pornchai

2016-01-01

Full Text Available Electrooculography (EOG signal is widely and successfully used to detect activities of human eye. The advantages of the EOG-based interface over other conventional interfaces have been presented in the last two decades; however, due to a lot of information in EOG signals, the extraction of useful features should be done before the classification task. In this study, an efficient feature extracted from two directional EOG signals: vertical and horizontal signals has been presented and evaluated. There are the maximum peak and valley amplitude values, the maximum peak and valley position values, and slope, which are derived from both vertical and horizontal signals. In the experiments, EOG signals obtained from five healthy subjects with ten directional eye movements were employed: up, down, right, left, up-right, up-left, down-right down-left clockwise and counterclockwise. The mean feature values and their standard deviations have been reported. The difference between the mean values of the proposed feature from different eye movements can be clearly seen. Using the scatter plot, the differences in features can be also clearly observed. Results show that classification accuracy can approach 100% with a simple distinction feature rule. The proposed features can be useful for various advanced human-computer interface applications in future researches.

Design, challenge, and promise of stimuli-responsive nanoantibiotics

Science.gov (United States)

Edson, Julius A.; Kwon, Young Jik

2016-10-01

Over the past few years, there have been calls for novel antimicrobials to combat the rise of drug-resistant bacteria. While some promising new discoveries have met this call, it is not nearly enough. The major problem is that although these new promising antimicrobials serve as a short-term solution, they lack the potential to provide a long-term solution. The conventional method of creating new antibiotics relies heavily on the discovery of an antimicrobial compound from another microbe. This paradigm of development is flawed due to the fact that microbes can easily transfer a resistant mechanism if faced with an environmental pressure. Furthermore, there has been some evidence to indicate that the environment of the microbe can provide a hint as to their virulence. Because of this, the use of materials with antimicrobial properties has been garnering interest. Nanoantibiotics, (nAbts), provide a new way to circumvent the current paradigm of antimicrobial discovery and presents a novel mechanism of attack not found in microbes yet; which may lead to a longer-term solution against drug-resistance formation. This allows for environment-specific activation and efficacy of the nAbts but may also open up and create new design methods for various applications. These nAbts provide promise, but there is still ample work to be done in their development. This review looks at possible ways of improving and optimizing nAbts by making them stimuli-responsive, then consider the challenges ahead, and industrial applications.[Figure not available: see fulltext.

TU-G-204-06: Correlation Between Texture Analysis-Based Model Observer and Human Observer in Diagnosis of Ischemic Infarct in Non-Contrast Head CT of Adults

International Nuclear Information System (INIS)

Li, B; Fujita, A; Buch, K; Sakai, O

2015-01-01

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIs over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast

TU-G-204-06: Correlation Between Texture Analysis-Based Model Observer and Human Observer in Diagnosis of Ischemic Infarct in Non-Contrast Head CT of Adults

Energy Technology Data Exchange (ETDEWEB)

Li, B; Fujita, A; Buch, K; Sakai, O [Boston University Medical Center, Boston, MA (United States)

2015-06-15

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIs over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast

Iris-based medical analysis by geometric deformation features.

Science.gov (United States)

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.

Phosphatization Associated Features of Ferromanganese Crusts at Lemkein Seamount, Marshall Islands

Science.gov (United States)

Choi, J.; Lee, I.; Park, B. K.; Kim, J.

2014-12-01

Old layers of ferromanganese crusts, especially in the Pacific Ocean, have been affected by phosphatization. Ferromanganese crusts on Lemkein seamount in Marshall Islands also are phosphatized (3.3 to 4.2 wt % of P concentration). Furthermore, they have characteristic features that are different from other ferromanganese crusts. These features occur near the phosphorite, which were thought to fill the pore spaces of ferromanganese crusts. Inside the features, ferromanganese crusts are botryoidally precipitated from the round-boundary. The features of the phosphatized lower crusts of Lemkein seamount are observed using microscope and SEM. Elemental compositions of the selected samples were analyzed by SEM-EDS. Based on the observation and analysis of samples, three characteristic structures are identified: (1) phosphate-filled circles, (2) tongue-shaped framboidal crust, and (3) massive framboidal crust. The phosphate-filled circles are mostly composed of phosphorite, and they include trace fossils such as foraminifera. Phosphatized ferromanganese crusts exist at the boundary of this structure. The tongue-shaped crust is connected with the lips downward, and ferromanganese crusts inside the tongue show distinct growth rim. The massive framboidal crust is located below the tongue. Ferromanganese crusts in the massive framboidal crust are enveloped by phosphate, and some of the crusts are phosphatized. Around the structures, Mn oxide phase is concentrated as a shape of corona on BSE image. All of the structures are in the phosphatized crusts that show columnar growth of ferromanganese crusts and have sub-parallel lamination. These observation and chemical analysis of the ferromanganese crusts can provide a clue of diagenetic processes during the formation of ferromanganese crusts.

Features of highly structured equatorial plasma irregularities deduced from CHAMP observations

Science.gov (United States)

Xiong, C.; Lühr, H.; Ma, S. Y.; Stolle, C.; Fejer, B. G.

2012-08-01

In this study five years of CHAMP (Challenging Mini-satellite Payload) fluxgate magnetometer (FGM) data is used to investigate the characteristics of Equatorial Plasma Bubbles (EPBs). We filtered the FGM data by using band-passes with four different cut-off periods to get the EPBs with different maximum spatial scale sizes in the meridional plane ranging from 76-608 km. Associated with the EPB observations at about 400 km, the typical altitude of CHAMP during the year 2000-2005, we also investigate the post-sunset equatorial vertical plasma drift data from ROCSAT-1 (Republic of China Satellite 1). Since the height of the F-layer is highly correlated with the vertical plasma drift and solar flux, we sorted the ROCSAT-1 data into different groups by F10.7. From the integrated vertical drift we have estimated the post-sunset uplift of the ionosphere. By comparing the properties of EPB occurrence for different scale sizes with the global distribution of plasma vertical uplift, we have found that EPBs reaching higher altitudes are more structured than those which are sampled by CHAMP near the top side of the depleted fluxtube. Such a result is in accord with 3-D model simulations (Aveiro and Hysell, 2010). Small-scale EPB structures are observed by CHAMP when the irregularities reach apex heights of 800 km and more. Such events are encountered primarily in the Brazilian sector during the months around November, when the post-sunset vertical plasma drift is high.

