Uncovering the Hidden Structure of Platoons: Formal and Emergent Leaders’ Perceptions of Organizational Networks

DTIC Science & Technology

2008-12-01

perceptions of formal and emergent leaders differ from those of non-leaders, and if so, how. We approach this topic through the lens of social network...analysis. 1.1 Social Networks The term “ social network” refers to a set of actors who are connected by a set of ties. Actors, often referred to as...the structure of any social system can be defined as a set of relations between all pairs of individuals who are members of the network (Krackhardt

Healing the Split Between the Gospel and the Media Culture.

ERIC Educational Resources Information Center

McDonnell, Jim

1998-01-01

Implores educators to help people discern between real and false paths to God as advertised in contemporary culture and mass media, and to communicate the Christian message in ways that uncover the transcendent meaning hidden in popular culture. (VWC)

Uncovering Information Hidden in Web Archives: Glimpse at Web Analysis Building on Data Warehouses; Towards Continuous Web Archiving: First Results and an Agenda for the Future; The Open Video Digital Library; After Migration to an Electronic Journal Collection: Impact on Faculty and Doctoral Students; Who Is Reading On-Line Education Journals? Why? And What Are They Reading?; Report on eLibrary@UBC4: Research, Collaboration and the Digital Library - Visions for 2010.

ERIC Educational Resources Information Center

Rauber, Andreas; Bruckner, Robert M.; Aschenbrenner, Andreas; Witvoet, Oliver; Kaiser, Max; Masanes, Julien; Marchionini, Gary; Geisler, Gary; King, Donald W.; Montgomery, Carol Hansen; Rudner, Lawrence M.; Gellmann, Jennifer S.; Miller-Whitehead, Marie; Iverson, Lee

2002-01-01

These six articles discuss Web archives and Web analysis building on data warehouses; international efforts at continuous Web archiving; the Open Video Digital Library; electronic journal collections in academic libraries; online education journals; and an electronic library symposium at the University of British Columbia. (LRW)

Unethical conduct by the nurse: a critical discourse analysis of Nurses Tribunal inquiries.

PubMed

Dixon, Kathleen A

2013-08-01

The aim of this study was to uncover and critically examine hidden assumptions that underpin the findings of nurses' unethical conduct arising from inquiries conducted by the Nurses Tribunal in New South Wales. This was a qualitative study located within a post-structural theoretical framework. Transcripts of five inquiries conducted between 1998 and 2003 were analysed using critical discourse analysis. The findings revealed two dominant discourses that were drawn upon in the inquiries to construct nurses' conduct as unethical. These were discourses of trust and accountability. The way the nurses were spoken about during the inquiries was shaped by normalising judgements that were used to discursively position the nurse through narrative.

The Hidden Curriculum: What Are We Actually Teaching about the Fundamentals of Care?

PubMed

MacMillan, Kathleen

2016-01-01

The issues of missed or inadequately provided basic nursing care and related complications are being identified as worldwide phenomena of interest. Without being aware of it, educators and practicing nurses may be teaching nursing students that fundamental nursing care is unimportant, uncomplicated and not really nursing's responsibility. This paper explores the concept of the "hidden curriculum" in nursing education, as it relates to fundamental nursing care and calls for greater partnerships between education and service to uncover the hidden curriculum; to effectively shape it to achieve alignment between classroom and practice; and, ultimately, to improve care processes and patient outcomes through collaboration. A renewed focus on the vital importance of what is considered "basics" to patient outcomes is required in nursing education. Copyright © 2016 Longwoods Publishing.

Uncovering the "Hidden" Multilingualism of Europe: An Italian Case Study

ERIC Educational Resources Information Center

Tamburelli, Marco

2014-01-01

Dominant notions of what constitutes a "language" and what a "dialect" within a continuum are entirely based on sociopolitical factors (i.e. the "languages by 'Ausbau'" of Kloss), totally disregarding structural and communicative aspects. This paper argues that such stance is no longer tenable in view of the modern…

Sitting on a Gold Mine.

ERIC Educational Resources Information Center

Zanic, Tom; Kirchenstein, Joel

1998-01-01

Many districts are holding property that could be put to better use. With a creative strategy for planning, analyzing, and implementing a plan for these public properties, local boards and administrators can uncover hidden value in their real estate assets. California's Santa Monica-Malibu Unified School District now receives $500,000 a year in…

Making the Case for Demographic Data in Extension Programming

ERIC Educational Resources Information Center

Curtis, Katherine J.; Verdoff, Daniel; Rizzo, Bill; Beaudoin, James

2012-01-01

Understanding one's community is essential for effective Extension programming across all program areas. The use of current and reliable demographic data is crucial for Extension to develop effective education and programming to track change and to uncover hidden community characteristics. We discuss what demographic data are, present…

Uncovering the hidden: complexity and strategies for diagnosing latent tuberculosis.

PubMed

Flores-Valdez, Mario Alberto

2017-10-24

Tuberculosis produces two clinical manifestations: active and latent (non-apparent) disease. The latter is estimated to affect one-third of the world population and constitutes a source of continued transmission should the disease emerge from its hidden state (reactivation). Methods to diagnose latent TB have been evolving and aim to detect the disease in people who are truly infected with M. tuberculosis , versus those where other mycobacteria, or even other pathologies not related to TB, are present. The current use of proteomic and transcriptomic approaches may lead to improved detection methods in the coming years.

Uncovering the Hidden Meaning of Cross-Curriculum Comparison Results on the Force Concept Inventory

ERIC Educational Resources Information Center

Ding, Lin; Caballero, Marcos D.

2014-01-01

In a recent study, Caballero and colleagues conducted a large-scale evaluation using the Force Concept Inventory (FCI) to compare student learning outcomes between two introductory physics curricula: the Matter and Interactions (M&I) mechanics course and a pedagogically-reformed-traditional-content (PRTC) mechanics course. Using a conventional…

Context, Complexity and Contestation: Birmingham's Agreed Syllabuses for Religious Education since the 1970s

ERIC Educational Resources Information Center

Parker, Stephen G.; Freathy, Rob J. K.

2011-01-01

The present article offers an historical perspective on the 1975, 1995 and 2007 Birmingham Agreed Syllabuses for Religious Education. It draws upon historical evidence uncovered as part of "The hidden history of curriculum change in religious education in English schools, 1969-1979" project, and curriculum history theories, especially…

How to Show One-Fourth? Uncovering Hidden Context through Reciprocal Learning

ERIC Educational Resources Information Center

Abramovich, S.; Brouwer, P.

2007-01-01

This paper suggests that mathematics teacher educators should listen carefully to what their students are saying. More specifically, it demonstrates how from one pre-teacher's non-traditional geometric representation of a unit fraction, a variety of learning environments that lead to the enrichment of mathematics for teaching can be developed. The…

In the Minds of OSCE Examiners: Uncovering Hidden Assumptions

ERIC Educational Resources Information Center

Chahine, Saad; Holmes, Bruce; Kowalewski, Zbigniew

2016-01-01

The Objective Structured Clinical Exam (OSCE) is a widely used method of assessment in medical education. Rater cognition has become an important area of inquiry in the medical education assessment literature generally, and in the OSCE literature specifically, because of concerns about potential compromises of validity. In this study, a novel…

Sexual Harassment and Abuse of Adolescent Schoolgirls in South India

ERIC Educational Resources Information Center

Leach, Fiona; Sitaram, Shashikala

2007-01-01

This article reports on a small exploratory study of adolescent girls' experiences of sexual harassment and abuse while attending secondary school in Karnataka State, South India. In South Asia, public discussion of sexual matters, especially relating to children, is largely taboo, and the study uncovers a hidden aspect of schooling, which…

Reporting on Race, Education & No Child Left Behind: A Guide for Journalists.

ERIC Educational Resources Information Center

Johnson, Tammy, Ed.

This handbook is a tool that reporters can use to uncover the hidden dimensions of race in public education and ask the right questions about the No Child Left Behind Act of 2001. Section 1, "Race Revealed", includes "Special Education" (Daniel J. Losen); "Dropout and Graduation Rates" (Daniel J. Losen);…

Machine learning for neuroimaging with scikit-learn.

PubMed

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

Machine learning for neuroimaging with scikit-learn

PubMed Central

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain. PMID:24600388

Nurse faculty experiences in problem-based learning: an interpretive phenomenologic analysis.

PubMed

Paige, Jane B; Smith, Regina O

2013-01-01

This study explored the nurse faculty experience of participating in a problem-based learning (PBL) faculty development program. Utilizing PBL as a pedagogical method requires a paradigm shift in the way faculty think about teaching, learning, and the teacher-student relationship. An interpretive phenomenological analysis approach was used to explore the faculty experience in a PBL development program. Four themes emerged: change in perception of the teacher-student relationship, struggle in letting go, uncertainty, and valuing PBL as a developmental process. Epistemic doubt happens when action and intent toward the PBL teaching perspective do not match underlying beliefs. Findings from this study call for ongoing administrative support for education on PBL while faculty take time to uncover hidden epistemological beliefs.

Observer-Pattern Modeling and Slow-Scale Bifurcation Analysis of Two-Stage Boost Inverters

NASA Astrophysics Data System (ADS)

Zhang, Hao; Wan, Xiaojin; Li, Weijie; Ding, Honghui; Yi, Chuanzhi

2017-06-01

This paper deals with modeling and bifurcation analysis of two-stage Boost inverters. Since the effect of the nonlinear interactions between source-stage converter and load-stage inverter causes the “hidden” second-harmonic current at the input of the downstream H-bridge inverter, an observer-pattern modeling method is proposed by removing time variance originating from both fundamental frequency and hidden second harmonics in the derived averaged equations. Based on the proposed observer-pattern model, the underlying mechanism of slow-scale instability behavior is uncovered with the help of eigenvalue analysis method. Then eigenvalue sensitivity analysis is used to select some key system parameters of two-stage Boost inverter, and some behavior boundaries are given to provide some design-oriented information for optimizing the circuit. Finally, these theoretical results are verified by numerical simulations and circuit experiment.

Hidden Stories: Uncovering the Visual Metaphor for Education and Communication

ERIC Educational Resources Information Center

Hube, Amy M.; Tremblay, Kenneth R., Jr.; Leigh, Katharine E.

2015-01-01

Design solutions have become increasingly complex and based on a rapidly growing body of knowledge. In order to articulate a design solution to a client, the graphic use of the design narrative can effectively communicate complex ideas. Two case study interventions were conducted in an interior design program in which students were introduced to…

Pragmatism and Progressivism in the Educational Thought and Practices of Booker T. Washington

ERIC Educational Resources Information Center

Chennault, Ronald E.

2013-01-01

The author of this article asserts that African-American author and educator Booker T. Washington's work situates him within the educational traditions of pragmatism and progressivism. The article uncovers some of Washington's hidden complexity by drawing upon and extending arguments for labeling him both an educational pragmatist and…

"Things Fall Apart so They Can Fall Together": Uncovering the Hidden Side of Writing a Teaching Award Application

ERIC Educational Resources Information Center

McCormack, Coralie; Vanags, Thea; Prior, Robyn

2014-01-01

Teaching awards are now common practice in higher education. However, few award applicants and their writing guides have investigated their experience of writing a teaching award application, a writing process recognised as different from that required in research publication. To systematically research and analyse their personal experiences two…

Uncovering Hidden Dimensions of Australian Early Childhood Policy History: Insights from Interviews with Policy "Elites"

ERIC Educational Resources Information Center

Logan, Helen; Sumsion, Jennifer; Press, Frances

2014-01-01

This article considers the value of elite interviews as a frequently overlooked methodology in investigations of policymaking in early childhood education and care (ECEC). We contextualise the discussion within a study that examines constructions of quality in Australian ECEC policymaking between 1972 and 2009. We conclude that, despite their…

Uncovering the density of nanowire surface trap states hidden in the transient photoconductance.

PubMed

Xu, Qiang; Dan, Yaping

2016-09-21

The gain of nanoscale photoconductors is closely correlated with surface trap states. Mapping out the density of surface trap states in the semiconductor bandgap is crucial for engineering the performance of nanoscale photoconductors. Traditional capacitive techniques for the measurement of surface trap states are not readily applicable to nanoscale devices. Here, we demonstrate a simple technique to extract the information on the density of surface trap states hidden in the transient photoconductance that is widely observed. With this method, we found that the density of surface trap states of a single silicon nanowire is ∼10(12) cm(-2) eV(-1) around the middle of the upper half bandgap.

A proposed OB-fold with a protein-interaction surface in Candida albicans telomerase protein Est3

PubMed Central

Yu, Eun Young; Wang, Feng; Lei, Ming; Lue, Neal F

2008-01-01

Ever shorter telomeres 3 (Est3) is an essential telomerase regulatory subunit thought to be unique to budding yeasts. Here we use multiple sequence alignment and hidden Markov model–hidden Markov model (HMM-HMM) comparison to uncover potential similarities between Est3 and the mammalian telomeric protein Tpp1. Analysis of site-specific mutants of Candida albicans Est3 revealed functional distinctions between residues that are conserved between Est3 and Tpp1 and those that are unique to Est3. Although both types of residues are important for telomere maintenance in vivo, only the former contributes to telomerase activity in vitro and facilitates the association of Est3 with telomerase core components. Consistent with a function in protein-protein interaction, the residues common to Est3 and Tpp1 map to one face of an OB-fold model structure, away from the canonical nucleic acid binding surface. We propose that Est3 and the OB-fold domain of Tpp1 mediate a conserved function in telomerase regulation. PMID:19172753

Self-Efficacy Beliefs and Mental Time Travel Ability: Uncovering a Hidden Relationship in Educational Settings

ERIC Educational Resources Information Center

Eren, Altay

2009-01-01

The aim of this study was threefold: first, it was to explore the profiles of student teachers' mental time travel ability; second, it was to examine the relationship between student teachers' mental time travel ability and self-efficacy beliefs; and third, it was to investigate the role of self-efficacy beliefs in relationship between the past…

Contract Faculty in Canada: Using Access to Information Requests to Uncover Hidden Academics in Canadian Universities

ERIC Educational Resources Information Center

Brownlee, Jamie

2015-01-01

In Canada, universities are undergoing a process of corporatization where business interests, values and practices are assuming a more prominent place in higher education. A key feature of this process has been the changing composition of academic labor. While it is generally accepted that universities are relying more heavily on contract faculty,…

Uncovering the Hidden Wage : Public Perceptions of Opportunities for Side Income in Various Occupations in the USSR

DTIC Science & Technology

1991-11-01

34 February 1991.31 pp. 26. Kevin Block. "Depoliticizing Ownership: An Examination of the Property Reform Debate and the New Law on Ownership in the USSR...RSFSR (Trud v SSSR, pp. 156-157). 18 Assuming librariam make the average of waer in "Cultme" (and they pulably made less), the official salary of a

Troublesome aspects of the Renyi-MaxEnt treatment.

PubMed

Plastino, A; Rocca, M C; Pennini, F

2016-07-01

We study in great detail the possible existence of a Renyi-associated thermodynamics, with negative results. In particular, we uncover a hidden relation in Renyi's variational problem (MaxEnt). This relation connects the two associated Lagrange multipliers (canonical ensemble) with the mean energy 〈U〉 and the Renyi parameter α. As a consequence of such relation, we obtain anomalous Renyi-MaxEnt thermodynamic results.

Uncovering hidden heterogeneity: Geo-statistical models illuminate the fine scale effects of boating infrastructure on sediment characteristics and contaminants.

PubMed

Hedge, L H; Dafforn, K A; Simpson, S L; Johnston, E L

2017-06-30

Infrastructure associated with coastal communities is likely to not only directly displace natural systems, but also leave environmental footprints' that stretch over multiple scales. Some coastal infrastructure will, there- fore, generate a hidden layer of habitat heterogeneity in sediment systems that is not immediately observable in classical impact assessment frameworks. We examine the hidden heterogeneity associated with one of the most ubiquitous coastal modifications; dense swing moorings fields. Using a model based geo-statistical framework we highlight the variation in sedimentology throughout mooring fields and reference locations. Moorings were correlated with patches of sediment with larger particle sizes, and associated metal(loid) concentrations in these patches were depressed. Our work highlights two important ideas i) mooring fields create a mosaic of habitat in which contamination decreases and grain sizes increase close to moorings, and ii) model- based frameworks provide an information rich, easy-to-interpret way to communicate complex analyses to stakeholders. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Data-based reconstruction of complex geospatial networks, nodal positioning and detection of hidden nodes

PubMed Central

Su, Ri-Qi; Wang, Wen-Xu; Wang, Xiao; Lai, Ying-Cheng

2016-01-01

Given a complex geospatial network with nodes distributed in a two-dimensional region of physical space, can the locations of the nodes be determined and their connection patterns be uncovered based solely on data? We consider the realistic situation where time series/signals can be collected from a single location. A key challenge is that the signals collected are necessarily time delayed, due to the varying physical distances from the nodes to the data collection centre. To meet this challenge, we develop a compressive-sensing-based approach enabling reconstruction of the full topology of the underlying geospatial network and more importantly, accurate estimate of the time delays. A standard triangularization algorithm can then be employed to find the physical locations of the nodes in the network. We further demonstrate successful detection of a hidden node (or a hidden source or threat), from which no signal can be obtained, through accurate detection of all its neighbouring nodes. As a geospatial network has the feature that a node tends to connect with geophysically nearby nodes, the localized region that contains the hidden node can be identified. PMID:26909187

Uncovering the Hidden Molecular Signatures of Breast Cancer

DTIC Science & Technology

2013-05-01

that! synergy! between! the! oncogene!MET!and!loss!of!p53!(tumor! protein !p53)!lead!to!a!tumor!phenotype!that! reflects! the! human! claudinDlow...membrane! protein ! levels! increase! continuously! in! accordance.! This! increase! has! been! directly! linked! to! a! corresponding! change! in...the!ESR! protein ! (Figure!1).!Alternatively,!a!signature!may! order!patients!in!such!a!way!that!associations!can!be!made!with!a!variety!of!other

Uncovering the Hidden Histories: Black and Asian People in the Two World Wars

ERIC Educational Resources Information Center

Gaze, Rupert

2005-01-01

The stories we tell in history are often stories about ourselves. This can lead to tremendous distortion. Rupert Gaze was shocked when a young black student told him that there was no point in his studying the Second World War because it had nothing to do with him or his family. While Gaze has worked for the Imperial War Museum (IWM) North, it has…

"I Don't Know What Literacy Is": Uncovering Hidden Literacies in a Community Library Using Ecological and Participatory Research Methodologies with Children

ERIC Educational Resources Information Center

Pahl, Kate; Allan, Chloe

2011-01-01

This article describes an ecological study in Eastside, a particular area of Rotherham, a town in the north of England, UK. The purpose of the study was to collect information about literacy practices in a community setting, focusing on a library. The researchers used an ecological approach to data collection. The methodology included approaches…

Hidden Structural Codes in Protein Intrinsic Disorder.

PubMed

Borkosky, Silvia S; Camporeale, Gabriela; Chemes, Lucía B; Risso, Marikena; Noval, María Gabriela; Sánchez, Ignacio E; Alonso, Leonardo G; de Prat Gay, Gonzalo

2017-10-17

Intrinsic disorder is a major structural category in biology, accounting for more than 30% of coding regions across the domains of life, yet consists of conformational ensembles in equilibrium, a major challenge in protein chemistry. Anciently evolved papillomavirus genomes constitute an unparalleled case for sequence to structure-function correlation in cases in which there are no folded structures. E7, the major transforming oncoprotein of human papillomaviruses, is a paradigmatic example among the intrinsically disordered proteins. Analysis of a large number of sequences of the same viral protein allowed for the identification of a handful of residues with absolute conservation, scattered along the sequence of its N-terminal intrinsically disordered domain, which intriguingly are mostly leucine residues. Mutation of these led to a pronounced increase in both α-helix and β-sheet structural content, reflected by drastic effects on equilibrium propensities and oligomerization kinetics, and uncovers the existence of local structural elements that oppose canonical folding. These folding relays suggest the existence of yet undefined hidden structural codes behind intrinsic disorder in this model protein. Thus, evolution pinpoints conformational hot spots that could have not been identified by direct experimental methods for analyzing or perturbing the equilibrium of an intrinsically disordered protein ensemble.

An investigation of social media data during a product recall scandal

NASA Astrophysics Data System (ADS)

Tse, Ying Kei; Loh, Hanlin; Ding, Juling; Zhang, Minhao

2018-07-01

As social media has become an important part of modern daily life, users often share product opinions online and these tend to spike when large companies undergo crises. This paper investigates customer online responses to a large company crisis by uncovering hidden insights in social media comments and presents a framework for handling social media data and crisis management. Analysis of textual Facebook data from users responding to the 2013 horsemeat scandal is presented. In this study, we used a novel comprehensive data analysis framework alongside a text-mining framework to objectively classify and understand customer perceptions during this horsemeat scandal. This framework provides an effective approach for investigating customer perception during a company crisis and measures the effectiveness of crisis management practices which the company has adopted. Our analyses show that social media can provide important insights into customer behaviour during crisis communications.

Information Superiority via Formal Concept Analysis

NASA Astrophysics Data System (ADS)

Koester, Bjoern; Schmidt, Stefan E.

This chapter will show how to get more mileage out of information. To achieve that, we first start with an introduction to the fundamentals of Formal Concept Analysis (FCA). FCA is a highly versatile field of applied lattice theory, which allows hidden relationships to be uncovered in relational data. Moreover, FCA provides a distinguished supporting framework to subsequently find and fill information gaps in a systematic and rigorous way. In addition, we would like to build bridges via a universal approach to other communities which can be related to FCA in order for other research areas to benefit from a theory that has been elaborated for more than twenty years. Last but not least, the essential benefits of FCA will be presented algorithmically as well as theoretically by investigating a real data set from the MIPT Terrorism Knowledge Base and also by demonstrating an application in the field of Web Information Retrieval and Web Intelligence.

Evolutionary conservation of codon optimality reveals hidden signatures of cotranslational folding.

PubMed

Pechmann, Sebastian; Frydman, Judith

2013-02-01

The choice of codons can influence local translation kinetics during protein synthesis. Whether codon preference is linked to cotranslational regulation of polypeptide folding remains unclear. Here, we derive a revised translational efficiency scale that incorporates the competition between tRNA supply and demand. Applying this scale to ten closely related yeast species, we uncover the evolutionary conservation of codon optimality in eukaryotes. This analysis reveals universal patterns of conserved optimal and nonoptimal codons, often in clusters, which associate with the secondary structure of the translated polypeptides independent of the levels of expression. Our analysis suggests an evolved function for codon optimality in regulating the rhythm of elongation to facilitate cotranslational polypeptide folding, beyond its previously proposed role of adapting to the cost of expression. These findings establish how mRNA sequences are generally under selection to optimize the cotranslational folding of corresponding polypeptides.

Folksonomies and clustering in the collaborative system CiteULike

NASA Astrophysics Data System (ADS)

Capocci, Andrea; Caldarelli, Guido

2008-06-01

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags.

Overview of artificial neural networks.

PubMed

Zou, Jinming; Han, Yi; So, Sung-Sau

2008-01-01

The artificial neural network (ANN), or simply neural network, is a machine learning method evolved from the idea of simulating the human brain. The data explosion in modem drug discovery research requires sophisticated analysis methods to uncover the hidden causal relationships between single or multiple responses and a large set of properties. The ANN is one of many versatile tools to meet the demand in drug discovery modeling. Compared to a traditional regression approach, the ANN is capable of modeling complex nonlinear relationships. The ANN also has excellent fault tolerance and is fast and highly scalable with parallel processing. This chapter introduces the background of ANN development and outlines the basic concepts crucially important for understanding more sophisticated ANN. Several commonly used learning methods and network setups are discussed briefly at the end of the chapter.

Uncovering hidden variation in polyploid wheat.

PubMed

Krasileva, Ksenia V; Vasquez-Gross, Hans A; Howell, Tyson; Bailey, Paul; Paraiso, Francine; Clissold, Leah; Simmonds, James; Ramirez-Gonzalez, Ricardo H; Wang, Xiaodong; Borrill, Philippa; Fosker, Christine; Ayling, Sarah; Phillips, Andrew L; Uauy, Cristobal; Dubcovsky, Jorge

2017-02-07

Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35-40 mutations per kb in each population. With these mutation densities, we identified an average of 23-24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops.

High-resolution definition of the Vibrio cholerae essential gene set with hidden Markov model–based analyses of transposon-insertion sequencing data

PubMed Central

Chao, Michael C.; Pritchard, Justin R.; Zhang, Yanjia J.; Rubin, Eric J.; Livny, Jonathan; Davis, Brigid M.; Waldor, Matthew K.

2013-01-01

The coupling of high-density transposon mutagenesis to high-throughput DNA sequencing (transposon-insertion sequencing) enables simultaneous and genome-wide assessment of the contributions of individual loci to bacterial growth and survival. We have refined analysis of transposon-insertion sequencing data by normalizing for the effect of DNA replication on sequencing output and using a hidden Markov model (HMM)-based filter to exploit heretofore unappreciated information inherent in all transposon-insertion sequencing data sets. The HMM can smooth variations in read abundance and thereby reduce the effects of read noise, as well as permit fine scale mapping that is independent of genomic annotation and enable classification of loci into several functional categories (e.g. essential, domain essential or ‘sick’). We generated a high-resolution map of genomic loci (encompassing both intra- and intergenic sequences) that are required or beneficial for in vitro growth of the cholera pathogen, Vibrio cholerae. This work uncovered new metabolic and physiologic requirements for V. cholerae survival, and by combining transposon-insertion sequencing and transcriptomic data sets, we also identified several novel noncoding RNA species that contribute to V. cholerae growth. Our findings suggest that HMM-based approaches will enhance extraction of biological meaning from transposon-insertion sequencing genomic data. PMID:23901011

Using chemical organization theory for model checking

PubMed Central

Kaleta, Christoph; Richter, Stephan; Dittrich, Peter

2009-01-01

Motivation: The increasing number and complexity of biomodels makes automatic procedures for checking the models' properties and quality necessary. Approaches like elementary mode analysis, flux balance analysis, deficiency analysis and chemical organization theory (OT) require only the stoichiometric structure of the reaction network for derivation of valuable information. In formalisms like Systems Biology Markup Language (SBML), however, information about the stoichiometric coefficients required for an analysis of chemical organizations can be hidden in kinetic laws. Results: First, we introduce an algorithm that uncovers stoichiometric information that might be hidden in the kinetic laws of a reaction network. This allows us to apply OT to SBML models using modifiers. Second, using the new algorithm, we performed a large-scale analysis of the 185 models contained in the manually curated BioModels Database. We found that for 41 models (22%) the set of organizations changes when modifiers are considered correctly. We discuss one of these models in detail (BIOMD149, a combined model of the ERK- and Wnt-signaling pathways), whose set of organizations drastically changes when modifiers are considered. Third, we found inconsistencies in 5 models (3%) and identified their characteristics. Compared with flux-based methods, OT is able to identify those species and reactions more accurately [in 26 cases (14%)] that can be present in a long-term simulation of the model. We conclude that our approach is a valuable tool that helps to improve the consistency of biomodels and their repositories. Availability: All data and a JAVA applet to check SBML-models is available from http://www.minet.uni-jena.de/csb/prj/ot/tools Contact: dittrich@minet.uni-jena.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19468053

Comparative Analysis of Proteomes and Functionomes Provides Insights into Origins of Cellular Diversification

PubMed Central

Caetano-Anollés, Gustavo

2013-01-01

Reconstructing the evolutionary history of modern species is a difficult problem complicated by the conceptual and technical limitations of phylogenetic tree building methods. Here, we propose a comparative proteomic and functionomic inferential framework for genome evolution that allows resolving the tripartite division of cells and sketching their history. Evolutionary inferences were derived from the spread of conserved molecular features, such as molecular structures and functions, in the proteomes and functionomes of contemporary organisms. Patterns of use and reuse of these traits yielded significant insights into the origins of cellular diversification. Results uncovered an unprecedented strong evolutionary association between Bacteria and Eukarya while revealing marked evolutionary reductive tendencies in the archaeal genomic repertoires. The effects of nonvertical evolutionary processes (e.g., HGT, convergent evolution) were found to be limited while reductive evolution and molecular innovation appeared to be prevalent during the evolution of cells. Our study revealed a strong vertical trace in the history of proteins and associated molecular functions, which was reliably recovered using the comparative genomics approach. The trace supported the existence of a stem line of descent and the very early appearance of Archaea as a diversified superkingdom, but failed to uncover a hidden canonical pattern in which Bacteria was the first superkingdom to deploy superkingdom-specific structures and functions. PMID:24492748

The way to uncover community structure with core and diversity

NASA Astrophysics Data System (ADS)

Chang, Y. F.; Han, S. K.; Wang, X. D.

2018-07-01

Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity, pre-given information and unstable results in different run, in this paper, we propose a simple and efficient method to deepen our understanding of the emergence and diversity of communities in complex systems. By introducing the rational random selection, our method reveals the hidden deterministic and normal diverse community states of community structure. To demonstrate this method, we test it with real-world systems. The results show that our method could not only detect community structure with high sensitivity and reliability, but also provide instructional information about the hidden deterministic community world and the real normal diverse community world by giving out the core-community, the real-community, the tide and the diversity. Thizs is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in complex systems.

A Game of Hide and Seek: Expectations of Clumpy Resources Influence Hiding and Searching Patterns

PubMed Central

Wilke, Andreas; Minich, Steven; Panis, Megane; Langen, Tom A.; Skufca, Joseph D.; Todd, Peter M.

2015-01-01

Resources are often distributed in clumps or patches in space, unless an agent is trying to protect them from discovery and theft using a dispersed distribution. We uncover human expectations of such spatial resource patterns in collaborative and competitive settings via a sequential multi-person game in which participants hid resources for the next participant to seek. When collaborating, resources were mostly hidden in clumpy distributions, but when competing, resources were hidden in more dispersed (random or hyperdispersed) patterns to increase the searching difficulty for the other player. More dispersed resource distributions came at the cost of higher overall hiding (as well as searching) times, decreased payoffs, and an increased difficulty when the hider had to recall earlier hiding locations at the end of the experiment. Participants’ search strategies were also affected by their underlying expectations, using a win-stay lose-shift strategy appropriate for clumpy resources when searching for collaboratively-hidden items, but moving equally far after finding or not finding an item in competitive settings, as appropriate for dispersed resources. Thus participants showed expectations for clumpy versus dispersed spatial resources that matched the distributions commonly found in collaborative versus competitive foraging settings. PMID:26154661

A chemical family-based strategy for uncovering hidden bioactive molecules and multicomponent interactions in herbal medicines.

PubMed

Song, Hui-Peng; Wu, Si-Qi; Hao, Haiping; Chen, Jun; Lu, Jun; Xu, Xiaojun; Li, Ping; Yang, Hua

2016-03-30

Two concepts involving natural products were proposed and demonstrated in this paper. (1) Natural product libraries (e.g. herbal extract) are not perfect for bioactivity screening because of the vast complexity of compound compositions, and thus a library reconstruction procedure is necessary before screening. (2) The traditional mode of "screening single compound" could be improved to "screening single compound, drug combination and multicomponent interaction" due to the fact that herbal medicines work by integrative effects of multi-components rather than single effective constituents. Based on the two concepts, we established a novel strategy aiming to make screening easier and deeper. Using thrombin as the model enzyme, we firstly uncovered the minor lead compounds, potential drug combinations and multicomponent interactions in an herbal medicine of Dan-Qi pair, showing a significant advantage over previous methods. This strategy was expected to be a new and promising mode for investigation of herbal medicines.

Uncovering the hidden iceberg structure of the Galactic halo

NASA Astrophysics Data System (ADS)

Moss, Vanessa A.; Di Teodoro, Enrico M.; McClure-Griffiths, Naomi M.; Lockman, Felix; Pisano, D. J.; Price, Daniel; Rees, Glen

2018-01-01

How the Milky Way gets its gas and keeps its measured star formation rate going are both long-standing mysteries in Galactic studies, with important implications for galaxy evolution across the Universe. I will present our recent discovery of two populations of neutral hydrogen (HI) in the halo of the Milky Way: 1) a narrow line-width dense population typical of the majority of bright high velocity cloud (HVC) components, and 2) a fainter, broad line-width diffuse population that aligns well with the population found in very sensitive pointings such as in Lockman et al. (2002). From our existing data, we concluded that the diffuse population likely outweighs the dense HI by a factor of 3. This discovery of diffuse HI, which appears to be prevalent throughout the halo, takes us closer to solving the Galactic mystery of accretion and reveals a gaseous neutral halo hidden from the view of most large-scale surveys. We are currently carrying out deep Parkes observations to investigate these results further, in order to truly uncover the nature of the diffuse HI and determine whether our 3:1 ratio (based on the limited existing data) is consistent with what is seen when Parkes and the 140 ft Green Bank telescope are employed at comparable sensitivity. With these data, through a combination of both known and new sightline measurements, we aim to reveal the structure of the Galactic halo in more detail than ever before.

Hidden consequences of political efficacy: Testing an efficacy-apathy model of political mobilization.

PubMed

Osborne, Danny; Yogeeswaran, Kumar; Sibley, Chris G

2015-10-01

Political efficacy-the belief that one can influence politics-is a key predictor of people's involvement in social movements. Political institutions that are open to change should, however, be seen as just. Thus, political efficacy may ironically undermine minority group members' support for collective action by simultaneously increasing their belief in the fairness of the system. The current study aims to examine this possibility in a national sample of Māori-New Zealand's indigenous minority population. Participants (N = 399) were Māori (Mage = 44.22; SD = 13.30) women (n = 272) and men (n = 115; unreported = 12) who completed a survey assessing their levels of (a) political efficacy, (b) system justification, and (c) support for the political mobilization of their group, as well as relevant demographic covariates. Consistent with past research, political efficacy had a positive direct effect on participants' support for the political mobilization of Māori. Nevertheless, political efficacy also had a negative indirect effect on political mobilization support via increases in system justification. These results held after controlling for participants' ethnic identification, self-efficacy, and conservatism. Our findings uncover a hidden consequence of political efficacy and show that, while believing that the political system is receptive to change predicts political mobilization, it can also undermine minorities' support for the mobilization of their group. Thus, our results uncover a previously unknown process that maintains inequality between ethnic minority and majority group members. (c) 2015 APA, all rights reserved).

An Annotation Agnostic Algorithm for Detecting Nascent RNA Transcripts in GRO-Seq.

PubMed

Azofeifa, Joseph G; Allen, Mary A; Lladser, Manuel E; Dowell, Robin D

2017-01-01

We present a fast and simple algorithm to detect nascent RNA transcription in global nuclear run-on sequencing (GRO-seq). GRO-seq is a relatively new protocol that captures nascent transcripts from actively engaged polymerase, providing a direct read-out on bona fide transcription. Most traditional assays, such as RNA-seq, measure steady state RNA levels which are affected by transcription, post-transcriptional processing, and RNA stability. GRO-seq data, however, presents unique analysis challenges that are only beginning to be addressed. Here, we describe a new algorithm, Fast Read Stitcher (FStitch), that takes advantage of two popular machine-learning techniques, hidden Markov models and logistic regression, to classify which regions of the genome are transcribed. Given a small user-defined training set, our algorithm is accurate, robust to varying read depth, annotation agnostic, and fast. Analysis of GRO-seq data without a priori need for annotation uncovers surprising new insights into several aspects of the transcription process.

Igloo-Plot: a tool for visualization of multidimensional datasets.

PubMed

Kuntal, Bhusan K; Ghosh, Tarini Shankar; Mande, Sharmila S

2014-01-01

Advances in science and technology have resulted in an exponential growth of multivariate (or multi-dimensional) datasets which are being generated from various research areas especially in the domain of biological sciences. Visualization and analysis of such data (with the objective of uncovering the hidden patterns therein) is an important and challenging task. We present a tool, called Igloo-Plot, for efficient visualization of multidimensional datasets. The tool addresses some of the key limitations of contemporary multivariate visualization and analysis tools. The visualization layout, not only facilitates an easy identification of clusters of data-points having similar feature compositions, but also the 'marker features' specific to each of these clusters. The applicability of the various functionalities implemented herein is demonstrated using several well studied multi-dimensional datasets. Igloo-Plot is expected to be a valuable resource for researchers working in multivariate data mining studies. Igloo-Plot is available for download from: http://metagenomics.atc.tcs.com/IglooPlot/. Copyright © 2014 Elsevier Inc. All rights reserved.

A usability study of CPOE's medication administration functions: impact on physician-nurse cooperation.

PubMed

Beuscart-Zéphir, Marie Catherine; Pelayo, Sylvia; Degoulet, Patrice; Anceaux, Françoise; Guerlinger, Sandra; Meaux, Jean-Jacques

2004-01-01

Implementation of CPOE systems in Healthcare Institutions has proven efficient in reducing medication errors but it also induces hidden side-effects on Doctor-Nurse cooperation. We propose a usability engineering approach to this problem. An extensive activity analysis of the medication ordering and administration process was performed in several departments of 3 different hospitals. Two of these hospitals are still using paper-based orders, while the 3rd one is in the roll-out phase of medication functions of its CPOE system. We performed a usability assessment of this CPOE system. The usability assessment uncovered usability problems for the entry of medication administration time scheduling by the physician and revealed that the information can be ambiguous for the nurse. The comparison of cooperation models in both situation shows that users tend to adopt a distributed decision making paradigm in the paper-based situation, while the CPOE system supports a centralized decision making process. This analysis can support recommendation for the re-engineering of the Human-Computer Interface.

A Hybrid Computational Method for the Discovery of Novel Reproduction-Related Genes

PubMed Central

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations. PMID:25768094

Revealing the hidden language of complex networks.

PubMed

Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Davis, Darren; Levnajic, Zoran; Janjic, Vuk; Karapandza, Rasa; Stojmirovic, Aleksandar; Pržulj, Nataša

2014-04-01

Sophisticated methods for analysing complex networks promise to be of great benefit to almost all scientific disciplines, yet they elude us. In this work, we make fundamental methodological advances to rectify this. We discover that the interaction between a small number of roles, played by nodes in a network, can characterize a network's structure and also provide a clear real-world interpretation. Given this insight, we develop a framework for analysing and comparing networks, which outperforms all existing ones. We demonstrate its strength by uncovering novel relationships between seemingly unrelated networks, such as Facebook, metabolic, and protein structure networks. We also use it to track the dynamics of the world trade network, showing that a country's role of a broker between non-trading countries indicates economic prosperity, whereas peripheral roles are associated with poverty. This result, though intuitive, has escaped all existing frameworks. Finally, our approach translates network topology into everyday language, bringing network analysis closer to domain scientists.

A hybrid computational method for the discovery of novel reproduction-related genes.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong

2015-01-01

Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.

Results of a Formal Methods Demonstration Project

NASA Technical Reports Server (NTRS)

Kelly, J.; Covington, R.; Hamilton, D.

1994-01-01

This paper describes the results of a cooperative study conducted by a team of researchers in formal methods at three NASA Centers to demonstrate FM techniques and to tailor them to critical NASA software systems. This pilot project applied FM to an existing critical software subsystem, the Shuttle's Jet Select subsystem (Phase I of an ongoing study). The present study shows that FM can be used successfully to uncover hidden issues in a highly critical and mature Functional Subsystem Software Requirements (FSSR) specification which are very difficult to discover by traditional means.

Bibliographic Resources for the Historian of Astronomy

NASA Astrophysics Data System (ADS)

Corbin, B. G.

1999-12-01

Many large library collections now have online bibliographic catalogs on the web. These provide many hidden resources for the historian of astronomy. Special searching techniques will allow the historian to scan bibliographic records of hundreds of entries relating to biographies of astronomers, collected works of astronomers, ancient and medieval astronomy and many other historical subjects. Abstract databases such as the Astrophysics Data System and ARIBIB are also adding much historical bibliographic information. ARIBIB will eventually contain scanned images of the Astronomischer Jahresbericht containing bibliographic entries for all literature of astronomy from 1899 to 1968 and Astronomy and Astrophysics Abstracts from 1969 to present. Commercial services such as UnCover and FirstSearch provide a means of reaching bibliographic entries for journal and book literature in the history of astronomy which were not easily located in the past. A broad overview of these collections and services will be given, and searching techniques for finding ``hidden" bibliographic data will be presented. Web page addresses will be given for all sources covered.