Classification Influence of Features on Given Emotions and Its Application in Feature Selection

Science.gov (United States)

Xing, Yin; Chen, Chuang; Liu, Li-Long

2018-04-01

In order to solve the problem that there is a large amount of redundant data in high-dimensional speech emotion features, we analyze deeply the extracted speech emotion features and select better features. Firstly, a given emotion is classified by each feature. Secondly, the recognition rate is ranked in descending order. Then, the optimal threshold of features is determined by rate criterion. Finally, the better features are obtained. When applied in Berlin and Chinese emotional data set, the experimental results show that the feature selection method outperforms the other traditional methods.

Wavelet-based Characterization of Small-scale Solar Emission Features at Low Radio Frequencies

Energy Technology Data Exchange (ETDEWEB)

Suresh, A. [Indian Institute of Science Education and Research, Pune-411008 (India); Sharma, R.; Oberoi, D. [National Centre for Radio Astrophysics, Tata Institute for Fundamental Research, Pune 411007 (India); Das, S. B. [Indian Institute of Science Education and Research, Kolkata-741249 (India); Pankratius, V.; Lonsdale, C. J.; Cappallo, R. J.; Corey, B. E.; Kratzenberg, E. [MIT Haystack Observatory, Westford, MA 01886 (United States); Timar, B. [California Institute of Technology, Pasadena, CA 91125 (United States); Bowman, J. D. [School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287 (United States); Briggs, F. [Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611 (Australia); Deshpande, A. A. [Raman Research Institute, Bangalore 560080 (India); Emrich, D. [International Centre for Radio Astronomy Research, Curtin University, Bentley, WA 6102 (Australia); Goeke, R. [Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Greenhill, L. J. [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138 (United States); Hazelton, B. J. [Department of Physics, University of Washington, Seattle, WA 98195 (United States); Johnston-Hollitt, M. [School of Chemical and Physical Sciences, Victoria University of Wellington, P.O. Box 600, Wellington 6140 (New Zealand); Kaplan, D. L. [Department of Physics, University of Wisconsin–Milwaukee, Milwaukee, WI 53201 (United States); Kasper, J. C., E-mail: akshay@students.iiserpune.ac.in [Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI 48109 (United States); and others

2017-07-01

Low radio frequency solar observations using the Murchison Widefield Array have recently revealed the presence of numerous weak short-lived narrowband emission features, even during moderately quiet solar conditions. These nonthermal features occur at rates of many thousands per hour in the 30.72 MHz observing bandwidth, and hence necessarily require an automated approach for their detection and characterization. Here, we employ continuous wavelet transform using a mother Ricker wavelet for feature detection from the dynamic spectrum. We establish the efficacy of this approach and present the first statistically robust characterization of the properties of these features. In particular, we examine distributions of their peak flux densities, spectral spans, temporal spans, and peak frequencies. We can reliably detect features weaker than 1 SFU, making them, to the best of our knowledge, the weakest bursts reported in literature. The distribution of their peak flux densities follows a power law with an index of −2.23 in the 12–155 SFU range, implying that they can provide an energetically significant contribution to coronal and chromospheric heating. These features typically last for 1–2 s and possess bandwidths of about 4–5 MHz. Their occurrence rate remains fairly flat in the 140–210 MHz frequency range. At the time resolution of the data, they appear as stationary bursts, exhibiting no perceptible frequency drift. These features also appear to ride on a broadband background continuum, hinting at the likelihood of them being weak type-I bursts.

A Method of Road Extraction from High-resolution Remote Sensing Images Based on Shape Features

Directory of Open Access Journals (Sweden)

LEI Xiaoqi

2016-02-01

Full Text Available Road extraction from high-resolution remote sensing image is an important and difficult task.Since remote sensing images include complicated information,the methods that extract roads by spectral,texture and linear features have certain limitations.Also,many methods need human-intervention to get the road seeds(semi-automatic extraction,which have the great human-dependence and low efficiency.The road-extraction method,which uses the image segmentation based on principle of local gray consistency and integration shape features,is proposed in this paper.Firstly,the image is segmented,and then the linear and curve roads are obtained by using several object shape features,so the method that just only extract linear roads are rectified.Secondly,the step of road extraction is carried out based on the region growth,the road seeds are automatic selected and the road network is extracted.Finally,the extracted roads are regulated by combining the edge information.In experiments,the images that including the better gray uniform of road and the worse illuminated of road surface were chosen,and the results prove that the method of this study is promising.

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...

Vascular regenerative surgery : promised land for tissue engineers?

NARCIS (Netherlands)

Fortunato, T.M.; De Bank, P.A.; Pula, G.

2017-01-01

Cardiovascular cell therapy is a promising new eld for the development of treatments for cardiovascular diseases, which remain a major cause of mortality around the world. In this review, we highlight the options currently available for the development of speci c cell therapy approaches applied to

7 T renal MRI : challenges and promises

NARCIS (Netherlands)

de Boer, A.; Hoogduin, J.M.; Blankestijn, P.J.; Li, X.; Luijten, P.R.; Metzger, G.J.; Raaijmakers, A.J.E.; Umutlu, L.; Visser, F.; Leiner, T.

The progression to 7 Tesla (7 T) magnetic resonance imaging (MRI) yields promises of substantial increase in signal-to-noise (SNR) ratio. This increase can be traded off to increase image spatial resolution or to decrease acquisition time. However, renal 7 T MRI remains challenging due to

Dynamic Stochastic Superresolution of sparsely observed turbulent systems

International Nuclear Information System (INIS)

Branicki, M.; Majda, A.J.

2013-01-01

Real-time capture of the relevant features of the unresolved turbulent dynamics of complex natural systems from sparse noisy observations and imperfect models is a notoriously difficult problem. The resulting lack of observational resolution and statistical accuracy in estimating the important turbulent processes, which intermittently send significant energy to the large-scale fluctuations, hinders efficient parameterization and real-time prediction using discretized PDE models. This issue is particularly subtle and important when dealing with turbulent geophysical systems with an vast range of interacting spatio-temporal scales and rough energy spectra near the mesh scale of numerical models. Here, we introduce and study a suite of general Dynamic Stochastic Superresolution (DSS) algorithms and show that, by appropriately filtering sparse regular observations with the help of cheap stochastic exactly solvable models, one can derive stochastically ‘superresolved’ velocity fields and gain insight into the important characteristics of the unresolved dynamics, including the detection of the so-called black swans. The DSS algorithms operate in Fourier domain and exploit the fact that the coarse observation network aliases high-wavenumber information into the resolved waveband. It is shown that these cheap algorithms are robust and have significant skill on a test bed of turbulent solutions from realistic nonlinear turbulent spatially extended systems in the presence of a significant model error. In particular, the DSS algorithms are capable of successfully capturing time-localized extreme events in the unresolved modes, and they provide good and robust skill for recovery of the unresolved processes in terms of pattern correlation. Moreover, we show that DSS improves the skill for recovering the primary modes associated with the sparse observation mesh which is equally important in applications. The skill of the various DSS algorithms depends on the energy spectrum

Ultrasonographic features of prenatal testicular torsion: Case report

Directory of Open Access Journals (Sweden)

Elif Ağaçayak

2013-01-01

Full Text Available Although prenatal testicular torsion (PNTT is rarely observed,it is an important condition that can cause bilateralvanishing testis. Generally, PNTT cases observed asextravaginal torsion and treatment is emergency surgicalop-eration. In this article, 39 week presented a case diagnosedin the prenatal testicular torsion. PNTT diagnosiswas confirmed by Doppler ultrasonography and emergencysurgery was performed. Extravaginal left testiculartorsion gangrene and necrosis of the testis was observedin the operation. Left orchiectomy was performed andintrauter-ine ultrasonographic diagnosis was found to becorrect.Key words: Testicular torsion, prenatal diagnosis, features,ultrasonography

Promise Zone Round 2 Applicant Geography and Goal Data

Data.gov (United States)

Department of Housing and Urban Development — This dataset includes Promise Zone initiative round II applicant project data from 111 urban, rural, and tribal communities who consented to share their application...

Case Study Observational Research: A Framework for Conducting Case Study Research Where Observation Data Are the Focus.

Science.gov (United States)

Morgan, Sonya J; Pullon, Susan R H; Macdonald, Lindsay M; McKinlay, Eileen M; Gray, Ben V

2017-06-01

Case study research is a comprehensive method that incorporates multiple sources of data to provide detailed accounts of complex research phenomena in real-life contexts. However, current models of case study research do not particularly distinguish the unique contribution observation data can make. Observation methods have the potential to reach beyond other methods that rely largely or solely on self-report. This article describes the distinctive characteristics of case study observational research, a modified form of Yin's 2014 model of case study research the authors used in a study exploring interprofessional collaboration in primary care. In this approach, observation data are positioned as the central component of the research design. Case study observational research offers a promising approach for researchers in a wide range of health care settings seeking more complete understandings of complex topics, where contextual influences are of primary concern. Future research is needed to refine and evaluate the approach.

Detonation nanodiamonds are promising nontoxic delivery system for urothelial cells.

Science.gov (United States)

Zupančič, Daša; Kreft, Mateja Erdani; Grdadolnik, Maja; Mitev, Dimitar; Iglič, Aleš; Veranič, Peter

2018-01-01

Detonation nanodiamonds (DNDs) are carbon-based nanomaterials that are among the most promising nanoparticles available for biomedical applications so far. This is due to their biocompatibility, which could be contributed to their inert core and conformable surface nature. However, DNDs cytotoxicity for urothelial cells and the routes of their internalization remains an open question in the aspect of nanodiamond surface. We therefore analyzed four types of DNDs for cytotoxicity and internalization with normal urothelial cells and two types of cancer urothelial cell lines in vitro. Viability of any of the cell types we used was not compromised with any of four DNDs we evaluated after 24-, 48- and 72-h incubation in three different concentrations of DNDs. Transmission electron microscopy revealed that all four types of DNDs were endocytosed into all three types of urothelial cells tested here. We observed DNDs in endosomes, as well as in multivesicular bodies and multilamellar bodies. These results propose using of DNDs as a delivery system for urological applications in human nanomedicine.

Features of highly structured equatorial plasma irregularities deduced from CHAMP observations

Directory of Open Access Journals (Sweden)

C. Xiong

2012-08-01

Full Text Available In this study five years of CHAMP (Challenging Mini-satellite Payload fluxgate magnetometer (FGM data is used to investigate the characteristics of Equatorial Plasma Bubbles (EPBs. We filtered the FGM data by using band-passes with four different cut-off periods to get the EPBs with different maximum spatial scale sizes in the meridional plane ranging from 76–608 km. Associated with the EPB observations at about 400 km, the typical altitude of CHAMP during the year 2000–2005, we also investigate the post-sunset equatorial vertical plasma drift data from ROCSAT-1 (Republic of China Satellite 1. Since the height of the F-layer is highly correlated with the vertical plasma drift and solar flux, we sorted the ROCSAT-1 data into different groups by F10.7. From the integrated vertical drift we have estimated the post-sunset uplift of the ionosphere. By comparing the properties of EPB occurrence for different scale sizes with the global distribution of plasma vertical uplift, we have found that EPBs reaching higher altitudes are more structured than those which are sampled by CHAMP near the top side of the depleted fluxtube. Such a result is in accord with 3-D model simulations (Aveiro and Hysell, 2010. Small-scale EPB structures are observed by CHAMP when the irregularities reach apex heights of 800 km and more. Such events are encountered primarily in the Brazilian sector during the months around November, when the post-sunset vertical plasma drift is high.

Information Theory for Gabor Feature Selection for Face Recognition

Directory of Open Access Journals (Sweden)

Shen Linlin

2006-01-01

Full Text Available A discriminative and robust feature—kernel enhanced informative Gabor feature—is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and nonredundant Gabor features, which are then further enhanced by kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004, our methods demonstrate a clear advantage over existing methods in accuracy, computation efficiency, and memory cost. The proposed method has been fully tested on the FERET database using the FERET evaluation protocol. Significant improvements on three of the test data sets are observed. Compared with the classical Gabor wavelet-based approaches using a huge number of features, our method requires less than 4 milliseconds to retrieve a few hundreds of features. Due to the substantially reduced feature dimension, only 4 seconds are required to recognize 200 face images. The paper also unified different Gabor filter definitions and proposed a training sample generation algorithm to reduce the effects caused by unbalanced number of samples available in different classes.