Hidden phase in a two-dimensional Sn layer stabilized by modulation hole doping

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

Ming, Fangfei; Mulugeta Amare, Daniel; Tu, Weisong

Semiconductor surfaces and ultrathin interfaces exhibit an interesting variety of two-dimensional quantum matter phases, such as charge density waves, spin density waves and superconducting condensates. Yet, the electronic properties of these broken symmetry phases are extremely difficult to control due to the inherent difficulty of doping a strictly two-dimensional material without introducing chemical disorder. Here we successfully exploit a modulation doping scheme to uncover, in conjunction with a scanning tunnelling microscope tip-assist, a hidden equilibrium phase in a hole-doped bilayer of Sn on Si(111). This new phase is intrinsically phase separated into insulating domains with polar and nonpolar symmetries. Itsmore » formation involves a spontaneous symmetry breaking process that appears to be electronically driven, notwithstanding the lack of metallicity in this system. This modulation doping approach allows access to novel phases of matter, promising new avenues for exploring competing quantum matter phases on a silicon platform.« less

Implications for research and practice of the biographic approach for storytelling.

PubMed

Ewens, Beverley; Hendricks, Joyce; Sundin, Deb

2017-01-23

Background Intensive care unit survivors face many physical and psychological difficulties during their recovery following discharge from hospital. These difficulties can significantly affect their quality of life. Healthcare providers and survivors' families often do not understand what recovery means in this population, which may affect the support provided. Aim To consider the potential of the biographical method in helping to create stories that illustrate recovery in intensive care survivors and other populations. Discussion This paper identifies how the biographical approach has provided survivors with a way to uncover the hidden parts of their lives through diaries and interviews, and reveal the hidden stories of intensive care survivorship and recovery. Conclusion The application of the biographical method enabled stories to be created that identified the disruption survivors encounter as they struggle to appear recovered. Implications for practice The biographical method can illuminate experiences uncaptured by other methods. This insight into recovery journeys can help healthcare practitioners and family members to understand and recognise the need for support during recovery.

Factors Affecting Infants’ Manual Search for Occluded Objects and the Genesis of Object Permanence

PubMed Central

Moore, M. Keith; Meltzoff, Andrew N.

2009-01-01

Two experiments systematically examined factors that influence infants’ manual search for hidden objects (N = 96). Experiment 1 used a new procedure to assess infants’ search for partially versus totally occluded objects. Results showed that 8.75-month-old infants solved partial occlusions by removing the occluder and uncovering the object, but these same infants failed to use this skill on total occlusions. Experiment 2 used sound-producing objects to provide a perceptual clue to the objects’ hidden location. Sound clues significantly increased the success rate on total occlusions for 10-month-olds, but not for 8.75-month-olds. An identity development account is offered for why infants succeed on partial occlusions earlier than total occlusions and why sound helps only the older infants. We propose a mechanism for how infants use object identity as a basis for developing a notion of permanence. Implications are drawn for understanding the dissociation between looking-time and search assessments of object permanence. PMID:18036668

Factors affecting infants' manual search for occluded objects and the genesis of object permanence.

PubMed

Moore, M Keith; Meltzoff, Andrew N

2008-04-01

Two experiments systematically examined factors that influence infants' manual search for hidden objects (N=96). Experiment 1 used a new procedure to assess infants' search for partially versus totally occluded objects. Results showed that 8.75-month-old infants solved partial occlusions by removing the occluder and uncovering the object, but these same infants failed to use this skill on total occlusions. Experiment 2 used sound-producing objects to provide a perceptual clue to the objects' hidden location. Sound clues significantly increased the success rate on total occlusions for 10-month-olds, but not for 8.75-month-olds. An identity development account is offered for why infants succeed on partial occlusions earlier than total occlusions and why sound helps only the older infants. We propose a mechanism for how infants use object identity as a basis for developing a notion of permanence. Implications are drawn for understanding the dissociation between looking time and search assessments of object permanence.

Hidden phase in a two-dimensional Sn layer stabilized by modulation hole doping

DOE PAGES

Ming, Fangfei; Mulugeta Amare, Daniel; Tu, Weisong; ...

2017-03-07

Semiconductor surfaces and ultrathin interfaces exhibit an interesting variety of two-dimensional quantum matter phases, such as charge density waves, spin density waves and superconducting condensates. Yet, the electronic properties of these broken symmetry phases are extremely difficult to control due to the inherent difficulty of doping a strictly two-dimensional material without introducing chemical disorder. Here we successfully exploit a modulation doping scheme to uncover, in conjunction with a scanning tunnelling microscope tip-assist, a hidden equilibrium phase in a hole-doped bilayer of Sn on Si(111). This new phase is intrinsically phase separated into insulating domains with polar and nonpolar symmetries. Itsmore » formation involves a spontaneous symmetry breaking process that appears to be electronically driven, notwithstanding the lack of metallicity in this system. This modulation doping approach allows access to novel phases of matter, promising new avenues for exploring competing quantum matter phases on a silicon platform.« less

Reading Hidden Messages Through Deciphered Manual Alphabets on Classic Artwork

NASA Astrophysics Data System (ADS)

Castronovo, Joseph Anthony, Jr.

1998-10-01

Decipherment is the tool used to uncover several types of hand signs that played vital roles in the creation of hidden messages in classic artwork. A 3,100 B.C. bas-relief of The 'Kaph' Telescope, formerly named The Narmer Palette, and Michaelangelo Buonarrotte's Battle of Cascina of 1506 were two key works of art that show certain similarities even though separated by 4,500 years. It is evident that Renaissance humanists provided artists with certain knowledge of the ancients. Results of incorporating a number of minor works of art showed that the competence of ancient Egyptians, Cretans and Australian Aboriginals, to name a few, as astronomers, was underestimated. Some deciphered Indus seals attested to a global understanding of the universe, with Gemini and the star of Thuban at the center of their attention. Certain forms of secrecy had to be undertaken for various reasons throughout the millennia. Three examples are: (1) In Italy, to keep controversial and truthful teachings discreet and hidden, artists embedded them in artwork long before the plight of Galileo Galilei and his discoveries. (2) Among Jewish Kabbalists, a well-known design was obscured in The Arnolfini Wedding painting for fear it would be lost due to persecution. (3) Michaelangelo Buonarrotte indicated several meanings through the hands of The Statue of Moses. They were overlooked by several societies, including the gesticulating culture of Italy, because they oppressed the value of signed languages. Spatial decipherment may testify to a need for the restoration of a spatial writing system for expanded linguistic accessibility. A 21st century model community for sign language residents and employees will benefit visual learners, particularly visual artists and non-phonetic decipherers, to better uncover, understand and perhaps use ancient hand forms to restore ancient knowledge. Moreover, the National Association of Teaching English (NATE) has recently endorsed the addition of two skills, viewing and visual representing, to the traditional list of reading, writing, speaking and listening. Students will master these two new skills far more effectively when they are exposed to such a signing community.

Intermittent fasting uncovers and rescues cognitive phenotypes in PTEN neuronal haploinsufficient mice.

PubMed

Cabral-Costa, J V; Andreotti, D Z; Mello, N P; Scavone, C; Camandola, S; Kawamoto, E M

2018-06-05

Phosphatase and tensin homolog (PTEN) is an important protein with key modulatory functions in cell growth and survival. PTEN is crucial during embryogenesis and plays a key role in the central nervous system (CNS), where it directly modulates neuronal development and synaptic plasticity. Loss of PTEN signaling function is associated with cognitive deficits and synaptic plasticity impairment. Accordingly, Pten mutations have a strong link with autism spectrum disorder. In this study, neuronal Pten haploinsufficient male mice were subjected to a long-term environmental intervention - intermittent fasting (IF) - and then evaluated for alterations in exploratory, anxiety and learning and memory behaviors. Although no significant effects on spatial memory were observed, mutant mice showed impaired contextual fear memory in the passive avoidance test - an outcome that was effectively rescued by IF. In this study, we demonstrated that IF modulation, in addition to its rescue of the memory deficit, was also required to uncover behavioral phenotypes otherwise hidden in this neuronal Pten haploinsufficiency model.

Uncovering the inertia of dislocation motion and negative mechanical response in crystals.

PubMed

Tang, Yizhe

2018-01-09

Dislocations are linear defects in crystals and their motion controls crystals' mechanical behavior. The dissipative nature of dislocation propagation is generally accepted although the specific mechanisms are still not fully understood. The inertia, which is undoubtedly the nature of motion for particles with mass, seems much less convincing for configuration propagation. We utilize atomistic simulations in conditions that minimize dissipative effects to enable uncovering of the hidden nature of dislocation motion, in three typical model metals Mg, Cu and Ta. We find that, with less/no dissipation, dislocation motion is under-damped and explicitly inertial at both low and high velocities. The inertia of dislocation motion is intrinsic, and more fundamental than the dissipative nature. The inertia originates from the kinetic energy imparted from strain energy and stored in the moving core. Peculiar negative mechanical response associated with the inertia is also discovered. These findings shed light on the fundamental nature of dislocation motion, reveal the underlying physics, and provide a new physical explanation for phenomena relevant to high-velocity dislocations.

Cultural boundary surfing in mental health nursing: a creative narration.

PubMed

Kidd, Jacquie

2010-01-01

In the mental health context, nurses navigate multifaceted boundaries every day in an effort to develop and maintain the therapeutic relationship; an endeavour that is breathtaking in its complexity. In this paper, I adopt an unconventional form of writing to explore the individual nature of cultural boundaries, and uncover hidden messages that impact on our efforts to build connections across cultures and ethnicities in mental health settings. Presented as a play, the conversation between protagonists explores cultural competence alongside the notion of 'discovery', and the potential of the Tidal Model to provide a vehicle for successful cultural boundary surfing.

Uncovering the Hidden Molecular Signatures of Breast Cancer

DTIC Science & Technology

2011-05-01

0389$&0>!1&! :79).3$$7! ,3D&! 0/8&! )56/%83:)/5! %&=3%*)5=! 93:)&5:! .$)5).3$! 3::%)4(:&0! )5.$(*)5=! :(8/%! =%3*&>! 0:3=&>! HFI ! 0:3:(0>! N&%A! 0:3:(0...5! :,&! 93%:).($3%! ’(&0:)/5! 4&)5=! 302&*! /6! :,&! 93:)&5:! *3:30&:;! P/%! &G389$&>! =)D&5! 3! :%350.%)9:)/53$! 0)=53:(%&! /6! HFI ! 3.:)D3:)/5! B:,3...0>! :,&!=&5&!0&:!./%%&09/5*)5=!:/! :%350.%)9:0! :,3:!3%&!*)66&%&5:)3$$7!&G9%&00&*! 1,&5! HFI ! )0! /D&%R&G9%&00&*E>! 93:)&5:0! 3%&! /%*&%&*! 3

A New Look at the Eclipse Timing Variation Diagram Analysis of Selected 3-body W UMa Systems

NASA Astrophysics Data System (ADS)

Christopoulou, P.-E.; Papageorgiou, A.

2015-07-01

The light travel effect produced by the presence of tertiary components can reveal much about the origin and evolution of over-contact binaries. Monitoring of W UMa systems over the last decade and/or the use of publicly available photometric surveys (NSVS, ASAS, etc.) has uncovered or suggested the presence of many unseen companions, which calls for an in-depth investigation of the parameters derived from cyclic period variations in order to confirm or reject the assumption of hidden companion(s). Progress in the analysis of eclipse timing variations is summarized here both from the empirical and the theoretical points of view, and a more extensive investigation of the proposed orbital parameters of third bodies is proposed. The code we have developed for this, implemented in Python, is set up to handle heuristic scanning with parameter perturbation in parameter space, and to establish realistic uncertainties from the least squares fitting. A computational example is given for TZ Boo, a W UMa system with a spectroscopically detected third component. Future options to be implemented include MCMC and bootstrapping.

Smart Health - Potential and Pathways: A Survey

NASA Astrophysics Data System (ADS)

Arulananthan, C.; Hanifa, Sabibullah Mohamed

2017-08-01

Healthcare is an imperative key field of research, where individuals or groups can be engaged in the self-tracking of any kind of biological, physical, behavioral, or environmental information. In a massive health care data, the valuable information is hidden. The quantity of the available unstructured data has been expanding on an exponential scale. The newly developing Disruptive Technologies can handle many challenges that face data analysis and ability to extract valuable information via data analytics. Connected Wellness in Healthcare would retrieve patient’s physiological, pathological and behavioral parameters through sensors to perform inner workings of human body analysis. Disruptive technologies can take us from a reactive illness-driven to a proactive wellness-driven system in health care. It is need to be strive and create a smart health system towards wellness-driven instead of being illness-driven, today’s biggest problem in health care. Wellness-driven-analytics application help to promote healthiest living environment called “Smart Health”, deliver empower based quality of living. The contributions of this survey reveals and opens (touches uncovered areas) the possible doors in the line of research on smart health and its computing technologies.

CollaborationViz: Interactive Visual Exploration of Biomedical Research Collaboration Networks

PubMed Central

Bian, Jiang; Xie, Mengjun; Hudson, Teresa J.; Eswaran, Hari; Brochhausen, Mathias; Hanna, Josh; Hogan, William R.

2014-01-01

Social network analysis (SNA) helps us understand patterns of interaction between social entities. A number of SNA studies have shed light on the characteristics of research collaboration networks (RCNs). Especially, in the Clinical Translational Science Award (CTSA) community, SNA provides us a set of effective tools to quantitatively assess research collaborations and the impact of CTSA. However, descriptive network statistics are difficult for non-experts to understand. In this article, we present our experiences of building meaningful network visualizations to facilitate a series of visual analysis tasks. The basis of our design is multidimensional, visual aggregation of network dynamics. The resulting visualizations can help uncover hidden structures in the networks, elicit new observations of the network dynamics, compare different investigators and investigator groups, determine critical factors to the network evolution, and help direct further analyses. We applied our visualization techniques to explore the biomedical RCNs at the University of Arkansas for Medical Sciences – a CTSA institution. And, we created CollaborationViz, an open-source visual analytical tool to help network researchers and administration apprehend the network dynamics of research collaborations through interactive visualization. PMID:25405477

Multilayer Brain Networks

NASA Astrophysics Data System (ADS)

Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

Graph pyramids for protein function prediction

PubMed Central

2015-01-01

Background Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Methods Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Results Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data. PMID:26044522

Graph pyramids for protein function prediction.

PubMed

Sandhan, Tushar; Yoo, Youngjun; Choi, Jin; Kim, Sun

2015-01-01

Uncovering the hidden organizational characteristics and regularities among biological sequences is the key issue for detailed understanding of an underlying biological phenomenon. Thus pattern recognition from nucleic acid sequences is an important affair for protein function prediction. As proteins from the same family exhibit similar characteristics, homology based approaches predict protein functions via protein classification. But conventional classification approaches mostly rely on the global features by considering only strong protein similarity matches. This leads to significant loss of prediction accuracy. Here we construct the Protein-Protein Similarity (PPS) network, which captures the subtle properties of protein families. The proposed method considers the local as well as the global features, by examining the interactions among 'weakly interacting proteins' in the PPS network and by using hierarchical graph analysis via the graph pyramid. Different underlying properties of the protein families are uncovered by operating the proposed graph based features at various pyramid levels. Experimental results on benchmark data sets show that the proposed hierarchical voting algorithm using graph pyramid helps to improve computational efficiency as well the protein classification accuracy. Quantitatively, among 14,086 test sequences, on an average the proposed method misclassified only 21.1 sequences whereas baseline BLAST score based global feature matching method misclassified 362.9 sequences. With each correctly classified test sequence, the fast incremental learning ability of the proposed method further enhances the training model. Thus it has achieved more than 96% protein classification accuracy using only 20% per class training data.

Large area optical mapping of surface contact angle.

PubMed

Dutra, Guilherme; Canning, John; Padden, Whayne; Martelli, Cicero; Dligatch, Svetlana

2017-09-04

Top-down contact angle measurements have been validated and confirmed to be as good if not more reliable than side-based measurements. A range of samples, including industrially relevant materials for roofing and printing, has been compared. Using the top-down approach, mapping in both 1-D and 2-D has been demonstrated. The method was applied to study the change in contact angle as a function of change in silver (Ag) nanoparticle size controlled by thermal evaporation. Large area mapping reveals good uniformity for commercial Aspen paper coated with black laser printer ink. A demonstration of the forensic and chemical analysis potential in 2-D is shown by uncovering the hidden CsF initials made with mineral oil on the coated Aspen paper. The method promises to revolutionize nanoscale characterization and industrial monitoring as well as chemical analyses by allowing rapid contact angle measurements over large areas or large numbers of samples in ways and times that have not been possible before.

Revealing the Hidden Language of Complex Networks

PubMed Central

Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Davis, Darren; Levnajic, Zoran; Janjic, Vuk; Karapandza, Rasa; Stojmirovic, Aleksandar; Pržulj, Nataša

2014-01-01

Sophisticated methods for analysing complex networks promise to be of great benefit to almost all scientific disciplines, yet they elude us. In this work, we make fundamental methodological advances to rectify this. We discover that the interaction between a small number of roles, played by nodes in a network, can characterize a network's structure and also provide a clear real-world interpretation. Given this insight, we develop a framework for analysing and comparing networks, which outperforms all existing ones. We demonstrate its strength by uncovering novel relationships between seemingly unrelated networks, such as Facebook, metabolic, and protein structure networks. We also use it to track the dynamics of the world trade network, showing that a country's role of a broker between non-trading countries indicates economic prosperity, whereas peripheral roles are associated with poverty. This result, though intuitive, has escaped all existing frameworks. Finally, our approach translates network topology into everyday language, bringing network analysis closer to domain scientists. PMID:24686408

Biphasic responses in multi-site phosphorylation systems.

PubMed

Suwanmajo, Thapanar; Krishnan, J

2013-12-06

Multi-site phosphorylation systems are repeatedly encountered in cellular biology and multi-site modification is a basic building block of post-translational modification. In this paper, we demonstrate how distributive multi-site modification mechanisms by a single kinase/phosphatase pair can lead to biphasic/partial biphasic dose-response characteristics for the maximally phosphorylated substrate at steady state. We use simulations and analysis to uncover a hidden competing effect which is responsible for this and analyse how it may be accentuated. We build on this to analyse different variants of multi-site phosphorylation mechanisms showing that some mechanisms are intrinsically not capable of displaying this behaviour. This provides both a consolidated understanding of how and under what conditions biphasic responses are obtained in multi-site phosphorylation and a basis for discriminating between different mechanisms based on this. We also demonstrate how this behaviour may be combined with other behaviour such as threshold and bistable responses, demonstrating the capacity of multi-site phosphorylation systems to act as complex molecular signal processors.

DeepDeath: Learning to predict the underlying cause of death with Big Data.

PubMed

Hassanzadeh, Hamid Reza; Ying Sha; Wang, May D

2017-07-01

Multiple cause-of-death data provides a valuable source of information that can be used to enhance health standards by predicting health related trajectories in societies with large populations. These data are often available in large quantities across U.S. states and require Big Data techniques to uncover complex hidden patterns. We design two different classes of models suitable for large-scale analysis of mortality data, a Hadoop-based ensemble of random forests trained over N-grams, and the DeepDeath, a deep classifier based on the recurrent neural network (RNN). We apply both classes to the mortality data provided by the National Center for Health Statistics and show that while both perform significantly better than the random classifier, the deep model that utilizes long short-term memory networks (LSTMs), surpasses the N-gram based models and is capable of learning the temporal aspect of the data without a need for building ad-hoc, expert-driven features.

The growth crisis--and how to escape it.

PubMed

Slywotzky, Adrian J; Wise, Richard

2002-07-01

At a time when companies are poised to seize the growth opportunities of a rebounding economy, many of them, whether they know it or not, face a growth crisis. Even during the boom years of the past decade, only a small fraction of companies enjoyed consistent double-digit revenue growth. And those that did often achieved it through short-term measures--such as mergers and inflated price increases--that don't provide the foundation for growth over the long term. But there is a way out of this predicament. The authors claim that companies can achieve sustained growth by leveraging their "hidden assets," a wide array of underused, intangible capabilities and advantages that most established companies already hold. To date, much of the research on intangible assets has centered on intellectual property and brand recognition. But in this article, the authors uncover a host of other assets that can help spark growth. They identify four major categories of hidden assets: customer relationships, strategic real estate, networks, and information. And they illustrate each with an example of a company that has creatively used its hidden assets to produce new sources of revenue. Executives have spent years learning to create growth using products, facilities, and working capital. But they should really focus on mobilizing their hidden assets to serve their customers' higher-order needs--in other words, create offerings that make customers' lives easier, better, or less expensive. Making that shift in mind-set isn't easy, admit the authors, but companies that do it may not only create meaningful new value for their customers but also produce double-digit revenue and earnings growth for investors.

Childhood temperament: passive gene-environment correlation, gene-environment interaction, and the hidden importance of the family environment.

PubMed

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill

2013-02-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.

"Dark matter" worlds of unstable RNA and protein.

PubMed

Baboo, Sabyasachi; Cook, Peter R

2014-01-01

Astrophysicists use the term "dark matter" to describe the majority of the matter and/or energy in the universe that is hidden from view, and biologists now apply it to the new families of RNA they are uncovering. We review evidence for an analogous hidden world containing peptides. The critical experiments involved pulse-labeling human cells with tagged amino acids for periods as short as five seconds. Results are extraordinary in two respects: both nucleus and cytoplasm become labeled, and most signals disappear with a half-life of less than one minute. Just as the synthesis of each mature mRNA is regulated by the abortive production of hundreds of shorter transcripts that are quickly degraded, it seems that the synthesis of each full-length protein in the stable proteome is regulated by an apparently wasteful production and degradation of shorter peptides. Some of the nuclear synthesis is probably a byproduct of nuclear ribosomes proofreading newly-made RNA for inappropriately-placed termination codons (a process that triggers "nonsense-mediated decay"). We speculate that some "dark-matter" peptides will play other important roles in the cell.

“Dark matter” worlds of unstable RNA and protein

PubMed Central

Baboo, Sabyasachi; Cook, Peter R

2014-01-01

Astrophysicists use the term “dark matter” to describe the majority of the matter and/or energy in the universe that is hidden from view, and biologists now apply it to the new families of RNA they are uncovering. We review evidence for an analogous hidden world containing peptides. The critical experiments involved pulse-labeling human cells with tagged amino acids for periods as short as five seconds. Results are extraordinary in two respects: both nucleus and cytoplasm become labeled, and most signals disappear with a half-life of less than one minute. Just as the synthesis of each mature mRNA is regulated by the abortive production of hundreds of shorter transcripts that are quickly degraded, it seems that the synthesis of each full-length protein in the stable proteome is regulated by an apparently wasteful production and degradation of shorter peptides. Some of the nuclear synthesis is probably a byproduct of nuclear ribosomes proofreading newly-made RNA for inappropriately-placed termination codons (a process that triggers “nonsense-mediated decay”). We speculate that some “dark-matter” peptides will play other important roles in the cell. PMID:25482115

Enactive account of pretend play and its application to therapy

PubMed Central

Rucinska, Zuzanna; Reijmers, Ellen

2015-01-01

This paper informs therapeutic practices that use play, by providing a non-standard philosophical account of pretense: the enactive account of pretend play (EAPP). The EAPP holds that pretend play activity need not invoke mental representational mechanisms; instead, it focuses on interaction and the role of affordances in shaping pretend play activity. One advantage of this re-characterization of pretense is that it may help us better understand the role of shared meanings and interacting in systemic therapies, which use playing to enhance dialog in therapy rather than to uncover hidden meanings. We conclude with bringing together findings from therapeutic practice and philosophical considerations. PMID:25784884

Lesbian health and the assumption of heterosexuality: an organizational perspective.

PubMed

Daley, Andrea

2003-01-01

This study used a qualitative research design to explore hospital policies and practices and the assumption of female heterosexuality. The assumption of heterosexuality is a product of discursive practices that normalize heterosexuality and individualize lesbian sexual identities. Literature indicates that the assumption of female heterosexuality is implicated in both the invisibility and marked visibility of lesbians as service users. This research adds to existing literature by shifting the focus of study from individual to organizational practices and, in so doing, seeks to uncover hidden truths, explore the functional power of language, and allow for the discovery of what we know and--equally as important--how we know.

Fingerprint image enhancement by differential hysteresis processing.

PubMed

Blotta, Eduardo; Moler, Emilce

2004-05-10

A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

Hidden Genetic Variation in LCA9-Associated Congenital Blindness Explained by 5'UTR Mutations and Copy-Number Variations of NMNAT1.

PubMed

Coppieters, Frauke; Todeschini, Anne Laure; Fujimaki, Takuro; Baert, Annelot; De Bruyne, Marieke; Van Cauwenbergh, Caroline; Verdin, Hannah; Bauwens, Miriam; Ongenaert, Maté; Kondo, Mineo; Meire, Françoise; Murakami, Akira; Veitia, Reiner A; Leroy, Bart P; De Baere, Elfride

2015-12-01

Leber congenital amaurosis (LCA) is a severe autosomal-recessive retinal dystrophy leading to congenital blindness. A recently identified LCA gene is NMNAT1, located in the LCA9 locus. Although most mutations in blindness genes are coding variations, there is accumulating evidence for hidden noncoding defects or structural variations (SVs). The starting point of this study was an LCA9-associated consanguineous family in which no coding mutations were found in the LCA9 region. Exploring the untranslated regions of NMNAT1 revealed a novel homozygous 5'UTR variant, c.-70A>T. Moreover, an adjacent 5'UTR variant, c.-69C>T, was identified in a second consanguineous family displaying a similar phenotype. Both 5'UTR variants resulted in decreased NMNAT1 mRNA abundance in patients' lymphocytes, and caused decreased luciferase activity in human retinal pigment epithelial RPE-1 cells. Second, we unraveled pseudohomozygosity of a coding NMNAT1 mutation in two unrelated LCA patients by the identification of two distinct heterozygous partial NMNAT1 deletions. Molecular characterization of the breakpoint junctions revealed a complex Alu-rich genomic architecture. Our study uncovered hidden genetic variation in NMNAT1-associated LCA and emphasized a shift from coding to noncoding regulatory mutations and repeat-mediated SVs in the molecular pathogenesis of heterogeneous recessive disorders such as hereditary blindness. © 2015 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

A comparative hidden Markov model analysis pipeline identifies proteins characteristic of cereal-infecting fungi

PubMed Central

2013-01-01

Background Fungal pathogens cause devastating losses in economically important cereal crops by utilising pathogen proteins to infect host plants. Secreted pathogen proteins are referred to as effectors and have thus far been identified by selecting small, cysteine-rich peptides from the secretome despite increasing evidence that not all effectors share these attributes. Results We take advantage of the availability of sequenced fungal genomes and present an unbiased method for finding putative pathogen proteins and secreted effectors in a query genome via comparative hidden Markov model analyses followed by unsupervised protein clustering. Our method returns experimentally validated fungal effectors in Stagonospora nodorum and Fusarium oxysporum as well as the N-terminal Y/F/WxC-motif from the barley powdery mildew pathogen. Application to the cereal pathogen Fusarium graminearum reveals a secreted phosphorylcholine phosphatase that is characteristic of hemibiotrophic and necrotrophic cereal pathogens and shares an ancient selection process with bacterial plant pathogens. Three F. graminearum protein clusters are found with an enriched secretion signal. One of these putative effector clusters contains proteins that share a [SG]-P-C-[KR]-P sequence motif in the N-terminal and show features not commonly associated with fungal effectors. This motif is conserved in secreted pathogenic Fusarium proteins and a prime candidate for functional testing. Conclusions Our pipeline has successfully uncovered conservation patterns, putative effectors and motifs of fungal pathogens that would have been overlooked by existing approaches that identify effectors as small, secreted, cysteine-rich peptides. It can be applied to any pathogenic proteome data, such as microbial pathogen data of plants and other organisms. PMID:24252298

Chinese Interpreting Studies: a data-driven analysis of a dynamic field of enquiry

PubMed Central

Pekelis, Leonid

2015-01-01

Over the five decades since its beginnings, Chinese Interpreting Studies (CIS) has evolved into a dynamic field of academic enquiry with more than 3,500 scholars and 4,200 publications. Using quantitative and qualitative analysis, this scientometric study delves deep into CIS citation data to examine some of the noteworthy trends and patterns of behavior in the field: how can the field’s progress be quantified by means of citation analysis? Do its authors tend repeatedly to cite ‘classic’ papers or are they more drawn to their colleagues’ latest research? What different effects does the choice of empirical vs. theoretical research have on the use of citations in the various research brackets? The findings show that the field is steadily moving forward with new papers continuously being cited, although a number of influential papers stand out, having received a stream of citations in all the years examined. CIS scholars also have a tendency to cite much older English than Chinese publications across all document types, and empirical research has the greatest influence on the citation behavior of doctoral scholars, while theoretical studies have the largest impact on that of article authors. The goal of this study is to demonstrate the merits of blending quantitative and qualitative analyses to uncover hidden trends. PMID:26401459

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

NASA Astrophysics Data System (ADS)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

Redesigning the exploitation of wheat genetic resources.

PubMed

Longin, C Friedrich H; Reif, Jochen C

2014-10-01

More than half a million wheat genetic resources are resting in gene banks worldwide. Unlocking their hidden favorable genetic diversity for breeding is pivotal for enhancing grain yield potential, and averting future food shortages. Here, we propose exploiting recent advances in hybrid wheat technology to uncover the masked breeding values of wheat genetic resources. The gathered phenotypic information will enable a targeted choice of accessions with high value for pre-breeding among this plethora of genetic resources. We intend to provoke a paradigm shift in pre-breeding strategies for grain yield, moving away from allele mining toward genome-wide selection to bridge the yield gap between genetic resources and elite breeding pools. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hermeneutic phenomenological analysis: the 'possibility' beyond 'actuality' in thematic analysis.

PubMed

Ho, Ken H M; Chiang, Vico C L; Leung, Doris

2017-07-01

This article discusses the ways researchers may become open to manifold interpretations of lived experience through thematic analysis that follows the tradition of hermeneutic phenomenology. Martin Heidegger's thinking about historical contexts of understandings and the notions of 'alētheia' and 'techne' disclose what he called meaning of lived experience, as the 'unchanging Being of changing beings'. While these notions remain central to hermeneutic phenomenological research, novice phenomenologists usually face the problem of how to incorporate these philosophical tenets into thematic analysis. Discussion paper. This discussion paper is based on our experiences of hermeneutic analysis supported by the writings of Heidegger. Literature reviewed for this paper ranges from 1927 - 2014. We draw on data from a study of foreign domestic helpers in Hong Kong to demonstrate how 'dwelling' in the language of participants' 'ek-sistence' supported us in a process of thematic analysis. Data were collected from December 2013 - February 2016. Nurses doing hermeneutic phenomenology have to develop self-awareness of one's own 'taken-for-granted' thinking to disclose the unspoken meanings hidden in the language of participants. Understanding the philosophical tenets of hermeneutic phenomenology allows nurses to preserve possibilities of interpretations in thinking. In so doing, methods of thematic analysis can uncover and present the structure of the meaning of lived experience. We provide our readers with vicarious experience of how to begin cultivating thinking that is aligned with hermeneutic phenomenological philosophical tenets to conduct thematic analysis. © 2017 John Wiley & Sons Ltd.

Childhood Temperament: Passive Gene-Environment Correlation, Gene-Environment Interaction, and the Hidden Importance of the Family Environment

PubMed Central

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H. Hill

2013-01-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e. passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e. gene-environment interaction). The sample comprised 807 twin pairs (M age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high Effortful Control, and this association was genetically mediated. Children with high Extraversion/Surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that Effortful Control and Extraversion/Surgency were more heritable in chaotic homes, and Negative Affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally. PMID:23398752

Endophytic actinobacteria: Diversity, secondary metabolism and mechanisms to unsilence biosynthetic gene clusters.

PubMed

Dinesh, Raghavan; Srinivasan, Veeraraghavan; T E, Sheeja; Anandaraj, Muthuswamy; Srambikkal, Hamza

2017-09-01

Endophytic actinobacteria, which reside in the inner tissues of host plants, are gaining serious attention due to their capacity to produce a plethora of secondary metabolites (e.g. antibiotics) possessing a wide variety of biological activity with diverse functions. This review encompasses the recent reports on endophytic actinobacterial species diversity, in planta habitats and mechanisms underlying their mode of entry into plants. Besides, their metabolic potential, novel bioactive compounds they produce and mechanisms to unravel their hidden metabolic repertoire by activation of cryptic or silent biosynthetic gene clusters (BGCs) for eliciting novel secondary metabolite production are discussed. The study also reviews the classical conservative techniques (chemical/biological/physical elicitation, co-culturing) as well as modern microbiology tools (e.g. next generation sequencing) that are being gainfully employed to uncover the vast hidden scaffolds for novel secondary metabolites produced by these endophytes, which would subsequently herald a revolution in drug engineering. The potential role of these endophytes in the agro-environment as promising biological candidates for inhibition of phytopathogens and the way forward to thoroughly exploit this unique microbial community by inducing expression of cryptic BGCs for encoding unseen products with novel therapeutic properties are also discussed.

Bacterial symbionts and natural products

PubMed Central

Crawford, Jason M.; Clardy, Jon

2011-01-01

The study of bacterial symbionts of eukaryotic hosts has become a powerful discovery engine for chemistry. This highlight looks at four case studies that exemplify the range of chemistry and biology involved in these symbioses: a bacterial symbiont of a fungus and a marine invertebrate that produce compounds with significant anticancer activity, and bacterial symbionts of insects and nematodes that produce compounds that regulate multilateral symbioses. In the last ten years, a series of shocking revelations – the molecular equivalents of a reality TV show’s uncovering the true parents of a well known individual or a deeply hidden family secret – altered the study of genetically encoded small molecules, natural products for short. These revelations all involved natural products produced by bacterial symbionts, and while details differed, two main plot lines emerged: parentage, in which the real producers of well known natural products with medical potential were not the organisms from which they were originally discovered, and hidden relationships, in which bacterially produced small molecules turned out to be the unsuspected regulators of complex interactions. For chemists, these studies led to new molecules, new biosynthetic pathways, and an understanding of the biological functions these molecules fulfill. PMID:21594283

Humanism, the Hidden Curriculum, and Educational Reform: A Scoping Review and Thematic Analysis.

PubMed

Martimianakis, Maria Athina Tina; Michalec, Barret; Lam, Justin; Cartmill, Carrie; Taylor, Janelle S; Hafferty, Frederic W

2015-11-01

Medical educators have used the hidden curriculum concept for over three decades to make visible the effects of tacit learning, including how culture, structures, and institutions influence professional identity formation. In response to calls to see more humanistic-oriented training in medicine, the authors examined how the hidden curriculum construct has been applied in the English language medical education literature with a particular (and centering) look at its use within literature pertaining to humanism. They also explored the ends to which the hidden curriculum construct has been used in educational reform efforts (at the individual, organizational, and/or systems levels) related to nurturing and/or increasing humanism in health care. The authors conducted a scoping review and thematic analysis that draws from the tradition of critical discourse analysis. They identified 1,887 texts in the literature search, of which 200 met inclusion criteria. The analysis documents a strong preoccupation with negative effects of the hidden curriculum, particularly the moral erosion of physicians and the perceived undermining of humanistic values in health care. A conflation between professionalism and humanism was noted. Proposals for reform largely target medical students and medical school faculty, with very little consideration for how organizations, institutions, and sociopolitical relations more broadly contribute to problematic behaviors. The authors argue that there is a need to transcend conceptualizations of the hidden curriculum as antithetical to humanism and offer suggestions for future research that explores the necessity and value of humanism and the hidden curriculum in medical education and training.

Accessing protein conformational ensembles using room-temperature X-ray crystallography

PubMed Central

Fraser, James S.; van den Bedem, Henry; Samelson, Avi J.; Lang, P. Therese; Holton, James M.; Echols, Nathaniel; Alber, Tom

2011-01-01

Modern protein crystal structures are based nearly exclusively on X-ray data collected at cryogenic temperatures (generally 100 K). The cooling process is thought to introduce little bias in the functional interpretation of structural results, because cryogenic temperatures minimally perturb the overall protein backbone fold. In contrast, here we show that flash cooling biases previously hidden structural ensembles in protein crystals. By analyzing available data for 30 different proteins using new computational tools for electron-density sampling, model refinement, and molecular packing analysis, we found that crystal cryocooling remodels the conformational distributions of more than 35% of side chains and eliminates packing defects necessary for functional motions. In the signaling switch protein, H-Ras, an allosteric network consistent with fluctuations detected in solution by NMR was uncovered in the room-temperature, but not the cryogenic, electron-density maps. These results expose a bias in structural databases toward smaller, overpacked, and unrealistically unique models. Monitoring room-temperature conformational ensembles by X-ray crystallography can reveal motions crucial for catalysis, ligand binding, and allosteric regulation. PMID:21918110

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis

PubMed Central

Aviner, Ranen; Shenoy, Anjana; Elroy-Stein, Orna; Geiger, Tamar

2015-01-01

Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression. PMID:26439921

The necessity of DNA taxonomy to reveal cryptic diversity and spatial distribution of meiofauna, with a focus on Nemertea.

PubMed

Leasi, Francesca; Norenburg, Jon L

2014-01-01

Meiofauna represent one of the most abundant and diverse communities in marine benthic ecosystems. However, an accurate assessment of diversity at the level of species has been and remains challenging for these microscopic organisms. Therefore, for many taxa, especially the soft body forms such as nemerteans, which often lack clear diagnostic morphological traits, DNA taxonomy is an effective means to assess species diversity. Morphological taxonomy of Nemertea is well documented as complicated by scarcity of unambiguous character states and compromised by diagnoses of a majority of species (and higher clades) being inadequate or based on ambiguous characters and character states. Therefore, recent studies have advocated for the primacy of molecular tools to solve the taxonomy of this group. DNA taxonomy uncovers possible hidden cryptic species, provides a coherent means to systematize taxa in definite clades, and also reveals possible biogeographic patterns. Here, we analyze diversity of nemertean species by considering the barcode region of the mitochondrial gene Cytochrome Oxidase subunit I (COI) and different species delineation approaches in order to infer evolutionarily significant units. In the aim to uncover actual diversity of meiofaunal nemerteans across different sites in Central America, COI sequences were obtained for specimens assigned here to the genera Cephalothrix, Ototyphlonemertes, and Tetrastemma-like worms, each commonly encountered in our sampling. Additional genetic, taxonomic, and geographic data of other specimens belonging to these genera were added from GenBank. Results are consistent across different DNA taxonomy approaches, and revealed (i) the presence of several hidden cryptic species and (ii) numerous potential misidentifications due to traditional taxonomy. (iii) We additionally test a possible biogeographic pattern of taxonomic units revealed by this study, and, except for a few cases, the putative species seem not to be widely distributed, in contrast to what traditional taxonomy would suggest for the recognized morphotypes.

Detecting Hidden Diversification Shifts in Models of Trait-Dependent Speciation and Extinction.