Information Theory for Gabor Feature Selection for Face Recognition

Science.gov (United States)

Shen, Linlin; Bai, Li

2006-12-01

A discriminative and robust feature—kernel enhanced informative Gabor feature—is proposed in this paper for face recognition. Mutual information is applied to select a set of informative and nonredundant Gabor features, which are then further enhanced by kernel methods for recognition. Compared with one of the top performing methods in the 2004 Face Verification Competition (FVC2004), our methods demonstrate a clear advantage over existing methods in accuracy, computation efficiency, and memory cost. The proposed method has been fully tested on the FERET database using the FERET evaluation protocol. Significant improvements on three of the test data sets are observed. Compared with the classical Gabor wavelet-based approaches using a huge number of features, our method requires less than 4 milliseconds to retrieve a few hundreds of features. Due to the substantially reduced feature dimension, only 4 seconds are required to recognize 200 face images. The paper also unified different Gabor filter definitions and proposed a training sample generation algorithm to reduce the effects caused by unbalanced number of samples available in different classes.

Why do promises affect trustworthiness, or do they?

NARCIS (Netherlands)

Ismayilov, Huseyn; Potters, Jan

2016-01-01

We set out to test whether the effect of promises on trustworthiness derives from the fact that they are made (internal consistency) or that they are received (social obligation). The results of an experimental trust game appeared at first to support the former mechanism. Even when trustee messages

Breast Cancer Detection with Gabor Features from Digital Mammograms

Directory of Open Access Journals (Sweden)

Yufeng Zheng

2010-01-01

Full Text Available A new breast cancer detection algorithm, named the “Gabor Cancer Detection” (GCD algorithm, utilizing Gabor features is proposed. Three major steps are involved in the GCD algorithm, preprocessing, segmentation (generating alarm segments, and classification (reducing false alarms. In preprocessing, a digital mammogram is down-sampled, quantized, denoised and enhanced. Nonlinear diffusion is used for noise suppression. In segmentation, a band-pass filter is formed by rotating a 1-D Gaussian filter (off center in frequency space, termed as “Circular Gaussian Filter” (CGF. A CGF can be uniquely characterized by specifying a central frequency and a frequency band. A mass or calcification is a space-occupying lesion and usually appears as a bright region on a mammogram. The alarm segments (suspicious to be masses/calcifications can be extracted out using a threshold that is adaptively decided upon the histogram analysis of the CGF-filtered mammogram. In classification, a Gabor filter bank is formed with five bands by four orientations (horizontal, vertical, 45 and 135 degree in Fourier frequency domain. For each mammographic image, twenty Gabor-filtered images are produced. A set of edge histogram descriptors (EHD are then extracted from 20 Gabor images for classification. An EHD signature is computed with four orientations of Gabor images along each band and five EHD signatures are then joined together to form an EHD feature vector of 20 dimensions. With the EHD features, the fuzzy C-means clustering technique and k-nearest neighbor (KNN classifier are used to reduce the number of false alarms. The experimental results tested on the DDSM database (University of South Florida show the promises of GCD algorithm in breast cancer detection, which achieved TP (true positive rate = 90% at FPI (false positives per image = 1.21 in mass detection; and TP = 93% at FPI = 1.19 in calcification detection.

3D face analysis by using Mesh-LBP feature

Science.gov (United States)

Wang, Haoyu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

Objective: Face Recognition is one of the widely application of image processing. Corresponding two-dimensional limitations, such as the pose and illumination changes, to a certain extent restricted its accurate rate and further development. How to overcome the pose and illumination changes and the effects of self-occlusion is the research hotspot and difficulty, also attracting more and more domestic and foreign experts and scholars to study it. 3D face recognition fusing shape and texture descriptors has become a very promising research direction. Method: Our paper presents a 3D point cloud based on mesh local binary pattern grid (Mesh-LBP), then feature extraction for 3D face recognition by fusing shape and texture descriptors. 3D Mesh-LBP not only retains the integrity of the 3D geometry, is also reduces the need for recognition process of normalization steps, because the triangle Mesh-LBP descriptor is calculated on 3D grid. On the other hand, in view of multi-modal consistency in face recognition advantage, construction of LBP can fusing shape and texture information on Triangular Mesh. In this paper, some of the operators used to extract Mesh-LBP, Such as the normal vectors of the triangle each face and vertex, the gaussian curvature, the mean curvature, laplace operator and so on. Conclusion: First, Kinect devices obtain 3D point cloud face, after the pretreatment and normalization, then transform it into triangular grid, grid local binary pattern feature extraction from face key significant parts of face. For each local face, calculate its Mesh-LBP feature with Gaussian curvature, mean curvature laplace operator and so on. Experiments on the our research database, change the method is robust and high recognition accuracy.

IDENTIFICATION OF BURSTING WATER MASER FEATURES IN ORION KL

International Nuclear Information System (INIS)

Hirota, Tomoya; Honma, Mareki; Kim, Mi Kyoung; Kobayashi, Hideyuki; Shibata, Katsunori M.; Tsuboi, Masato; Fujisawa, Kenta; Kawaguchi, Noriyuki; Imai, Hiroshi; Omodaka, Toshihiro; Shimoikura, Tomomi; Yonekura, Yoshinori

2011-01-01

In 2011 February, a burst event of the H 2 O maser in Orion KL (Kleinmann-Low object) has started after a 13 year silence. This is the third time such phenomena has been detected in Orion KL, followed by the events in 1979-1985 and 1998. We have carried out astrometric observations of the bursting H 2 O maser features in Orion KL with the VLBI Exploration of Radio Astrometry (VERA), a Japanese very long baseline interferometry network dedicated for astrometry. The total flux of the bursting feature at the local standard of rest (LSR) velocity of 7.58 km s -1 reaches 4.4 x 10 4 Jy in 2011 March. The intensity of the bursting feature is three orders of magnitude larger than that of the same velocity feature in the quiescent phase in 2006. Two months later, another new feature appears at the LSR velocity of 6.95 km s -1 in 2011 May, separated by 12 mas north of the 7.58 km s -1 feature. Thus, the current burst occurs at two spatially different features. The bursting masers are elongated along the northwest-southeast direction as reported in the previous burst in 1998. We determine the absolute positions of the bursting features for the first time ever with a submilliarcsecond (mas) accuracy. Their positions are coincident with the shocked molecular gas called the Orion Compact Ridge. We tentatively detect the absolute proper motions of the bursting features toward the southwest direction. It is most likely that the outflow from the radio source I or another young stellar object interacting with the Compact Ridge is a possible origin of the H 2 O maser burst.

A Proposed Astronomy Learning Progression for Remote Telescope Observation

Science.gov (United States)

Slater, Timothy F.; Burrows, Andrea C.; French, Debbie A.; Sanchez, Richard A.; Tatge, Coty B.

2014-01-01

Providing meaningful telescope observing experiences for students who are deeply urban or distantly rural place-bound--or even daylight time-bound--has consistently presented a formidable challenge for astronomy educators. For nearly 2 decades, the Internet has promised unfettered access for large numbers of students to conduct remote telescope…

Children's rights, international human rights and the promise of ...

African Journals Online (AJOL)

Children's rights, international human rights and the promise of Islamic legal theory. ... Law, Democracy & Development ... law but also religion and ethics, thus offering a multidimensional approach covering the total personality of the child.

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

Unsupervised Feature Subset Selection

DEFF Research Database (Denmark)

Søndberg-Madsen, Nicolaj; Thomsen, C.; Pena, Jose

2003-01-01

This paper studies filter and hybrid filter-wrapper feature subset selection for unsupervised learning (data clustering). We constrain the search for the best feature subset by scoring the dependence of every feature on the rest of the features, conjecturing that these scores discriminate some ir...... irrelevant features. We report experimental results on artificial and real data for unsupervised learning of naive Bayes models. Both the filter and hybrid approaches perform satisfactorily....

When do letter features migrate? A boundary condition for feature-integration theory.

Science.gov (United States)

Butler, B E; Mewhort, D J; Browse, R A

1991-01-01

Feature-integration theory postulates that a lapse of attention will allow letter features to change position and to recombine as illusory conjunctions (Treisman & Paterson, 1984). To study such errors, we used a set of uppercase letters known to yield illusory conjunctions in each of three tasks. The first, a bar-probe task, showed whole-character mislocations but not errors based on feature migration and recombination. The second, a two-alternative forced-choice detection task, allowed subjects to focus on the presence or absence of subletter features and showed illusory conjunctions based on feature migration and recombination. The third was also a two-alternative forced-choice detection task, but we manipulated the subjects' knowledge of the shape of the stimuli: In the case-certain condition, the stimuli were always in uppercase, but in the case-uncertain condition, the stimuli could appear in either upper- or lowercase. Subjects in the case-certain condition produced illusory conjunctions based on feature recombination, whereas subjects in the case-uncertain condition did not. The results suggest that when subjects can view the stimuli as feature groups, letter features regroup as illusory conjunctions; when subjects encode the stimuli as letters, whole items may be mislocated, but subletter features are not. Thus, illusory conjunctions reflect the subject's processing strategy, rather than the architecture of the visual system.

Spectroscopic Observations of Geo-Stationary Satellites Over the Korean Peninsula

Directory of Open Access Journals (Sweden)

D. K. Lee

2001-11-01

Full Text Available Low resolution spectroscopic observations of geo-stationary satellites over the Korean peninsula have been carried out at the KyungHee Optical Satellite Observing Facility (KOSOF with a 40cm telescope. We have observed 9 telecommunication satellites and 1 weather satellite of 6 countries. The obtained spectral data showed that satellites could be classified and grouped with similar basic spectral feature. We divided the 10 satellites into 4 groups based on spectral slop and reflectance. It is suggested that the material types of the satellites can be determined through spectral comparisons with the ground laboratory data. We will continuously observe additional geo-stationary satellites for the accurate classification of spectral features.

Clinical and electrophysiological findings in patients with phenylketonuria and epilepsy: Reflex features.

Science.gov (United States)

Yildiz Celik, Senay; Bebek, Nerses; Gurses, Candan; Baykan, Betul; Gokyigit, Aysen

2018-03-23

Phenylketonuria (PKU) is the most common form of amino acid metabolism disorders with autosomal recessive inheritance. The brain damage can be prevented by early diagnosis and a phenylalanine-restricted diet. Untreated or late-treated patients may show mental retardation and other cognitive dysfunctions, as well as motor disability and/or epilepsy. Three patients with PKU and epilepsy were recognized to have reflex epileptic features, and there were ten consecutive adult patients with PKU and epilepsy who were evaluated retrospectively. Medical history, ages at diagnosis and therapy onset, age at seizure onset, seizure types and reflex features, neurological findings, cranial imaging, electroencephalography (EEG) findings, and final clinical condition were evaluated. Reflex epilepsy features were examined in detail. The cases (6 females, 4 males) were diagnosed at ages between 3.5months and 12years. All patients had various degrees of mental-motor retardation and focal or generalized seizures with age at seizure onset varied between neonatal period and 15years. Three patients had febrile seizure, 3 patients had myoclonia, and 3 patients had status epilepticus. All patients had abnormal EEG findings except one. There was a slowing of background activity, and generalized discharges were observed in 7 patients; 3 of them had asymmetrical discharges. One patient had right hippocampal sclerosis (HS), and another patient had hypointensities in the basal ganglia and corpus callosum. Reflex features were clinically observed in 3 of the patients; however, EEG results did not show any related findings. One patient had reflex seizures triggered by photic stimuli, hot water, and startling; one by photic stimuli; and the other one by startling. Reports on the clinical and electrophysiological features of adult patients with PKU were scant. We emphasized that reflex clinical features may be observed in this metabolic disease, and focal epileptiform abnormalities and asymmetry

An efficient approach for differentiating Alzheimer's disease from normal elderly based on multicenter MRI using gray-level invariant features.