PubMed

Beaulieu, Jeremy M; O'Meara, Brian C

2016-07-01

The distribution of diversity can vary considerably from clade to clade. Attempts to understand these patterns often employ state-dependent speciation and extinction models to determine whether the evolution of a particular novel trait has increased speciation rates and/or decreased extinction rates. It is still unclear, however, whether these models are uncovering important drivers of diversification, or whether they are simply pointing to more complex patterns involving many unmeasured and co-distributed factors. Here we describe an extension to the popular state-dependent speciation and extinction models that specifically accounts for the presence of unmeasured factors that could impact diversification rates estimated for the states of any observed trait, addressing at least one major criticism of BiSSE (Binary State Speciation and Extinction) methods. Specifically, our model, which we refer to as HiSSE (Hidden State Speciation and Extinction), assumes that related to each observed state in the model are "hidden" states that exhibit potentially distinct diversification dynamics and transition rates than the observed states in isolation. We also demonstrate how our model can be used as character-independent diversification models that allow for a complex diversification process that is independent of the evolution of a character. Under rigorous simulation tests and when applied to empirical data, we find that HiSSE performs reasonably well, and can at least detect net diversification rate differences between observed and hidden states and detect when diversification rate differences do not correlate with the observed states. We discuss the remaining issues with state-dependent speciation and extinction models in general, and the important ways in which HiSSE provides a more nuanced understanding of trait-dependent diversification. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A gratuitous β-Lactamase inducer uncovers hidden active site dynamics of the Staphylococcus aureus BlaR1 sensor domain.

PubMed

Frederick, Thomas E; Peng, Jeffrey W

2018-01-01

Increasing evidence shows that active sites of proteins have non-trivial conformational dynamics. These dynamics include active site residues sampling different local conformations that allow for multiple, and possibly novel, inhibitor binding poses. Yet, active site dynamics garner only marginal attention in most inhibitor design efforts and exert little influence on synthesis strategies. This is partly because synthesis requires a level of atomic structural detail that is frequently missing in current characterizations of conformational dynamics. In particular, while the identity of the mobile protein residues may be clear, the specific conformations they sample remain obscure. Here, we show how an appropriate choice of ligand can significantly sharpen our abilities to describe the interconverting binding poses (conformations) of protein active sites. Specifically, we show how 2-(2'-carboxyphenyl)-benzoyl-6-aminopenicillanic acid (CBAP) exposes otherwise hidden dynamics of a protein active site that binds β-lactam antibiotics. When CBAP acylates (binds) the active site serine of the β-lactam sensor domain of BlaR1 (BlaRS), it shifts the time scale of the active site dynamics to the slow exchange regime. Slow exchange enables direct characterization of inter-converting protein and bound ligand conformations using NMR methods. These methods include chemical shift analysis, 2-d exchange spectroscopy, off-resonance ROESY of the bound ligand, and reduced spectral density mapping. The active site architecture of BlaRS is shared by many β-lactamases of therapeutic interest, suggesting CBAP could expose functional motions in other β-lactam binding proteins. More broadly, CBAP highlights the utility of identifying chemical probes common to structurally homologous proteins to better expose functional motions of active sites.

Competing magnetostructural phases in a semiclassical system

NASA Astrophysics Data System (ADS)

O'Neal, Kenneth R.; Lee, Jun Hee; Kim, Maeng-Suk; Manson, Jamie L.; Liu, Zhenxian; Fishman, Randy S.; Musfeldt, Janice L.

2017-11-01

The interplay between charge, structure, and magnetism gives rise to rich phase diagrams in complex materials with exotic properties emerging when phases compete. Molecule-based materials are particularly advantageous in this regard due to their low energy scales, flexible lattices, and chemical tunability. Here, we bring together high pressure Raman scattering, modeling, and first principles calculations to reveal the pressure-temperature-magnetic field phase diagram of Mn[N(CN)2]2. We uncover how hidden soft modes involving octahedral rotations drive two pressure-induced transitions triggering the low → high magnetic anisotropy crossover and a unique reorientation of exchange planes. These magnetostructural transitions and their mechanisms highlight the importance of spin-lattice interactions in establishing phases with novel magnetic properties in Mn(II)-containing systems.

Cultural Differences in Perceptual Reorganization in US and Pirahã Adults

PubMed Central

Yoon, Jennifer M. D.; Witthoft, Nathan; Winawer, Jonathan; Frank, Michael C.; Everett, Daniel L.; Gibson, Edward

2014-01-01

Visual illusions and other perceptual phenomena can be used as tools to uncover the otherwise hidden constructive processes that give rise to perception. Although many perceptual processes are assumed to be universal, variable susceptibility to certain illusions and perceptual effects across populations suggests a role for factors that vary culturally. One striking phenomenon is seen with two-tone images—photos reduced to two tones: black and white. Deficient recognition is observed in young children under conditions that trigger automatic recognition in adults. Here we show a similar lack of cue-triggered perceptual reorganization in the Pirahã, a hunter-gatherer tribe with limited exposure to modern visual media, suggesting such recognition is experience- and culture-specific. PMID:25411970

Topology versus Anderson localization: Nonperturbative solutions in one dimension

NASA Astrophysics Data System (ADS)

Altland, Alexander; Bagrets, Dmitry; Kamenev, Alex

2015-02-01

We present an analytic theory of quantum criticality in quasi-one-dimensional topological Anderson insulators. We describe these systems in terms of two parameters (g ,χ ) representing localization and topological properties, respectively. Certain critical values of χ (half-integer for Z classes, or zero for Z2 classes) define phase boundaries between distinct topological sectors. Upon increasing system size, the two parameters exhibit flow similar to the celebrated two-parameter flow of the integer quantum Hall insulator. However, unlike the quantum Hall system, an exact analytical description of the entire phase diagram can be given in terms of the transfer-matrix solution of corresponding supersymmetric nonlinear sigma models. In Z2 classes we uncover a hidden supersymmetry, present at the quantum critical point.

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

NASA Astrophysics Data System (ADS)

Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community detection in complex networks.

A persistent circhoral ultradian rhythm is identified in human core temperature.

PubMed

Lindsley, G; Dowse, H B; Burgoon, P W; Kolka, M A; Stephenson, L A

1999-01-01

There have been inconclusive reports of intermittent rhythmic fluctuations in human core temperature, with the fluctuations having a period of about an hour. However, there has been no definitive demonstration of the phenomenon. This is likely due to the intermittency and seeming instability of the events. They have been assumed to be secondary rather than autonomous phenomena, putatively arising from the oscillation between rapid eye movement (REM) and non-REM (NREM) sleep. In this study, we report identification of a clear, persistent circhoral ultradian rhythm in core temperature with a period for this study sample of 64 +/- 8 minutes. It appeared simultaneously with an intact circadian core temperature rhythm, persisted despite complex perturbations in core temperature brought about by the sequelae of 40 h of sleep deprivation, and could not be attributed to sleep stage alternation or other endogenous or exogenous factors. Analysis of power spectra using the maximum entropy spectral analysis (MESA) method, which can uncover hidden rhythmicities, demonstrated that the apparent intermittency of the rhythm is due to periodic interference of this rhythm by other rhythmic events. The persistence of this oscillation suggests that, in this system as in the endocrine system, circhoral regulation is an integral component of thermoregulatory control. Identifying the source and functional role of this novel rhythm warrants further work.

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

NASA Astrophysics Data System (ADS)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

An Analysis of Earth Science Data Analytics Use Cases

NASA Technical Reports Server (NTRS)

Shie, Chung-Lin; Kempler, Steve

2014-01-01

The increase in the number and volume, and sources, of globally available Earth science data measurements and datasets have afforded Earth scientists and applications researchers unprecedented opportunities to study our Earth in ever more sophisticated ways. In fact, the NASA Earth Observing System Data Information System (EOSDIS) archives have doubled from 2007 to 2014, to 9.1 PB (Ramapriyan, 2009; and https:earthdata.nasa.govaboutsystem-- performance). In addition, other US agency, international programs, field experiments, ground stations, and citizen scientists provide a plethora of additional sources for studying Earth. Co--analyzing huge amounts of heterogeneous data to glean out unobvious information is a daunting task. Earth science data analytics (ESDA) is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. It can include Data Preparation, Data Reduction, and Data Analysis. Through work associated with the Earth Science Information Partners (ESIP) Federation, a collection of Earth science data analytics use cases have been collected and analyzed for the purpose of extracting the types of Earth science data analytics employed, and requirements for data analytics tools and techniques yet to be implemented, based on use case needs. ESIP generated use case template, ESDA use cases, use case types, and preliminary use case analysis (this is a work in progress) will be presented.

Sex allocation theory reveals a hidden cost of neonicotinoid exposure in a parasitoid wasp

PubMed Central

Whitehorn, Penelope R.; Cook, Nicola; Blackburn, Charlotte V.; Gill, Sophie M.; Green, Jade; Shuker, David M.

2015-01-01

Sex allocation theory has proved to be one the most successful theories in evolutionary ecology. However, its role in more applied aspects of ecology has been limited. Here we show how sex allocation theory helps uncover an otherwise hidden cost of neonicotinoid exposure in the parasitoid wasp Nasonia vitripennis. Female N. vitripennis allocate the sex of their offspring in line with Local Mate Competition (LMC) theory. Neonicotinoids are an economically important class of insecticides, but their deployment remains controversial, with evidence linking them to the decline of beneficial species. We demonstrate for the first time to our knowledge, that neonicotinoids disrupt the crucial reproductive behaviour of facultative sex allocation at sub-lethal, field-relevant doses in N. vitripennis. The quantitative predictions we can make from LMC theory show that females exposed to neonicotinoids are less able to allocate sex optimally and that this failure imposes a significant fitness cost. Our work highlights that understanding the ecological consequences of neonicotinoid deployment requires not just measures of mortality or even fecundity reduction among non-target species, but also measures that capture broader fitness costs, in this case offspring sex allocation. Our work also highlights new avenues for exploring how females obtain information when allocating sex under LMC. PMID:25925105

Uncovering the cognitive processes underlying mental rotation: an eye-movement study.

PubMed

Xue, Jiguo; Li, Chunyong; Quan, Cheng; Lu, Yiming; Yue, Jingwei; Zhang, Chenggang

2017-08-30

Mental rotation is an important paradigm for spatial ability. Mental-rotation tasks are assumed to involve five or three sequential cognitive-processing states, though this has not been demonstrated experimentally. Here, we investigated how processing states alternate during mental-rotation tasks. Inference was carried out using an advanced statistical modelling and data-driven approach - a discriminative hidden Markov model (dHMM) trained using eye-movement data obtained from an experiment consisting of two different strategies: (I) mentally rotate the right-side figure to be aligned with the left-side figure and (II) mentally rotate the left-side figure to be aligned with the right-side figure. Eye movements were found to contain the necessary information for determining the processing strategy, and the dHMM that best fit our data segmented the mental-rotation process into three hidden states, which we termed encoding and searching, comparison, and searching on one-side pair. Additionally, we applied three classification methods, logistic regression, support vector model and dHMM, of which dHMM predicted the strategies with the highest accuracy (76.8%). Our study did confirm that there are differences in processing states between these two of mental-rotation strategies, and were consistent with the previous suggestion that mental rotation is discrete process that is accomplished in a piecemeal fashion.

Dynamic Alignment Models for Neural Coding

PubMed Central

Kollmorgen, Sepp; Hahnloser, Richard H. R.

2014-01-01

Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448

Analysis of surface EMG baseline for detection of hidden muscle activity

NASA Astrophysics Data System (ADS)

Zhang, Xu; Zhou, Ping

2014-02-01

Objective. This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach. Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used. Both analyses were applied to computer simulations of surface EMG baseline with the presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results. Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance. The findings implied the presence of a hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level.

Analysis of Surface EMG Baseline for Detection of Hidden Muscle Activity

PubMed Central

Zhang, Xu; Zhou, Ping

2014-01-01

Objective This study explored the feasibility of detecting hidden muscle activity in surface electromyogram (EMG) baseline. Approach Power spectral density (PSD) analysis and multi-scale entropy (MSE) analysis were used respectively. Both analyses were applied to computer simulations of surface EMG baseline with presence (representing activity data) or absence (representing reference data) of hidden muscle activity, as well as surface electrode array EMG baseline recordings of healthy control and amyotrophic lateral sclerosis (ALS) subjects. Main results Although the simulated reference data and the activity data yielded no distinguishable difference in the time domain, they demonstrated a significant difference in the frequency and signal complexity domains with the PSD and MSE analyses. For a comparison using pooled data, such a difference was also observed when the PSD and MSE analyses were applied to surface electrode array EMG baseline recordings of healthy control and ALS subjects, which demonstrated no distinguishable difference in the time domain. Compared with the PSD analysis, the MSE analysis appeared to be more sensitive for detecting the difference in surface EMG baselines between the two groups. Significance The findings implied presence of hidden muscle activity in surface EMG baseline recordings from the ALS subjects. To promote the presented analysis as a useful diagnostic or investigatory tool, future studies are necessary to assess the pathophysiological nature or origins of the hidden muscle activity, as well as the baseline difference at the individual subject level. PMID:24445526

Simple yet Hidden Counterexamples in Undergraduate Real Analysis

ERIC Educational Resources Information Center

Shipman, Barbara A.; Shipman, Patrick D.

2013-01-01

We study situations in introductory analysis in which students affirmed false statements as true, despite simple counterexamples that they easily recognized afterwards. The study draws attention to how simple counterexamples can become hidden in plain sight, even in an active learning atmosphere where students proposed simple (as well as more…

Uncovering the unknown: A grounded theory study exploring the impact of self-awareness on the culture of feedback in residency education.

PubMed

Ramani, Subha; Könings, Karen; Mann, Karen V; van der Vleuten, Cees

2017-10-01

Self-assessment and reflection are essential for meaningful feedback. We aimed to explore whether the well-known Johari window model of self-awareness could guide feedback conversations between faculty and residents and enhance the institutional feedback culture. We had previously explored perceptions of residents and faculty regarding sociocultural factors impacting feedback. We re-analyzed data targeting themes related to self-assessment, reflection, feedback seeking and acceptance, aiming to generate individual and institutional feedback strategies applicable to each quadrant of the window. We identified the following themes for each quadrant: (1) Behaviors known to self and others - Validating the known; (2) Behaviors unknown to self but known to others - Accepting the blind; (3) Behaviors known to self and unknown to others - Disclosure of hidden; and (4) Behaviors unknown to self and others - Uncovering the unknown. Normalizing self-disclosure of limitations, encouraging feedback seeking, training in nonjudgmental feedback and providing opportunities for longitudinal relationships could promote self-awareness, ultimately expanding the "open" quadrant of the Johari window. The Johari window, a model of self-awareness in interpersonal communications, could provide a robust framework for individuals to improve their feedback conversations and institutions to design feedback initiatives that enhance its quality and impact.

Uncovering Metaethical Assumptions in Bioethical Discourse across Cultures.

PubMed

Sullivan, Laura Specker

2016-03-01

Much of bioethical discourse now takes place across cultures. This does not mean that cross-cultural understanding has increased. Many cross-cultural bioethical discussions are marked by entrenched disagreement about whether and why local practices are justified. In this paper, I argue that a major reason for these entrenched disagreements is that problematic metaethical commitments are hidden in these cross-cultural discourses. Using the issue of informed consent in East Asia as an example of one such discourse, I analyze two representative positions in the discussion and identify their metaethical commitments. I suggest that the metaethical assumptions of these positions result from their shared method of ethical justification: moral principlism. I then show why moral principlism is problematic in cross-cultural analyses and propose a more useful method for pursuing ethical justification across cultures.

Uncovering the Role of RNA-Binding Proteins in Gene Expression in the Immune System.

PubMed

Díaz-Muñoz, Manuel D; Turner, Martin

2018-01-01

Fighting external pathogens requires an ever-changing immune system that relies on tight regulation of gene expression. Transcriptional control is the first step to build efficient responses while preventing immunodeficiencies and autoimmunity. Post-transcriptional regulation of RNA editing, location, stability, and translation are the other key steps for final gene expression, and they are all controlled by RNA-binding proteins (RBPs). Nowadays we have a deep understanding of how transcription factors control the immune system but recent evidences suggest that post-transcriptional regulation by RBPs is equally important for both development and activation of immune responses. Here, we review current knowledge about how post-transcriptional control by RBPs shapes our immune system and discuss the perspective of RBPs being the key players of a hidden immune cell epitranscriptome.

Covered versus uncovered self-expandable metal stents for malignant biliary strictures: A meta-analysis and systematic review.

PubMed

Moole, Harsha; Bechtold, Matthew L; Cashman, Micheal; Volmar, Fritz H; Dhillon, Sonu; Forcione, David; Taneja, Deepak; Puli, Srinivas R

2016-09-01

Self-expandable metal stents (SEMS) are used for palliating inoperable malignant biliary strictures. It is unclear if covered metal stents are superior to uncovered metal stents in these patients. We compared clinical outcomes in patients with covered and uncovered stents. Studies using covered and uncovered metallic stents for palliation in patients with malignant biliary stricture were reviewed. Articles were searched in MEDLINE, PubMed, and Ovid journals. Fixed and random effects models were used to calculate the pooled proportions. Initial search identified 1436 reference articles, of which 132 were selected and reviewed. Thirteen studies (n = 2239) for covered and uncovered metallic stents which met the inclusion criteria were included in this analysis. Odds ratio for stent occlusion rates in covered vs. uncovered stents was 0.79 (95 % CI = 0.65 to 0.96). Survival benefit in patients with covered vs. uncovered stents showed the odds ratio to be 1.29 (95 % CI = 0.95 to 1.74). Pooled odds ratio for migration of covered vs. uncovered stents was 9.9 (95 % CI = 4.5 to 22.3). Covered stents seemed to have significantly lesser occlusion rates, increased odds of migration, and increased odds of pancreatitis compared to uncovered stents. There was no statistically significant difference in the survival benefit, overall adverse event rate, and patency period of covered vs. uncovered metal stents in patients with malignant biliary strictures.

Hidden Process Models

DTIC Science & Technology

2009-12-18

cannot be detected with univariate techniques, but require multivariate analysis instead (Kamitani and Tong [2005]). Two other time series analysis ...learning for time series analysis . The historical record of DBNs can be traced back to Dean and Kanazawa [1988] and Dean and Wellman [1991], with...Rev. 8-98) Prescribed by ANSI Std Z39-18 Keywords: Hidden Process Models, probabilistic time series modeling, functional Magnetic Resonance Imaging

Multiple capacitors for natural genetic variation in Drosophila melanogaster.

PubMed

Takahashi, Kazuo H

2013-03-01

Cryptic genetic variation (CGV) or a standing genetic variation that is not ordinarily expressed as a phenotype is released when the robustness of organisms is impaired under environmental or genetic perturbations. Evolutionary capacitors modulate the amount of genetic variation exposed to natural selection and hidden cryptically; they have a fundamental effect on the evolvability of traits on evolutionary timescales. In this study, I have demonstrated the effects of multiple genomic regions of Drosophila melanogaster on CGV in wing shape. I examined the effects of 61 genomic deficiencies on quantitative and qualitative natural genetic variation in the wing shape of D. melanogaster. I have identified 10 genomic deficiencies that do not encompass a known candidate evolutionary capacitor, Hsp90, exposing natural CGV differently depending on the location of the deficiencies in the genome. Furthermore, five genomic deficiencies uncovered qualitative CGV in wing morphology. These findings suggest that CGV in wing shape of wild-type D. melanogaster is regulated by multiple capacitors with divergent functions. Future analysis of genes encompassed by these genomic regions would help elucidate novel capacitor genes and better understand the general features of capacitors regarding natural genetic variation. © 2012 Blackwell Publishing Ltd.

Energy dissipation in quasi-linear viscoelastic tissues, cells, and extracellular matrix.

PubMed

Babaei, Behzad; Velasquez-Mao, A J; Pryse, Kenneth M; McConnaughey, William B; Elson, Elliot L; Genin, Guy M

2018-05-21

Characterizing how a tissue's constituents give rise to its viscoelasticity is important for uncovering how hidden timescales underlie multiscale biomechanics. These constituents are viscoelastic in nature, and their mechanics must typically be assessed from the uniaxial behavior of a tissue. Confounding the challenge is that tissue viscoelasticity is typically associated with nonlinear elastic responses. Here, we experimentally assessed how fibroblasts and extracellular matrix (ECM) within engineered tissue constructs give rise to the nonlinear viscoelastic responses of a tissue. We applied a constant strain rate, "triangular-wave" loading and interpreted responses using the Fung quasi-linear viscoelastic (QLV) material model. Although the Fung QLV model has several well-known weaknesses, it was well suited to the behaviors of the tissue constructs, cells, and ECM tested. Cells showed relatively high damping over certain loading frequency ranges. Analysis revealed that, even in cases where the Fung QLV model provided an excellent fit to data, the the time constant derived from the model was not in general a material parameter. Results have implications for design of protocols for the mechanical characterization of biological materials, and for the mechanobiology of cells within viscoelastic tissues. Copyright © 2018. Published by Elsevier Ltd.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Electronic Tuning In The Hidden Order Compound URu2Si 2 Through Si → P substitution

NASA Astrophysics Data System (ADS)

Gallagher, Andrew

Crystalline materials that include 4f- and 5 f-electron elements frequently exhibit a variety of intriguing phenomena including spin and charge orderings, spin and valence fluctuations, heavy fermion behavior, breakdown of Fermi liquid behavior, and unconventional superconductivity. [5, 6, 7, 8, 9, 10, 11, 12, 13] Amongst such materials, the Kondo lattice system URu2Si2 stands out as being particularly unusual. [14, 15, 16] While at high temperature it exhibits behavior that is typical for an f-electron lattice immersed in a sea of conduction electrons, at T0 = 17:5 K there is a second order phase transition that is followed by unconventional superconductivity near Tc ≈ 1:5 K. [15] Despite three decades of work, the order parameter for the transition at T0 remains unknown and hence, it has been named "hidden order". There have been a multitude of experimental attempts to unravel hidden order, mainly through tuning of the electronic state via pressure, applied magnetic field, and chemical substitution. [17, 18] While these strategies reveal interesting phase diagrams, a longstanding challenge is that any such approach explores the phase space along an unknown vector: i.e., many different factors are affected. To address this issue, we developed a new organizational map for the U-based ThCr2Si2-type compounds that are related to URu2Si2 and thus guided, we explored a new chemical tuning axis: Si -> P. Our studies were enabled by the development of a new molten metal crystal growth method for URu2Si2 which produces high quality single crystals and allows us to introduce high vapor pressure elements, such as phosphorous. [19, 20] Si → P tuning reveals that while the high temperature Kondo lattice behavior is robust, the low temperature phenomena are remarkably sensitive to electronic tuning. [21, 22] In the URu2Si2-xPx phase diagram we find that while hidden order is monotonically suppressed and destroyed for x < 0.035, the superconducting strength evolves non-monotonically with a maximum near x = 0.01 and that superconductivity is destroyed near x ≈ 0.028. For 0.03 < x < 0.26 there is a region with Kondo coherence but no ordered state. Antiferromagnetism abruptly appears for x = 0.26. This phase diagram differs significantly from those produced by most other tuning strategies in URu2Si2, including applied pressure, and isoelectronic chemical substitution (i.e. Ru→Fe and Os), where hidden order and magnetism share a common phase boundary. [2, 23, 24] We discuss implications for understanding hidden order, its relationship to magnetism, and prospects for uncovering novel sibling electronic states.

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-04-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-01-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

Tracking Problem Solving by Multivariate Pattern Analysis and Hidden Markov Model Algorithms

ERIC Educational Resources Information Center

Anderson, John R.

2012-01-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application…

Numerous Transitions of Sex Chromosomes in Diptera

PubMed Central

Vicoso, Beatriz; Bachtrog, Doris

2015-01-01

Many species groups, including mammals and many insects, determine sex using heteromorphic sex chromosomes. Diptera flies, which include the model Drosophila melanogaster, generally have XY sex chromosomes and a conserved karyotype consisting of six chromosomal arms (five large rods and a small dot), but superficially similar karyotypes may conceal the true extent of sex chromosome variation. Here, we use whole-genome analysis in 37 fly species belonging to 22 different families of Diptera and uncover tremendous hidden diversity in sex chromosome karyotypes among flies. We identify over a dozen different sex chromosome configurations, and the small dot chromosome is repeatedly used as the sex chromosome, which presumably reflects the ancestral karyotype of higher Diptera. However, we identify species with undifferentiated sex chromosomes, others in which a different chromosome replaced the dot as a sex chromosome or in which up to three chromosomal elements became incorporated into the sex chromosomes, and others yet with female heterogamety (ZW sex chromosomes). Transcriptome analysis shows that dosage compensation has evolved multiple times in flies, consistently through up-regulation of the single X in males. However, X chromosomes generally show a deficiency of genes with male-biased expression, possibly reflecting sex-specific selective pressures. These species thus provide a rich resource to study sex chromosome biology in a comparative manner and show that similar selective forces have shaped the unique evolution of sex chromosomes in diverse fly taxa. PMID:25879221

Mind the gap: financial London and the regional class pay gap.

PubMed

Friedman, Sam; Laurison, Daniel

2017-09-01

The hidden barriers, or 'gender pay gap', preventing women from earning equivalent incomes to men is well documented. Yet recent research has uncovered that, in Britain, there is also a comparable class-origin pay gap in higher professional and managerial occupations. So far this analysis has only been conducted at the national level and it is not known whether there are regional differences within the UK. This paper uses pooled data from the 2014 and 2015 Labour Force Survey (N = 7,534) to stage a more spatially sensitive analysis that examines regional variation in the class pay gap. We find that this 'class ceiling' is not evenly spatially distributed. Instead it is particularly marked in Central London, where those in high-status occupations who are from working-class backgrounds earn, on average, £10,660 less per year than those whose parents were in higher professional and managerial employment. Finally, we inspect the Capital further to reveal that the class pay gap is largest within Central London's banking and finance sector. Challenging policy conceptions of London as the 'engine room' of social mobility, these findings suggest that class disadvantage within high-status occupations is particularly acute in the Capital. The findings also underline the value of investigating regional differences in social mobility, and demonstrate how such analysis can unravel important and previously unrecognized spatial dimensions of class inequality. © London School of Economics and Political Science 2017.

Synchronisation, electronic circuit implementation, and fractional-order analysis of 5D ordinary differential equations with hidden hyperchaotic attractors

NASA Astrophysics Data System (ADS)

Wei, Zhouchao; Rajagopal, Karthikeyan; Zhang, Wei; Kingni, Sifeu Takougang; Akgül, Akif

2018-04-01

Hidden hyperchaotic attractors can be generated with three positive Lyapunov exponents in the proposed 5D hyperchaotic Burke-Shaw system with only one stable equilibrium. To the best of our knowledge, this feature has rarely been previously reported in any other higher-dimensional systems. Unidirectional linear error feedback coupling scheme is used to achieve hyperchaos synchronisation, which will be estimated by using two indicators: the normalised average root-mean squared synchronisation error and the maximum cross-correlation coefficient. The 5D hyperchaotic system has been simulated using a specially designed electronic circuit and viewed on an oscilloscope, thereby confirming the results of the numerical integration. In addition, fractional-order hidden hyperchaotic system will be considered from the following three aspects: stability, bifurcation analysis and FPGA implementation. Such implementations in real time represent hidden hyperchaotic attractors with important consequences for engineering applications.

Generalization and capacity of extensively large two-layered perceptrons.

PubMed

Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido

2002-09-01

The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, alpha(c), at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different.

Uncovering the Role of RNA-Binding Proteins in Gene Expression in the Immune System

PubMed Central

Díaz-Muñoz, Manuel D.; Turner, Martin

2018-01-01

Fighting external pathogens requires an ever-changing immune system that relies on tight regulation of gene expression. Transcriptional control is the first step to build efficient responses while preventing immunodeficiencies and autoimmunity. Post-transcriptional regulation of RNA editing, location, stability, and translation are the other key steps for final gene expression, and they are all controlled by RNA-binding proteins (RBPs). Nowadays we have a deep understanding of how transcription factors control the immune system but recent evidences suggest that post-transcriptional regulation by RBPs is equally important for both development and activation of immune responses. Here, we review current knowledge about how post-transcriptional control by RBPs shapes our immune system and discuss the perspective of RBPs being the key players of a hidden immune cell epitranscriptome. PMID:29875770

Domestic science: making chemistry your cup of tea.

PubMed

Keene, Melanie

2008-03-01

In the early Victorian home, there were plenty of scientific lessons to be uncovered. With the appropriate interrogation, everyday objects could transform seemingly mundane activities such as eating breakfast, washing clothes or reading by candle-light into household lectures that gave children a familiar base from which to explore the hidden properties and marvellous histories of common commodities. Responding to an unprecedented hunger for scientific knowledge, a profusion of introductory texts appeared in the mid-nineteenth century that directed lessons into homes across Britain and beyond. In particular, the science of chemistry found its way into this domestic setting, as writers promoted its practice and practitioners as a source of authoritative expertise on everyday life. One of the most compelling illustrations of this encounter between the public and chemistry took place over a simple cup of tea.

Suppression bias at the Journal of Occupational and Environmental Medicine.

PubMed

Egilman, David S

2005-01-01

When the Journal of Occupational and Environmental Medicine rejected an article on corporate suppression of science on the grounds that the topic "was not a high priority" for journal readers, the author bought advertising space in JOEM to present his findings. The JOEM editor regretted he had not seen the ad to prevent its publication, and subsequently allowed the corporate-sponsored authors of a criticized study to respond to the advertisement. The editor then refused to allow the ad's author to respond in turn, suppressing scientific information with the apparent intent of protecting the interests and profits of the corporate sponsor. A reputable journal has a responsibility to eschew corporate interests and work to uncover science hidden by interests that do not prioritize the pursuit of truth. JOEM needs to re-examine its priorities.

Automation and adaptation: Nurses' problem-solving behavior following the implementation of bar coded medication administration technology.

PubMed

Holden, Richard J; Rivera-Rodriguez, A Joy; Faye, Héléne; Scanlon, Matthew C; Karsh, Ben-Tzion

2013-08-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses' operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA's impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians' work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign.

Sex allocation theory reveals a hidden cost of neonicotinoid exposure in a parasitoid wasp.

PubMed

Whitehorn, Penelope R; Cook, Nicola; Blackburn, Charlotte V; Gill, Sophie M; Green, Jade; Shuker, David M

2015-05-22

Sex allocation theory has proved to be one the most successful theories in evolutionary ecology. However, its role in more applied aspects of ecology has been limited. Here we show how sex allocation theory helps uncover an otherwise hidden cost of neonicotinoid exposure in the parasitoid wasp Nasonia vitripennis. Female N. vitripennis allocate the sex of their offspring in line with Local Mate Competition (LMC) theory. Neonicotinoids are an economically important class of insecticides, but their deployment remains controversial, with evidence linking them to the decline of beneficial species. We demonstrate for the first time to our knowledge, that neonicotinoids disrupt the crucial reproductive behaviour of facultative sex allocation at sub-lethal, field-relevant doses in N. vitripennis. The quantitative predictions we can make from LMC theory show that females exposed to neonicotinoids are less able to allocate sex optimally and that this failure imposes a significant fitness cost. Our work highlights that understanding the ecological consequences of neonicotinoid deployment requires not just measures of mortality or even fecundity reduction among non-target species, but also measures that capture broader fitness costs, in this case offspring sex allocation. Our work also highlights new avenues for exploring how females obtain information when allocating sex under LMC. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Automation and adaptation: Nurses’ problem-solving behavior following the implementation of bar coded medication administration technology

PubMed Central

Holden, Richard J.; Rivera-Rodriguez, A. Joy; Faye, Héléne; Scanlon, Matthew C.; Karsh, Ben-Tzion

2012-01-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses’ operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA’s impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians’ work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign. PMID:24443642

A Finite Element Analysis of a Class of Problems in Elasto-Plasticity with Hidden Variables.

DTIC Science & Technology

1985-09-01

RD-R761 642 A FINITE ELEMENT ANALYSIS OF A CLASS OF PROBLEMS IN 1/2 ELASTO-PLASTICITY MIlT (U) TEXAS INST FOR COMPUTATIONAL MECHANICS AUSTIN J T ODEN...end Subtitle) S. TYPE OF REPORT & PERIOD COVERED A FINITE ELEMENT ANALYSIS OF A CLASS OF PROBLEMS Final Report IN ELASTO-PLASTICITY WITH HIDDEN...aieeoc ede It neceeeary nd Identify by block number) ;"Elastoplasticity, finite deformations; non-convex analysis ; finite element methods, metal forming

Infinite hidden conditional random fields for human behavior analysis.

PubMed

Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

2013-01-01

Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.

Application of dynamic topic models to toxicogenomics data.

PubMed

Lee, Mikyung; Liu, Zhichao; Huang, Ruili; Tong, Weida

2016-10-06

All biological processes are inherently dynamic. Biological systems evolve transiently or sustainably according to sequential time points after perturbation by environment insults, drugs and chemicals. Investigating the temporal behavior of molecular events has been an important subject to understand the underlying mechanisms governing the biological system in response to, such as, drug treatment. The intrinsic complexity of time series data requires appropriate computational algorithms for data interpretation. In this study, we propose, for the first time, the application of dynamic topic models (DTM) for analyzing time-series gene expression data. A large time-series toxicogenomics dataset was studied. It contains over 3144 microarrays of gene expression data corresponding to rat livers treated with 131 compounds (most are drugs) at two doses (control and high dose) in a repeated schedule containing four separate time points (4-, 8-, 15- and 29-day). We analyzed, with DTM, the topics (consisting of a set of genes) and their biological interpretations over these four time points. We identified hidden patterns embedded in this time-series gene expression profiles. From the topic distribution for compound-time condition, a number of drugs were successfully clustered by their shared mode-of-action such as PPARɑ agonists and COX inhibitors. The biological meaning underlying each topic was interpreted using diverse sources of information such as functional analysis of the pathways and therapeutic uses of the drugs. Additionally, we found that sample clusters produced by DTM are much more coherent in terms of functional categories when compared to traditional clustering algorithms. We demonstrated that DTM, a text mining technique, can be a powerful computational approach for clustering time-series gene expression profiles with the probabilistic representation of their dynamic features along sequential time frames. The method offers an alternative way for uncovering hidden patterns embedded in time series gene expression profiles to gain enhanced understanding of dynamic behavior of gene regulation in the biological system.

Detect and exploit hidden structure in fatty acid signature data

USGS Publications Warehouse

Budge, Suzanne; Bromaghin, Jeffrey F.; Thiemann, Gregory

2017-01-01

Estimates of predator diet composition are essential to our understanding of their ecology. Although several methods of estimating diet are practiced, methods based on biomarkers have become increasingly common. Quantitative fatty acid signature analysis (QFASA) is a popular method that continues to be refined and extended. Quantitative fatty acid signature analysis is based on differences in the signatures of prey types, often species, which are recognized and designated by investigators. Similarly, predator signatures may be structured by known factors such as sex or age class, and the season or region of sample collection. The recognized structure in signature data inherently influences QFASA results in important and typically beneficial ways. However, predator and prey signatures may contain additional, hidden structure that investigators either choose not to incorporate into an analysis or of which they are unaware, being caused by unknown ecological mechanisms. Hidden structure also influences QFASA results, most often negatively. We developed a new method to explore signature data for hidden structure, called divisive magnetic clustering (DIMAC). Our DIMAC approach is based on the same distance measure used in diet estimation, closely linking methods of data exploration and parameter estimation, and it does not require data transformation or distributional assumptions, as do many multivariate ordination methods in common use. We investigated the potential benefits of the DIMAC method to detect and subsequently exploit hidden structure in signature data using two prey signature libraries with quite different characteristics. We found that the existence of hidden structure in prey signatures can increase the confusion between prey types and thereby reduce the accuracy and precision of QFASA diet estimates. Conversely, the detection and exploitation of hidden structure represent a potential opportunity to improve predator diet estimates and may lead to new insights into the ecology of either predator or prey. The DIMAC algorithm is implemented in the R diet estimation package qfasar.

A Rule-Based Spatial Reasoning Approach for OpenStreetMap Data Quality Enrichment; Case Study of Routing and Navigation

PubMed Central

2017-01-01

Finding relevant geospatial information is increasingly critical because of the growing volume of geospatial data available within the emerging “Big Data” era. Users are expecting that the availability of massive datasets will create more opportunities to uncover hidden information and answer more complex queries. This is especially the case with routing and navigation services where the ability to retrieve points of interest and landmarks make the routing service personalized, precise, and relevant. In this paper, we propose a new geospatial information approach that enables the retrieval of implicit information, i.e., geospatial entities that do not exist explicitly in the available source. We present an information broker that uses a rule-based spatial reasoning algorithm to detect topological relations. The information broker is embedded into a framework where annotations and mappings between OpenStreetMap data attributes and external resources, such as taxonomies, support the enrichment of queries to improve the ability of the system to retrieve information. Our method is tested with two case studies that leads to enriching the completeness of OpenStreetMap data with footway crossing points-of-interests as well as building entrances for routing and navigation purposes. It is concluded that the proposed approach can uncover implicit entities and contribute to extract required information from the existing datasets. PMID:29088125

Perspectives of nursing and midwifery students regarding the role of the hidden curriculum in patient education: A qualitative study.

PubMed

Azadi, Zohreh; Ravanipour, Maryam; Yazdankhahfard, Mohammadreza; Motamed, Niloofar; Pouladi, Shahnaz

2017-01-01

Although education is one of the most substantial needs of patients that should be taught by nurses and midwives, it is not clearly defined through the hidden curriculum in students' teaching programs. The aim of this study was to explore the patient education through the hidden curriculum in the perspectives of nursing and midwifery students. A qualitative, content analysis study was performed and twenty nursing and midwifery students were interviewed. Data were collected using face-to-face semi-structured interviews and analyzed using conventional content analysis approach. Students' perception of the hidden curriculum in patient education emerged in three main themes concerning: (1) interactions, (2) teaching and learning opportunities, and (3) reflective evaluation. The hidden curriculum in patient education can be transferred as interactions between professors, students, nurses, doctors, and also patients who are rooted from paying attention to the human dimension of the patient, avoiding the materialistic treatment of the patient and treating the patient with dignity. Educational policies and students' assignments should be designed based on the patient's educational goals and the goal of evaluation has to be presented to the students clearly.

Perspectives of nursing and midwifery students regarding the role of the hidden curriculum in patient education: A qualitative study

PubMed Central

Azadi, Zohreh; Ravanipour, Maryam; Yazdankhahfard, Mohammadreza; Motamed, Niloofar; Pouladi, Shahnaz

2017-01-01

BACKGROUND: Although education is one of the most substantial needs of patients that should be taught by nurses and midwives, it is not clearly defined through the hidden curriculum in students’ teaching programs. The aim of this study was to explore the patient education through the hidden curriculum in the perspectives of nursing and midwifery students. MATERIALS AND METHODS: A qualitative, content analysis study was performed and twenty nursing and midwifery students were interviewed. Data were collected using face-to-face semi-structured interviews and analyzed using conventional content analysis approach. RESULTS: Students’ perception of the hidden curriculum in patient education emerged in three main themes concerning: (1) interactions, (2) teaching and learning opportunities, and (3) reflective evaluation. CONCLUSIONS: The hidden curriculum in patient education can be transferred as interactions between professors, students, nurses, doctors, and also patients who are rooted from paying attention to the human dimension of the patient, avoiding the materialistic treatment of the patient and treating the patient with dignity. Educational policies and students’ assignments should be designed based on the patient's educational goals and the goal of evaluation has to be presented to the students clearly. PMID:29296609

Semi-simultaneous application of neutron and X-ray radiography in revealing the defects in an Al casting.

PubMed

Balaskó, M; Korösi, F; Szalay, Zs

2004-10-01

A semi-simultaneous application of neutron and X-ray radiography (NR, XR) respectively, was applied to an Al casting. The experiments were performed at the 10MW VVR-SM research reactor in Budapest (Hungary). The aim was to reveal, identify and parameterize the hidden defects in the Al casting. The joint application of NR and XR revealed hidden defects located in the Al casting. Image analysis of the NR and XR images unveiled a cone-like dimensionality of the defects. The spectral density analysis of the images showed a distinctly different character for the hidden defect region of Al casting in comparison with that of the defect-free one.

Life imitating art: depictions of the hidden curriculum in medical television programs.

PubMed

Stanek, Agatha; Clarkin, Chantalle; Bould, M Dylan; Writer, Hilary; Doja, Asif

2015-09-26

The hidden curriculum represents influences occurring within the culture of medicine that indirectly alter medical professionals' interactions, beliefs and clinical practices throughout their training. One approach to increase medical student awareness of the hidden curriculum is to provide them with readily available examples of how it is enacted in medicine; as such the purpose of this study was to examine depictions of the hidden curriculum in popular medical television programs. One full season of ER, Grey's Anatomy and Scrubs were selected for review. A summative content analysis was performed to ascertain the presence of depictions of the hidden curriculum, as well as to record the type, frequency and quality of examples. A second reviewer also viewed a random selection of episodes from each series to establish coding reliability. The most prevalent themes across all television programs were: the hierarchical nature of medicine; challenges during transitional stages in medicine; the importance of role modeling; patient dehumanization; faking or overstating one's capabilities; unprofessionalism; the loss of idealism; and difficulties with work-life balance. The hidden curriculum is frequently depicted in popular medical television shows. These examples of the hidden curriculum could serve as a valuable teaching resource in undergraduate medical programs.

zipHMMlib: a highly optimised HMM library exploiting repetitions in the input to speed up the forward algorithm.

PubMed

Sand, Andreas; Kristiansen, Martin; Pedersen, Christian N S; Mailund, Thomas

2013-11-22

Hidden Markov models are widely used for genome analysis as they combine ease of modelling with efficient analysis algorithms. Calculating the likelihood of a model using the forward algorithm has worst case time complexity linear in the length of the sequence and quadratic in the number of states in the model. For genome analysis, however, the length runs to millions or billions of observations, and when maximising the likelihood hundreds of evaluations are often needed. A time efficient forward algorithm is therefore a key ingredient in an efficient hidden Markov model library. We have built a software library for efficiently computing the likelihood of a hidden Markov model. The library exploits commonly occurring substrings in the input to reuse computations in the forward algorithm. In a pre-processing step our library identifies common substrings and builds a structure over the computations in the forward algorithm which can be reused. This analysis can be saved between uses of the library and is independent of concrete hidden Markov models so one preprocessing can be used to run a number of different models.Using this library, we achieve up to 78 times shorter wall-clock time for realistic whole-genome analyses with a real and reasonably complex hidden Markov model. In one particular case the analysis was performed in less than 8 minutes compared to 9.6 hours for the previously fastest library. We have implemented the preprocessing procedure and forward algorithm as a C++ library, zipHMM, with Python bindings for use in scripts. The library is available at http://birc.au.dk/software/ziphmm/.

Informatic analysis for hidden pulse attack exploiting spectral characteristics of optics in plug-and-play quantum key distribution system

NASA Astrophysics Data System (ADS)

Ko, Heasin; Lim, Kyongchun; Oh, Junsang; Rhee, June-Koo Kevin

2016-10-01

Quantum channel loopholes due to imperfect implementations of practical devices expose quantum key distribution (QKD) systems to potential eavesdropping attacks. Even though QKD systems are implemented with optical devices that are highly selective on spectral characteristics, information theory-based analysis about a pertinent attack strategy built with a reasonable framework exploiting it has never been clarified. This paper proposes a new type of trojan horse attack called hidden pulse attack that can be applied in a plug-and-play QKD system, using general and optimal attack strategies that can extract quantum information from phase-disturbed quantum states of eavesdropper's hidden pulses. It exploits spectral characteristics of a photodiode used in a plug-and-play QKD system in order to probe modulation states of photon qubits. We analyze the security performance of the decoy-state BB84 QKD system under the optimal hidden pulse attack model that shows enormous performance degradation in terms of both secret key rate and transmission distance.

Application of Deep Learning and Supervised Learning Methods to Recognize Nonlinear Hidden Pattern in Water Stress Levels from Spatiotemporal Datasets across Rural and Urban US Counties

NASA Astrophysics Data System (ADS)

Eisenhart, T.; Josset, L.; Rising, J. A.; Devineni, N.; Lall, U.

2017-12-01

In the wake of recent water crises, the need to understand and predict the risk of water stress in urban and rural areas has grown. This understanding has the potential to improve decision making in public resource management, policy making, risk management and investment decisions. Assuming an underlying relationship between urban and rural water stress and observable features, we apply Deep Learning and Supervised Learning models to uncover hidden nonlinear patterns from spatiotemporal datasets. Results of interest includes prediction accuracy on extreme categories (i.e. urban areas highly prone to water stress) and not solely the average risk for urban or rural area, which adds complexity to the tuning of model parameters. We first label urban water stressed counties using annual water quality violations and compile a comprehensive spatiotemporal dataset that captures the yearly evolution of climatic, demographic and economic factors of more than 3,000 US counties over the 1980-2010 period. As county-level data reporting is not done on a yearly basis, we test multiple imputation methods to get around the issue of missing data. Using Python libraries, TensorFlow and scikit-learn, we apply and compare the ability of, amongst other methods, Recurrent Neural Networks (testing both LSTM and GRU cells), Convolutional Neural Networks and Support Vector Machines to predict urban water stress. We evaluate the performance of those models over multiple time spans and combine methods to diminish the risk of overfitting and increase prediction power on test sets. This methodology seeks to identify hidden nonlinear patterns to assess the predominant data features that influence urban and rural water stress. Results from this application at the national scale will assess the performance of deep learning models to predict water stress risk areas across all US counties and will highlight a predominant Machine Learning method for modeling water stress risk using spatiotemporal data.

Learning history and cholinergic modulation in the dorsal hippocampus are necessary for rats to infer the status of a hidden event.

PubMed

Fast, Cynthia D; Flesher, M Melissa; Nocera, Nathanial A; Fanselow, Michael S; Blaisdell, Aaron P

2016-06-01

Identifying statistical patterns between environmental stimuli enables organisms to respond adaptively when cues are later observed. However, stimuli are often obscured from detection, necessitating behavior under conditions of ambiguity. Considerable evidence indicates decisions under ambiguity rely on inference processes that draw on past experiences to generate predictions under novel conditions. Despite the high demand for this process and the observation that it deteriorates disproportionately with age, the underlying mechanisms remain unknown. We developed a rodent model of decision-making during ambiguity to examine features of experience that contribute to inference. Rats learned either a simple (positive patterning) or complex (negative patterning) instrumental discrimination between the illumination of one or two lights. During test, only one light was lit while the other relevant light was blocked from physical detection (covered by an opaque shield, rendering its status ambiguous). We found experience with the complex negative patterning discrimination was necessary for rats to behave sensitively to the ambiguous test situation. These rats behaved as if they inferred the presence of the hidden light, responding differently than when the light was explicitly absent (uncovered and unlit). Differential expression profiles of the immediate early gene cFos indicated hippocampal involvement in the inference process while localized microinfusions of the muscarinic antagonist, scopolamine, into the dorsal hippocampus caused rats to behave as if only one light was present. That is, blocking cholinergic modulation prevented the rat from inferring the presence of the hidden light. Collectively, these results suggest cholinergic modulation mediates recruitment of hippocampal processes related to past experiences and transfer of these processes to make decisions during ambiguous situations. Our results correspond with correlations observed between human brain function and inference abilities, suggesting our experiments may inform interventions to alleviate or prevent cognitive dysfunction. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Detection and electrical characterization of hidden layers using time-domain analysis of terahertz reflections

NASA Astrophysics Data System (ADS)

Geltner, I.; Hashimshony, D.; Zigler, A.

2002-07-01

We use a time-domain analysis method to characterize the outer layer of a multilayer structure regardless of the inner ones, thus simplifying the characterization of all the layers. We combine this method with THz reflection spectroscopy to detect nondestructively a hidden aluminum oxide layer under opaque paint and to measure its conductivity and high-frequency dielectric constant in the THz range.

A Network Based Method for Analysis of lncRNA-Disease Associations and Prediction of lncRNAs Implicated in Diseases

PubMed Central

Yang, Xiaofei; Gao, Lin; Guo, Xingli; Shi, Xinghua; Wu, Hao; Song, Fei; Wang, Bingbo

2014-01-01

Increasing evidence has indicated that long non-coding RNAs (lncRNAs) are implicated in and associated with many complex human diseases. Despite of the accumulation of lncRNA-disease associations, only a few studies had studied the roles of these associations in pathogenesis. In this paper, we investigated lncRNA-disease associations from a network view to understand the contribution of these lncRNAs to complex diseases. Specifically, we studied both the properties of the diseases in which the lncRNAs were implicated, and that of the lncRNAs associated with complex diseases. Regarding the fact that protein coding genes and lncRNAs are involved in human diseases, we constructed a coding-non-coding gene-disease bipartite network based on known associations between diseases and disease-causing genes. We then applied a propagation algorithm to uncover the hidden lncRNA-disease associations in this network. The algorithm was evaluated by leave-one-out cross validation on 103 diseases in which at least two genes were known to be involved, and achieved an AUC of 0.7881. Our algorithm successfully predicted 768 potential lncRNA-disease associations between 66 lncRNAs and 193 diseases. Furthermore, our results for Alzheimer's disease, pancreatic cancer, and gastric cancer were verified by other independent studies. PMID:24498199

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

NASA Astrophysics Data System (ADS)

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

2001-03-01

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

Uncovering Influence through Social Network Analysis: The Role of Schools in Education for Sustainable Development

ERIC Educational Resources Information Center

Kolleck, Nina

2016-01-01

This paper examines the implementation of Education for Sustainable Development (ESD) in Germany and explores the possibilities of Social Network Analysis (SNA) for uncovering influential actors in educational policy innovation processes. From the theoretical perspective, an actor's influence is inferred from its relative position within…

Claiming space for an engaged anthropology: spatial inequality and social exclusion.

PubMed

Low, Setha M

2011-01-01

I use the concept of “engaged anthropology” to frame a discussion of how “spatializing culture” uncovers systems of exclusion that are hidden or naturalized and thus rendered invisible to other methodological approaches. “Claiming Space for an Engaged Anthropology” is doubly meant: to claim more intellectual and professional space for engagement and to propose that anthropology include the dimension of space as a theoretical construct. I draw on three fieldwork examples to illustrate the value of the approach: (1) a Spanish American plaza, reclaimed from a Eurocentric past, for indigenous groups and contemporary cultural interpretation; (2) Moore Street Market, an enclosed Latino food market in Brooklyn, New York, reclaimed for a translocal set of social relations rather than a gentrified redevelopment project; (3) gated communities in Texas and New York and cooperatives in New York, reclaiming public space and confronting race and class segregation created by neoliberal enclosure and securitization.

Network features of sector indexes spillover effects in China: A multi-scale view

NASA Astrophysics Data System (ADS)

Feng, Sida; Huang, Shupei; Qi, Yabin; Liu, Xueyong; Sun, Qingru; Wen, Shaobo

2018-04-01

The spillover effects among sectors are of concern for distinct market participants, who are in distinct investment horizons and concerned with the information in different time scales. In order to uncover the hidden spillover information in multi-time scales in the rapidly changing stock market and thereby offer guidance to different investors concerning distinct time scales from a system perspective, this paper constructed directional spillover effect networks for the economic sectors in distinct time scales. The results are as follows: (1) The "2-4 days" scale is the most risky scale, and the "8-16 days" scale is the least risky one. (2) The most influential and sensitive sectors are distinct in different time scales. (3) Although two sectors in the same community may not have direct spillover relations, the volatility of one sector will have a relatively strong influence on the other through indirect relations.

Cultures of choice: towards a sociology of choice as a cultural phenomenon.

PubMed

Schwarz, Ori

2017-09-07

The article explores different ways to conceptualize the relationship between choice and culture. These two notions are often constructed as opposites: while sociologies of modernization (such as Giddens') portray a shift from cultural traditions to culturally disembedded choice, dispositional sociologies (such as Bourdieu's) uncover cultural determination as the hidden truth behind apparent choice. However, choice may be real and cultural simultaneously. Culture moulds choice not only by inculcating dispositions or shaping repertoires of alternatives, but also by offering culturally specific choice practices, ways of choosing embedded in meaning, normativity, and materiality; and by shaping attributions of choice in everyday life. By bringing together insights from rival schools, I portray an outline for a comparative cultural sociology of choice, and demonstrate its purchase while discussing the digitalization of choice; and cultural logics that shape choice attribution in ways opposing neoliberal trends. © London School of Economics and Political Science 2017.

Reaction Mechanisms on Multiwell Potential Energy Surfaces in Combustion (and Atmospheric) Chemistry

DOE PAGES

Osborn, David L.

2017-03-15

Chemical reactions occurring on a potential energy surface with multiple wells are ubiquitous in low temperature combustion and the oxidation of volatile organic compounds in earth’s atmosphere. The rich variety of structural isomerizations that compete with collisional stabilization make characterizing such complex-forming reactions challenging. This review describes recent experimental and theoretical advances that deliver increasingly complete views of their reaction mechanisms. New methods for creating reactive intermediates coupled with multiplexed measurements provide many experimental observables simultaneously. Automated methods to explore potential energy surfaces can uncover hidden reactive pathways, while master equation methods enable a holistic treatment of both sequential andmore » well-skipping pathways. Our ability to probe and understand nonequilibrium effects and reaction sequences is increasing. These advances provide the fundamental science base for predictive models of combustion and the atmosphere that are crucial to address global challenges.« less

Big Data Analytics for Genomic Medicine

PubMed Central

He, Karen Y.; Ge, Dongliang; He, Max M.

2017-01-01

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients’ genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a Big Data infrastructure exhibit challenges, they also provide a feasible opportunity to develop an efficient and effective approach to identify clinically actionable genetic variants for individualized diagnosis and therapy. In this paper, we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. We introduce possible solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data to implement genomic medicine. Additionally, we also present a practical Big Data toolset for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs. PMID:28212287

Statistical significance of combinatorial regulations

PubMed Central

Terada, Aika; Okada-Hatakeyama, Mariko; Tsuda, Koji; Sese, Jun

2013-01-01

More than three transcription factors often work together to enable cells to respond to various signals. The detection of combinatorial regulation by multiple transcription factors, however, is not only computationally nontrivial but also extremely unlikely because of multiple testing correction. The exponential growth in the number of tests forces us to set a strict limit on the maximum arity. Here, we propose an efficient branch-and-bound algorithm called the “limitless arity multiple-testing procedure” (LAMP) to count the exact number of testable combinations and calibrate the Bonferroni factor to the smallest possible value. LAMP lists significant combinations without any limit, whereas the family-wise error rate is rigorously controlled under the threshold. In the human breast cancer transcriptome, LAMP discovered statistically significant combinations of as many as eight binding motifs. This method may contribute to uncover pathways regulated in a coordinated fashion and find hidden associations in heterogeneous data. PMID:23882073

Reaction Mechanisms on Multiwell Potential Energy Surfaces in Combustion (and Atmospheric) Chemistry

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

Osborn, David L.

Chemical reactions occurring on a potential energy surface with multiple wells are ubiquitous in low temperature combustion and the oxidation of volatile organic compounds in earth’s atmosphere. The rich variety of structural isomerizations that compete with collisional stabilization make characterizing such complex-forming reactions challenging. This review describes recent experimental and theoretical advances that deliver increasingly complete views of their reaction mechanisms. New methods for creating reactive intermediates coupled with multiplexed measurements provide many experimental observables simultaneously. Automated methods to explore potential energy surfaces can uncover hidden reactive pathways, while master equation methods enable a holistic treatment of both sequential andmore » well-skipping pathways. Our ability to probe and understand nonequilibrium effects and reaction sequences is increasing. These advances provide the fundamental science base for predictive models of combustion and the atmosphere that are crucial to address global challenges.« less

Coupling the Leidenfrost effect and elastic deformations to power sustained bouncing

NASA Astrophysics Data System (ADS)

Waitukaitis, Scott R.; Zuiderwijk, Antal; Souslov, Anton; Coulais, Corentin; van Hecke, Martin

2017-11-01

The Leidenfrost effect occurs when an object near a hot surface vaporizes rapidly enough to lift itself up and hover. Although well understood for liquids and stiff sublimable solids, nothing is known about the effect with materials whose stiffness lies between these extremes. Here we introduce a new phenomenon that occurs with vaporizable soft solids--the elastic Leidenfrost effect. By dropping hydrogel spheres onto hot surfaces we find that, rather than hovering, they energetically bounce several times their diameter for minutes at a time. With high-speed video during a single impact, we uncover high-frequency microscopic gap dynamics at the sphere/substrate interface. We show how these otherwise-hidden agitations constitute work cycles that harvest mechanical energy from the vapour and sustain the bouncing. Our findings suggest a new strategy for injecting mechanical energy into a widely used class of soft materials, with potential relevance to fields such as active matter, soft robotics and microfluidics.

Query-Based Outlier Detection in Heterogeneous Information Networks.

PubMed

Kuck, Jonathan; Zhuang, Honglei; Yan, Xifeng; Cam, Hasan; Han, Jiawei

2015-03-01

Outlier or anomaly detection in large data sets is a fundamental task in data science, with broad applications. However, in real data sets with high-dimensional space, most outliers are hidden in certain dimensional combinations and are relative to a user's search space and interest. It is often more effective to give power to users and allow them to specify outlier queries flexibly, and the system will then process such mining queries efficiently. In this study, we introduce the concept of query-based outlier in heterogeneous information networks, design a query language to facilitate users to specify such queries flexibly, define a good outlier measure in heterogeneous networks, and study how to process outlier queries efficiently in large data sets. Our experiments on real data sets show that following such a methodology, interesting outliers can be defined and uncovered flexibly and effectively in large heterogeneous networks.

Query-Based Outlier Detection in Heterogeneous Information Networks

PubMed Central

Kuck, Jonathan; Zhuang, Honglei; Yan, Xifeng; Cam, Hasan; Han, Jiawei

2015-01-01

Outlier or anomaly detection in large data sets is a fundamental task in data science, with broad applications. However, in real data sets with high-dimensional space, most outliers are hidden in certain dimensional combinations and are relative to a user’s search space and interest. It is often more effective to give power to users and allow them to specify outlier queries flexibly, and the system will then process such mining queries efficiently. In this study, we introduce the concept of query-based outlier in heterogeneous information networks, design a query language to facilitate users to specify such queries flexibly, define a good outlier measure in heterogeneous networks, and study how to process outlier queries efficiently in large data sets. Our experiments on real data sets show that following such a methodology, interesting outliers can be defined and uncovered flexibly and effectively in large heterogeneous networks. PMID:27064397

Uncovering temporal structure in hippocampal output patterns

PubMed Central

de Jong, Laurel Watkins; Pfeiffer, Brad E; Foster, David

2018-01-01

Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Replay is observed during hippocampal sharp-wave-ripple-associated population burst events (PBEs) and is critical for consolidation and recall-guided behaviors. PBE activity has historically been analyzed as a phenomenon subordinate to the place code. Here, we use hidden Markov models to study PBEs observed in rats during exploration of both linear mazes and open fields. We demonstrate that estimated models are consistent with a spatial map of the environment, and can even decode animals’ positions during behavior. Moreover, we demonstrate the model can be used to identify hippocampal replay without recourse to the place code, using only PBE model congruence. These results suggest that downstream regions may rely on PBEs to provide a substrate for memory. Additionally, by forming models independent of animal behavior, we lay the groundwork for studies of non-spatial memory. PMID:29869611

Uncovering temporal structure in hippocampal output patterns.

PubMed

Maboudi, Kourosh; Ackermann, Etienne; de Jong, Laurel Watkins; Pfeiffer, Brad E; Foster, David; Diba, Kamran; Kemere, Caleb

2018-06-05

Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Replay is observed during hippocampal sharp-wave-ripple-associated population burst events (PBEs) and is critical for consolidation and recall-guided behaviors. PBE activity has historically been analyzed as a phenomenon subordinate to the place code. Here, we use hidden Markov models to study PBEs observed in rats during exploration of both linear mazes and open fields. We demonstrate that estimated models are consistent with a spatial map of the environment, and can even decode animals' positions during behavior. Moreover, we demonstrate the model can be used to identify hippocampal replay without recourse to the place code, using only PBE model congruence. These results suggest that downstream regions may rely on PBEs to provide a substrate for memory. Additionally, by forming models independent of animal behavior, we lay the groundwork for studies of non-spatial memory. © 2018, Maboudi et al.

Improving Thin Bed Identification in Sarawak Basin Field using Short Time Fourier Transform Half Cepstrum (STFTHC) method

NASA Astrophysics Data System (ADS)

Nizarul, O.; Hermana, M.; Bashir, Y.; Ghosh, D. P.

2016-02-01

In delineating complex subsurface geological feature, broad band of frequencies are needed to unveil the often hidden features of hydrocarbon basin such as thin bedding. The ability to resolve thin geological horizon on seismic data is recognized to be a fundamental importance for hydrocarbon exploration, seismic interpretation and reserve prediction. For thin bedding, high frequency content is needed to enable tuning, which can be done by applying the band width extension technique. This paper shows an application of Short Time Fourier Transform Half Cepstrum (STFTHC) method, a frequency bandwidth expansion technique for non-stationary seismic signal in increasing the temporal resolution to uncover thin beds and improve characterization of the basin. A wedge model and synthetic seismic data is used to quantify the algorithm as well as real data from Sarawak basin were used to show the effectiveness of this method in enhancing the resolution.

Big Data Analytics for Genomic Medicine.

PubMed

He, Karen Y; Ge, Dongliang; He, Max M

2017-02-15

Genomic medicine attempts to build individualized strategies for diagnostic or therapeutic decision-making by utilizing patients' genomic information. Big Data analytics uncovers hidden patterns, unknown correlations, and other insights through examining large-scale various data sets. While integration and manipulation of diverse genomic data and comprehensive electronic health records (EHRs) on a Big Data infrastructure exhibit challenges, they also provide a feasible opportunity to develop an efficient and effective approach to identify clinically actionable genetic variants for individualized diagnosis and therapy. In this paper, we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. We introduce possible solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data to implement genomic medicine. Additionally, we also present a practical Big Data toolset for identifying clinically actionable genetic variants using high-throughput NGS data and EHRs.

Understanding Road Usage Patterns in Urban Areas

NASA Astrophysics Data System (ADS)

Wang, Pu; Hunter, Timothy; Bayen, Alexandre M.; Schechtner, Katja; González, Marta C.

2012-12-01

In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a network of road usage by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.

Genetics of inherited cardiocutaneous syndromes: a review

PubMed Central

Bardawil, Tara; Khalil, Samar; Bergqvist, Christina; Abbas, Ossama; Kibbi, Abdul Ghani; Bitar, Fadi; Nemer, Georges; Kurban, Mazen

2016-01-01

The life of a human being originates as a single cell which, under the influence of certain factors, divides sequentially into multiple cells that subsequently become committed to develop and differentiate into the different structures and organs. Alterations occurring early on in the development process may lead to fetal demise in utero. Conversely, abnormalities at later stages may result in structural and/or functional abnormalities of varying severities. The cardiovascular system and skin share certain developmental and structural factors; therefore, it is not surprising to find several inherited syndromes with both cardiac and skin manifestations. Here, we will review the overlapping pathways in the development of the skin and heart, as well as the resulting syndromes. We will also highlight several cutaneous clues that may help physicians screen and uncover cardiac anomalies that may be otherwise hidden and result in sudden cardiac death. PMID:27933191

Deriving Earth Science Data Analytics Tools/Techniques Requirements

NASA Astrophysics Data System (ADS)

Kempler, S. J.

2015-12-01

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists. Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics tools/techniques requirements that would support specific ESDA type goals. Representative existing data analytics tools/techniques relevant to ESDA will also be addressed.

Deriving Earth Science Data Analytics Requirements

NASA Technical Reports Server (NTRS)

Kempler, Steven J.

2015-01-01

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists.Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics toolstechniques requirements that would support specific ESDA type goals. Representative existing data analytics toolstechniques relevant to ESDA will also be addressed.

A deep intronic CLRN1 (USH3A) founder mutation generates an aberrant exon and underlies severe Usher syndrome on the Arabian Peninsula.

PubMed

Khan, Arif O; Becirovic, Elvir; Betz, Christian; Neuhaus, Christine; Altmüller, Janine; Maria Riedmayr, Lisa; Motameny, Susanne; Nürnberg, Gudrun; Nürnberg, Peter; Bolz, Hanno J

2017-05-03

Deafblindness is mostly due to Usher syndrome caused by recessive mutations in the known genes. Mutation-negative patients therefore either have distinct diseases, mutations in yet unknown Usher genes or in extra-exonic parts of the known genes - to date a largely unexplored possibility. In a consanguineous Saudi family segregating Usher syndrome type 1 (USH1), NGS of genes for Usher syndrome, deafness and retinal dystrophy and subsequent whole-exome sequencing each failed to identify a mutation. Genome-wide linkage analysis revealed two small candidate regions on chromosome 3, one containing the USH3A gene CLRN1, which has never been associated with Usher syndrome in Saudi Arabia. Whole-genome sequencing (WGS) identified a homozygous deep intronic mutation, c.254-649T > G, predicted to generate a novel donor splice site. CLRN1 minigene-based analysis confirmed the splicing of an aberrant exon due to usage of this novel motif, resulting in a frameshift and a premature termination codon. We identified this mutation in an additional two of seven unrelated mutation-negative Saudi USH1 patients. Locus-specific markers indicated that c.254-649T > G CLRN1 represents a founder allele that may significantly contribute to deafblindness in this population. Our finding underlines the potential of WGS to uncover atypically localized, hidden mutations in patients who lack exonic mutations in the known disease genes.

Chemometric analysis of soil pollution data using the Tucker N-way method.

PubMed

Stanimirova, I; Zehl, K; Massart, D L; Vander Heyden, Y; Einax, J W

2006-06-01

N-way methods, particularly the Tucker method, are often the methods of choice when analyzing data sets arranged in three- (or higher) way arrays, which is the case for most environmental data sets. In the future, applying N-way methods will become an increasingly popular way to uncover hidden information in complex data sets. The reason for this is that classical two-way approaches such as principal component analysis are not as good at revealing the complex relationships present in data sets. This study describes in detail the application of a chemometric N-way approach, namely the Tucker method, in order to evaluate the level of pollution in soil from a contaminated site. The analyzed soil data set was five-way in nature. The samples were collected at different depths (way 1) from two locations (way 2) and the levels of thirteen metals (way 3) were analyzed using a four-step-sequential extraction procedure (way 4), allowing detailed information to be obtained about the bioavailability and activity of the different binding forms of the metals. Furthermore, the measurements were performed under two conditions (way 5), inert and non-inert. The preferred Tucker model of definite complexity showed that there was no significant difference in measurements analyzed under inert or non-inert conditions. It also allowed two depth horizons, characterized by different accumulation pathways, to be distinguished, and it allowed the relationships between chemical elements and their biological activities and mobilities in the soil to be described in detail.

Coupling of Action-Perception Brain Networks during Musical Pulse Processing: Evidence from Region-of-Interest-Based Independent Component Analysis.

PubMed

Burunat, Iballa; Tsatsishvili, Valeri; Brattico, Elvira; Toiviainen, Petri

2017-01-01

Our sense of rhythm relies on orchestrated activity of several cerebral and cerebellar structures. Although functional connectivity studies have advanced our understanding of rhythm perception, this phenomenon has not been sufficiently studied as a function of musical training and beyond the General Linear Model (GLM) approach. Here, we studied pulse clarity processing during naturalistic music listening using a data-driven approach (independent component analysis; ICA). Participants' (18 musicians and 18 controls) functional magnetic resonance imaging (fMRI) responses were acquired while listening to music. A targeted region of interest (ROI) related to pulse clarity processing was defined, comprising auditory, somatomotor, basal ganglia, and cerebellar areas. The ICA decomposition was performed under different model orders, i.e., under a varying number of assumed independent sources, to avoid relying on prior model order assumptions. The components best predicted by a measure of the pulse clarity of the music, extracted computationally from the musical stimulus, were identified. Their corresponding spatial maps uncovered a network of auditory (perception) and motor (action) areas in an excitatory-inhibitory relationship at lower model orders, while mainly constrained to the auditory areas at higher model orders. Results revealed (a) a strengthened functional integration of action-perception networks associated with pulse clarity perception hidden from GLM analyses, and (b) group differences between musicians and non-musicians in pulse clarity processing, suggesting lifelong musical training as an important factor that may influence beat processing.

Improving the Quality of Alerts and Predicting Intruder's Next Goal with Hidden Colored Petri-Net

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

Yu, Dong; Frincke, Deb A.

2006-06-22

Intrusion detection systems (IDS) often provide poor quality alerts, which are insufficient to support rapid identification of ongoing attacks or predict an intruder’s next likely goal. In this paper, we propose a novel approach to alert post-processing and correlation, the Hidden Colored Petri-Net (HCPN). Different from most other alert correlation methods, our approach treats the alert correlation problem as an inference problem rather than a filter problem. Our approach assumes that the intruder’s actions are unknown to the IDS and can be inferred only from the alerts generated by the IDS sensors. HCPN can describe the relationship between different stepsmore » carried out by intruders, model observations (alerts) and transitions (actions) separately, and associate each token element (system state) with a probability (or confidence). The model is an extension to Colored Petri-Net (CPN) .It is so called “hidden” because the transitions (actions) are not directly observable but can be inferred by looking through the observations (alerts). These features make HCPN especially suitable for discovering intruders’ actions from their partial observations (alerts,) and predicting intruders’ next goal. Our experiments on DARPA evaluation datasets and the attack scenarios from the Grand Challenge Problem (GCP) show that HCPN has promise as a way to reducing false positives and negatives, predicting intruder’s next possible action, uncovering intruders’ intrusion strategies after the attack scenario has happened, and providing confidence scores.« less

Global hidden harvest of freshwater fish revealed by household surveys.

PubMed

Fluet-Chouinard, Etienne; Funge-Smith, Simon; McIntyre, Peter B

2018-06-18

Consumption of wild-caught freshwater fish is concentrated in low-income countries, where it makes a critical contribution to food security and livelihoods. Underestimation of inland harvests in official statistics has long been suspected due to unmonitored subsistence fisheries. To overcome the lack of data from extensive small-scale harvests, we used household consumption surveys to estimate freshwater fish catches in 42 low- and middle-income countries between 1997 and 2014. After accounting for trade and aquaculture, these countries collectively consumed 3.6 MT (CI, 1.5-5.8) more wild-caught freshwater fish than officially reported, reflecting a net underreporting of 64.8% (CI, 27.1-103.9%). Individual countries were more likely to underestimate ( n = 31) than overestimate ( n = 11) catches, despite conservative assumptions in our calculations. Extrapolating our findings suggests that the global inland catch reported as 10.3 MT in 2008 was more likely 16.6 MT (CI, 2.3-30.9), which accords with recent independent predictions for rivers and lakes. In human terms, these hidden harvests are equivalent to the total animal protein consumption of 36.9 (CI, 30.8-43.4) million people, including many who rely upon wild fish to achieve even minimal protein intake. The widespread underreporting uncovered by household consumption surveys indicates that inland fisheries contribute far more to global food security than has been recognized previously. Our findings also amplify concerns about the sustainability of intensive fishery exploitation as degradation of rivers, lakes, and wetlands continues apace.

Hidden flows and waste processing--an analysis of illustrative futures.

PubMed

Schiller, F; Raffield, T; Angus, A; Herben, M; Young, P J; Longhurst, P J; Pollard, S J T

2010-12-14

An existing materials flow model is adapted (using Excel and AMBER model platforms) to account for waste and hidden material flows within a domestic environment. Supported by national waste data, the implications of legislative change, domestic resource depletion and waste technology advances are explored. The revised methodology offers additional functionality for economic parameters that influence waste generation and disposal. We explore this accounting system under hypothetical future waste and resource management scenarios, illustrating the utility of the model. A sensitivity analysis confirms that imports, domestic extraction and their associated hidden flows impact mostly on waste generation. The model offers enhanced utility for policy and decision makers with regard to economic mass balance and strategic waste flows, and may promote further discussion about waste technology choice in the context of reducing carbon budgets.

Characteristics of Hidden Status Among Users of Crack, Powder Cocaine, and Heroin in Central Harlem

PubMed Central

Davis, W. Rees; Johnson, Bruce D.; Liberty, Hilary James; Randolph, Doris D.

2007-01-01

This article analyzes hidden status among crack, powder cocaine, and heroin users and setters, in contrast to more accessible users/sellers. Several sampling strategies acquired 657 users (N=559) and sellers (N=98). Indicators of hidden status were those who (1) paid rent in full in the last 30 days, (2) used nonstreet drug procurement. (3) had legal jobs, and (4) earned $1,000 or more in legal income in the last 30 days. Nearly half had at least one indicator: approximately 16% of users/sellers had two to four indicators. In logistic regression analyses, those who had not panhandled in the last 30 days, those who had used powder cocaine in the last 30 days, and those never arrested were the most likely to have hidden status, whether the analysis predicted those having any indicators or those having two to four indicators. The four indicators begin to operationally define hidden status among users of cocaine and heroin. PMID:17710217

Communication and the Socialization of Dance Students: An Analysis of the Hidden Curriculum in a Residential Arts School.

ERIC Educational Resources Information Center

Oseroff-Varnell, Dee

1998-01-01

Examines the socialization process of newcomers to a residential high school for performing arts. Finds that communication appeared particularly useful in reducing affective uncertainty and providing students with reassurance and support. Analyzes the hidden curriculum of this school, identifying four aspects: control versus freedom, inclusion…

Functional Evaluation of Hidden Figures Object Analysis in Children with Autistic Disorder

ERIC Educational Resources Information Center

Malisza, Krisztina L.; Clancy, Christine; Shiloff, Deborah; Foreman, Derek; Holden, Jeanette; Jones, Cheryl; Paulson, K.; Summers, Randy; Yu, C. T.; Chudley, Albert E.

2011-01-01

Functional magnetic resonance imaging (fMRI) during performance of a hidden figures task (HFT) was used to compare differences in brain function in children diagnosed with autism disorder (AD) compared to children with attention-deficit/hyperactivity disorder (ADHD) and typical controls (TC). Overall greater functional MRI activity was observed in…

A Bourdieusian Analysis of Cultural Reproduction: Socialisation and the "Hidden Curriculum" in Professional Football

ERIC Educational Resources Information Center

Cushion, Christopher J.; Jones, Robyn L.

2014-01-01

This article draws on the theoretical concepts of Pierre Bourdieu to provide an explanatory account of how socialisation and the hidden curriculum within coaching practice contribute toward the formation of social identities and powerful schemes of internalised dispositions. Drawing on a 10 month ethnography within professional football, the…

Intelligent data analysis to model and understand live cell time-lapse sequences.

PubMed

Paterson, Allan; Ashtari, M; Ribé, D; Stenbeck, G; Tucker, A

2012-01-01

One important aspect of cellular function, which is at the basis of tissue homeostasis, is the delivery of proteins to their correct destinations. Significant advances in live cell microscopy have allowed tracking of these pathways by following the dynamics of fluorescently labelled proteins in living cells. This paper explores intelligent data analysis techniques to model the dynamic behavior of proteins in living cells as well as to classify different experimental conditions. We use a combination of decision tree classification and hidden Markov models. In particular, we introduce a novel approach to "align" hidden Markov models so that hidden states from different models can be cross-compared. Our models capture the dynamics of two experimental conditions accurately with a stable hidden state for control data and multiple (less stable) states for the experimental data recapitulating the behaviour of particle trajectories within live cell time-lapse data. In addition to having successfully developed an automated framework for the classification of protein transport dynamics from live cell time-lapse data our model allows us to understand the dynamics of a complex trafficking pathway in living cells in culture.

Multivariate analysis for scanning tunneling spectroscopy data

NASA Astrophysics Data System (ADS)

Yamanishi, Junsuke; Iwase, Shigeru; Ishida, Nobuyuki; Fujita, Daisuke

2018-01-01

We applied principal component analysis (PCA) to two-dimensional tunneling spectroscopy (2DTS) data obtained on a Si(111)-(7 × 7) surface to explore the effectiveness of multivariate analysis for interpreting 2DTS data. We demonstrated that several components that originated mainly from specific atoms at the Si(111)-(7 × 7) surface can be extracted by PCA. Furthermore, we showed that hidden components in the tunneling spectra can be decomposed (peak separation), which is difficult to achieve with normal 2DTS analysis without the support of theoretical calculations. Our analysis showed that multivariate analysis can be an additional powerful way to analyze 2DTS data and extract hidden information from a large amount of spectroscopic data.

State Space Model with hidden variables for reconstruction of gene regulatory networks.

PubMed

Wu, Xi; Li, Peng; Wang, Nan; Gong, Ping; Perkins, Edward J; Deng, Youping; Zhang, Chaoyang

2011-01-01

State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN. True GRNs and synthetic gene expression datasets were generated using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks. Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN. This study provides useful information in handling the hidden variables and improving the inference precision.

Improved Extreme Learning Machine based on the Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Cui, Licheng; Zhai, Huawei; Wang, Benchao; Qu, Zengtang

2018-03-01

Extreme learning machine and its improved ones is weak in some points, such as computing complex, learning error and so on. After deeply analyzing, referencing the importance of hidden nodes in SVM, an novel analyzing method of the sensitivity is proposed which meets people’s cognitive habits. Based on these, an improved ELM is proposed, it could remove hidden nodes before meeting the learning error, and it can efficiently manage the number of hidden nodes, so as to improve the its performance. After comparing tests, it is better in learning time, accuracy and so on.

Adult-acquired hidden penis in obese patients: a critical survey of the literature.

PubMed

Cavayero, Chase T; Cooper, Meghan A; Harlin, Stephen L

2015-03-01

Hidden penis is anatomically defined by a lack of firm attachments of the skin and dartos fascia to the underlying Buck fascia. To critically appraise the research evidence that could support the most effective surgical techniques for adult-acquired hidden penis in obese patients. Studies investigating patients with a diagnosis of hidden penis were identified. Of these studies, only those with adult patients classified as overweight or obese (body mass index >25) were included in the review. Three reviewers examined the abstracts of the studies identified in the initial Medline search, and abstracts considered potentially relevant underwent full-text review. Studies that included patients with congenital, iatrogenic (eg, circumcision issues or aesthetic genital surgery), or traumatic causes of hidden penis were excluded. Studies that did not define the diagnostic criteria for hidden penis were excluded to minimize the risk of definition bias. The quality of evidence for each study was determined after considering the following sources of bias: method of allocation to study groups, data analysis, presence of baseline differences between groups, objectivity of outcome, and completeness of follow-up. Using these criteria, studies were then graded as high, moderate, or low in quality. Seven studies with a total of 119 patients met the inclusion criteria. All but 1 of the studies were nonrandomized. One study provided a clear presentation of results and appropriate statistical analysis. Six studies accounted for individual-based differences, and 1 study failed to account for baseline differences altogether. Four studies addressed follow-up. One study was of high quality, 2 were of moderate quality, and 4 were of low quality. Building a clinical practice guideline for the surgical management of hidden penis has proven difficult because of a lack of high-quality, statistically significant data in the research synthesis. The authors elucidate the challenges and epitomize the collective wisdom of surgeons who have investigated this problem and emphasize the need for rigorous evaluative studies. © 2015 The American Osteopathic Association.