Directory of Open Access Journals (Sweden)

Muwei Li

Full Text Available Machine learning techniques, along with imaging markers extracted from structural magnetic resonance images, have been shown to increase the accuracy to differentiate patients with Alzheimer's disease (AD from normal elderly controls. Several forms of anatomical features, such as cortical volume, shape, and thickness, have demonstrated discriminative capability. These approaches rely on accurate non-linear image transformation, which could invite several nuisance factors, such as dependency on transformation parameters and the degree of anatomical abnormality, and an unpredictable influence of residual registration errors. In this study, we tested a simple method to extract disease-related anatomical features, which is suitable for initial stratification of the heterogeneous patient populations often encountered in clinical data. The method employed gray-level invariant features, which were extracted from linearly transformed images, to characterize AD-specific anatomical features. The intensity information from a disease-specific spatial masking, which was linearly registered to each patient, was used to capture the anatomical features. We implemented a two-step feature selection for anatomic recognition. First, a statistic-based feature selection was implemented to extract AD-related anatomical features while excluding non-significant features. Then, seven knowledge-based ROIs were used to capture the local discriminative powers of selected voxels within areas that were sensitive to AD or mild cognitive impairment (MCI. The discriminative capability of the proposed feature was measured by its performance in differentiating AD or MCI from normal elderly controls (NC using a support vector machine. The statistic-based feature selection, together with the knowledge-based masks, provided a promising solution for capturing anatomical features of the brain efficiently. For the analysis of clinical populations, which are inherently heterogeneous

Featureous: an Integrated Approach to Location, Analysis and Modularization of Features in Java Applications

DEFF Research Database (Denmark)

Olszak, Andrzej

, it is essential that features are properly modularized within the structural organization of software systems. Nevertheless, in many object-oriented applications, features are not represented explicitly. Consequently, features typically end up scattered and tangled over multiple source code units......, such as architectural layers, packages and classes. This lack of modularization is known to make application features difficult to locate, to comprehend and to modify in isolation from one another. To overcome these problems, this thesis proposes Featureous, a novel approach to location, analysis and modularization...... quantitative and qualitative results suggest that Featureous succeeds at efficiently locating features in unfamiliar codebases, at aiding feature-oriented comprehension and modification, and at improving modularization of features using Java packages....

Faculty-Student Engagement in Teaching Observation and Assessment: A Hong Kong Initiative

Science.gov (United States)

Pounder, James S.; Ho Hung-lam, Elizabeth; Groves, Julie May

2016-01-01

There is now a worldwide focus on the quality of university teaching and yet there is general dissatisfaction in universities with the student evaluation of teaching system. Peer observation of teaching seems to hold much promise in the assessment of teaching quality, but such observation pays little attention to the quality of teaching as…

Innovations in individual feature history management - The significance of feature-based temporal model

Science.gov (United States)

Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

2008-01-01

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

Promising Themes for Antismoking Campaigns Targeting Youth and Young Adults.

Science.gov (United States)

Brennan, Emily; Gibson, Laura A; Kybert-Momjian, Ani; Liu, Jiaying; Hornik, Robert C

2017-01-01

Behavior change campaigns typically try to change beliefs that influence behaviors, with targeted beliefs comprising the campaign theme. We present an empirical approach for choosing among a large number of potential themes, and results from the implementation of this approach for campaigns aimed at 4 behavioral targets: (1) preventing smoking initiation among youth, and (2) preventing initiation, (3) stopping progression to daily smoking and (4) encouraging cessation among young adults. An online survey of 13- to 17-year-olds and 18- to 25-year-olds in the United States (US), in which 20 potential campaign themes were represented by 154 beliefs. For each behavioral target, themes were ranked based on the strength of belief-intention and belief-behavior associations and size of the population not already endorsing the beliefs. The most promising themes varied across behavioral targets but 3 were consistently promising: consequences of smoking for mood, social acceptance and social popularity. Using a robust and systematic approach, this study provides campaign developers with empirical data to inform their selection of promising themes. Findings related to the campaign to prevent initiation among youth informed the development of the US Food and Drug Administration's "The Real Cost" campaign.

Observations of gamma-ray emission in solar flares

International Nuclear Information System (INIS)

Forrest, D.J.; Chupp, E.L.; Suri, A.N.; Reppin, C.

1973-01-01

This paper reviews the observations of gamma-ray emission made from the OSO-7 satellite in connection with two solar flares in early August 1972. The details of the measurements and a preliminary interpretation of some of the observed features are given. (U.S.)

Dependency Parsing with Transformed Feature

Directory of Open Access Journals (Sweden)

Fuxiang Wu

2017-01-01

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

An improved feature extraction algorithm based on KAZE for multi-spectral image

Science.gov (United States)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

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

Science.gov (United States)

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

2009-11-18

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

KirCII- promising tool for polyketide diversification

DEFF Research Database (Denmark)

Musiol-Kroll, Ewa Maria; Härtner, Thomas; Kulik, Andreas

2014-01-01

Kirromycin is produced by Streptomyces collinus Tü 365. This compound is synthesized by a large assembly line of type I polyketide synthases and non-ribosomal peptide synthetases (PKS I/NRPS), encoded by the genes kirAI-kirAVI and kirB. The PKSs KirAI-KirAV have no acyltransferase domains integra...... introducing the non-native substrates in an in vivo context. Thus, KirCII represents a promising tool for polyketide diversification....

Autonomous Navigation in Partially Observable Environments Using Hierarchical Q-Learning

NARCIS (Netherlands)

Zhou, Y.; van Kampen, E.; Chu, Q.

2016-01-01

Flapping-wing MAVs represent an attractive alternative to conventional designs with rotary wings, since they promise a much higher efficiency in forward flight. However, further insight into the flapping-wing aerodynamics is still needed to get closer to the flight performance observed in natural

Results of Joint Observations of Jupiter's Atmosphere by Juno and a Network of Earth-Based Observing Stations

Science.gov (United States)

Orton, Glenn; Momary, Thomas; Bolton, Scott; Levin, Steven; Hansen, Candice; Janssen, Michael; Adriani, Alberto; Gladstone, G. Randall; Bagenal, Fran; Ingersoll, Andrew

2017-04-01

The Juno mission has promoted and coordinated a network of Earth-based observations, including both Earth-proximal and ground-based facilities, to extend and enhance observations made by the Juno mission. The spectral region and timeline of all of these observations are summarized in the web site: https://www.missionjuno.swri.edu/planned-observations. Among the earliest of these were observation of Jovian auroral phenomena at X-ray, ultraviolet and infrared wavelengths and measurements of Jovian synchrotron radiation from the Earth simultaneously with the measurement of properties of the upstream solar wind. Other observations of significance to the magnetosphere measured the mass loading from Io by tracking its observed volcanic activity and the opacity of its torus. Observations of Jupiter's neutral atmosphere included observations of reflected sunlight from the near-ultraviolet through the near-infrared and thermal emission from 5 μm through the radio region. The point of these measurements is to relate properties of the deep atmosphere that are the focus of Juno's mission to the state of the "weather layer" at much higher atmospheric levels. These observations cover spectral regions not included in Juno's instrumentation, provide spatial context for Juno's often spatially limited coverage of Jupiter, and they describe the evolution of atmospheric features in time that are measured only once by Juno. We will summarize the results of measurements during the approach phase of the mission that characterized the state of the atmosphere, as well as observations made by Juno and the supporting campaign during Juno's perijoves 1 (2016 August 27), 3 (2016 December 11), 4 (2017 February 2) and possibly "early" results from 5 (2017 March 27). Besides a global network of professional astronomers, the Juno mission also benefited from the enlistment of a network of dedicated amateur astronomers who provided a quasi-continuous picture of the evolution of features observed by