Quantification of Operational Risk Using A Data Mining

NASA Technical Reports Server (NTRS)

Perera, J. Sebastian

1999-01-01

What is Data Mining? - Data Mining is the process of finding actionable information hidden in raw data. - Data Mining helps find hidden patterns, trends, and important relationships often buried in a sea of data - Typically, automated software tools based on advanced statistical analysis and data modeling technology can be utilized to automate the data mining process

Resilience Among Students at the Basic Enlisted Submarine School

DTIC Science & Technology

2016-12-01

reported resilience. The Hayes’ Macro in the Statistical Package for the Social Sciences (SSPS) was used to uncover factors relevant to mediation analysis... Statistical Package for the Social Sciences (SPSS) was used to uncover factors relevant to mediation analysis. Findings suggest that the encouragement of...to Stressful Experiences Scale RTC Recruit Training Command SPSS Statistical Package for the Social Sciences SS Social Support SWB Subjective Well

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

PubMed Central

Robertson, Colin; Sawford, Kate; Gunawardana, Walimunige S. N.; Nelson, Trisalyn A.; Nathoo, Farouk; Stephen, Craig

2011-01-01

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines. PMID:21949763

Hidden symmetries of Eisenhart-Duval lift metrics and the Dirac equation with flux

NASA Astrophysics Data System (ADS)

Cariglia, Marco

2012-10-01

The Eisenhart-Duval lift allows embedding nonrelativistic theories into a Lorentzian geometrical setting. In this paper we study the lift from the point of view of the Dirac equation and its hidden symmetries. We show that dimensional reduction of the Dirac equation for the Eisenhart-Duval metric in general gives rise to the nonrelativistic Lévy-Leblond equation in lower dimension. We study in detail in which specific cases the lower dimensional limit is given by the Dirac equation, with scalar and vector flux, and the relation between lift, reduction, and the hidden symmetries of the Dirac equation. While there is a precise correspondence in the case of the lower dimensional massive Dirac equation with no flux, we find that for generic fluxes it is not possible to lift or reduce all solutions and hidden symmetries. As a by-product of this analysis, we construct new Lorentzian metrics with special tensors by lifting Killing-Yano and closed conformal Killing-Yano tensors and describe the general conformal Killing-Yano tensor of the Eisenhart-Duval lift metrics in terms of lower dimensional forms. Last, we show how, by dimensionally reducing the higher dimensional operators of the massless Dirac equation that are associated with shared hidden symmetries, it is possible to recover hidden symmetry operators for the Dirac equation with flux.

How hidden are hidden processes? A primer on crypticity and entropy convergence

NASA Astrophysics Data System (ADS)

Mahoney, John R.; Ellison, Christopher J.; James, Ryan G.; Crutchfield, James P.

2011-09-01

We investigate a stationary process's crypticity—a measure of the difference between its hidden state information and its observed information—using the causal states of computational mechanics. Here, we motivate crypticity and cryptic order as physically meaningful quantities that monitor how hidden a hidden process is. This is done by recasting previous results on the convergence of block entropy and block-state entropy in a geometric setting, one that is more intuitive and that leads to a number of new results. For example, we connect crypticity to how an observer synchronizes to a process. We show that the block-causal-state entropy is a convex function of block length. We give a complete analysis of spin chains. We present a classification scheme that surveys stationary processes in terms of their possible cryptic and Markov orders. We illustrate related entropy convergence behaviors using a new form of foliated information diagram. Finally, along the way, we provide a variety of interpretations of crypticity and cryptic order to establish their naturalness and pervasiveness. This is also a first step in developing applications in spatially extended and network dynamical systems.

Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations*

PubMed Central

Feehan, Dennis M.; Salganik, Matthew J.

2018-01-01

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new estimator can be used when data are collected via complex sample designs and from incomplete sampling frames. However, the generalized scale-up estimator also requires data from two samples: one from the frame population and one from the hidden population. In some situations these data from the hidden population can be collected by adding a small number of questions to already planned studies. For other situations, we develop interpretable adjustment factors that can be applied to the basic scale-up estimator. We conclude with practical recommendations for the design and analysis of future studies. PMID:29375167

Leadership Aspects of Hidden Curriculum Students Practice in Nigerian Universities: A Preview of Students' Union Government Contributions in University Governance

ERIC Educational Resources Information Center

Emesini, Nnenna Orieoma

2016-01-01

The paper examined the leadership aspect of Hidden Curriculum that students practice in Nigerian Universities and their contributions to university governance. Four research questions guided the study and Ex-Post-Facto Method was adopted as the design. Unstructured interviews with staff/students officials cum critical analysis of Students' Union…

"The School, Whose Place Is This"? The Deep Structures of the Hidden Curriculum in Indigenous Education in Bolivia

ERIC Educational Resources Information Center

Regalsky, Pablo; Laurie, Nina

2007-01-01

In this paper we examine state and indigenous education in Bolivia. Focusing on debates about the hidden curriculum, we conceptualize the school as a political space where tensions between the overlapping jurisdictional powers of the hispanicizing state and indigenous authorities are played out. Our analysis of these tensions highlights the…

Political Life in the Hidden Curriculum: Does It Make a Difference?

ERIC Educational Resources Information Center

Ehman, Lee H.; Gillespie, Judith A.

The research reported here is an attempt to explore the attitudes of students in high schools and to take a look at the hidden curriculum and its political dimensions. The analysis is divided into an exploration and categorization of different types of schools, a definition of different kinds of attitudes and behavior on the part of students, and…

Multivariate longitudinal data analysis with mixed effects hidden Markov models.

PubMed

Raffa, Jesse D; Dubin, Joel A

2015-09-01

Multiple longitudinal responses are often collected as a means to capture relevant features of the true outcome of interest, which is often hidden and not directly measurable. We outline an approach which models these multivariate longitudinal responses as generated from a hidden disease process. We propose a class of models which uses a hidden Markov model with separate but correlated random effects between multiple longitudinal responses. This approach was motivated by a smoking cessation clinical trial, where a bivariate longitudinal response involving both a continuous and a binomial response was collected for each participant to monitor smoking behavior. A Bayesian method using Markov chain Monte Carlo is used. Comparison of separate univariate response models to the bivariate response models was undertaken. Our methods are demonstrated on the smoking cessation clinical trial dataset, and properties of our approach are examined through extensive simulation studies. © 2015, The International Biometric Society.

New findings on object permanence: A developmental difference between two types of occlusion

PubMed Central

Moore, M. Keith; Meltzoff, Andrew N.

2013-01-01

Manual search for totally occluded objects was investigated in 10-, 12- and 14-month-old infants. Infants responded to two types of total hiding in different ways, supporting the inference that object permanence is not a once-and-for-all attainment. Occlusion of an object by movement of a screen over it was solved at an earlier age than occlusion in which an object was carried under the screen. This dissociation was not explained by motivation, motor skill or means–ends coordination, because for both tasks the same object was hidden in the same place under the same screen and required the same uncovering response. This dissociation generalized across an experimentally manipulated change in recovery means—infants removed cloths while seated at a table in Expt 1 and were required to crawl through 3-D space to displace semi-rigid pillows in Expt 2. Further analysis revealed that emotional response varied as a function of hiding, suggesting an affective correlate of infant cognition. There are four empirical findings to account for: developmental change, task dissociation, generalization of the effects across recovery means, and emotional reactions. An identity-development theory is proposed explaining these findings in terms of infants’ understanding of object identity and the developmental relationship between object identity and object permanence. Object identity is seen as a necessary precursor to the development of object permanence. PMID:25364086

New findings on object permanence: A developmental difference between two types of occlusion.

PubMed

Moore, M Keith; Meltzoff, Andrew N

1999-11-01

Manual search for totally occluded objects was investigated in 10-, 12- and 14-month-old infants. Infants responded to two types of total hiding in different ways, supporting the inference that object permanence is not a once-and-for-all attainment. Occlusion of an object by movement of a screen over it was solved at an earlier age than occlusion in which an object was carried under the screen. This dissociation was not explained by motivation, motor skill or means-ends coordination, because for both tasks the same object was hidden in the same place under the same screen and required the same uncovering response. This dissociation generalized across an experimentally manipulated change in recovery means-infants removed cloths while seated at a table in Expt 1 and were required to crawl through 3-D space to displace semi-rigid pillows in Expt 2. Further analysis revealed that emotional response varied as a function of hiding, suggesting an affective correlate of infant cognition. There are four empirical findings to account for: developmental change, task dissociation, generalization of the effects across recovery means, and emotional reactions. An identity-development theory is proposed explaining these findings in terms of infants' understanding of object identity and the developmental relationship between object identity and object permanence. Object identity is seen as a necessary precursor to the development of object permanence.

Long noncoding RNAs responsive to Fusarium oxysporum infection in Arabidopsis thaliana.

PubMed

Zhu, Qian-Hao; Stephen, Stuart; Taylor, Jennifer; Helliwell, Chris A; Wang, Ming-Bo

2014-01-01

Short noncoding RNAs have been demonstrated to play important roles in regulation of gene expression and stress responses, but the repertoire and functions of long noncoding RNAs (lncRNAs) remain largely unexplored, particularly in plants. To explore the role of lncRNAs in disease resistance, we used a strand-specific RNA-sequencing approach to identify lncRNAs responsive to Fusarium oxysporum infection in Arabidopsis thaliana. Antisense transcription was found in c. 20% of the annotated A. thaliana genes. Several noncoding natural antisense transcripts responsive to F. oxysporum infection were found in genes implicated in disease defense. While the majority of the novel transcriptionally active regions (TARs) were adjacent to annotated genes and could be an extension of the annotated transcripts, 159 novel intergenic TARs, including 20 F. oxysporum-responsive lncTARs, were identified. Ten F. oxysporum-induced lncTARs were functionally characterized using T-DNA insertion or RNA-interference knockdown lines, and five were demonstrated to be related to disease development. Promoter analysis suggests that some of the F. oxysporum-induced lncTARs are direct targets of transcription factor(s) responsive to pathogen attack. Our results demonstrated that strand-specific RNA sequencing is a powerful tool for uncovering hidden levels of transcriptome and that IncRNAs are important components of the antifungal networks in A. thaliana. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Two distinct, geographically overlapping lineages of the corallimorpharian Ricordea florida (Cnidaria: Hexacorallia: Ricordeidae)

NASA Astrophysics Data System (ADS)

Torres-Pratts, H.; Lado-Insua, T.; Rhyne, A. L.; Rodríguez-Matos, L.; Schizas, N. V.

2011-06-01

We examined the genetic variation of the corallimorpharian Ricordea florida; it is distributed throughout the Caribbean region and is heavily harvested for the marine aquarium trade. Eighty-four distinct individuals of R. florida were sequenced from four geographically distant Caribbean locations (Curaçao, Florida, Guadeloupe, and Puerto Rico). Analysis of the ribosomal nuclear region (ITS1, 5.8S, ITS2) uncovered two geographically partially overlapping genetic lineages in R. florida, probably representing two cryptic species. Lineage 1 was found in Florida and Puerto Rico, and Lineage 2 was found in Florida, Puerto Rico, Guadeloupe, and Curaçao. Because of the multi-allelic nature of the ITS region, four individuals from Lineage 1 and six from Lineage 2 were cloned to evaluate the levels of hidden intra-individual variability. Pairwise genetic comparisons indicated that the levels of intra-individual and intra-lineage variability (<1%) were approximately an order of magnitude lower than the divergence (~9%) observed between the two lineages. The fishery regulations of the aquarium trade regard R. florida as one species. More refined regulations should take into account the presence of two genetic lineages, and they should be managed separately in order to preserve the long-term evolutionary potential of this corallimorpharian. The discovery of two distinct lineages in R. florida illustrates the importance of evaluating genetic variability in harvested species prior to the implementation of management policies.

Resources of learning through hidden curriculum: Iranian nursing students’ perspective

PubMed Central

Karimi, Zohreh; Ashktorab, Tahereh; Mohammadi, Eesa; Abedi, Heidarali; Zarea, Kourosh

2015-01-01

Background: Students tend to internalize and perpetuate the patterns of behavior and the values surrounding them. Review of literature showed that there are several student learning sources through the hidden curriculum, but they have not been identified in nursing yet. Hence, the purpose of this study is explanation of learning resources in the hidden curriculum in the view of baccalaureate nursing students. Materials and Methods: This qualitative study was carried out in 2012 with the participation of 32 baccalaureate nursing students in Nursing and Midwifery College of Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran by purposeful sampling strategies. Data were collected by semi-structured interviews and continued to the level of data saturation and themes’ emergence. Data analysis was performed through inductive content analysis method. Result: “Instructor as the unique learning element,” “various learning resources in the clinical setting,” and “instructive nature of the education environment” were extracted as the main themes, each of which incorporated some categories. Conclusion: Baccalaureate undergraduate nursing students learnt the hidden curriculum by the resources such as instructors, resources existing in the clinical setting, and the university campus. Therefore, more research is recommended for the identification of other resources. In order to promote positive messages and reduce the negative messages of the hidden curricula running at academic and clinical settings, nursing educators and nurses need to learn more about this issue in the nursing profession. PMID:26430684

Analyzing 7000 texts on deep brain stimulation: what do they tell us?

PubMed

Ineichen, Christian; Christen, Markus

2015-01-01

The enormous increase in numbers of scientific publications in the last decades requires quantitative methods for obtaining a better understanding of topics and developments in various fields. In this exploratory study, we investigate the emergence, trends, and connections of topics within the whole text corpus of the deep brain stimulation (DBS) literature based on more than 7000 papers (title and abstracts) published between 1991 to 2014 using a network approach. Taking the co-occurrence of basic terms that represent important topics within DBS as starting point, we outline the statistics of interconnections between DBS indications, anatomical targets, positive, and negative effects, as well as methodological, technological, and economic issues. This quantitative approach confirms known trends within the literature (e.g., regarding the emergence of psychiatric indications). The data also reflect an increased discussion about complex issues such as personality connected tightly to the ethical context, as well as an apparent focus on depression as important DBS indication, where the co-occurrence of terms related to negative effects is low both for the indication as well as the related anatomical targets. We also discuss consequences of the analysis from a bioethical perspective, i.e., how such a quantitative analysis could uncover hidden subject matters that have ethical relevance. For example, we find that hardware-related issues in DBS are far more robustly connected to an ethical context compared to impulsivity, concrete side-effects or death/suicide. Our contribution also outlines the methodology of quantitative text analysis that combines statistical approaches with expert knowledge. It thus serves as an example how innovative quantitative tools can be made useful for gaining a better understanding in the field of DBS.

Analyzing 7000 texts on deep brain stimulation: what do they tell us?

PubMed Central

Ineichen, Christian; Christen, Markus

2015-01-01

The enormous increase in numbers of scientific publications in the last decades requires quantitative methods for obtaining a better understanding of topics and developments in various fields. In this exploratory study, we investigate the emergence, trends, and connections of topics within the whole text corpus of the deep brain stimulation (DBS) literature based on more than 7000 papers (title and abstracts) published between 1991 to 2014 using a network approach. Taking the co-occurrence of basic terms that represent important topics within DBS as starting point, we outline the statistics of interconnections between DBS indications, anatomical targets, positive, and negative effects, as well as methodological, technological, and economic issues. This quantitative approach confirms known trends within the literature (e.g., regarding the emergence of psychiatric indications). The data also reflect an increased discussion about complex issues such as personality connected tightly to the ethical context, as well as an apparent focus on depression as important DBS indication, where the co-occurrence of terms related to negative effects is low both for the indication as well as the related anatomical targets. We also discuss consequences of the analysis from a bioethical perspective, i.e., how such a quantitative analysis could uncover hidden subject matters that have ethical relevance. For example, we find that hardware-related issues in DBS are far more robustly connected to an ethical context compared to impulsivity, concrete side-effects or death/suicide. Our contribution also outlines the methodology of quantitative text analysis that combines statistical approaches with expert knowledge. It thus serves as an example how innovative quantitative tools can be made useful for gaining a better understanding in the field of DBS. PMID:26578908

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

A Spectroscopic Search for White Dwarf Companions to 101 Nearby M Dwarfs

NASA Astrophysics Data System (ADS)

Bar, Ira; Vreeswijk, Paul; Gal-Yam, Avishay; Ofek, Eran O.; Nelemans, Gijs

2017-11-01

Recent studies of the stellar population in the solar neighborhood (<20 pc) suggest that there are undetected white dwarfs (WDs) in multiple systems with main-sequence companions. Detecting these hidden stars and obtaining a more complete census of nearby WDs is important for our understanding of stellar and galactic evolution, as well as the study of explosive phenomena. In an attempt to uncover these hidden WDs, we present intermediate resolution spectroscopy over the wavelength range of 3000-25000 Å of 101 nearby M dwarfs (dMs), observed with the Very Large Telescope X-Shooter spectrograph. For each star we search for a hot component superimposed on the dM spectrum. X-Shooter has excellent blue sensitivity and thus can reveal a faint hot WD despite the brightness of its red companion. Visual examination shows no clear evidence of a WD in any of the spectra. We place upper limits on the effective temperatures of WDs that may still be hiding by fitting dM templates to the spectra and modeling the WD spectra. On average our survey is sensitive to WDs hotter than about 5300 K. This suggests that the frequency of WD companions of {T}{eff}≳ 5300 {{K}} with separation of the order of ≲50 au among the local dM population is <3% at the 95% confidence level. The reduced spectra are made available via the WISeREP3 repository. Based on observations collected in service mode using the Very Large Telescope (VLT) under program IDs 095_D-0949(A) and 096_D-0963(A).

Secreted glyceraldehye-3-phosphate dehydrogenase is a multifunctional autocrine transferrin receptor for cellular iron acquisition.

PubMed

Sheokand, Navdeep; Kumar, Santosh; Malhotra, Himanshu; Tillu, Vikas; Raje, Chaaya Iyengar; Raje, Manoj

2013-06-01

The long held view is that mammalian cells obtain transferrin (Tf) bound iron utilizing specialized membrane anchored receptors. Here we report that, during increased iron demand, cells secrete the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) which enhances cellular uptake of Tf and iron. These observations could be mimicked by utilizing purified GAPDH injected into mice as well as when supplemented in culture medium of model cell lines and primary cell types that play a key role in iron metabolism. Transferrin and iron delivery was evaluated by biochemical, biophysical and imaging based assays. This mode of iron uptake is a saturable, energy dependent pathway, utilizing raft as well as non-raft domains of the cell membrane and also involves the membrane protein CD87 (uPAR). Tf internalized by this mode is also catabolized. Our research demonstrates that, even in cell types that express the known surface receptor based mechanism for transferrin uptake, more transferrin is delivered by this route which represents a hidden dimension of iron homeostasis. Iron is an essential trace metal for practically all living organisms however its acquisition presents major challenges. The current paradigm is that living organisms have developed well orchestrated and evolved mechanisms involving iron carrier molecules and their specific receptors to regulate its absorption, transport, storage and mobilization. Our research uncovers a hidden and primitive pathway of bulk iron trafficking involving a secreted receptor that is a multifunctional glycolytic enzyme that has implications in pathological conditions such as infectious diseases and cancer. Copyright © 2013 Elsevier B.V. All rights reserved.

Spontaneous Symmetry Breaking as a Basis of Particle Mass

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

Quigg, Chris; /Fermilab /CERN

2007-04-01

Electroweak theory joins electromagnetism with the weak force in a single quantum field theory, ascribing the two fundamental interactions--so different in their manifestations--to a common symmetry principle. How the electroweak gauge symmetry is hidden is one of the most urgent and challenging questions facing particle physics. The provisional answer incorporated in the ''standard model'' of particle physics was formulated in the 1960s by Higgs, by Brout & Englert, and by Guralnik, Hagen, & Kibble: The agent of electroweak symmetry breaking is an elementary scalar field whose self-interactions select a vacuum state in which the full electroweak symmetry is hidden, leavingmore » a residual phase symmetry of electromagnetism. By analogy with the Meissner effect of the superconducting phase transition, the Higgs mechanism, as it is commonly known, confers masses on the weak force carriers W{sup {+-}} and Z. It also opens the door to masses for the quarks and leptons, and shapes the world around us. It is a good story--though an incomplete story--and we do not know how much of the story is true. Experiments that explore the Fermi scale (the energy regime around 1 TeV) during the next decade will put the electroweak theory to decisive test, and may uncover new elements needed to construct a more satisfying completion of the electroweak theory. The aim of this article is to set the stage by reporting what we know and what we need to know, and to set some ''Big Questions'' that will guide our explorations.« less

Domain adaptation via transfer component analysis.

PubMed

Pan, Sinno Jialin; Tsang, Ivor W; Kwok, James T; Yang, Qiang

2011-02-01

Domain adaptation allows knowledge from a source domain to be transferred to a different but related target domain. Intuitively, discovering a good feature representation across domains is crucial. In this paper, we first propose to find such a representation through a new learning method, transfer component analysis (TCA), for domain adaptation. TCA tries to learn some transfer components across domains in a reproducing kernel Hilbert space using maximum mean miscrepancy. In the subspace spanned by these transfer components, data properties are preserved and data distributions in different domains are close to each other. As a result, with the new representations in this subspace, we can apply standard machine learning methods to train classifiers or regression models in the source domain for use in the target domain. Furthermore, in order to uncover the knowledge hidden in the relations between the data labels from the source and target domains, we extend TCA in a semisupervised learning setting, which encodes label information into transfer components learning. We call this extension semisupervised TCA. The main contribution of our work is that we propose a novel dimensionality reduction framework for reducing the distance between domains in a latent space for domain adaptation. We propose both unsupervised and semisupervised feature extraction approaches, which can dramatically reduce the distance between domain distributions by projecting data onto the learned transfer components. Finally, our approach can handle large datasets and naturally lead to out-of-sample generalization. The effectiveness and efficiency of our approach are verified by experiments on five toy datasets and two real-world applications: cross-domain indoor WiFi localization and cross-domain text classification.

Exposing the dark sector with future Z factories

NASA Astrophysics Data System (ADS)

Liu, Jia; Wang, Lian-Tao; Wang, Xiao-Ping; Xue, Wei

2018-05-01

We investigate the prospects of searching dark sector models via exotic Z -boson decay at future e+e- colliders with Giga Z and Tera Z options. Four general categories of dark sector models, Higgs portal dark matter, vector-portal dark matter, inelastic dark matter, and axionlike particles, are considered. Focusing on channels motivated by the dark sector models, we carry out a model-independent study of the sensitivities of Z factories in probing exotic decays. The limits on branching ratios of the exotic Z decay are typically O (10-6- 10-8.5) for the Giga Z and O (10-7.5- 10-11) for the Tera Z , and they are compared with the projection for the high luminosity LHC. We demonstrate that future Z factories can provide its unique and leading sensitivity and highlight the complementarity with other experiments, including the indirect and direct dark matter search limits and the existing collider limits. Future Z factories will play a leading role in uncovering the hidden sector of the Universe in the future.

[A unit for emergency psychiatry and crisis intervention--concepts, structure and initial experiences].

PubMed

Feuerlein, W; Bronisch, T; Fürmaier, A

1983-03-01

The article reports on a ward with 12 beds which has been set up for emergency cases in psychiatry or for immediate intervention in case of a crisis experienced by a patient. In the theoretical part of this article, it is explained that crisis situations are present in most of the psychiatric emergency patients. The article then goes briefly into the fundamentals of therapeutic strategy in such patients: A therapy which helps to uncover hidden conflicts, the pros and cons of therapy focussed on conflict and on supportive measures; as well as a therapy which supports and promotes the ego. This is followed by a comparison of the ward with corresponding facilities in Germany and abroad and a description of their structure, their patients and their function within a psychiatric care system. The concluding part of the article is devoted to a description of the authors' initial experiences and impressions gained during their work with the ward patients, quoting several examples.

Digitizing mass spectrometry data to explore the chemical diversity and distribution of marine cyanobacteria and algae

PubMed Central

Luzzatto-Knaan, Tal; Garg, Neha; Wang, Mingxun; Glukhov, Evgenia; Peng, Yao; Ackermann, Gail; Amir, Amnon; Duggan, Brendan M; Ryazanov, Sergey; Gerwick, Lena; Knight, Rob; Alexandrov, Theodore; Bandeira, Nuno; Gerwick, William H; Dorrestein, Pieter C

2017-01-01

Natural product screening programs have uncovered molecules from diverse natural sources with various biological activities and unique structures. However, much is yet underexplored and additional information is hidden in these exceptional collections. We applied untargeted mass spectrometry approaches to capture the chemical space and dispersal patterns of metabolites from an in-house library of marine cyanobacterial and algal collections. Remarkably, 86% of the metabolomics signals detected were not found in other available datasets of similar nature, supporting the hypothesis that marine cyanobacteria and algae possess distinctive metabolomes. The data were plotted onto a world map representing eight major sampling sites, and revealed potential geographic locations with high chemical diversity. We demonstrate the use of these inventories as a tool to explore the diversity and distribution of natural products. Finally, we utilized this tool to guide the isolation of a new cyclic lipopeptide, yuvalamide A, from a marine cyanobacterium. DOI: http://dx.doi.org/10.7554/eLife.24214.001 PMID:28492366

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

Self-made shelters protect spiders from predation

PubMed Central

Manicom, Carryn; Schwarzkopf, Lin; Alford, Ross A.; Schoener, Thomas W.

2008-01-01

Many animals modify their environments, apparently to reduce predation risk, but the success of such endeavors, and their impact on the density and distribution of populations, are rarely rigorously demonstrated. We staged a manipulative experiment to assess the effectiveness of self-made shelters by web spiders as protection from natural enemies. Scincid lizards were included or excluded from 21 replicated 200-m2 plots, and spiders therein were classified as exposed or sheltered, depending on whether they were uncovered in their web or hidden in cocoons, leaves/debris, or burrows. We found that exposed spiders were greatly affected by the presence of predatory scincid lizards, whereas sheltered spiders were not. More specifically, lizards, which forage close to the ground, reduced the abundance of exposed spiders by two-thirds but had no effect on the abundance of sheltered spiders. Sheltered spiders were able to avoid predation and share space with lizards, suggesting that shelter construction is a mechanism for reducing predation risk and has important population consequences. PMID:18772383

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

PubMed

Hassani-Pak, Keywan; Rawlings, Christopher

2017-06-13

Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

Two New Species of Bibloplectus Reitter (Coleoptera: Staphylinidae: Pselaphinae) from the Orlando Park Collection, Field Museum of Natural History.

PubMed

Owens, Brittany E; Carlton, Christopher E

2018-04-10

Two new species of Bibloplectus Reitter, 1881 are described from the Orlando Park Collection of Pselaphinae at the FMNH (Field Museum of Natural History, Chicago, IL, USA): Bibloplectus silvestris Owens and Carlton, new species (type locality, Urbana, IL, USA) and Bibloplectus wingi Owens and Carlton, new species (type locality, Shades State Park, IN, USA). Types of these new species were part of a series of specimens bearing unpublished Park manuscript names in both the pinned and slide collection at the FMNH. They bring the total number of species in the genus in eastern North America to twenty-three. Resolving these manuscript names adds to previous efforts to uncover elements of the hidden diversity of North American Bibloplectus from museum collections (Owens and Carlton 2016, Owens and Carlton 2017) and highlights the importance of close examination of the Orlando Park pselaphine collection as a valuable historic and taxonomic resource.

Quantum confinement effect in 6H-SiC quantum dots observed via plasmon-exciton coupling-induced defect-luminescence quenching

NASA Astrophysics Data System (ADS)

Guo, Xiaoxiao; Zhang, Yumeng; Fan, Baolu; Fan, Jiyang

2017-03-01

The quantum confinement effect is one of the crucial physical effects that discriminate a quantum material from its bulk material. It remains a mystery why the 6H-SiC quantum dots (QDs) do not exhibit an obvious quantum confinement effect. We study the photoluminescence of the coupled colloidal system of SiC QDs and Ag nanoparticles. The experimental result in conjunction with the theoretical calculation reveals that there is strong coupling between the localized electron-hole pair in the SiC QD and the localized surface plasmon in the Ag nanoparticle. It results in resonance energy transfer between them and resultant quenching of the blue surface-defect luminescence of the SiC QDs, leading to uncovering of a hidden near-UV emission band. This study shows that this emission band originates from the interband transition of the 6H-SiC QDs and it exhibits a remarkable quantum confinement effect.

Emergent Topological Phenomena in Thin Films of Pyrochlore Iridates

NASA Astrophysics Data System (ADS)

Yang, Bohm-Jung; Nagaosa, Naoto

2014-06-01

Because of the recent development of thin film and artificial superstructure growth techniques, it is possible to control the dimensionality of the system, smoothly between two and three dimensions. In this Letter we unveil the dimensional crossover of emergent topological phenomena in correlated topological materials. In particular, by focusing on the thin film of pyrochlore iridate antiferromagnets grown along the [111] direction, we demonstrate that the thin film can have a giant anomalous Hall conductance, proportional to the thickness of the film, even though there is no Hall effect in 3D bulk material. Moreover, in the case of ultrathin films, a quantized anomalous Hall conductance can be observed, despite the fact that the system is an antiferromagnet. In addition, we uncover the emergence of a new topological phase, the nontrivial topological properties of which are hidden in the bulk insulator and manifest only in thin films. This shows that the thin film of correlated topological materials is a new platform to search for unexplored novel topological phenomena.

Empowering students with the hidden curriculum.

PubMed

Neve, Hilary; Collett, Tracey

2017-11-27

The hidden curriculum (HC) refers to unscripted, ad hoc learning that occurs outside the formal, taught curriculum and can have a powerful influence on the professional development of students. While this learning may be positive, it may conflict with that taught in the formal curriculum. Medical schools take a range of steps to address these negative effects; however, the existence and nature of the concept tends to be hidden from students. Since 2007, our medical school has incorporated into its small group programme an educational activity exploring the concept of the hidden curriculum. We undertook a qualitative evaluation of our intervention, conducting a thematic analysis of students' wiki reflections about the HC. We also analysed students' responses to a short questionnaire about the educational approach used. The majority of students felt that the HC session was important and relevant. Most appeared able to identify positive and negative HC experiences and consider how these might influence their learning and development, although a few students found the concept of the HC hard to grasp. Revealing and naming the hidden curriculum can make students aware of its existence and understand its potential impact. The hidden curriculum may also be a useful tool for triggering debate about issues such as power, patient centredness, personal resilience and career stereotypes in medicine. Supporting students to think critically about HC experiences may empower them to make active choices about which messages to take on board. The hidden curriculum can have a powerful influence on the professional development of students. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

First results from GeMS/GSAOI for project SUNBIRD: Supernovae UNmasked By Infra-Red Detection

NASA Astrophysics Data System (ADS)

Kool, E. C.; Ryder, S.; Kankare, E.; Mattila, S.; Reynolds, T.; McDermid, R. M.; Pérez-Torres, M. A.; Herrero-Illana, R.; Schirmer, M.; Efstathiou, A.; Bauer, F. E.; Kotilainen, J.; Väisänen, P.; Baldwin, C.; Romero-Cañizales, C.; Alberdi, A.

2018-02-01

Core collapse supernova (CCSN) rates suffer from large uncertainties as many CCSNe exploding in regions of bright background emission and significant dust extinction remain unobserved. Such a shortfall is particularly prominent in luminous infrared galaxies (LIRGs), which have high star formation (and thus CCSN) rates and host bright and crowded nuclear regions, where large extinctions and reduced search detection efficiency likely lead to a significant fraction of CCSNe remaining undiscovered. We present the first results of project SUNBIRD (Supernovae UNmasked By Infra-Red Detection), where we aim to uncover CCSNe that otherwise would remain hidden in the complex nuclear regions of LIRGs, and in this way improve the constraints on the fraction that is missed by optical seeing-limited surveys. We observe in the near-infrared 2.15 μm Ks-band, which is less affected by dust extinction compared to the optical, using the multiconjugate adaptive optics imager GeMS/GSAOI on Gemini South, allowing us to achieve a spatial resolution that lets us probe close in to the nuclear regions. During our pilot program and subsequent first full year we have discovered three CCSNe and one candidate with projected nuclear offsets as small as 200 pc. When compared to the total sample of LIRG CCSNe discovered in the near-IR and optical, we show that our method is singularly effective in uncovering CCSNe in nuclear regions and we conclude that the majority of CCSNe exploding in LIRGs are not detected as a result of dust obscuration and poor spatial resolution.

Molecular evidence of cryptic speciation in the "cosmopolitan" excavating sponge Cliona celata (Porifera, Clionaidae).

PubMed

Xavier, J R; Rachello-Dolmen, P G; Parra-Velandia, F; Schönberg, C H L; Breeuwer, J A J; van Soest, R W M

2010-07-01

Over the past several decades molecular tools have shown an enormous potential to aid in the clarification of species boundaries in the marine realm, particularly in morphologically simple groups. In this paper we report a case of cryptic speciation in an allegedly cosmopolitan and ecologically important species-the excavating sponge Cliona celata (Clionaidae, Hadromerida). In the Northeast Atlantic and Mediterranean C. celata displays a discontinuous distribution of its putative growth stages (boring, encrusting, and massive) leading us to investigate its specific status. Phylogenetic reconstructions of mitochondrial (COI, Atp8) and nuclear (28S) gene fragments revealed levels of genetic diversity and divergence compatible with interspecific relationships. We therefore demonstrate C. celata as constituting a species complex comprised of at least four morphologically indistinct species, each showing a far more restricted distribution: two species on the Atlantic European coasts and two on the Mediterranean and adjacent Atlantic coasts (Macaronesian islands). Our results provide further confirmation that the different morphotypes do indeed constitute either growth stages or ecologically adapted phenotypes as boring and massive forms were found in two of the four uncovered species. We additionally provide an overview of the cases of cryptic speciation which have been reported to date within the Porifera, and highlight how taxonomic crypsis may confound scientific interpretation and hamper biotechnological advancement. Our work together with previous studies suggests that overconservative systematic traditions but also morphological stasis have led to genetic complexity going undetected and that a DNA-assisted taxonomy may play a key role in uncovering the hidden diversity in this taxonomic group. Copyright 2010 Elsevier Inc. All rights reserved.

Evolution of bacterial-like phosphoprotein phosphatases in photosynthetic eukaryotes features ancestral mitochondrial or archaeal origin and possible lateral gene transfer.

PubMed

Uhrig, R Glen; Kerk, David; Moorhead, Greg B

2013-12-01

Protein phosphorylation is a reversible regulatory process catalyzed by the opposing reactions of protein kinases and phosphatases, which are central to the proper functioning of the cell. Dysfunction of members in either the protein kinase or phosphatase family can have wide-ranging deleterious effects in both metazoans and plants alike. Previously, three bacterial-like phosphoprotein phosphatase classes were uncovered in eukaryotes and named according to the bacterial sequences with which they have the greatest similarity: Shewanella-like (SLP), Rhizobiales-like (RLPH), and ApaH-like (ALPH) phosphatases. Utilizing the wealth of data resulting from recently sequenced complete eukaryotic genomes, we conducted database searching by hidden Markov models, multiple sequence alignment, and phylogenetic tree inference with Bayesian and maximum likelihood methods to elucidate the pattern of evolution of eukaryotic bacterial-like phosphoprotein phosphatase sequences, which are predominantly distributed in photosynthetic eukaryotes. We uncovered a pattern of ancestral mitochondrial (SLP and RLPH) or archaeal (ALPH) gene entry into eukaryotes, supplemented by possible instances of lateral gene transfer between bacteria and eukaryotes. In addition to the previously known green algal and plant SLP1 and SLP2 protein forms, a more ancestral third form (SLP3) was found in green algae. Data from in silico subcellular localization predictions revealed class-specific differences in plants likely to result in distinct functions, and for SLP sequences, distinctive and possibly functionally significant differences between plants and nonphotosynthetic eukaryotes. Conserved carboxyl-terminal sequence motifs with class-specific patterns of residue substitutions, most prominent in photosynthetic organisms, raise the possibility of complex interactions with regulatory proteins.

Magnetic Correlations in URu2Si2 under Chemical and Hydrostatic Pressure

NASA Astrophysics Data System (ADS)

Williams, Travis; Aczel, Adam; Broholm, Collin; Buyers, William; Leao, Juscelino; Luke, Graeme; Rodriguez-Riviera, Jose; Stone, Matthew; Wilson, Murray; Yamani, Zahra

URu2Si2 has been an intense area of study for the last 30 years due to a mysterious hidden order phase that appears below T0 = 17.5 K. The hidden order phase has been shown to be extremely sensitive to perturbations, being destroyed quickly by the application of a magnetic field, hydrostatic or uniaxial pressure, and chemical doping. While attempting to understand the properties of URu2Si2, neutron scattering has found spin correlations that are intimately related to this hidden order phase and which are also suppressed with these perturbations. Here, I will outline some recent neutron scattering work to study these correlations in two exceptional cases where the hidden order phase is enhanced: hydrostatic pressure and chemical pressure using Fe- and Os-doping. In both of these cases, T0 increases before an antiferromagnetic phase emerges. By performing a careful analysis of the neutron data, we show that these two phases are much more related than had been previously appreciated. This implies that the hidden order is likely compatible with an antiferromagnetic ground state, placing constraints on the nature of the missing order parameter.

Effect of Ixekizumab Treatment on Work Productivity for Patients With Moderate-to-Severe Plaque Psoriasis: Analysis of Results From 3 Randomized Phase 3 Clinical Trials.

PubMed

Armstrong, April W; Lynde, Charles W; McBride, Sandy R; Ståhle, Mona; Edson-Heredia, Emily; Zhu, Baojin; Amato, David; Nikaï, Enkeleida; Yang, Fan Emily; Gordon, Kenneth B

2016-06-01

Therapies that reduce psoriasis symptoms may improve work productivity. To assess the effect of ixekizumab therapy on work productivity, measured by the Work Productivity and Activity Impairment-Psoriasis (WPAI-PSO). Three multicenter, randomized double-blind phase 3 trials conducted during the following periods: December 2011 through August 2014 (UNCOVER-1), May 2012 through April 2015 (UNCOVER-2), and August 2012 through July 2014 (UNCOVER-3). Adult outpatients with moderate-to-severe chronic plaque psoriasis were included. In UNCOVER-1, patients were randomized 1:1:1 to subcutaneous placebo or 80 mg ixekizumab every 2 weeks (Q2W) or every 4 weeks (Q4W) for 12 weeks; UNCOVER-2 and UNCOVER-3 also had an etanercept arm (50 mg twice weekly). Maintenance of initial ixekizumab response was evaluated in UNCOVER-1 and UNCOVER-2 during a randomized withdrawal period following week 12 through week 60. The WPAI-PSO questionnaire was administered at baseline and week 12 for all patients and at weeks 24, 36, 52, and 60 for patients in UNCOVER-1 and UNCOVER-2. Change in work productivity from baseline as measured by WPAI-PSO scores. Across trials, 5101 patients consented; 3866 were randomized (mean [SD] age, UNCOVER-1, 45.7 [12.9] y, 68.1% male; UNCOVER-2: 45.0 [13.0] y, 67.1% male; UNCOVER-3: 45.8 [13.1] y, 68.2% male). At week 12 in UNCOVER-1, the ixekizumab Q4W and ixekizumab Q2W groups showed significantly greater improvements in WPAI-PSO scores (least squares mean change from baseline [SE]) relative to placebo: absenteeism (-3.5 [0.87], P < .001; -2.6 [0.84], P = .003, respectively, vs 0.2 [0.88]), presenteeism (-18.8 [1.28], P < .001; -18.3 [1.24], P < .001, vs 0.5 [1.30]), work productivity loss (-20.6 [1.38], P < .001; -19.8 [1.33], P < .001, vs -0.8 [1.40]), and activity impairment (-24.5 [1.18], P < .001; -25.2 [1.15], P < .001, vs 0.8 [1.18]). Similar results were obtained for UNCOVER-2 and UNCOVER-3, with the exception of absenteeism with ixekizumab Q4W in UNCOVER-2. Additionally, ixekizumab-treated patients showed significantly greater improvements in WPAI-PSO scores vs etanercept-treated patients: UNCOVER-2: presenteeism, work productivity loss, activity impairment (P < .001 both doses), UNCOVER-3: activity impairment (ie, regular activities outside of work) (ixekizumab Q2W; P = .009). Improvements in WPAI-PSO scores at week 12 were sustained to at least week 60. Ixekizumab-treated patients reported short- and long-term improvements in work productivity, which could lead to reduced productivity-related cost burden in patients with psoriasis. clinicaltrials.gov Identifiers: NCT01474512, NCT01597245, NCT01646177.

Conformable covered versus uncovered self-expandable metallic stents for palliation of malignant gastroduodenal obstruction: a randomized prospective study.

PubMed

Lim, Sun Gyo; Kim, Jin Hong; Lee, Kee Myung; Shin, Sung Jae; Kim, Chan Gyoo; Kim, Kyung Ho; Kim, Ho Gak; Yang, Chang Heon

2014-07-01

A conformable self-expandable metallic stent was developed to overcome the limitation of previous self-expandable metallic stents. The aim of this study was to evaluate outcomes after placement of conformable covered and uncovered self-expandable metallic stents for palliation of malignant gastroduodenal obstruction. A single-blind, randomized, parallel-group, prospective study were conducted in 4 medical centres between March 2009 and July 2012. 134 patients with unresectable malignant gastroduodenal obstruction were assigned to a covered double-layered (n=66) or uncovered unfixed-cell braided (n=68) stent placement group. Primary analysis was performed to compare re-intervention rates between two groups. 120 patients were analysed (59 in the covered group and 61 in the uncovered group). Overall rates of re-intervention were not significantly different between the two groups: 13/59 (22.0%) in the covered group vs. 13/61 (21.3%) in the uncovered group, p=0.999. Stent migration was more frequent in the covered group than in the uncovered group (p=0.003). The tumour ingrowth rate was higher in the uncovered group than in the covered group (p=0.016). The rates of re-intervention did not significantly differ between the two stents. Conformable covered double-layered and uncovered unfixed-cell braided stents were associated with different patterns of stent malfunction. Copyright © 2014 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Uncovering Pre-Service Teacher Beliefs about Young Children: A Photographic Elicitation Methodology

ERIC Educational Resources Information Center

Stockall, Nancy; Davis, Sara

2011-01-01

This illustrative paper provides an introduction to using mixed qualitative methods of photo-elicitation, face to face interviews and semiotic analysis to uncover pre-service students' beliefs about young children. The researchers share their experience on conducting a study using photo-elicitation and engaging pre-service teachers in a discussion…

Two Tales of Time: Uncovering the Significance of Sequential Patterns among Contribution Types in Knowledge-Building Discourse

ERIC Educational Resources Information Center

Chen, Bodong; Resendes, Monica; Chai, Ching Sing; Hong, Huang-Yao

2017-01-01

As collaborative learning is actualized through evolving dialogues, temporality inevitably matters for the analysis of collaborative learning. This study attempts to uncover sequential patterns that distinguish "productive" threads of knowledge-building discourse. A database of Grade 1-6 knowledge-building discourse was first coded for…

Negotiating the Gaze and Learning the Hidden Curriculum: A Critical Race Analysis of the Embodiment of Female Students of Color at a Predominantly White Institution

ERIC Educational Resources Information Center

Esposito, Jennifer

2011-01-01

This study examines the hidden curriculum within a predominantly White institution (PWI) of higher education, and examines how women of color encountered the curriculum. I used critical race theory to explore how race and gender influenced the manner in which women of color negotiated their roles and promoted a culture of femininity that helped…

A method of hidden Markov model optimization for use with geophysical data sets

NASA Technical Reports Server (NTRS)

Granat, R. A.

2003-01-01

Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements: it should be consistent, require minimal parameter tuning, and produce scientifically meaningful results in reasonable time. We introduce a hidden Markov model (HMM)-based method for analysis of geophysical data sets that attempts to address these issues.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

PubMed

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. PMID:26080057

Extracting hidden messages in steganographic images

DOE PAGES

Quach, Tu-Thach

2014-07-17

The eventual goal of steganalytic forensic is to extract the hidden messages embedded in steganographic images. A promising technique that addresses this problem partially is steganographic payload location, an approach to reveal the message bits, but not their logical order. It works by finding modified pixels, or residuals, as an artifact of the embedding process. This technique is successful against simple least-significant bit steganography and group-parity steganography. The actual messages, however, remain hidden as no logical order can be inferred from the located payload. This paper establishes an important result addressing this shortcoming: we show that the expected mean residualsmore » contain enough information to logically order the located payload provided that the size of the payload in each stego image is not fixed. The located payload can be ordered as prescribed by the mean residuals to obtain the hidden messages without knowledge of the embedding key, exposing the vulnerability of these embedding algorithms. We provide experimental results to support our analysis.« less

Analysing the hidden curriculum: use of a cultural web

PubMed Central

Mossop, Liz; Dennick, Reg; Hammond, Richard; Robbé, Iain

2013-01-01

CONTEXT Major influences on learning about medical professionalism come from the hidden curriculum. These influences can contribute positively or negatively towards the professional enculturation of clinical students. The fact that there is no validated method for identifying the components of the hidden curriculum poses problems for educators considering professionalism. The aim of this study was to analyse whether a cultural web, adapted from a business context, might assist in the identification of elements of the hidden curriculum at a UK veterinary school. METHODS A qualitative approach was used. Seven focus groups consisting of three staff groups and four student groups were organised. Questioning was framed using the cultural web, which is a model used by business owners to assess their environment and consider how it affects their employees and customers. The focus group discussions were recorded, transcribed and analysed thematically using a combination of a priori and emergent themes. RESULTS The cultural web identified elements of the hidden curriculum for both students and staff. These included: core assumptions; routines; rituals; control systems; organisational factors; power structures, and symbols. Discussions occurred about how and where these issues may affect students’ professional identity development. CONCLUSIONS The cultural web framework functioned well to help participants identify elements of the hidden curriculum. These aspects aligned broadly with previously described factors such as role models and institutional slang. The influence of these issues on a student’s development of a professional identity requires discussion amongst faculty staff, and could be used to develop learning opportunities for students. The framework is promising for the analysis of the hidden curriculum and could be developed as an instrument for implementation in other clinical teaching environments. PMID:23323652

Feminist Approaches to Triangulation: Uncovering Subjugated Knowledge and Fostering Social Change in Mixed Methods Research

ERIC Educational Resources Information Center

Hesse-Biber, Sharlene

2012-01-01

This article explores the deployment of triangulation in the service of uncovering subjugated knowledge and promoting social change for women and other oppressed groups. Feminist approaches to mixed methods praxis create a tight link between the research problem and the research design. An analysis of selected case studies of feminist praxis…

A Phenomenological Study of Non-LGBT Students with LGBQ Parents

ERIC Educational Resources Information Center

Bourdon, Thomas

2013-01-01

There is a lack of qualitative research that has sought to uncover the lived experiences of students who identify as heterosexual/cisgender (i.e., non-LGBT) but have at least one parent who identifies as LGBQ. This phenomenological analysis aimed to uncover common themes for students who have gone through their educational journey with this…

Uncovering the Links between Prospective Teachers' Personal Responsibility, Academic Optimism, Hope, and Emotions about Teaching: A Mediation Analysis

ERIC Educational Resources Information Center

Eren, Altay

2014-01-01

Prospective teachers' sense of personal responsibility has not been examined together with their academic optimism, hope, and emotions about teaching in a single study to date. However, to consider hope, academic optimism, and emotions about teaching together with personal responsibility is important to uncover the factors affecting…

A scheme of hidden-structure attribute-based encryption with multiple authorities

NASA Astrophysics Data System (ADS)

Ling, J.; Weng, A. X.

2018-05-01

In the most of the CP-ABE schemes with hidden access structure, both all the user attributes and the key generation are managed by only one authority. The key generation efficiency will decrease as the number of user increases, and the data will encounter security issues as the only authority is attacked. We proposed a scheme of hidden-structure attribute-based encryption with multiple authorities, which introduces multiple semi-trusted attribute authorities, avoiding the threat even though one or more authorities are attacked. We also realized user revocation by managing a revocation list. Based on DBDH assumption, we proved that our scheme is of IND-CMA security. The analysis shows that our scheme improves the key generation efficiency.

Traveling the Silk Road: A Measurement of a Large Anonymous Online Marketplace

DTIC Science & Technology

2012-11-28

Silk Road, an anonymous, international online marketplace that operates as a Tor hidden service and uses Bitcoin as its exchange currency. We gather...analysis of Silk Road, an anonymous, international on- line marketplace that operates as a Tor hidden service and uses Bitcoin as its exchange currency. We...anonymity, Silk Road needs to also preserve payment anonymity. To that effect, Silk Road only supports Bitcoin (BTC, [30]) as a trading currency

Non-equilibrium thermodynamics theory of econometric source discovery for large data analysis

NASA Astrophysics Data System (ADS)

van Bergem, Rutger; Jenkins, Jeffrey; Benachenhou, Dalila; Szu, Harold

2014-05-01

Almost all consumer and firm transactions are achieved using computers and as a result gives rise to increasingly large amounts of data available for analysts. The gold standard in Economic data manipulation techniques matured during a period of limited data access, and the new Large Data Analysis (LDA) paradigm we all face may quickly obfuscate most tools used by Economists. When coupled with an increased availability of numerous unstructured, multi-modal data sets, the impending 'data tsunami' could have serious detrimental effects for Economic forecasting, analysis, and research in general. Given this reality we propose a decision-aid framework for Augmented-LDA (A-LDA) - a synergistic approach to LDA which combines traditional supervised, rule-based Machine Learning (ML) strategies to iteratively uncover hidden sources in large data, the artificial neural network (ANN) Unsupervised Learning (USL) at the minimum Helmholtz free energy for isothermal dynamic equilibrium strategies, and the Economic intuitions required to handle problems encountered when interpreting large amounts of Financial or Economic data. To make the ANN USL framework applicable to economics we define the temperature, entropy, and energy concepts in Economics from non-equilibrium molecular thermodynamics of Boltzmann viewpoint, as well as defining an information geometry, on which the ANN can operate using USL to reduce information saturation. An exemplar of such a system representation is given for firm industry equilibrium. We demonstrate the traditional ML methodology in the economics context and leverage firm financial data to explore a frontier concept known as behavioral heterogeneity. Behavioral heterogeneity on the firm level can be imagined as a firm's interactions with different types of Economic entities over time. These interactions could impose varying degrees of institutional constraints on a firm's business behavior. We specifically look at behavioral heterogeneity for firms that are operating with the label of `Going-Concern' and firms labeled according to institutional influence they may be experiencing, such as constraints on firm hiring/spending while in a Bankruptcy or a Merger procedure. Uncovering invariant features, or behavioral data metrics from observable firm data in an economy can greatly benefit the FED, World Bank, etc. We find that the ML/LDA communities can benefit from Economic intuitions just as much as Economists can benefit from generic data exploration tools. The future of successful Economic data understanding, modeling, simulation, and visualization can be amplified by new A-LDA models and approaches for new and analogous models of Economic system dynamics. The potential benefits of improved economic data analysis and real time decision aid tools are numerous for researchers, analysts, and federal agencies who all deal with increasingly large amounts of complex data to support their decision making.

A Hidden Active Site in the Potential Drug Target Mycobacterium tuberculosis dUTPase Is Accessible through Small Amplitude Protein Conformational Changes*

PubMed Central

Lopata, Anna; Leveles, Ibolya; Bendes, Ábris Ádám; Viskolcz, Béla; Vértessy, Beáta G.; Jójárt, Balázs; Tóth, Judit

2016-01-01

dUTPases catalyze the hydrolysis of dUTP into dUMP and pyrophosphate to maintain the proper nucleotide pool for DNA metabolism. Recent evidence suggests that dUTPases may also represent a selective drug target in mycobacteria because of the crucial role of these enzymes in maintaining DNA integrity. Nucleotide-hydrolyzing enzymes typically harbor a buried ligand-binding pocket at interdomain or intersubunit clefts, facilitating proper solvent shielding for the catalyzed reaction. The mechanism by which substrate binds this hidden pocket and product is released in dUTPases is unresolved because of conflicting crystallographic and spectroscopic data. We sought to resolve this conflict by using a combination of random acceleration molecular dynamics (RAMD) methodology and structural and biochemical methods to study the dUTPase from Mycobacterium tuberculosis. In particular, the RAMD approach used in this study provided invaluable insights into the nucleotide dissociation process that reconciles all previous experimental observations. Specifically, our data suggest that nucleotide binding takes place as a small stretch of amino acids transiently slides away and partially uncovers the active site. The in silico data further revealed a new dUTPase conformation on the pathway to a relatively open active site. To probe this model, we developed the Trp21 reporter and collected crystallographic, spectroscopic, and kinetic data that confirmed the interaction of Trp21 with the active site shielding C-terminal arm, suggesting that the RAMD method is effective. In summary, our computational simulations and spectroscopic results support the idea that small loop movements in dUTPase allow the shuttlingof the nucleotides between the binding pocket and the solvent. PMID:27815500

A window into the future of the Earth, hidden in the jungles of Costa Rica's volcanoes

NASA Astrophysics Data System (ADS)

Fisher, J. B.; Schwandner, F. M.; Asner, G. P.; Schimel, D.; Norby, R. J.; Keller, M.; Pavlick, R.; Braverman, A. J.; Pieri, D. C.; Diaz, J. A.; Gutierrez, M.; Duarte, E. A.; Lewicki, J. L.; Manning, C. E.; Deering, C. D.; Seibt, U.; Miller, G. R.; Drewry, D.; Chambers, J.

2017-12-01

The CO2 fertilization response of the terrestrial biosphere contributes among the largest sensitivities and uncertainties across projections of the Earth's future. The source of that uncertainty can be pinpointed to the largest fluxes in the biosphere: the tropics. Free Air CO2 Enrichment (FACE) experiments have contributed immensely to our understanding of short-term CO2 fertilization, but, outside of a small pilot study in development, have been absent in the tropics. This is largely due to numerous hurdles of not only conducting such experiments in challenging environments, but also due to the need to expand their extent considerably to encompass the enormous diversity of species-level responses, in addition to the need for multi-decadal scale responses. As such, we have remained at a critical impasse in our ability to advance understanding of the response of the tropical biosphere to increasing CO2. Recent discoveries have found a cluster of volcanoes degassing CO2 into tropical ecosystems in Costa Rica at concentrations similar to future Earth atmosphere levels. The degassing has been occurring persistently from 10s to 100s of years over 10s to 100s of square kilometers, at different levels depending on the volcano. Fortuitously, this provides a natural "experiment" across a range of conditions needed to assess a widespread and long-lived tropical ecosystem response to elevated CO2: tree species will have had time to shift in composition, traits, structure, and function. Nonetheless, due both to the challenges with assessing these changes on the ground, and heterogeneity causing problems with coarse-scale satellite remote sensing observations, this "window" into the future of the Earth has remained veiled. Here, we describe an airborne-based plan designed to uncover this gem hidden in the jungles of Costa Rica's volcanoes.

The joy at birth: an interpretive hermeneutic literature review.

PubMed

Crowther, Susan; Smythe, Elizabeth; Spence, Deb

2014-04-01

this literature review examines the experience of joy at birth and what that joy means. The premise is that the whole of the birthing experience has not been fully explicated in the literature and that something of significance remains unexplored and unspoken. It is argued that a hermeneutic phenomenological approach to reviewing literature provides unique insights and leads to deeper understandings about birth and the experience of joy that attunes at that moment. the philosophical underpinnings informed by Heidegger and Gadamer are central to this review and therefore the process of reviewing literature hermeneutically is described. Heideggerian phenomenology is used as the method to ask the questions of the literature in order that concealed and hidden experiences of joy at birth are made visible where they are gleaned from the literature. A hermeneutic lens is used to uncover relationships within the phenomenon of joy at birth and meaning. although a vast birth literature was reviewed joy at birth was often ignored, hidden or covered over. Reviewing the literature on relationships, professional presence, place of birth, birth satisfaction studies and birth as peak and spiritual experience provides glimpses of the phenomenon 'joy at birth'. it is argued that joy at birth remains largely neglected as a phenomenon worthy of consideration. Plausible interpretations are presented that suggest that joy at birth points to something significant and meaningful. Spiritual and sacred meaning is alluded to in the papers reviewed yet the majority of papers that investigate birth leave this meaning unspoken. The review highlights a need for further thinking and questioning about birth that would direct on-going investigation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Body size affects the evolution of hidden colour signals in moths.

PubMed

Kang, Changku; Zahiri, Reza; Sherratt, Thomas N

2017-08-30

Many cryptic prey have also evolved hidden contrasting colour signals which are displayed to would-be predators. Given that these hidden contrasting signals may confer additional survival benefits to the prey by startling/intimidating predators, it is unclear why they have evolved in some species, but not in others. Here, we have conducted a comparative phylogenetic analysis of the evolution of colour traits in the family Erebidae (Lepidoptera), and found that the hidden contrasting colour signals are more likely to be found in larger species. To understand why this relationship occurs, we present a general mathematical model, demonstrating that selection for a secondary defence such as deimatic display will be stronger in large species when (i) the primary defence (crypsis) is likely to fail as its body size increases and/or (ii) the secondary defence is more effective in large prey. To test the model assumptions, we conducted behavioural experiments using a robotic moth which revealed that survivorship advantages were higher against wild birds when the moth has contrasting hindwings and large size. Collectively, our results suggest that the evolutionary association between large size and hidden contrasting signals has been driven by a combination of the need for a back-up defence and its efficacy. © 2017 The Author(s).

Algorithms for Hidden Markov Models Restricted to Occurrences of Regular Expressions

PubMed Central

Tataru, Paula; Sand, Andreas; Hobolth, Asger; Mailund, Thomas; Pedersen, Christian N. S.

2013-01-01

Hidden Markov Models (HMMs) are widely used probabilistic models, particularly for annotating sequential data with an underlying hidden structure. Patterns in the annotation are often more relevant to study than the hidden structure itself. A typical HMM analysis consists of annotating the observed data using a decoding algorithm and analyzing the annotation to study patterns of interest. For example, given an HMM modeling genes in DNA sequences, the focus is on occurrences of genes in the annotation. In this paper, we define a pattern through a regular expression and present a restriction of three classical algorithms to take the number of occurrences of the pattern in the hidden sequence into account. We present a new algorithm to compute the distribution of the number of pattern occurrences, and we extend the two most widely used existing decoding algorithms to employ information from this distribution. We show experimentally that the expectation of the distribution of the number of pattern occurrences gives a highly accurate estimate, while the typical procedure can be biased in the sense that the identified number of pattern occurrences does not correspond to the true number. We furthermore show that using this distribution in the decoding algorithms improves the predictive power of the model. PMID:24833225

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

PubMed

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

Mal-Xtract: Hidden Code Extraction using Memory Analysis

NASA Astrophysics Data System (ADS)

Lim, Charles; Syailendra Kotualubun, Yohanes; Suryadi; Ramli, Kalamullah

2017-01-01

Software packer has been used effectively to hide the original code inside a binary executable, making it more difficult for existing signature based anti malware software to detect malicious code inside the executable. A new method of written and rewritten memory section is introduced to to detect the exact end time of unpacking routine and extract original code from packed binary executable using Memory Analysis running in an software emulated environment. Our experiment results show that at least 97% of the original code from the various binary executable packed with different software packers could be extracted. The proposed method has also been successfully extracted hidden code from recent malware family samples.

"We are all there silently coping." The hidden experiences of parents of adults with Asperger syndrome.

PubMed

Griffith, Gemma M; Totsika, Vasiliki; Nash, Susie; Jones, Robert S P; Hastings, Richard P

2012-09-01

The experiences of older parents of adults with Asperger syndrome have not been explored in the research literature. Four families who had middle-aged offspring with Asperger syndrome were interviewed (3 mothers and 1 couple), and the interviews were analysed using interpretative phenomenological analysis (IPA). Six themes emerged from the analysis: (a) providers of "hidden" support, (b) role of advocate, (c) social isolation, (d) intrafamilial relationships, (e) support for parents, and (f) future concerns. The findings of this study offer insight into the experience of parents of adult sons with Asperger syndrome. Implications for future support interventions and research are suggested.

ICP-MS as a novel detection system for quantitative element-tagged immunoassay of hidden peanut allergens in foods.

PubMed

Careri, Maria; Elviri, Lisa; Mangia, Alessandro; Mucchino, Claudio

2007-03-01

A novel ICP-MS-based ELISA immunoassay via element-tagged determination was devised for quantitative analysis of hidden allergens in food. The method was able to detect low amounts of peanuts (down to approximately 2 mg peanuts kg(-1) cereal-based matrix) by using a europium-tagged antibody. Selectivity was proved by the lack of detectable cross-reaction with a number of protein-rich raw materials.

Hidden Lineage Complexity of Glycan-Dependent HIV-1 Broadly Neutralizing Antibodies Uncovered by Digital Panning and Native-Like gp140 Trimer.

PubMed

He, Linling; Lin, Xiaohe; de Val, Natalia; Saye-Francisco, Karen L; Mann, Colin J; Augst, Ryan; Morris, Charles D; Azadnia, Parisa; Zhou, Bin; Sok, Devin; Ozorowski, Gabriel; Ward, Andrew B; Burton, Dennis R; Zhu, Jiang

2017-01-01

Germline precursors and intermediates of broadly neutralizing antibodies (bNAbs) are essential to the understanding of humoral response to HIV-1 infection and B-cell lineage vaccine design. Using a native-like gp140 trimer probe, we examined antibody libraries constructed from donor-17, the source of glycan-dependent PGT121-class bNAbs recognizing the N332 supersite on the HIV-1 envelope glycoprotein. To facilitate this analysis, a digital panning method was devised that combines biopanning of phage-displayed antibody libraries, 900 bp long-read next-generation sequencing, and heavy/light (H/L)-paired antibodyomics. In addition to single-chain variable fragments resembling the wild-type bNAbs, digital panning identified variants of PGT124 (a member of the PGT121 class) with a unique insertion in the heavy chain complementarity-determining region 1, as well as intermediates of PGT124 exhibiting notable affinity for the native-like trimer and broad HIV-1 neutralization. In a competition assay, these bNAb intermediates could effectively compete with mouse sera induced by a scaffolded BG505 gp140.681 trimer for the N332 supersite. Our study thus reveals previously unrecognized lineage complexity of the PGT121-class bNAbs and provides an array of library-derived bNAb intermediates for evaluation of immunogens containing the N332 supersite. Digital panning may prove to be a valuable tool in future studies of bNAb diversity and lineage development.

Hidden Lineage Complexity of Glycan-Dependent HIV-1 Broadly Neutralizing Antibodies Uncovered by Digital Panning and Native-Like gp140 Trimer

PubMed Central

He, Linling; Lin, Xiaohe; de Val, Natalia; Saye-Francisco, Karen L.; Mann, Colin J.; Augst, Ryan; Morris, Charles D.; Azadnia, Parisa; Zhou, Bin; Sok, Devin; Ozorowski, Gabriel; Ward, Andrew B.; Burton, Dennis R.; Zhu, Jiang

2017-01-01

Germline precursors and intermediates of broadly neutralizing antibodies (bNAbs) are essential to the understanding of humoral response to HIV-1 infection and B-cell lineage vaccine design. Using a native-like gp140 trimer probe, we examined antibody libraries constructed from donor-17, the source of glycan-dependent PGT121-class bNAbs recognizing the N332 supersite on the HIV-1 envelope glycoprotein. To facilitate this analysis, a digital panning method was devised that combines biopanning of phage-displayed antibody libraries, 900 bp long-read next-generation sequencing, and heavy/light (H/L)-paired antibodyomics. In addition to single-chain variable fragments resembling the wild-type bNAbs, digital panning identified variants of PGT124 (a member of the PGT121 class) with a unique insertion in the heavy chain complementarity-determining region 1, as well as intermediates of PGT124 exhibiting notable affinity for the native-like trimer and broad HIV-1 neutralization. In a competition assay, these bNAb intermediates could effectively compete with mouse sera induced by a scaffolded BG505 gp140.681 trimer for the N332 supersite. Our study thus reveals previously unrecognized lineage complexity of the PGT121-class bNAbs and provides an array of library-derived bNAb intermediates for evaluation of immunogens containing the N332 supersite. Digital panning may prove to be a valuable tool in future studies of bNAb diversity and lineage development. PMID:28883821

Increasing the Yield in Targeted Next-Generation Sequencing by Implicating CNV Analysis, Non-Coding Exons and the Overall Variant Load: The Example of Retinal Dystrophies

PubMed Central

Eisenberger, Tobias; Neuhaus, Christine; Khan, Arif O.; Decker, Christian; Preising, Markus N.; Friedburg, Christoph; Bieg, Anika; Gliem, Martin; Issa, Peter Charbel; Holz, Frank G.; Baig, Shahid M.; Hellenbroich, Yorck; Galvez, Alberto; Platzer, Konrad; Wollnik, Bernd; Laddach, Nadja; Ghaffari, Saeed Reza; Rafati, Maryam; Botzenhart, Elke; Tinschert, Sigrid; Börger, Doris; Bohring, Axel; Schreml, Julia; Körtge-Jung, Stefani; Schell-Apacik, Chayim; Bakur, Khadijah; Al-Aama, Jumana Y.; Neuhann, Teresa; Herkenrath, Peter; Nürnberg, Gudrun; Nürnberg, Peter; Davis, John S.; Gal, Andreas; Bergmann, Carsten; Lorenz, Birgit; Bolz, Hanno J.

2013-01-01

Retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA) are major causes of blindness. They result from mutations in many genes which has long hampered comprehensive genetic analysis. Recently, targeted next-generation sequencing (NGS) has proven useful to overcome this limitation. To uncover “hidden mutations” such as copy number variations (CNVs) and mutations in non-coding regions, we extended the use of NGS data by quantitative readout for the exons of 55 RP and LCA genes in 126 patients, and by including non-coding 5′ exons. We detected several causative CNVs which were key to the diagnosis in hitherto unsolved constellations, e.g. hemizygous point mutations in consanguineous families, and CNVs complemented apparently monoallelic recessive alleles. Mutations of non-coding exon 1 of EYS revealed its contribution to disease. In view of the high carrier frequency for retinal disease gene mutations in the general population, we considered the overall variant load in each patient to assess if a mutation was causative or reflected accidental carriership in patients with mutations in several genes or with single recessive alleles. For example, truncating mutations in RP1, a gene implicated in both recessive and dominant RP, were causative in biallelic constellations, unrelated to disease when heterozygous on a biallelic mutation background of another gene, or even non-pathogenic if close to the C-terminus. Patients with mutations in several loci were common, but without evidence for di- or oligogenic inheritance. Although the number of targeted genes was low compared to previous studies, the mutation detection rate was highest (70%) which likely results from completeness and depth of coverage, and quantitative data analysis. CNV analysis should routinely be applied in targeted NGS, and mutations in non-coding exons give reason to systematically include 5′-UTRs in disease gene or exome panels. Consideration of all variants is indispensable because even truncating mutations may be misleading. PMID:24265693

Increasing the yield in targeted next-generation sequencing by implicating CNV analysis, non-coding exons and the overall variant load: the example of retinal dystrophies.

PubMed

Eisenberger, Tobias; Neuhaus, Christine; Khan, Arif O; Decker, Christian; Preising, Markus N; Friedburg, Christoph; Bieg, Anika; Gliem, Martin; Charbel Issa, Peter; Holz, Frank G; Baig, Shahid M; Hellenbroich, Yorck; Galvez, Alberto; Platzer, Konrad; Wollnik, Bernd; Laddach, Nadja; Ghaffari, Saeed Reza; Rafati, Maryam; Botzenhart, Elke; Tinschert, Sigrid; Börger, Doris; Bohring, Axel; Schreml, Julia; Körtge-Jung, Stefani; Schell-Apacik, Chayim; Bakur, Khadijah; Al-Aama, Jumana Y; Neuhann, Teresa; Herkenrath, Peter; Nürnberg, Gudrun; Nürnberg, Peter; Davis, John S; Gal, Andreas; Bergmann, Carsten; Lorenz, Birgit; Bolz, Hanno J

2013-01-01

Retinitis pigmentosa (RP) and Leber congenital amaurosis (LCA) are major causes of blindness. They result from mutations in many genes which has long hampered comprehensive genetic analysis. Recently, targeted next-generation sequencing (NGS) has proven useful to overcome this limitation. To uncover "hidden mutations" such as copy number variations (CNVs) and mutations in non-coding regions, we extended the use of NGS data by quantitative readout for the exons of 55 RP and LCA genes in 126 patients, and by including non-coding 5' exons. We detected several causative CNVs which were key to the diagnosis in hitherto unsolved constellations, e.g. hemizygous point mutations in consanguineous families, and CNVs complemented apparently monoallelic recessive alleles. Mutations of non-coding exon 1 of EYS revealed its contribution to disease. In view of the high carrier frequency for retinal disease gene mutations in the general population, we considered the overall variant load in each patient to assess if a mutation was causative or reflected accidental carriership in patients with mutations in several genes or with single recessive alleles. For example, truncating mutations in RP1, a gene implicated in both recessive and dominant RP, were causative in biallelic constellations, unrelated to disease when heterozygous on a biallelic mutation background of another gene, or even non-pathogenic if close to the C-terminus. Patients with mutations in several loci were common, but without evidence for di- or oligogenic inheritance. Although the number of targeted genes was low compared to previous studies, the mutation detection rate was highest (70%) which likely results from completeness and depth of coverage, and quantitative data analysis. CNV analysis should routinely be applied in targeted NGS, and mutations in non-coding exons give reason to systematically include 5'-UTRs in disease gene or exome panels. Consideration of all variants is indispensable because even truncating mutations may be misleading.

Beyond positivism: Understanding and addressing childhood obesity disparities through a Critical Theory perspective.

PubMed

Schroeder, Krista; Kulage, Kristine M; Lucero, Robert

2015-10-01

We apply Critical Theory to examine menu labeling with the aim of uncovering important implications for nursing practice, research, and policy. Our critical analysis uncovers barriers to menu labeling's effectiveness, particularly for vulnerable populations. Nurses must work to minimize the impact of these barriers and optimize the effectiveness of menu labeling, in order to strengthen the fight against obesity. We suggest changes, guided by this critical analysis, which can be implemented by nurses working in clinical practice, research, and policy. © 2015, Wiley Periodicals, Inc.

Beyond Positivism: Understanding and addressing childhood obesity disparities through a Critical Theory perspective

PubMed Central

Schroeder, Krista; Kulage, Kristine M.; Lucero, Robert

2016-01-01

Purpose We apply Critical Theory to examine menu labeling with the aim of uncovering important implications for nursing practice, research, and policy. Conclusions Our critical analysis uncovers barriers to menu labeling's effectiveness, particularly for vulnerable populations. Nurses must work to minimize the impact of these barriers and optimize the effectiveness of menu labeling, in order to strengthen the fight against obesity. Practice implications We suggest changes, guided by this critical analysis,that can be implemented by nurses working in clinical practice, research, and policy. PMID:26112774

Heuristic aspect of the lateral root initiation index: A case study of the role of nitric oxide in root branching.

PubMed

Lira-Ruan, Verónica; Mendivil, Selene Napsucialy; Dubrovsky, Joseph G

2013-10-01

Lateral root (LR) initiation (LRI) is a central process in root branching. Based on LR and/or LR primordium densities, it has been shown that nitric oxide (NO) promotes LRI. However, because NO inhibits primary root growth, we hypothesized that NO may have an opposite effect if the analysis is performed on a cellular basis. Using a previously proposed parameter, the LRI index (which measures how many LRI events take place along a root portion equivalent to the length of a single file of 100 cortical cells of average length), we addressed this hypothesis and illustrate here that the LRI index provides a researcher with a tool to uncover hidden but important information about root initiation. • Arabidopsis thaliana roots were treated with an NO donor (sodium nitroprusside [SNP]) and/or an NO scavenger (2-(4-carboxyphenyl)-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide [cPTIO]). LRI was analyzed separately in the root portions formed before and during the treatment. In the latter, SNP caused root growth inhibition and an increase in the LR density accompanied by a decrease in LRI index, indicating overall inhibitory outcome of the NO donor on branching. The inhibitory effect of SNP was reversed by cPTIO, showing the NO-specific action of SNP on LRI. • Analysis of the LRI index permits the discovery of otherwise unknown modes of action of a substance on the root system formation. NO has a dual action on root branching, slightly promoting it in the root portion formed before the treatment and strongly inhibiting it in the root portion formed during the treatment.

Uncovering the Nutritional Landscape of Food

PubMed Central

Kim, Seunghyeon; Sung, Jaeyun; Foo, Mathias; Jin, Yong-Su; Kim, Pan-Jun

2015-01-01

Recent progresses in data-driven analysis methods, including network-based approaches, are revolutionizing many classical disciplines. These techniques can also be applied to food and nutrition, which must be studied to design healthy diets. Using nutritional information from over 1,000 raw foods, we systematically evaluated the nutrient composition of each food in regards to satisfying daily nutritional requirements. The nutrient balance of a food was quantified and termed nutritional fitness; this measure was based on the food’s frequency of occurrence in nutritionally adequate food combinations. Nutritional fitness offers a way to prioritize recommendable foods within a global network of foods, in which foods are connected based on the similarities of their nutrient compositions. We identified a number of key nutrients, such as choline and α-linolenic acid, whose levels in foods can critically affect the nutritional fitness of the foods. Analogously, pairs of nutrients can have the same effect. In fact, two nutrients can synergistically affect the nutritional fitness, although the individual nutrients alone may not have an impact. This result, involving the tendency among nutrients to exhibit correlations in their abundances across foods, implies a hidden layer of complexity when exploring for foods whose balance of nutrients within pairs holistically helps meet nutritional requirements. Interestingly, foods with high nutritional fitness successfully maintain this nutrient balance. This effect expands our scope to a diverse repertoire of nutrient-nutrient correlations, which are integrated under a common network framework that yields unexpected yet coherent associations between nutrients. Our nutrient-profiling approach combined with a network-based analysis provides a more unbiased, global view of the relationships between foods and nutrients, and can be extended towards nutritional policies, food marketing, and personalized nutrition. PMID:25768022

An Assessment of the Detection of Highly Enriched Uranium and its Use in an Improvised Nuclear Device using the Monte Carlo Computer Code MCNP-5

NASA Astrophysics Data System (ADS)

Cochran, Thomas

2007-04-01

In 2002 and again in 2003, an investigative journalist unit at ABC News transported a 6.8 kilogram metallic slug of depleted uranium (DU) via shipping container from Istanbul, Turkey to Brooklyn, NY and from Jakarta, Indonesia to Long Beach, CA. Targeted inspection of these shipping containers by Department of Homeland Security (DHS) personnel, included the use of gamma-ray imaging, portal monitors and hand-held radiation detectors, did not uncover the hidden DU. Monte Carlo analysis of the gamma-ray intensity and spectrum of a DU slug and one consisting of highly-enriched uranium (HEU) showed that DU was a proper surrogate for testing the ability of DHS to detect the illicit transport of HEU. Our analysis using MCNP-5 illustrated the ease of fully shielding an HEU sample to avoid detection. The assembly of an Improvised Nuclear Device (IND) -- a crude atomic bomb -- from sub-critical pieces of HEU metal was then examined via Monte Carlo criticality calculations. Nuclear explosive yields of such an IND as a function of the speed of assembly of the sub-critical HEU components were derived. A comparison was made between the more rapid assembly of sub-critical pieces of HEU in the ``Little Boy'' (Hiroshima) weapon's gun barrel and gravity assembly (i.e., dropping one sub-critical piece of HEU on another from a specified height). Based on the difficulty of detection of HEU and the straightforward construction of an IND utilizing HEU, current U.S. government policy must be modified to more urgently prioritize elimination of and securing the global inventories of HEU.

Complexity in pH-Dependent Ribozyme Kinetics: Dark pKa Shifts and Wavy Rate-pH Profiles.

PubMed

Frankel, Erica A; Bevilacqua, Philip C

2018-02-06

Charged bases occur in RNA enzymes, or ribozymes, where they play key roles in catalysis. Cationic bases donate protons and perform electrostatic catalysis, while anionic bases accept protons. We previously published simulations of rate-pH profiles for ribozymes in terms of species plots for the general acid and general base that have been useful for understanding how ribozymes respond to pH. In that study, we did not consider interaction between the general acid and general base or interaction with other species on the RNA. Since that report, diverse small ribozyme classes have been discovered, many of which have charged nucleobases or metal ions in the active site that can either directly interact and participate in catalysis or indirectly interact as "influencers". Herein, we simulate experimental rate-pH profiles in terms of species plots in which reverse protonated charged nucleobases interact. These analyses uncover two surprising features of pH-dependent enzyme kinetics. (1) Cooperativity between the general acid and general base enhances population of the functional forms of a ribozyme and manifests itself as hidden or "dark" pK a shifts, real pK a shifts that accelerate the reaction but are not readily observed by standard experimental approaches, and (2) influencers favorably shift the pK a s of proton-transferring nucleobases and manifest themselves as "wavy" rate-pH profiles. We identify parallels with the protein enzyme literature, including reverse protonation and wavelike behavior, while pointing out that RNA is more prone to reverse protonation. The complexities uncovered, which arise from simple pairwise interactions, should aid deconvolution of complex rate-pH profiles for RNA and protein enzymes and suggest veiled catalytic devices for promoting catalysis that can be tested by experiment and calculation.

Anisotropic scene geometry resampling with occlusion filling for 3DTV applications

NASA Astrophysics Data System (ADS)

Kim, Jangheon; Sikora, Thomas

2006-02-01

Image and video-based rendering technologies are receiving growing attention due to their photo-realistic rendering capability in free-viewpoint. However, two major limitations are ghosting and blurring due to their sampling-based mechanism. The scene geometry which supports to select accurate sampling positions is proposed using global method (i.e. approximate depth plane) and local method (i.e. disparity estimation). This paper focuses on the local method since it can yield more accurate rendering quality without large number of cameras. The local scene geometry has two difficulties which are the geometrical density and the uncovered area including hidden information. They are the serious drawback to reconstruct an arbitrary viewpoint without aliasing artifacts. To solve the problems, we propose anisotropic diffusive resampling method based on tensor theory. Isotropic low-pass filtering accomplishes anti-aliasing in scene geometry and anisotropic diffusion prevents filtering from blurring the visual structures. Apertures in coarse samples are estimated following diffusion on the pre-filtered space, the nonlinear weighting of gradient directions suppresses the amount of diffusion. Aliasing artifacts from low density are efficiently removed by isotropic filtering and the edge blurring can be solved by the anisotropic method at one process. Due to difference size of sampling gap, the resampling condition is defined considering causality between filter-scale and edge. Using partial differential equation (PDE) employing Gaussian scale-space, we iteratively achieve the coarse-to-fine resampling. In a large scale, apertures and uncovered holes can be overcoming because only strong and meaningful boundaries are selected on the resolution. The coarse-level resampling with a large scale is iteratively refined to get detail scene structure. Simulation results show the marked improvements of rendering quality.

Observational Signatures Of Agn Feedback Across Cosmic Time

NASA Astrophysics Data System (ADS)

Wylezalek, Dominika

2017-06-01

While many compelling models of AGN feedback exist, there is no clear data-driven picture of how winds are launched, how they propagate through the galaxy and what impact they have on the galactic gas. Recent work suggests that AGN luminosity plays an important role. The following described projects focus on understanding the power, reach and impact of feedback processes exerted by AGN of different power. I first describe recent efforts in our group of relating feedback signatures in powerful quasars to the specific star formation rate in their host galaxies, where our results are consistent with the AGN having a `negative' impact through feedback on the galaxies' star formation history. Feedback signatures seem to be best observable in gas-rich galaxies where the coupling of the AGN-driven wind to the gas is strongest, in agreement with recent simulations. But how and where does this quenching happen? Is it accomplished through the mechanical action of jets or through nuclear winds driven by radiation pressure? Finally, I show that AGN signatures and AGN-driven winds can be easily hidden and not be apparent in the integrated spectrum of a galaxy hosting a low/intermediate-luminosity AGN. Using data from the new SDSS-IV MaNGA survey, we have developed a new AGN selection algorithm tailored to IFU data and we are uncovering a much more nuanced picture of AGN activity allowing us to discover AGN signatures at large distances from the galaxy center. This implies that large IFU surveys, such as the SDSS-IV MaNGA survey, might uncover many previously unknown AGN and feedback signatures related to them. Outflows and feedback from low- and intermediate-luminosity AGN might have been underestimated in the past but can potentially significantly contribute to the AGN/host-galaxy self-regulation.