Photonic crystals: features and applications (physics research and technology)

CERN Document Server

2013-01-01

The present book is focused on the study of unprecedented control and manipulation of light by photonic crystals (PCs) and their applications. These are micro- or usually nano-structures composed of periodic indexes of refraction of dielectrics with high refractive index contrast. They exhibit optical frequency band gaps in analogy to electronic bands for a periodic potential of a semiconductor crystal lattice. The gemstone opal and butterflys feathers colours are already referred to as natural examples of photonic crystals. The characteristics of such supper-lattices were first reported by Yablonovitch in 1987. The exploitation of photonic crystals is a promising tool in communication, sensors, optical computing, and nanophotonics. Discussed are the various features of one-dimensional (1D) and two-dimensional (2D) photonic crystals, photonic quasi crystals, heterostuctures and PC fibres under a variety of conditions using several materials, and metamaterials. It also focuses on the applications of PCs in opt...

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training.

Science.gov (United States)

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer.

Environmentally Sustainable Aluminum-Coordinated Poly(tetrahydroxybenzoquinone) as a Promising Cathode for Sodium Ion Batteries.

Science.gov (United States)

Kim, Hee Joong; Kim, Youngjin; Shim, Jimin; Jung, Kyung Hwa; Jung, Min Soo; Kim, Hanseul; Lee, Jong-Chan; Lee, Kyu Tae

2018-01-31

Na-ion batteries are attractive as an alternative to Li-ion batteries because of their lower cost. Organic compounds have been considered as promising electrode materials due to their environmental friendliness and molecular diversity. Herein, aluminum-coordinated poly(tetrahydroxybenzoquinone) (P(THBQ-Al)), one of the coordination polymers, is introduced for the first time as a promising cathode for Na-ion batteries. P(THBQ-Al) is synthesized through a facile coordination reaction between benzoquinonedihydroxydiolate (C 6 O 6 H 2 2- ) and Al 3+ as ligands and complex metal ions, respectively. Tetrahydroxybenzoquinone is environmentally sustainable, because it can be obtained from natural resources such as orange peels. Benzoquinonedihydroxydiolate also contributes to delivering high reversible capacity, because each benzoquinonedihydroxydiolate unit is capable of two electron reactions through the sodiation of its conjugated carbonyl groups. Electrochemically inactive Al 3+ improves the structural stability of P(THBQ-Al) during cycling because of a lack of a change in its oxidation state. Moreover, P(THBQ-Al) is thermally stable and insoluble in nonaqueous electrolytes. These result in excellent electrochemical performance including a high reversible capacity of 113 mA h g -1 and stable cycle performance with negligible capacity fading over 100 cycles. Moreover, the reaction mechanism of P(THBQ-Al) is clarified through ex situ XPS and IR analyses, in which the reversible sodiation of C═O into C-O-Na is observed.

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

Science.gov (United States)

Ito, Motohiro; Kawahara, Jun I

2016-01-01

The present study examined whether attention can be flexibly controlled to monitor two different feature dimensions (shape and color) in a temporal search task. Specifically, we investigated the occurrence of contingent attentional capture (i.e., interference from task-relevant distractors) and resulting set reconfiguration (i.e., enhancement of single task-relevant set). If observers can restrict searches to a specific value for each relevant feature dimension independently, the capture and reconfiguration effect should only occur when the single relevant distractor in each dimension appears. Participants identified a target letter surrounded by a non-green square or a non-square green frame. The results revealed contingent attentional capture, as target identification accuracy was lower when the distractor contained a target-defining feature than when it contained a nontarget feature. Resulting set reconfiguration was also obtained in that accuracy was superior when the current target's feature (e.g., shape) corresponded to the defining feature of the present distractor (shape) than when the current target's feature did not match the distractor's feature (color). This enhancement was not due to perceptual priming. The present study demonstrated that the principles of contingent attentional capture and resulting set reconfiguration held even when multiple target feature dimensions were monitored. Copyright © 2015 Elsevier B.V. All rights reserved.

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

Science.gov (United States)

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Score level fusion scheme based on adaptive local Gabor features for face-iris-fingerprint multimodal biometric

Science.gov (United States)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Chen, Ying

2014-05-01

A multimodal biometric system has been considered a promising technique to overcome the defects of unimodal biometric systems. We have introduced a fusion scheme to gain a better understanding and fusion method for a face-iris-fingerprint multimodal biometric system. In our case, we use particle swarm optimization to train a set of adaptive Gabor filters in order to achieve the proper Gabor basic functions for each modality. For a closer analysis of texture information, two different local Gabor features for each modality are produced by the corresponding Gabor coefficients. Next, all matching scores of the two Gabor features for each modality are projected to a single-scalar score via a trained, supported, vector regression model for a final decision. A large-scale dataset is formed to validate the proposed scheme using the Facial Recognition Technology database-fafb and CASIA-V3-Interval together with FVC2004-DB2a datasets. The experimental results demonstrate that as well as achieving further powerful local Gabor features of multimodalities and obtaining better recognition performance by their fusion strategy, our architecture also outperforms some state-of-the-art individual methods and other fusion approaches for face-iris-fingerprint multimodal biometric systems.