Anomalous neural circuit function in schizophrenia during a virtual Morris water task.

PubMed

Folley, Bradley S; Astur, Robert; Jagannathan, Kanchana; Calhoun, Vince D; Pearlson, Godfrey D

2010-02-15

Previous studies have reported learning and navigation impairments in schizophrenia patients during virtual reality allocentric learning tasks. The neural bases of these deficits have not been explored using functional MRI despite well-explored anatomic characterization of these paradigms in non-human animals. Our objective was to characterize the differential distributed neural circuits involved in virtual Morris water task performance using independent component analysis (ICA) in schizophrenia patients and controls. Additionally, we present behavioral data in order to derive relationships between brain function and performance, and we have included a general linear model-based analysis in order to exemplify the incremental and differential results afforded by ICA. Thirty-four individuals with schizophrenia and twenty-eight healthy controls underwent fMRI scanning during a block design virtual Morris water task using hidden and visible platform conditions. Independent components analysis was used to deconstruct neural contributions to hidden and visible platform conditions for patients and controls. We also examined performance variables, voxel-based morphometry and hippocampal subparcellation, and regional BOLD signal variation. Independent component analysis identified five neural circuits. Mesial temporal lobe regions, including the hippocampus, were consistently task-related across conditions and groups. Frontal, striatal, and parietal circuits were recruited preferentially during the visible condition for patients, while frontal and temporal lobe regions were more saliently recruited by controls during the hidden platform condition. Gray matter concentrations and BOLD signal in hippocampal subregions were associated with task performance in controls but not patients. Patients exhibited impaired performance on the hidden and visible conditions of the task, related to negative symptom severity. While controls showed coupling between neural circuits, regional neuroanatomy, and behavior, patients activated different task-related neural circuits, not associated with appropriate regional neuroanatomy. GLM analysis elucidated several comparable regions, with the exception of the hippocampus. Inefficient allocentric learning and memory in patients may be related to an inability to recruit appropriate task-dependent neural circuits. Copyright 2009 Elsevier Inc. All rights reserved.

Mining Bug Databases for Unidentified Software Vulnerabilities

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

Dumidu Wijayasekara; Milos Manic; Jason Wright

2012-06-01

Identifying software vulnerabilities is becoming more important as critical and sensitive systems increasingly rely on complex software systems. It has been suggested in previous work that some bugs are only identified as vulnerabilities long after the bug has been made public. These vulnerabilities are known as hidden impact vulnerabilities. This paper discusses the feasibility and necessity to mine common publicly available bug databases for vulnerabilities that are yet to be identified. We present bug database analysis of two well known and frequently used software packages, namely Linux kernel and MySQL. It is shown that for both Linux and MySQL, amore » significant portion of vulnerabilities that were discovered for the time period from January 2006 to April 2011 were hidden impact vulnerabilities. It is also shown that the percentage of hidden impact vulnerabilities has increased in the last two years, for both software packages. We then propose an improved hidden impact vulnerability identification methodology based on text mining bug databases, and conclude by discussing a few potential problems faced by such a classifier.« less

Geologic and Seismologic Investigation

DTIC Science & Technology

1988-12-01

Descriptions, Hidden and Buchanan Dams 4 1.6.1 Hidden Dam 4 1.6.2 Buchanan Dam 5 2 TECTONIC SETTING 2.1 General 7 2.2 Cretaceous-Cenozoic Tectonic ...Activity 7 2.2.1 Cretaceous-Paleogene 8 2.2.2 Neogene 9 2.2.3 Late Cenozoic Tectonic Model 9 3 REGIONAL GEOLOGY 3.1 General 11 3.2 Geologic Units 11...detected by the imagery analysis which indicates there has been no tectonic movement from about 100,000 to 400,000 years ago to the present. The field

Parsing Social Network Survey Data from Hidden Populations Using Stochastic Context-Free Grammars

PubMed Central

Poon, Art F. Y.; Brouwer, Kimberly C.; Strathdee, Steffanie A.; Firestone-Cruz, Michelle; Lozada, Remedios M.; Kosakovsky Pond, Sergei L.; Heckathorn, Douglas D.; Frost, Simon D. W.

2009-01-01

Background Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a ÔhiddenÕ population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process. Methodology/Principal Findings Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits. Conclusions SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics. PMID:19738904

Evidence of a high-Andean, mid-Holocene plant community: An ancient DNA analysis of glacially preserved remains.

PubMed

Gould, Billie A; León, Blanca; Buffen, Aron M; Thompson, Lonnie G

2010-09-01

Around the world, tropical glaciers and ice caps are retreating at unprecedented rates because of climate change. In at least one location, along the margin of the Quelccaya Ice Cap in southeastern Peru, ancient plant remains have been continually uncovered since 2002. We used genetic analysis to identify plants that existed at these sites during the mid-Holocene. • We examined remains between 4576 and 5222 yr old, using PCR amplification, cloning, and sequencing of a fragment of the chloroplast trnL intron. We then matched these sequences to sequences in GenBank. • We found evidence of at least five taxa characteristic of wetlands, which occur primarily at lower elevations in the region today. • A diverse community most likely existed at these locations the last time they were ice-free and thus has the potential to reestablish with time. This is the first genetic analysis of vegetation uncovered by receding glacial ice, and it may become one of many as ancient plant materials are newly uncovered in a changing climate.

Understanding women's sleep management: beyond medicalization-healthicization?

PubMed

Hislop, Jenny; Arber, Sara

2003-11-01

This paper addresses sleep, which to date has been a neglected area within the sociology of health and illness. We explore the extent to which the concepts of medicalization and healthicization provide appropriate models for understanding the management of women's sleep disruption. The prescription of sleeping pills remains as an indicator of the medicalization of sleep, while the trend towards the healthicization of sleep as part of healthy lifestyle practice is reflected in the increased focus of the media, pharmaceutical and complementary health care industries on sleep. The paper analyses qualitative data on women aged 40 and over to argue that the medicalization-healthicization framework fails to encapsulate a complete understanding of how women manage sleep disruption within the social context of their lives. It suggests that by looking inside the world of women's sleep we uncover a hidden dimension of self-directed personalized activity which plays a key role in women's response to sleep disruption. We propose an alternative model for the management of women's sleep which incorporates a core of personalised activity, linked to strategies associated with healthicization and medicalization.

Dark Energy and Dark Matter Hidden in the Geometry of Space?

NASA Astrophysics Data System (ADS)

Buchert, Thomas

A spatially flat and infinite Universe in the form of a "concordant" standard model of cosmology rules present-day thinking of cosmologists. The price to pay is an unknown physical origin of Dark Energy and Dark Matter that are supposed to exist and even appear to rule the dynamics of our Universe. A growing number of cosmologists question the existence of dark constituents: the standard model of cosmology may be just too simple, since it neglects the influence of structure in the Universe on its global expansion history. The key-issue appears to be the curvature of space: the formation of structure interacts with the geometry of space, changing our global picture of the Universe. This chapter explains the underlying mechanism that works in the right direction to uncover the dark faces of the standard model of cosmology. If successful, this novel approach furnishes a new paradigm of modern cosmology. Hundreds of researchers have recently embarked into studies of this new subject. We understand much at present, but there are many open questions.

Yearning, learning, and conceding: reasons men and women change their childbearing intentions.

PubMed

Iacovou, Maria; Tavares, Lara Patrício

2011-01-01

People's childbearing intentions change over the course of their reproductive lives. These changes have been conceptualized as occurring in response to the realization that an individual is unlikely to achieve his or her intended fertility, because of constraints such as the "biological clock" or lack of a partner. In this article, we find that changes to child-bearing plans are influenced by a much wider range of factors than this. People change their plans in response to the wishes of their partners, in response to social norms, as the result of repartnering, and as the result of learning about the costs and benefits of parenthood; there are also differences between the factors that influence men's and women's decision-making. In a departure from existing studies in this area, we use a flexible analytical framework that enables us to analyze increases in planned fertility separately from decreases. This allows us to uncover several complexities of the decision-making process that would otherwise be hidden, and leads us to conclude that the determinants of increases in planned fertility are not simply equal and opposite to the determinants of decreases.

Uncovering the hidden impacts of inequality on mental health: a global study.

PubMed

Yu, Shoukai

2018-05-18

Women are nearly twice as likely as men to suffer from mental illness. This gender disparity in depressive disorders may relate to social inequalities and living standards across nations. Currently, these disparities were not reflected at the level of health policies. This study utilized global data for depressive disorders and socioeconomic data from the United Nations' World Bank databases and Global Burden of Disease database to demonstrate the correlation between social inequality and gender disparities in mental health. This study investigated the association among the ratio of female to male depressive disorder rates, gross domestic product, the GINI Index, and the gender inequality index for 122 countries. The research yielded some major findings. First, there exists a significant correlation between gender inequality and gender disparities in mental health. Second, the GINI index is significantly associated with male-but not female-depressive disorder rates. Third, gender disparities in depressive disorders are associated with a country's wealth. These findings can help to inform society, policy-makers, and clinicians to improve the overall health level globally.

Bioinformatic perspectives on NRPS/PKS megasynthases: advances and challenges.

PubMed

Jenke-Kodama, Holger; Dittmann, Elke

2009-07-01

The increased understanding of both fundamental principles and mechanistic variations of NRPS/PKS megasynthases along with the unprecedented availability of microbial sequences has inspired a number of in silico studies of both enzyme families. The insights that can be extracted from these analyses go far beyond a rough classification of data and have turned bioinformatics into a frontier field of natural products research. As databases are flooded with NRPS/PKS gene sequence of microbial genomes and metagenomes, increasingly reliable structural prediction methods can help to uncover hidden treasures. Already, phylogenetic analyses have revealed that NRPS/PKS pathways should not simply be regarded as enzyme complexes, specifically evolved to product a selected natural product. Rather, they represent a collection of genetic opinions, allowing biosynthetic pathways to be shuffled in a process of perpetual chemical innovations and pathways diversification in nature can give impulses for specificities, protein interactions and genetic engineering of libraries of novel peptides and polyketides. The successful translation of the knowledge obtained from bioinformatic dissection of NRPS/PKS megasynthases into new techniques for drug discovery and design remain challenges for the future.

Genetic characterization and disease mechanism of retinitis pigmentosa; current scenario.

PubMed

Ali, Muhammad Umar; Rahman, Muhammad Saif Ur; Cao, Jiang; Yuan, Ping Xi

2017-08-01

Retinitis pigmentosa is a group of genetically transmitted disorders affecting 1 in 3000-8000 individual people worldwide ultimately affecting the quality of life. Retinitis pigmentosa is characterized as a heterogeneous genetic disorder which leads by progressive devolution of the retina leading to a progressive visual loss. It can occur in syndromic (with Usher syndrome and Bardet-Biedl syndrome) as well as non-syndromic nature. The mode of inheritance can be X-linked, autosomal dominant or autosomal recessive manner. To date 58 genes have been reported to associate with retinitis pigmentosa most of them are either expressed in photoreceptors or the retinal pigment epithelium. This review focuses on the disease mechanisms and genetics of retinitis pigmentosa. As retinitis pigmentosa is tremendously heterogeneous disorder expressing a multiplicity of mutations; different variations in the same gene might induce different disorders. In recent years, latest technologies including whole-exome sequencing contributing effectively to uncover the hidden genesis of retinitis pigmentosa by reporting new genetic mutations. In future, these advancements will help in better understanding the genotype-phenotype correlations of disease and likely to develop new therapies.

Delta II - SIRTF

NASA Image and Video Library

2003-03-06

The Space Infrared Telescope Facility (SIRTF) is uncovered in the clean room of Building AE to permit workers access to the spacecraft to begin final preparations for its launch aboard a Delta II rocket. The observatory was shipped to Florida from the Lockheed Martin plant in Sunnyvale, Calif. SIRTF will obtain images and spectra by detecting the infrared energy, or heat, radiated by objects in space between wavelengths of 3 and 180 microns (1 micron is one-millionth of a meter). Most of this infrared radiation is blocked by the Earth's atmosphere and cannot be observed from the ground. Consisting of an 0.85-meter telescope and three cryogenically cooled science instruments, SIRTF is one of NASA's largest infrared telescopes to be launched. Its highly sensitive instruments will give a unique view of the Universe and peer into regions of space that are hidden from optical telescopes on the ground or orbiting telescopes such as the Hubble Space Telescope. SIRTF is scheduled for launch April 15 at 4:34:07 a.m. EDT from Launch Complex 17-B, Cape Canaveral Air Force Station.

Revisiting the European sovereign bonds with a permutation-information-theory approach

NASA Astrophysics Data System (ADS)

Fernández Bariviera, Aurelio; Zunino, Luciano; Guercio, María Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

2013-12-01

In this paper we study the evolution of the informational efficiency in its weak form for seventeen European sovereign bonds time series. We aim to assess the impact of two specific economic situations in the hypothetical random behavior of these time series: the establishment of a common currency and a wide and deep financial crisis. In order to evaluate the informational efficiency we use permutation quantifiers derived from information theory. Specifically, time series are ranked according to two metrics that measure the intrinsic structure of their correlations: permutation entropy and permutation statistical complexity. These measures provide the rectangular coordinates of the complexity-entropy causality plane; the planar location of the time series in this representation space reveals the degree of informational efficiency. According to our results, the currency union contributed to homogenize the stochastic characteristics of the time series and produced synchronization in the random behavior of them. Additionally, the 2008 financial crisis uncovered differences within the apparently homogeneous European sovereign markets and revealed country-specific characteristics that were partially hidden during the monetary union heyday.

A survey of context recognition in surgery.

PubMed

Pernek, Igor; Ferscha, Alois

2017-10-01

With the introduction of operating rooms of the future context awareness has gained importance in the surgical environment. This paper organizes and reviews different approaches for recognition of context in surgery. Major electronic research databases were queried to obtain relevant publications submitted between the years 2010 and 2015. Three different types of context were identified: (i) the surgical workflow context, (ii) surgeon's cognitive and (iii) technical state context. A total of 52 relevant studies were identified and grouped based on the type of context detected and sensors used. Different approaches were summarized to provide recommendations for future research. There is still room for improvement in terms of methods used and evaluations performed. Machine learning should be used more extensively to uncover hidden relationships between different properties of the surgeon's state, particularly when performing cognitive context recognition. Furthermore, validation protocols should be improved by performing more evaluations in situ and with a higher number of unique participants. The paper also provides a structured outline of recent context recognition methods to facilitate development of new generation context-aware surgical support systems.

Three-dimensional reconstruction of highly complex microscopic samples using scanning electron microscopy and optical flow estimation.

PubMed

Baghaie, Ahmadreza; Pahlavan Tafti, Ahmad; Owen, Heather A; D'Souza, Roshan M; Yu, Zeyun

2017-01-01

Scanning Electron Microscope (SEM) as one of the major research and industrial equipment for imaging of micro-scale samples and surfaces has gained extensive attention from its emerge. However, the acquired micrographs still remain two-dimensional (2D). In the current work a novel and highly accurate approach is proposed to recover the hidden third-dimension by use of multi-view image acquisition of the microscopic samples combined with pre/post-processing steps including sparse feature-based stereo rectification, nonlocal-based optical flow estimation for dense matching and finally depth estimation. Employing the proposed approach, three-dimensional (3D) reconstructions of highly complex microscopic samples were achieved to facilitate the interpretation of topology and geometry of surface/shape attributes of the samples. As a byproduct of the proposed approach, high-definition 3D printed models of the samples can be generated as a tangible means of physical understanding. Extensive comparisons with the state-of-the-art reveal the strength and superiority of the proposed method in uncovering the details of the highly complex microscopic samples.

Minimum of the order parameter fluctuations of seismicity before major earthquakes in Japan.

PubMed

Sarlis, Nicholas V; Skordas, Efthimios S; Varotsos, Panayiotis A; Nagao, Toshiyasu; Kamogawa, Masashi; Tanaka, Haruo; Uyeda, Seiya

2013-08-20

It has been shown that some dynamic features hidden in the time series of complex systems can be uncovered if we analyze them in a time domain called natural time χ. The order parameter of seismicity introduced in this time domain is the variance of χ weighted for normalized energy of each earthquake. Here, we analyze the Japan seismic catalog in natural time from January 1, 1984 to March 11, 2011, the day of the M9 Tohoku earthquake, by considering a sliding natural time window of fixed length comprised of the number of events that would occur in a few months. We find that the fluctuations of the order parameter of seismicity exhibit distinct minima a few months before all of the shallow earthquakes of magnitude 7.6 or larger that occurred during this 27-y period in the Japanese area. Among the minima, the minimum before the M9 Tohoku earthquake was the deepest. It appears that there are two kinds of minima, namely precursory and nonprecursory, to large earthquakes.

Hidden Symmetries in String Theory

NASA Astrophysics Data System (ADS)

Chervonyi, Iurii

In this thesis we study hidden symmetries within the framework of string theory. Symmetries play a very important role in physics: they lead to drastic simplifications, which allow one to compute various physical quantities without relying on perturbative techniques. There are two kinds of hidden symmetries investigated in this work: the first type is associated with dynamics of quantum fields and the second type is related to integrability of strings on various backgrounds. Integrability is a remarkable property of some theories that allows one to determine all dynamical properties of the system using purely analytical methods. The goals of this thesis are twofold: extension of hidden symmetries known in General Relativity to stringy backgrounds in higher dimensions and construction of new integrable string theories. In the context of the first goal we study hidden symmetries of stringy backgrounds, with and without supersymmetry. For supersymmetric geometries produced by D-branes we identify the backgrounds with solvable equations for geodesics, which can potentially give rise to integrable string theories. Relaxing the requirement of supersymmetry, we also study charged black holes in higher dimensions and identify their hidden symmetries encoded in so-called Killing(-Yano) tensors. We construct the explicit form of the Killing(-Yano) tensors for the charged rotating black hole in arbitrary number of dimensions, study behavior of such tensors under string dualities, and use the analysis of hidden symmetries to explain why exact solutions for black rings (black holes with non-spherical event horizons) in more than five dimensions remain elusive. As a byproduct we identify the standard parameterization of AdSp x Sq backgrounds with elliptic coordinates on a flat base. The second goal of this work is construction of new integrable string theories by applying continuous deformations of known examples. We use the recent developments called (generalized) lambda-deformation to construct new integrable backgrounds depending on several continuous parameters and study analytical properties of the such deformations.

Identification of hidden relationships from the coupling of hydrophobic cluster analysis and domain architecture information.

PubMed

Faure, Guilhem; Callebaut, Isabelle

2013-07-15

Describing domain architecture is a critical step in the functional characterization of proteins. However, some orphan domains do not match any profile stored in dedicated domain databases and are thereby difficult to analyze. We present here an original novel approach, called TREMOLO-HCA, for the analysis of orphan domain sequences and inspired from our experience in the use of Hydrophobic Cluster Analysis (HCA). Hidden relationships between protein sequences can be more easily identified from the PSI-BLAST results, using information on domain architecture, HCA plots and the conservation degree of amino acids that may participate in the protein core. This can lead to reveal remote relationships with known families of domains, as illustrated here with the identification of a hidden Tudor tandem in the human BAHCC1 protein and a hidden ET domain in the Saccharomyces cerevisiae Taf14p and human AF9 proteins. The results obtained in such a way are consistent with those provided by HHPRED, based on pairwise comparisons of HHMs. Our approach can, however, be applied even in absence of domain profiles or known 3D structures for the identification of novel families of domains. It can also be used in a reverse way for refining domain profiles, by starting from known protein domain families and identifying highly divergent members, hitherto considered as orphan. We provide a possible integration of this approach in an open TREMOLO-HCA package, which is fully implemented in python v2.7 and is available on request. Instructions are available at http://www.impmc.upmc.fr/∼callebau/tremolohca.html. isabelle.callebaut@impmc.upmc.fr Supplementary Data are available at Bioinformatics online.

Hidden negative linear compressibility in lithium l-tartrate.

PubMed

Yeung, Hamish H-M; Kilmurray, Rebecca; Hobday, Claire L; McKellar, Scott C; Cheetham, Anthony K; Allan, David R; Moggach, Stephen A

2017-02-01

By decoupling the mechanical behaviour of building units for the first time in a wine-rack framework containing two different strut types, we show that lithium l-tartrate exhibits NLC with a maximum value, K max = -21 TPa -1 , and an overall NLC capacity, χ NLC = 5.1%, that are comparable to the most exceptional materials to date. Furthermore, the contributions from molecular strut compression and angle opening interplay to give rise to so-called "hidden" negative linear compressibility, in which NLC is absent at ambient pressure, switched on at 2 GPa and sustained up to the limit of our experiment, 5.5 GPa. Analysis of the changes in crystal structure using variable-pressure synchrotron X-ray diffraction reveals new chemical and geometrical design rules to assist the discovery of other materials with exciting hidden anomalous mechanical properties.

May Stakeholders be Involved in Design Without Informed Consent? The Case of Hidden Design.

PubMed

Pols, A J K

2017-06-01

Stakeholder involvement in design is desirable from both a practical and an ethical point of view. It is difficult to do well, however, and some problems recur again and again, both of a practical nature, e.g. stakeholders acting strategically rather than openly, and of an ethical nature, e.g. power imbalances unduly affecting the outcome of the process. Hidden Design has been proposed as a method to deal with the practical problems of stakeholder involvement. It aims to do so by taking the observation of stakeholder actions, rather than the outcomes of a deliberative process, as its input. Furthermore, it hides from stakeholders the fact that a design process is taking place so that they will not behave differently than they otherwise would. Both aspects of Hidden Design have raised ethical worries. In this paper I make an ethical analysis of what it means for a design process to leave participants uninformed or deceived rather than acquiring their informed consent beforehand, and to use observation of actions rather than deliberation as input for design, using Hidden Design as a case study. This analysis is based on two sets of normative guidelines: the ethical guidelines for psychological research involving deception or uninformed participants from two professional psychological organisations, and Habermasian norms for a fair and just (deliberative) process. It supports the conclusion that stakeholder involvement in design organised in this way can be ethically acceptable, though under a number of conditions and constraints.

Statistical mechanics of unsupervised feature learning in a restricted Boltzmann machine with binary synapses

NASA Astrophysics Data System (ADS)

Huang, Haiping

2017-05-01

Revealing hidden features in unlabeled data is called unsupervised feature learning, which plays an important role in pretraining a deep neural network. Here we provide a statistical mechanics analysis of the unsupervised learning in a restricted Boltzmann machine with binary synapses. A message passing equation to infer the hidden feature is derived, and furthermore, variants of this equation are analyzed. A statistical analysis by replica theory describes the thermodynamic properties of the model. Our analysis confirms an entropy crisis preceding the non-convergence of the message passing equation, suggesting a discontinuous phase transition as a key characteristic of the restricted Boltzmann machine. Continuous phase transition is also confirmed depending on the embedded feature strength in the data. The mean-field result under the replica symmetric assumption agrees with that obtained by running message passing algorithms on single instances of finite sizes. Interestingly, in an approximate Hopfield model, the entropy crisis is absent, and a continuous phase transition is observed instead. We also develop an iterative equation to infer the hyper-parameter (temperature) hidden in the data, which in physics corresponds to iteratively imposing Nishimori condition. Our study provides insights towards understanding the thermodynamic properties of the restricted Boltzmann machine learning, and moreover important theoretical basis to build simplified deep networks.

Colonoscopy video quality assessment using hidden Markov random fields

NASA Astrophysics Data System (ADS)

Park, Sun Young; Sargent, Dusty; Spofford, Inbar; Vosburgh, Kirby

2011-03-01

With colonoscopy becoming a common procedure for individuals aged 50 or more who are at risk of developing colorectal cancer (CRC), colon video data is being accumulated at an ever increasing rate. However, the clinically valuable information contained in these videos is not being maximally exploited to improve patient care and accelerate the development of new screening methods. One of the well-known difficulties in colonoscopy video analysis is the abundance of frames with no diagnostic information. Approximately 40% - 50% of the frames in a colonoscopy video are contaminated by noise, acquisition errors, glare, blur, and uneven illumination. Therefore, filtering out low quality frames containing no diagnostic information can significantly improve the efficiency of colonoscopy video analysis. To address this challenge, we present a quality assessment algorithm to detect and remove low quality, uninformative frames. The goal of our algorithm is to discard low quality frames while retaining all diagnostically relevant information. Our algorithm is based on a hidden Markov model (HMM) in combination with two measures of data quality to filter out uninformative frames. Furthermore, we present a two-level framework based on an embedded hidden Markov model (EHHM) to incorporate the proposed quality assessment algorithm into a complete, automated diagnostic image analysis system for colonoscopy video.

A Fast SVD-Hidden-nodes based Extreme Learning Machine for Large-Scale Data Analytics.

PubMed

Deng, Wan-Yu; Bai, Zuo; Huang, Guang-Bin; Zheng, Qing-Hua

2016-05-01

Big dimensional data is a growing trend that is emerging in many real world contexts, extending from web mining, gene expression analysis, protein-protein interaction to high-frequency financial data. Nowadays, there is a growing consensus that the increasing dimensionality poses impeding effects on the performances of classifiers, which is termed as the "peaking phenomenon" in the field of machine intelligence. To address the issue, dimensionality reduction is commonly employed as a preprocessing step on the Big dimensional data before building the classifiers. In this paper, we propose an Extreme Learning Machine (ELM) approach for large-scale data analytic. In contrast to existing approaches, we embed hidden nodes that are designed using singular value decomposition (SVD) into the classical ELM. These SVD nodes in the hidden layer are shown to capture the underlying characteristics of the Big dimensional data well, exhibiting excellent generalization performances. The drawback of using SVD on the entire dataset, however, is the high computational complexity involved. To address this, a fast divide and conquer approximation scheme is introduced to maintain computational tractability on high volume data. The resultant algorithm proposed is labeled here as Fast Singular Value Decomposition-Hidden-nodes based Extreme Learning Machine or FSVD-H-ELM in short. In FSVD-H-ELM, instead of identifying the SVD hidden nodes directly from the entire dataset, SVD hidden nodes are derived from multiple random subsets of data sampled from the original dataset. Comprehensive experiments and comparisons are conducted to assess the FSVD-H-ELM against other state-of-the-art algorithms. The results obtained demonstrated the superior generalization performance and efficiency of the FSVD-H-ELM. Copyright © 2016 Elsevier Ltd. All rights reserved.

Phylogenetic analysis at deep timescales: unreliable gene trees, bypassed hidden support, and the coalescence/concatalescence conundrum.

PubMed

Gatesy, John; Springer, Mark S

2014-11-01

Large datasets are required to solve difficult phylogenetic problems that are deep in the Tree of Life. Currently, two divergent systematic methods are commonly applied to such datasets: the traditional supermatrix approach (= concatenation) and "shortcut" coalescence (= coalescence methods wherein gene trees and the species tree are not co-estimated). When applied to ancient clades, these contrasting frameworks often produce congruent results, but in recent phylogenetic analyses of Placentalia (placental mammals), this is not the case. A recent series of papers has alternatively disputed and defended the utility of shortcut coalescence methods at deep phylogenetic scales. Here, we examine this exchange in the context of published phylogenomic data from Mammalia; in particular we explore two critical issues - the delimitation of data partitions ("genes") in coalescence analysis and hidden support that emerges with the combination of such partitions in phylogenetic studies. Hidden support - increased support for a clade in combined analysis of all data partitions relative to the support evident in separate analyses of the various data partitions, is a hallmark of the supermatrix approach and a primary rationale for concatenating all characters into a single matrix. In the most extreme cases of hidden support, relationships that are contradicted by all gene trees are supported when all of the genes are analyzed together. A valid fear is that shortcut coalescence methods might bypass or distort character support that is hidden in individual loci because small gene fragments are analyzed in isolation. Given the extensive systematic database for Mammalia, the assumptions and applicability of shortcut coalescence methods can be assessed with rigor to complement a small but growing body of simulation work that has directly compared these methods to concatenation. We document several remarkable cases of hidden support in both supermatrix and coalescence paradigms and argue that in most instances, the emergent support in the shortcut coalescence analyses is an artifact. By referencing rigorous molecular clock studies of Mammalia, we suggest that inaccurate gene trees that imply unrealistically deep coalescences debilitate shortcut coalescence analyses of the placental dataset. We document contradictory coalescence results for Placentalia, and outline a critical conundrum that challenges the general utility of shortcut coalescence methods at deep phylogenetic scales. In particular, the basic unit of analysis in coalescence analysis, the coalescence-gene, is expected to shrink in size as more taxa are analyzed, but as the amount of data for reconstruction of a gene tree ratchets downward, the number of nodes in the gene tree that need to be resolved ratchets upward. Some advocates of shortcut coalescence methods have attempted to address problems with inaccurate gene trees by concatenating multiple coalescence-genes to yield "gene trees" that better match the species tree. However, this hybrid concatenation/coalescence approach, "concatalescence," contradicts the most basic biological rationale for performing a coalescence analysis in the first place. We discuss this reality in the context of recent simulation work that also suggests inaccurate reconstruction of gene trees is more problematic for shortcut coalescence methods than deep coalescence of independently segregating loci is for concatenation methods. Copyright © 2014 Elsevier Inc. All rights reserved.

Hidden momentum of electrons, nuclei, atoms, and molecules

NASA Astrophysics Data System (ADS)

Cameron, Robert P.; Cotter, J. P.

2018-04-01

We consider the positions and velocities of electrons and spinning nuclei and demonstrate that these particles harbour hidden momentum when located in an electromagnetic field. This hidden momentum is present in all atoms and molecules, however it is ultimately canceled by the momentum of the electromagnetic field. We point out that an electron vortex in an electric field might harbour a comparatively large hidden momentum and recognize the phenomenon of hidden hidden momentum.

“Invisible” Conformers of an Antifungal Disulfide Protein Revealed by Constrained Cold and Heat Unfolding, CEST-NMR Experiments, and Molecular Dynamics Calculations

PubMed Central

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-01-01

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20–40 % at 298 K in a disulfide-rich protein. In addition, sensitive 15N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR “dark matter”. Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. PMID:25676351

Different designs of kinase-phosphatase interactions and phosphatase sequestration shapes the robustness and signal flow in the MAPK cascade

PubMed Central

2012-01-01

Background The three layer mitogen activated protein kinase (MAPK) signaling cascade exhibits different designs of interactions between its kinases and phosphatases. While the sequential interactions between the three kinases of the cascade are tightly preserved, the phosphatases of the cascade, such as MKP3 and PP2A, exhibit relatively diverse interactions with their substrate kinases. Additionally, the kinases of the MAPK cascade can also sequester their phosphatases. Thus, each topologically distinct interaction design of kinases and phosphatases could exhibit unique signal processing characteristics, and the presence of phosphatase sequestration may lead to further fine tuning of the propagated signal. Results We have built four architecturally distinct types of models of the MAPK cascade, each model with identical kinase-kinase interactions but unique kinases-phosphatases interactions. Our simulations unravelled that MAPK cascade’s robustness to external perturbations is a function of nature of interaction between its kinases and phosphatases. The cascade’s output robustness was enhanced when phosphatases were sequestrated by their target kinases. We uncovered a novel implicit/hidden negative feedback loop from the phosphatase MKP3 to its upstream kinase Raf-1, in a cascade resembling the B cell MAPK cascade. Notably, strength of the feedback loop was reciprocal to the strength of phosphatases’ sequestration and stronger sequestration abolished the feedback loop completely. An experimental method to verify the presence of the feedback loop is also proposed. We further showed, when the models were activated by transient signal, memory (total time taken by the cascade output to reach its unstimulated level after removal of signal) of a cascade was determined by the specific designs of interaction among its kinases and phosphatases. Conclusions Differences in interaction designs among the kinases and phosphatases can differentially shape the robustness and signal response behaviour of the MAPK cascade and phosphatase sequestration dramatically enhances the robustness to perturbations in each of the cascade. An implicit negative feedback loop was uncovered from our analysis and we found that strength of the negative feedback loop is reciprocally related to the strength of phosphatase sequestration. Duration of output phosphorylation in response to a transient signal was also found to be determined by the individual cascade’s kinase-phosphatase interaction design. PMID:22748295

[Assessment of hidden curriculum components by medical students].

PubMed

Ortega B, Javiera; Fasce H, Eduardo; Pérez V, Cristhian; Ibáñez G, Pilar; Márquez U, Carolina; Parra P, Paula

2014-11-01

Hidden curriculum refers to the unwritten, unofficial, and often unintended lessons, values, and perspectives that students learn at the university, which influences the acquisition of professional skills. To analyze the perception about the influence of the hidden curriculum in the education of medical students at the Universidad de Concepción, Chile. Qualitative investigation with case study approach. Seventeen graduated medical students were selected by probability sampling. A semi-structured interview was used to collect the information and a content analysis was applied. Forty seven percent of participants recognized having fulfilled their academic expectations. As favorable factors for academic achievement the students underlined clinical practice, access to patients and to clinical fields. As negative factors, they identified the lack of commitment, educational support and over-specialization of their mentors. The results show the strengths and weaknesses of the educational environment of undergraduated medical students. This information should be used to modify teaching environments.

Numerical Analysis of Modeling Based on Improved Elman Neural Network

PubMed Central

Jie, Shao

2014-01-01

A modeling based on the improved Elman neural network (IENN) is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE) varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA) with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL) model, Chebyshev neural network (CNN) model, and basic Elman neural network (BENN) model, the proposed model has better performance. PMID:25054172

Comparison of outcomes among secondary covered metallic, uncovered metallic, and plastic biliary stents in treating occluded primary metallic stents in malignant distal biliary obstruction.

PubMed

Cho, Jae Hee; Jeon, Tae Joo; Park, Jeong Youp; Kim, Hee Man; Kim, Yoon Jae; Park, Seung Woo; Chung, Jae Bock; Song, Si Young; Bang, Seungmin

2011-02-01

The self-expandable metallic stent (SEMS) has been widely used for unresectable malignant biliary obstruction but eventually becomes occluded by tumor ingrowth/overgrowth and sludge. Therefore, we aimed to determine the therapeutic effectiveness of secondary stents and to find differences according to various combinations of the first and second stents for the management of occluded SEMSs in patients with malignant distal biliary obstruction. Between 1999 and November 2008, 77 patients with malignant biliary obstruction underwent secondary biliary stent placement as "stent-in-stent" at three university hospitals in Korea (40 covered, 26 uncovered, and 11 plastic stents). The membrane of the covered SEMS was regarded as the barrier against tumor ingrowth. We categorized the patients into three groups based on whether the covered SEMS was either the first or the second stent: membrane-SEMS (18 covered-covered; 9 covered-uncovered; 22 uncovered-covered SEMS), bare-SEMS (17 uncovered-uncovered SEMS), and plastic stent (3 covered-plastic; 8 uncovered-plastic). The median patency of second stents was 138, 109, and 88 days (covered, uncovered, and plastic stents). The second covered SEMSs had a significantly longer patency than plastic stents (p=0.047). In a multivariate analysis including membrane-SEMS, bare-SEMS, and plastic stent groups, the bare-SEMS had a worse cumulative stent patency (HR=2.04, CI=1.08-3.86) and survival time (HR=2.37, CI=1.25-4.49) than the membrane-SEMS. Patients with ampulla of Vater cancer had better stent patency (HR=0.27, CI=0.08-0.98) and survival (HR=0.17, CI=0.04-0.77) than those with other pancreatobiliary malignancies. In addition, antitumor treatment prolonged survival time (HR=0.50, CI=0.26-0.99). The placement of additional biliary stents using the "stent-in-stent" method is an effective treatment for an occluded metallic primary stent. In addition, double biliary SEMS placement using at least one covered SEMS (in the primary and/or secondary procedure) might provide longer cumulative stent patency and survival than using uncovered SEMSs in both procedures.

Hidden Markov model analysis of force/torque information in telemanipulation

NASA Technical Reports Server (NTRS)

Hannaford, Blake; Lee, Paul

1991-01-01

A model for the prediction and analysis of sensor information recorded during robotic performance of telemanipulation tasks is presented. The model uses the hidden Markov model to describe the task structure, the operator's or intelligent controller's goal structure, and the sensor signals. A methodology for constructing the model parameters based on engineering knowledge of the task is described. It is concluded that the model and its optimal state estimation algorithm, the Viterbi algorithm, are very succesful at the task of segmenting the data record into phases corresponding to subgoals of the task. The model provides a rich modeling structure within a statistical framework, which enables it to represent complex systems and be robust to real-world sensory signals.

Nonlinear dynamical modes of climate variability: from curves to manifolds

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton

PubMed Central

Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel

2009-01-01

The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741

The hidden societal cost of antibiotic resistance per antibiotic prescribed in the United States: an exploratory analysis.

PubMed

Michaelidis, Constantinos I; Fine, Michael J; Lin, Chyongchiou Jeng; Linder, Jeffrey A; Nowalk, Mary Patricia; Shields, Ryan K; Zimmerman, Richard K; Smith, Kenneth J

2016-11-08

Ambulatory antibiotic prescribing contributes to the development of antibiotic resistance and increases societal costs. Here, we estimate the hidden societal cost of antibiotic resistance per antibiotic prescribed in the United States. In an exploratory analysis, we used published data to develop point and range estimates for the hidden societal cost of antibiotic resistance (SCAR) attributable to each ambulatory antibiotic prescription in the United States. We developed four estimation methods that focused on the antibiotic-resistance attributable costs of hospitalization, second-line inpatient antibiotic use, second-line outpatient antibiotic use, and antibiotic stewardship, then summed the estimates across all methods. The total SCAR attributable to each ambulatory antibiotic prescription was estimated to be $13 (range: $3-$95). The greatest contributor to the total SCAR was the cost of hospitalization ($9; 69 % of the total SCAR). The costs of second-line inpatient antibiotic use ($1; 8 % of the total SCAR), second-line outpatient antibiotic use ($2; 15 % of the total SCAR) and antibiotic stewardship ($1; 8 %). This apperars to be an error.; of the total SCAR) were modest contributors to the total SCAR. Assuming an average antibiotic cost of $20, the total SCAR attributable to each ambulatory antibiotic prescription would increase antibiotic costs by 65 % (range: 15-475 %) if incorporated into antibiotic costs paid by patients or payers. Each ambulatory antibiotic prescription is associated with a hidden SCAR that substantially increases the cost of an antibiotic prescription in the United States. This finding raises concerns regarding the magnitude of misalignment between individual and societal antibiotic costs.

Lived experience of economic and political trends related to globalization.

PubMed

Cushon, Jennifer A; Muhajarine, Nazeem; Labonte, Ronald

2010-01-01

A multi-method case study examined how the economic and political processes of globalization have influenced the determinants of health among low-income children in Saskatoon, Saskatchewan, Canada. This paper presents the results from the qualitative interview component of the case study. The purpose of the interviews was to uncover the lived experience of low-income families and their children in Saskatoon with regards to political and economic trends related to globalization, an important addition to the usual globalization and health research that relies primarily on cross-country regressions in which the personal impacts remain hidden. In-depth phenomenological interviews with 26 low-income parents of young children (aged zero to five) who were residents of Saskatoon. A combination of volunteer and criterion sampling was used. Interview questions were open-ended and based upon an analytical framework. Analysis proceeded through immersion in the data, a process of open coding, and finally through a process of selective coding. The larger case study and interviews indicate that globalization has largely not been benefiting low-income parents with young children. Low-income families with young children were struggling to survive, despite the tremendous economic growth occurring in Saskatchewan and Saskatoon at the time of the interviews. This often led to participants expressing a sense of helplessness, despair, isolation, and/or anger. Respondents' experiences suggest that globalization-related changes in social conditions and public policies and programs have great potential to negatively affect family health through either psychosocial effects in individuals and/or decreased levels of social cohesion in the community.

Measuring the intangibles: a metrics for the economic complexity of countries and products.

PubMed

Cristelli, Matthieu; Gabrielli, Andrea; Tacchella, Andrea; Caldarelli, Guido; Pietronero, Luciano

2013-01-01

We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation.

Informed walks: whispering hints to gene hunters inside networks' jungle.