Comparison of laminite fracture features at different scales

OpenAIRE

Zihms, Stephanie; Miranda, Tiago; Lewis, Helen; Hall, Stephen

2017-01-01

Laminites (NE Brazil) are well laminated carbonates that provide insight into the geomechanical behaviour of layered systems, especially when comparing deformation characteristics observed in the laboratory with outcrop / field scale deformations. This is useful in order to a)  validate where laboratory experiments can reproduce field scale deformation types b)  understand which feature characteristics can or cannot be scaled

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

Directory of Open Access Journals (Sweden)

Chundi eWang

2016-05-01

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

Promised and Delivered Inducements and Contributions: An Integrated View of Psychological Contract Appraisal

Science.gov (United States)

Lambert, Lisa Schurer

2011-01-01

The reciprocal exchange of employees' work for pay that is central to employment relationships is viewed here through the lens of the psychological contract. A psychological contract involves promised inducements, promised contributions, delivered inducements, and delivered contributions: How an employee cognitively integrates these 4 elements is…

The Math Promise: Celebrating at Home and School

Science.gov (United States)

Legnard, Danielle; Austin, Susan

2014-01-01

The Math Promise is a contract that family members make with one another. They commit to spending mathematical time together; getting to know each other's mathematical thinking and understanding; and finding time to play math games, solve problems, and notice mathematics in their daily lives. Whether parents and children are cooking in the…

Promising lines of investigations in the realms of laboratory astrophysics with the aid of powerful lasers

International Nuclear Information System (INIS)

Belyaev, V. S.; Batishchev, P. A.; Bolshakov, V. V.; Elkin, K. S.; Karabadzhak, G. F.; Kovkov, D. V.; Matafonov, A. P.; Raykunov, G. G.; Yakhin, R. A.; Pikuz, S. A.; Skobelev, I. Yu.; Faenov, A. Ya.; Fortov, V. E.; Krainov, V. P.; Rozanov, V. B.

2013-01-01

The results of work on choosing and substantiating promising lines of research in the realms of laboratory astrophysics with the aid of powerful lasers are presented. These lines of research are determined by the possibility of simulating, under laboratory conditions, problematic processes of presentday astrophysics, such as (i) the generation and evolution of electromagnetic fields in cosmic space and the role of magnetic fields there at various spatial scales; (ii) the mechanisms of formation and evolution of cosmic gamma-ray bursts and relativistic jets; (iii) plasma instabilities in cosmic space and astrophysical objects, plasma jets, and shock waves; (iv) supernova explosions and mechanisms of the explosion of supernovae featuring a collapsing core; (v) nuclear processes in astrophysical objects; (vi) cosmic rays and mechanisms of their production and acceleration to high energies; and (vii) astrophysical sources of x-ray radiation. It is shown that the use of existing powerful lasers characterized by an intensity in the range of 10 18 –10 22 W/cm 2 and a pulse duration of 0.1 to 1 ps and high-energy lasers characterized by an energy in excess of 1 kJ and a pulse duration of 1 to 10 ns makes it possible to perform investigations in laboratory astrophysics along all of the chosen promising lines. The results obtained by experimentally investigating laser plasma with the aid of the laser facility created at Central Research Institute of Machine Building (TsNIIMash) and characterized by a power level of 10 TW demonstrate the potential of such facilities for performing a number of experiments in the realms of laboratory astrophysics.

7 T renal MRI: challenges and promises.

Science.gov (United States)

de Boer, Anneloes; Hoogduin, Johannes M; Blankestijn, Peter J; Li, Xiufeng; Luijten, Peter R; Metzger, Gregory J; Raaijmakers, Alexander J E; Umutlu, Lale; Visser, Fredy; Leiner, Tim

2016-06-01

The progression to 7 Tesla (7 T) magnetic resonance imaging (MRI) yields promises of substantial increase in signal-to-noise (SNR) ratio. This increase can be traded off to increase image spatial resolution or to decrease acquisition time. However, renal 7 T MRI remains challenging due to inhomogeneity of the radiofrequency field and due to specific absorption rate (SAR) constraints. A number of studies has been published in the field of renal 7 T imaging. While the focus initially was on anatomic imaging and renal MR angiography, later studies have explored renal functional imaging. Although anatomic imaging remains somewhat limited by inhomogeneous excitation and SAR constraints, functional imaging results are promising. The increased SNR at 7 T has been particularly advantageous for blood oxygen level-dependent and arterial spin labelling MRI, as well as sodium MR imaging, thanks to changes in field-strength-dependent magnetic properties. Here, we provide an overview of the currently available literature on renal 7 T MRI. In addition, we provide a brief overview of challenges and opportunities in renal 7 T MR imaging.

Observer variation in chest radiography of acute lower respiratory infections in children: a systematic review

International Nuclear Information System (INIS)

Swingler, George H

2001-01-01

Knowledge of the accuracy of chest radiograph findings in acute lower respiratory infection in children is important when making clinical decisions. I conducted a systematic review of agreement between and within observers in the detection of radiographic features of acute lower respiratory infections in children, and described the quality of the design and reporting of studies, whether included or excluded from the review. Included studies were those of observer variation in the interpretation of radiographic features of lower respiratory infection in children (neonatal nurseries excluded) in which radiographs were read independently and a clinical population was studied. I searched MEDLINE, HealthSTAR and HSRPROJ databases (1966 to 1999), handsearched the reference lists of identified papers and contacted authors of identified studies. I performed the data extraction alone. Ten studies of observer interpretation of radiographic features of lower respiratory infection in children were identified. Seven of the studies satisfied four or more of the seven design and reporting criteria. Six studies met the inclusion criteria for the review. Inter-observer agreement varied with the radiographic feature examined. Kappa statistics ranged from around 0.80 for individual radiographic features to 0.27–0.38 for bacterial vs viral etiology. Little information was identified on observer agreement on radiographic features of lower respiratory tract infections in children. Agreement varied with the features assessed from 'fair' to 'very good'. Aspects of the quality of the methods and reporting need attention in future studies, particularly the description of criteria for radiographic features

The promising opportunity of dismantlement

International Nuclear Information System (INIS)

Anon.

2009-01-01

Civil engineering, mechanics and waste conditioning companies are thriving around the market of nuclear facilities dismantlement which is promised to a huge development in the coming decade. This paper presents a map of the opportunities of the dismantlement market throughout Europe (research and power reactors, fuel fabrication plants, spent fuel reprocessing plants) and a cost estimation of a given dismantling work with respect to the different steps of the work. In France a small core of about twenty companies is involved in nuclear dismantlement but the French market is also looking towards foreign specialists of this activity. The British market is also targeted by the French companies but for all the actors the technological or commercial advance gained today will be determining for the future markets. (J.S.)

Natural Flavonoids as Promising Analgesic Candidates: A Systematic Review.

Science.gov (United States)

Xiao, Xiao; Wang, Xiaoyu; Gui, Xuan; Chen, Lu; Huang, Baokang

2016-11-01