PubMed

Bourdakou, Marilena M; Spyrou, George M

2017-10-11

Systemic approaches offer a different point of view on the analysis of several types of molecular associations as well as on the identification of specific gene communities in several cancer types. However, due to lack of sufficient data needed to construct networks based on experimental evidence, statistical gene co-expression networks are widely used instead. Many efforts have been made to exploit the information hidden in these networks. However, these approaches still need to capitalize comprehensively the prior knowledge encrypted into molecular pathway associations and improve their efficiency regarding the discovery of both exclusive subnetworks as candidate biomarkers and conserved subnetworks that may uncover common origins of several cancer types. In this study we present the development of the Informed Walks model based on random walks that incorporate information from molecular pathways to mine candidate genes and gene-gene links. The proposed model has been applied to TCGA (The Cancer Genome Atlas) datasets from seven different cancer types, exploring the reconstructed co-expression networks of the whole set of genes and driving to highlighted sub-networks for each cancer type. In the sequel, we elucidated the impact of each subnetwork on the indication of underlying exclusive and common molecular mechanisms as well as on the short-listing of drugs that have the potential to suppress the corresponding cancer type through a drug-repurposing pipeline. We have developed a method of gene subnetwork highlighting based on prior knowledge, capable to give fruitful insights regarding the underlying molecular mechanisms and valuable input to drug-repurposing pipelines for a variety of cancer types.

Exposing hidden alternative backbone conformations in X-ray crystallography using qFit

DOE PAGES

Keedy, Daniel A.; Fraser, James S.; van den Bedem, Henry; ...

2015-10-27

Proteins must move between different conformations of their native ensemble to perform their functions. Crystal structures obtained from high-resolution X-ray diffraction data reflect this heterogeneity as a spatial and temporal conformational average. Although movement between natively populated alternative conformations can be critical for characterizing molecular mechanisms, it is challenging to identify these conformations within electron density maps. Alternative side chain conformations are generally well separated into distinct rotameric conformations, but alternative backbone conformations can overlap at several atomic positions. Our model building program qFit uses mixed integer quadratic programming (MIQP) to evaluate an extremely large number of combinations of sidechainmore » conformers and backbone fragments to locally explain the electron density. Here, we describe two major modeling enhancements to qFit: peptide flips and alternative glycine conformations. We find that peptide flips fall into four stereotypical clusters and are enriched in glycine residues at the n+1 position. The potential for insights uncovered by new peptide flips and glycine conformations is exemplified by HIV protease, where different inhibitors are associated with peptide flips in the “flap” regions adjacent to the inhibitor binding site. Our results paint a picture of peptide flips as conformational switches, often enabled by glycine flexibility, that result in dramatic local rearrangements. Our results furthermore demonstrate the power of large-scale computational analysis to provide new insights into conformational heterogeneity. Furthermore, improved modeling of backbone heterogeneity with high-resolution X-ray data will connect dynamics to the structure-function relationship and help drive new design strategies for inhibitors of biomedically important systems.« less

Measuring the Intangibles: A Metrics for the Economic Complexity of Countries and Products

PubMed Central

Cristelli, Matthieu; Gabrielli, Andrea; Tacchella, Andrea; Caldarelli, Guido; Pietronero, Luciano

2013-01-01

We investigate a recent methodology we have proposed to extract valuable information on the competitiveness of countries and complexity of products from trade data. Standard economic theories predict a high level of specialization of countries in specific industrial sectors. However, a direct analysis of the official databases of exported products by all countries shows that the actual situation is very different. Countries commonly considered as developed ones are extremely diversified, exporting a large variety of products from very simple to very complex. At the same time countries generally considered as less developed export only the products also exported by the majority of countries. This situation calls for the introduction of a non-monetary and non-income-based measure for country economy complexity which uncovers the hidden potential for development and growth. The statistical approach we present here consists of coupled non-linear maps relating the competitiveness/fitness of countries to the complexity of their products. The fixed point of this transformation defines a metrics for the fitness of countries and the complexity of products. We argue that the key point to properly extract the economic information is the non-linearity of the map which is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We present a detailed comparison of the results of this approach directly with those of the Method of Reflections by Hidalgo and Hausmann, showing the better performance of our method and a more solid economic, scientific and consistent foundation. PMID:23940633

The Resistome of Low-Impacted Marine Environments Is Composed by Distant Metallo-β-Lactamases Homologs

PubMed Central

Fonseca, Erica L.; Andrade, Bruno G. N.; Vicente, Ana C. P.

2018-01-01

The worldwide dispersion and sudden emergence of new antibiotic resistance genes (ARGs) determined the need in uncovering which environment participate most as their source and reservoir. ARGs closely related to those currently found in human pathogens occur in the resistome of anthropogenic impacted environments. However, the role of pristine environment as the origin and source of ARGs remains underexplored and controversy, particularly, the marine environments represented by the oceans. Here, due to the ocean nature, we hypothesized that the resistome of this pristine/low-impacted marine environment is represented by distant ARG homologs. To test this hypothesis we performed an in silico analysis on the Global Ocean Sampling (GOS) metagenomic project dataset focusing on the metallo-β-lactamases (MβLs) as the ARG model. MβLs have been a challenge to public health, since they hydrolyze the carbapenems, one of the last therapeutic choice in clinics. Using Hidden Markov Model (HMM) profiles, we were successful in identifying a high diversity of distant MβL homologs, related to the B1, B2, and B3 subclasses. The majority of them were distributed across the Atlantic, Indian, and Pacific Oceans being related to the chromosomally encoded MβL GOB present in Elizabethkingia genus. It was observed only a reduced number of metagenomic sequence homologs related to the acquired MβL enzymes (VIM, SPM-1, and AIM-1) that currently have impact in clinics. Therefore, low antibiotic impacted marine environment, as the ocean, are unlikely the source of ARGs that have been causing enormous threat to the public health. PMID:29675014

The Resistome of Low-Impacted Marine Environments Is Composed by Distant Metallo-β-Lactamases Homologs.

PubMed

Fonseca, Erica L; Andrade, Bruno G N; Vicente, Ana C P

2018-01-01

The worldwide dispersion and sudden emergence of new antibiotic resistance genes (ARGs) determined the need in uncovering which environment participate most as their source and reservoir. ARGs closely related to those currently found in human pathogens occur in the resistome of anthropogenic impacted environments. However, the role of pristine environment as the origin and source of ARGs remains underexplored and controversy, particularly, the marine environments represented by the oceans. Here, due to the ocean nature, we hypothesized that the resistome of this pristine/low-impacted marine environment is represented by distant ARG homologs. To test this hypothesis we performed an in silico analysis on the Global Ocean Sampling (GOS) metagenomic project dataset focusing on the metallo-β-lactamases (MβLs) as the ARG model. MβLs have been a challenge to public health, since they hydrolyze the carbapenems, one of the last therapeutic choice in clinics. Using Hidden Markov Model (HMM) profiles, we were successful in identifying a high diversity of distant MβL homologs, related to the B1, B2, and B3 subclasses. The majority of them were distributed across the Atlantic, Indian, and Pacific Oceans being related to the chromosomally encoded MβL GOB present in Elizabethkingia genus. It was observed only a reduced number of metagenomic sequence homologs related to the acquired MβL enzymes (VIM, SPM-1, and AIM-1) that currently have impact in clinics. Therefore, low antibiotic impacted marine environment, as the ocean, are unlikely the source of ARGs that have been causing enormous threat to the public health.

Hidden Attractors in Dynamical Systems. From Hidden Oscillations in Hilbert-Kolmogorov Aizerman, and Kalman Problems to Hidden Chaotic Attractor in Chua Circuits

NASA Astrophysics Data System (ADS)

Leonov, G. A.; Kuznetsov, N. V.

From a computational point of view, in nonlinear dynamical systems, attractors can be regarded as self-excited and hidden attractors. Self-excited attractors can be localized numerically by a standard computational procedure, in which after a transient process a trajectory, starting from a point of unstable manifold in a neighborhood of equilibrium, reaches a state of oscillation, therefore one can easily identify it. In contrast, for a hidden attractor, a basin of attraction does not intersect with small neighborhoods of equilibria. While classical attractors are self-excited, attractors can therefore be obtained numerically by the standard computational procedure. For localization of hidden attractors it is necessary to develop special procedures, since there are no similar transient processes leading to such attractors. At first, the problem of investigating hidden oscillations arose in the second part of Hilbert's 16th problem (1900). The first nontrivial results were obtained in Bautin's works, which were devoted to constructing nested limit cycles in quadratic systems, that showed the necessity of studying hidden oscillations for solving this problem. Later, the problem of analyzing hidden oscillations arose from engineering problems in automatic control. In the 50-60s of the last century, the investigations of widely known Markus-Yamabe's, Aizerman's, and Kalman's conjectures on absolute stability have led to the finding of hidden oscillations in automatic control systems with a unique stable stationary point. In 1961, Gubar revealed a gap in Kapranov's work on phase locked-loops (PLL) and showed the possibility of the existence of hidden oscillations in PLL. At the end of the last century, the difficulties in analyzing hidden oscillations arose in simulations of drilling systems and aircraft's control systems (anti-windup) which caused crashes. Further investigations on hidden oscillations were greatly encouraged by the present authors' discovery, in 2010 (for the first time), of chaotic hidden attractor in Chua's circuit. This survey is dedicated to efficient analytical-numerical methods for the study of hidden oscillations. Here, an attempt is made to reflect the current trends in the synthesis of analytical and numerical methods.

Global-constrained hidden Markov model applied on wireless capsule endoscopy video segmentation

NASA Astrophysics Data System (ADS)

Wan, Yiwen; Duraisamy, Prakash; Alam, Mohammad S.; Buckles, Bill

2012-06-01

Accurate analysis of wireless capsule endoscopy (WCE) videos is vital but tedious. Automatic image analysis can expedite this task. Video segmentation of WCE into the four parts of the gastrointestinal tract is one way to assist a physician. The segmentation approach described in this paper integrates pattern recognition with statiscal analysis. Iniatially, a support vector machine is applied to classify video frames into four classes using a combination of multiple color and texture features as the feature vector. A Poisson cumulative distribution, for which the parameter depends on the length of segments, models a prior knowledge. A priori knowledge together with inter-frame difference serves as the global constraints driven by the underlying observation of each WCE video, which is fitted by Gaussian distribution to constrain the transition probability of hidden Markov model.Experimental results demonstrated effectiveness of the approach.

DAB user's guide

NASA Technical Reports Server (NTRS)

Trosin, J.

1985-01-01

Use of the Display AButments (DAB) which plots PAN AIR geometries is presented. The DAB program creates hidden line displays of PAN AIR geometries and labels specified geometry components, such as abutments, networks, and network edges. It is used to alleviate the very time consuming and error prone abutment list checking phase of developing a valid PAN AIR geometry, and therefore represents a valuable tool for debugging complex PAN AIR geometry definitions. DAB is written in FORTRAN 77 and runs on a Digital Equipment Corporation VAX 11/780 under VMS. It utilizes a special color version of the SKETCH hidden line analysis routine.

Factor Analysis of Traffic Safety in Urban Roads Based on FTA-LEC

NASA Astrophysics Data System (ADS)

Shuicheng, TIAN; Xingbo, YANG; Xiaoqing, SHEN; Detao, ZHANG

2018-05-01

In order to reduce the number and the loss of urban road traffic accidents in our country, improve the safety of road traffic, a statistical analysis of the research report on major road traffic accidents in 2016 was conducted. The risk factors affecting urban road traffic in China were analyzed by using FTA to find the basic hidden events. Secondly, the risk value of the identified hidden danger events were calculated and classified into four levels I, II, III and IV through the LEC evaluation method. Finally, the graded results of risk factors are verified through a case of specific accidents in Beijing. The results show that: the case verified the scientificalness and effectiveness of hazard classification and provided guidance for urban road traffic management.

Content Analysis as a Best Practice in Technical Communication Research

ERIC Educational Resources Information Center

Thayer, Alexander; Evans, Mary; McBride, Alicia; Queen, Matt; Spyridakis, Jan

2007-01-01

Content analysis is a powerful empirical method for analyzing text, a method that technical communicators can use on the job and in their research. Content analysis can expose hidden connections among concepts, reveal relationships among ideas that initially seem unconnected, and inform the decision-making processes associated with many technical…

The hidden and implicit curricula in cultural context: new insights from Doha and New York.

PubMed

Fins, Joseph J; Rodríguez del Pozo, Pablo

2011-03-01

The authors report their longitudinal experience teaching a clerkship in clinical ethics and palliative care at the Weill Cornell Medical College campuses in New York and Doha. This course uses participant observation and reflective practice to counteract the hidden curriculum when learning about clinical ethics and end-of-life care. The authors consider how this formal element of the curriculum is influenced by the implicit and hidden curricula in different cultural contexts and how these differing venues affect communication and information exchange, using the anthropological concept of high- and low-context societies. The authors' analysis provides additional information on Weill Cornell's educational efforts in the medical humanities, bioethics, and palliative care across the curriculum and across cultural settings. By contrasting high-context Doha, where much information is culturally embedded and seemingly hidden, with low-context New York, where information is made overt, the authors theorize that in each setting, the proportion of implicit and explicit curricular elements is determined by the extramural cultural environment. They argue that there are many hidden and implicit curricula and that each is dependent on modes of communication in any given setting. They assert that these variations can be seen not only across differing societies but also, for example, among individual U.S. medical schools because of local custom, history, or mission. Because these contextual factors influence the relative importance of what is implicit and explicit in the student's educational experience, medical educators need to be aware of their local cultural contexts in order to engage in effective pedagogy.

A Teachable Moment Uncovered by Video Analysis

NASA Astrophysics Data System (ADS)

Gates, Joshua

2011-05-01

Early in their study of one-dimensional kinematics, my students build an algebraic model that describes the effects of a rolling ball's (perpendicular) collision with a wall. The goal is for the model to predict the ball's velocity when it returns to a fixed point approximately 50-100 cm from the wall as a function of its velocity as it passes this point initially. They are told to assume that the ball's velocity does not change while it rolls to or from the wall—that the velocity change all happens very quickly and only at the wall. In order to evaluate this assumption following the data collection, I have the students analyze one such collision using video analysis. The results uncover an excellent teachable moment about assumptions and their impact on models and error analysis.

Learning about gender on campus: an analysis of the hidden curriculum for medical students.

PubMed

Cheng, Ling-Fang; Yang, Hsing-Chen

2015-03-01

Gender sensitivity is a crucial factor in the provision of quality health care. This paper explores acquired gendered values and attitudes among medical students through an analysis of the hidden curriculum that exists within formal medical classes and informal learning. Discourse analysis was adopted as the research method. Data were collected from the Bulletin Board System (BBS), which represented an essential communication platform among students in Taiwan before the era of Facebook. The study examined 197 gender-related postings on the BBS boards of nine of 11 universities with a medical department in Taiwan, over a period of 10 years from 2000 to 2010. The five distinctive characteristics of the hidden curriculum were as follows: (i) gendered stereotypes of physiological knowledge; (ii) biased treatment of women; (iii) stereotyped gender-based division of labour; (iv) sexual harassment and a hostile environment, and (v) ridiculing of lesbian, gay, bisexual and transgender (LGBT) people. Both teachers and students co-produced a heterosexual masculine culture and sexism, including 'benevolent sexism' and 'hostile sexism'. As a result, the self-esteem and learning opportunities of female and LGBT students have been eroded. The paper explores gender dynamics in the context of a hidden curriculum in which heterosexual masculinity and stereotyped sexism are prevalent as norms. Both teachers and students, whether through formal medical classes or informal extracurricular interactive activities, are noted to contribute to the consolidation of such norms. The study tentatively suggests three strategies for integrating gender into medical education: (i) by separating physiological knowledge from gender stereotyping in teaching; (ii) by highlighting the importance of gender sensitivity in the language used within and outside the classroom by teachers and students, and (iii) by broadening the horizons of both teachers and students by recounting examples of the lived experiences of those who have been excluded and discriminated against, particularly members of LGBT and other minorities. © 2015 John Wiley & Sons Ltd.

Geophysical Investigations at Hidden Dam, Raymond, California Flow Simulations

USGS Publications Warehouse

Minsley, Burke J.; Ikard, Scott

2010-01-01

Numerical flow modeling and analysis of observation-well data at Hidden Dam are carried out to supplement recent geophysical field investigations at the site (Minsley and others, 2010). This work also is complementary to earlier seepage-related studies at Hidden Dam documented by Cedergren (1980a, b). Known seepage areas on the northwest right abutment area of the downstream side of the dam was documented by Cedergren (1980a, b). Subsequent to the 1980 seepage study, a drainage blanket with a sub-drain system was installed to mitigate downstream seepage. Flow net analysis provided by Cedergren (1980a, b) suggests that the primary seepage mechanism involves flow through the dam foundation due to normal reservoir pool elevations, which results in upflow that intersects the ground surface in several areas on the downstream side of the dam. In addition to the reservoir pool elevations and downstream surface topography, flow is also controlled by the existing foundation geology as well as the presence or absence of a horizontal drain in the downstream portion of the dam. The current modeling study is aimed at quantifying how variability in dam and foundation hydrologic properties influences seepage as a function of reservoir stage. Flow modeling is implemented using the COMSOL Multiphysics software package, which solves the partially saturated flow equations in a two-dimensional (2D) cross-section of Hidden Dam that also incorporates true downstream topography. Use of the COMSOL software package provides a more quantitative approach than the flow net analysis by Cedergren (1980a, b), and allows for rapid evaluation of the influence of various parameters such as reservoir level, dam structure and geometry, and hydrogeologic properties of the dam and foundation materials. Historical observation-well data are used to help validate the flow simulations by comparing observed and predicted water levels for a range of reservoir elevations. The flow models are guided by, and discussed in the context of, the geophysical work (Minsley and others, 2010) where appropriate.

Temporal framing and the hidden-zero effect: rate-dependent outcomes on delay discounting.

PubMed

Naudé, Gideon P; Kaplan, Brent A; Reed, Derek D; Henley, Amy J; DiGennaro Reed, Florence D

2018-05-01

Recent research suggests that presenting time intervals as units (e.g., days) or as specific dates, can modulate the degree to which humans discount delayed outcomes. Another framing effect involves explicitly stating that choosing a smaller-sooner reward is mutually exclusive to receiving a larger-later reward, thus presenting choices as an extended sequence. In Experiment 1, participants (N = 201) recruited from Amazon Mechanical Turk completed the Monetary Choice Questionnaire in a 2 (delay framing) by 2 (zero framing) design. Regression suggested a main effect of delay, but not zero, framing after accounting for other demographic variables and manipulations. We observed a rate-dependent effect for the date-framing group, such that those with initially steep discounting exhibited greater sensitivity to the manipulation than those with initially shallow discounting. Subsequent analyses suggest these effects cannot be explained by regression to the mean. Experiment 2 addressed the possibility that the null effect of zero framing was due to within-subject exposure to the hidden- and explicit-zero conditions. A new Amazon Mechanical Turk sample completed the Monetary Choice Questionnaire in either hidden- or explicit-zero formats. Analyses revealed a main effect of reward magnitude, but not zero framing, suggesting potential limitations to the generality of the hidden-zero effect. © 2018 Society for the Experimental Analysis of Behavior.

Decoding and modelling of time series count data using Poisson hidden Markov model and Markov ordinal logistic regression models.

PubMed

Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I

2018-01-01

Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.

Pilot testing model to uncover industrial symbiosis in Brazilian industrial clusters.

PubMed

Saraceni, Adriana Valélia; Resende, Luis Mauricio; de Andrade Júnior, Pedro Paulo; Pontes, Joseane

2017-04-01

The main objective of this study was to create a pilot model to uncover industrial symbiosis practices in Brazilian industrial clusters. For this purpose, a systematic revision was conducted in journals selected from two categories of the ISI Web of Knowledge: Engineering, Environmental and Engineering, Industrial. After an in-depth revision of literature, results allowed the creation of an analysis structure. A methodology based on fuzzy logic was applied and used to attribute the weights of industrial symbiosis variables. It was thus possible to extract the intensity indicators of the interrelations required to analyse the development level of each correlation between the variables. Determination of variables and their weights initially resulted in a framework for the theory of industrial symbiosis assessments. Research results allowed the creation of a pilot model that could precisely identify the loopholes or development levels in each sphere. Ontology charts for data analysis were also generated. This study contributes to science by presenting the foundations for building an instrument that enables application and compilation of the pilot model, in order to identify opportunity to symbiotic development, which derives from "uncovering" existing symbioses.

Comfort and convenience analysis of advanced restraint systems

DOT National Transportation Integrated Search

1975-08-25

Five restraint systems were evaluated in terms of comfort and convenience by ten subjects. Statistical analysis of particular questions and system comparisons uncovered potential problems. The standard lap and shoulder belt system (1974 Chevrolet Imp...

The secret art of managing healthcare expenses: investigating implicit rationing and autonomy in public healthcare systems.

PubMed

Lauridsen, S M R; Norup, M S; Rossel, P J H

2007-12-01

Rationing healthcare is a difficult task, which includes preventing patients from accessing potentially beneficial treatments. Proponents of implicit rationing argue that politicians cannot resist pressure from strong patient groups for treatments and conclude that physicians should ration without informing patients or the public. The authors subdivide this specific programme of implicit rationing, or "hidden rationing", into local hidden rationing, unsophisticated global hidden rationing and sophisticated global hidden rationing. They evaluate the appropriateness of these methods of rationing from the perspectives of individual and political autonomy and conclude that local hidden rationing and unsophisticated global hidden rationing clearly violate patients' individual autonomy, that is, their right to participate in medical decision-making. While sophisticated global hidden rationing avoids this charge, the authors point out that it nonetheless violates the political autonomy of patients, that is, their right to engage in public affairs as citizens. A defence of any of the forms of hidden rationing is therefore considered to be incompatible with a defence of autonomy.

Comparative mRNA analysis of behavioral and genetic mouse models of aggression.

PubMed

Malki, Karim; Tosto, Maria G; Pain, Oliver; Sluyter, Frans; Mineur, Yann S; Crusio, Wim E; de Boer, Sietse; Sandnabba, Kenneth N; Kesserwani, Jad; Robinson, Edward; Schalkwyk, Leonard C; Asherson, Philip

2016-04-01

Mouse models of aggression have traditionally compared strains, most notably BALB/cJ and C57BL/6. However, these strains were not designed to study aggression despite differences in aggression-related traits and distinct reactivity to stress. This study evaluated expression of genes differentially regulated in a stress (behavioral) mouse model of aggression with those from a recent genetic mouse model aggression. The study used a discovery-replication design using two independent mRNA studies from mouse brain tissue. The discovery study identified strain (BALB/cJ and C57BL/6J) × stress (chronic mild stress or control) interactions. Probe sets differentially regulated in the discovery set were intersected with those uncovered in the replication study, which evaluated differences between high and low aggressive animals from three strains specifically bred to study aggression. Network analysis was conducted on overlapping genes uncovered across both studies. A significant overlap was found with the genetic mouse study sharing 1,916 probe sets with the stress model. Fifty-one probe sets were found to be strongly dysregulated across both studies mapping to 50 known genes. Network analysis revealed two plausible pathways including one centered on the UBC gene hub which encodes ubiquitin, a protein well-known for protein degradation, and another on P38 MAPK. Findings from this study support the stress model of aggression, which showed remarkable molecular overlap with a genetic model. The study uncovered a set of candidate genes including the Erg2 gene, which has previously been implicated in different psychopathologies. The gene networks uncovered points at a Redox pathway as potentially being implicated in aggressive related behaviors. © 2016 Wiley Periodicals, Inc.

Follow that fish: Uncovering the hidden blue economy in coral reef fisheries.

PubMed

Grafeld, Shanna; Oleson, Kirsten L L; Teneva, Lida; Kittinger, John N

2017-01-01

Despite their importance for human well-being, nearshore fisheries are often data poor, undervalued, and underappreciated in policy and development programs. We assess the value chain for nearshore Hawaiian coral reef fisheries, mapping post-catch distribution and disposition, and quantifying associated monetary, food security, and cultural values. We estimate that the total annual value of the nearshore fishery in Hawai'i is $10.3-$16.4 million, composed of non-commercial ($7.2-$12.9 million) and commercial ($2.97 million licensed + $148,500-$445,500 unlicensed) catch. Hawaii's nearshore fisheries provide >7 million meals annually, with most (>5 million) from the non-commercial sector. Over a third (36%) of meals were planktivores, 26% piscivores, 21% primary consumers, and 18% secondary consumers. Only 62% of licensed commercial catch is accounted for in purchase reports, leaving 38% of landings unreported in sales. Value chains are complex, with major buyers for the commercial fishery including grocery stores (66%), retailers (19%), wholesalers (14%), and restaurants (<1%), who also trade and sell amongst themselves. The bulk of total nearshore catch (72-74%) follows a short value chain, with non-commercial fishers keeping catch for household consumption or community sharing. A small amount (~37,000kg) of reef fish-the equivalent of 1.8% of local catch-is imported annually into Hawai'i, 23,000kg of which arrives as passenger luggage on commercial flights from Micronesia. Evidence of exports to the US mainland exists, but is unquantifiable given existing data. Hawaiian nearshore fisheries support fundamental cultural values including subsistence, activity, traditional knowledge, and social cohesion. These small-scale coral reef fisheries provide large-scale benefits to the economy, food security, and cultural practices of Hawai'i, underscoring the need for sustainable management. This research highlights the value of information on the value chain for small-scale production systems, making the hidden economy of these fisheries visible and illuminating a range of conservation interventions applicable to Hawai'i and beyond.

The Hidden Curriculum as Emancipatory and Non-Emancipatory Tools.

ERIC Educational Resources Information Center

Kanpol, Barry

Moral values implied in school practices and policies constitute the "hidden curriculum." Because the hidden curriculum may promote certain moral values to students, teachers are partially responsible for the moral education of students. A component of the hidden curriculum, institutional political resistance, concerns teacher opposition to…

Safety and Tolerability of Ixekizumab: Integrated Analysis of Injection-Site Reactions from 11 Clinical Trials.

PubMed

Shear, Neil H; Paul, Carle; Blauvelt, Andrew; Gooderham, Melinda; Leonardi, Craig; Reich, Kristian; Ohtsuki, Mamitaro; Pangallo, Beth; Xu, Wen; Ball, Susan; Ridenour, Terri; Torisu-Itakura, Hitoe; Agada, Noah; Mallbris, Lotus

2018-02-01

BACKGROUND: Injection-site reactions (ISRs) are reported with biologic therapies. The objective of this study was to comprehensively characterize ISRs among moderate-to-severe psoriasis patients treated with ixekizumab, a high-affinity monoclonal antibody that selectively targets interleukin (IL)-17A.

METHODS: ISRs are presented from UNCOVER-1, UNCOVER-2, and UNCOVER-3 (12 weeks) and all ixekizumab-exposed patients in 11 controlled and uncontrolled trials (156 weeks).

RESULTS: At week 12, reported ISR frequency with 80 mg ixekizumab every 2 weeks (IXE Q2W, 16.8%) was comparable with etanercept twice weekly (16.4%); both were significantly higher than placebo (3.3%). With IXE Q2W, ISRs were mild (12.3%), moderate (3.9%), or severe (0.7%), typically reported in the first 2 weeks (median onset, 6.6 days), and most commonly characterized as nonspecified, erythema, and pain. Generally, erythema onset was delayed, whereas pain occurred around drug administration. Discontinuation from ixekizumab due to ISRs (0.4%) occurred in the first 12 weeks. After 2 weeks, ISR frequency decreased and remained stable (≤4.2%) through week 156. No ISR-related serious adverse events were reported in ixekizumab-treated patients. ISR data were solicited if patients reported injection-associated events. Since nonspecified ISR was the most commonly reported term, specific types might be underreported.

CONCLUSIONS: ISRs have been reported with ixekizumab during clinical trials. These reactions are typically tolerable, manageable, and decrease over time.

Clinicaltrials.gov: NCT01474512 (UNCOVER-1); NCT01597245 (UNCOVER-2); NCT01646177 (UNCOVER-3); NCT01777191 (UNCOVER-A); NCT01624233 (UNCOVER-J); NCT01107457 (I1F-MC-RHAJ); NCT02561806 (I1F-MC-RHBS); NCT02387801 (I1F-US-RHBO);NCT02513550 (I1F-MC-RHBP); NCT02634801 (I1F-EW-RHBZ)

J Drugs Dermatol. 2018;17(2):200-206.

THIS ARTICLE HAD BEEN MADE AVAILABLE FREE OF CHARGE.

PLEASE SCROLL DOWN TO ACCESS THE FULL TEXT OF THIS ARTICLE WITHOUT LOGGING IN.

NO PURCHASE NECESSARY.

PLEASE CONTACT THE PUBLISHER WITH ANY QUESTIONS.

Monitoring volcano activity through Hidden Markov Model

NASA Astrophysics Data System (ADS)

Cassisi, C.; Montalto, P.; Prestifilippo, M.; Aliotta, M.; Cannata, A.; Patanè, D.

2013-12-01

During 2011-2013, Mt. Etna was mainly characterized by cyclic occurrences of lava fountains, totaling to 38 episodes. During this time interval Etna volcano's states (QUIET, PRE-FOUNTAIN, FOUNTAIN, POST-FOUNTAIN), whose automatic recognition is very useful for monitoring purposes, turned out to be strongly related to the trend of RMS (Root Mean Square) of the seismic signal recorded by stations close to the summit area. Since RMS time series behavior is considered to be stochastic, we can try to model the system generating its values, assuming to be a Markov process, by using Hidden Markov models (HMMs). HMMs are a powerful tool in modeling any time-varying series. HMMs analysis seeks to recover the sequence of hidden states from the observed emissions. In our framework, observed emissions are characters generated by the SAX (Symbolic Aggregate approXimation) technique, which maps RMS time series values with discrete literal emissions. The experiments show how it is possible to guess volcano states by means of HMMs and SAX.

Self-Organizing Hidden Markov Model Map (SOHMMM).

PubMed

Ferles, Christos; Stafylopatis, Andreas

2013-12-01

A hybrid approach combining the Self-Organizing Map (SOM) and the Hidden Markov Model (HMM) is presented. The Self-Organizing Hidden Markov Model Map (SOHMMM) establishes a cross-section between the theoretic foundations and algorithmic realizations of its constituents. The respective architectures and learning methodologies are fused in an attempt to meet the increasing requirements imposed by the properties of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein chain molecules. The fusion and synergy of the SOM unsupervised training and the HMM dynamic programming algorithms bring forth a novel on-line gradient descent unsupervised learning algorithm, which is fully integrated into the SOHMMM. Since the SOHMMM carries out probabilistic sequence analysis with little or no prior knowledge, it can have a variety of applications in clustering, dimensionality reduction and visualization of large-scale sequence spaces, and also, in sequence discrimination, search and classification. Two series of experiments based on artificial sequence data and splice junction gene sequences demonstrate the SOHMMM's characteristics and capabilities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Micro-XRF complemented by x-radiography and digital microscopy imaging for the study of hidden paintings

NASA Astrophysics Data System (ADS)

Gasanova, Svetlana; Hermon, Sorin

2017-07-01

The present study describes a novel approach to the study of hidden by integrating the non-invasive micro-X-Ray Fluorescence spectroscopy, X-radiography and digital microscopy. The case study analysed is a portrait of a male figure discovered under the painting of Ecce Homo, attributed to Titian's studio with an estimated date in the 1550s. The X-radiography images exposed the details of the underpainting, which appeared to be a nearly finished portrait of a standing man, overpainted by the current composition of Ecce Homo at a 180° angle. The microscopy observations of the upper painting's cracks and flaked areas enabled the study of the exposed underlayers in terms of their colour appearance and pigment particles. The subsequent pigment analysis was performed by micro-XRF. Since the described XRF analysis was performed not in scanner mode, the correct selection of the measurement spots for the micro analysis and separation between pigments of the lower and the upper painting was of paramount importance. The described approach for spot selection was based on the results of the preceding X-radiography and digital microscopy tests. The presence of lead white, vermilion, copper green and iron earth in the underlying portrait was confirmed by the multiple point XRF analysis of Pb, Hg, Cu, Fe and Mn lines. The described investigation method proved to be useful in the identification of the pigments of the underlying painting and consequently assisted in the tentative reconstruction of its colour palette. Moreover, the undertaken approach allowed discovering the potential of micro-XRF technique in the study of hidden compositions.

Electronic health record analysis via deep poisson factor models

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

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Exploring relation types for literature-based discovery.

PubMed

Preiss, Judita; Stevenson, Mark; Gaizauskas, Robert

2015-09-01

Literature-based discovery (LBD) aims to identify "hidden knowledge" in the medical literature by: (1) analyzing documents to identify pairs of explicitly related concepts (terms), then (2) hypothesizing novel relations between pairs of unrelated concepts that are implicitly related via a shared concept to which both are explicitly related. Many LBD approaches use simple techniques to identify semantically weak relations between concepts, for example, document co-occurrence. These generate huge numbers of hypotheses, difficult for humans to assess. More complex techniques rely on linguistic analysis, for example, shallow parsing, to identify semantically stronger relations. Such approaches generate fewer hypotheses, but may miss hidden knowledge. The authors investigate this trade-off in detail, comparing techniques for identifying related concepts to discover which are most suitable for LBD. A generic LBD system that can utilize a range of relation types was developed. Experiments were carried out comparing a number of techniques for identifying relations. Two approaches were used for evaluation: replication of existing discoveries and the "time slicing" approach.(1) RESULTS: Previous LBD discoveries could be replicated using relations based either on document co-occurrence or linguistic analysis. Using relations based on linguistic analysis generated many fewer hypotheses, but a significantly greater proportion of them were candidates for hidden knowledge. The use of linguistic analysis-based relations improves accuracy of LBD without overly damaging coverage. LBD systems often generate huge numbers of hypotheses, which are infeasible to manually review. Improving their accuracy has the potential to make these systems significantly more usable. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Delirium superimposed on dementia: defining disease states and course from longitudinal measurements of a multivariate index using latent class analysis and hidden Markov chains.

PubMed

Ciampi, Antonio; Dyachenko, Alina; Cole, Martin; McCusker, Jane

2011-12-01

The study of mental disorders in the elderly presents substantial challenges due to population heterogeneity, coexistence of different mental disorders, and diagnostic uncertainty. While reliable tools have been developed to collect relevant data, new approaches to study design and analysis are needed. We focus on a new analytic approach. Our framework is based on latent class analysis and hidden Markov chains. From repeated measurements of a multivariate disease index, we extract the notion of underlying state of a patient at a time point. The course of the disorder is then a sequence of transitions among states. States and transitions are not observable; however, the probability of being in a state at a time point, and the transition probabilities from one state to another over time can be estimated. Data from 444 patients with and without diagnosis of delirium and dementia were available from a previous study. The Delirium Index was measured at diagnosis, and at 2 and 6 months from diagnosis. Four latent classes were identified: fairly healthy, moderately ill, clearly sick, and very sick. Dementia and delirium could not be separated on the basis of these data alone. Indeed, as the probability of delirium increased, so did the probability of decline of mental functions. Eight most probable courses were identified, including good and poor stable courses, and courses exhibiting various patterns of improvement. Latent class analysis and hidden Markov chains offer a promising tool for studying mental disorders in the elderly. Its use may show its full potential as new data become available.

Toward Systems Metabolic Engineering of Streptomycetes for Secondary Metabolites Production.

PubMed

Robertsen, Helene Lunde; Weber, Tilmann; Kim, Hyun Uk; Lee, Sang Yup

2018-01-01

Streptomycetes are known for their inherent ability to produce pharmaceutically relevant secondary metabolites. Discovery of medically useful, yet novel compounds has become a great challenge due to frequent rediscovery of known compounds and a consequent decline in the number of relevant clinical trials in the last decades. A paradigm shift took place when the first whole genome sequences of streptomycetes became available, from which silent or "cryptic" biosynthetic gene clusters (BGCs) were discovered. Cryptic BGCs reveal a so far untapped potential of the microorganisms for the production of novel compounds, which has spurred new efforts in understanding the complex regulation between primary and secondary metabolism. This new trend has been accompanied with development of new computational resources (genome and compound mining tools), generation of various high-quality omics data, establishment of molecular tools, and other strain engineering strategies. They all come together to enable systems metabolic engineering of streptomycetes, allowing more systematic and efficient strain development. In this review, the authors present recent progresses within systems metabolic engineering of streptomycetes for uncovering their hidden potential to produce novel compounds and for the improved production of secondary metabolites. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Signatures of AGN feedback

NASA Astrophysics Data System (ADS)

Wylezalek, Dominika; Zakamska, Nadia L.; MaNGA-GMOS Team

2017-01-01

Feedback from actively accreting SMBHs (Active Galactic Nuclei, AGN) is now widely considered to be the main driver in regulating the growth of massive galaxies. Observational proof for this scenario has, however, been hard to come by. Many attempts at finding a conclusive observational proof that AGN may be able to quench star formation and regulate the host galaxies' growth have shown that this problem is highly complex.I will present results from several projects that focus on understanding the power, reach and impact of feedback processes exerted by AGN. I will describe recent efforts in our group of relating feedback signatures to the specific star formation rate in their host galaxies, where our results are consistent with the AGN having a `negative' impact through feedback on the galaxies' star formation history (Wylezalek+2016a,b). Furthermore, I will show that powerful AGN-driven winds can be easily hidden and not be apparent in the integrated spectrum of the galaxy. This implies that large IFU surveys, such as the SDSS-IV MaNGA survey, might uncover many previously unknown AGN and outflows that are potentially very relevant for understanding the role of AGN in galaxy evolution (Wylezalek+2016c)!

Flavor structure of the cosmic-ray electron/positron excesses at DAMPE

NASA Astrophysics Data System (ADS)

Ge, Shao-Feng; He, Hong-Jian; Wang, Yu-Chen

2018-06-01

The Dark Matter Particle Explorer (DAMPE) satellite detector announced its first result for measuring the cosmic-ray electron/positron (CRE) energy spectrum up to 4.6 TeV, including a tentative peak-like event excess at (1.3-1.5) TeV. In this work, we uncover a significant hidden excess in the DAMPE CRE spectrum over the energy range (0.6-1.1) TeV, which has a non-peak-like structure. We propose a new mechanism to explain this excess by a set of 1.5 TeV μ± events with subsequent decays into e± plus neutrinos. For explaining this new excess together with the peak excess around 1.4 TeV, we demonstrate that the flavor structure of the original lepton final-state produced by dark matter (DM) annihilations (or other mechanism) should have a composition ratio Ne : (Nμ + 1/6 Nτ) = 1 : y, with y ≃ 2.6- 10.8. For lepton portal DM models, this puts nontrivial constraint on the lepton-DM-mediator couplings λe : (λμ4 + 1/6 λτ4) 1/4 = 1 : y1/4 with a narrow range y1/4 ≃ 1.3- 1.8.

New axion and hidden photon constraints from a solar data global fit

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

Vinyoles, N.; Serenelli, A.; Isern, J.

2015-10-01

We present a new statistical analysis that combines helioseismology (sound speed, surface helium and convective radius) and solar neutrino observations (the {sup 8}B and {sup 7}Be fluxes) to place upper limits to the properties of non standard weakly interacting particles. Our analysis includes theoretical and observational errors, accounts for tensions between input parameters of solar models and can be easily extended to include other observational constraints. We present two applications to test the method: the well studied case of axions and axion-like particles and the more novel case of low mass hidden photons. For axions we obtain an upper limitmore » at 3σ for the axion-photon coupling constant of g{sub aγ} < 4.1 · 10{sup −10} GeV{sup −1}. For hidden photons we obtain the most restrictive upper limit available accross a wide range of masses for the product of the kinetic mixing and mass of χ m < 1.8 ⋅ 10{sup −12} eV at 3σ. Both cases improve the previous solar constraints based on the Standard Solar Models showing the power of using a global statistical approach.« less

Implementation of neural network for color properties of polycarbonates

NASA Astrophysics Data System (ADS)

Saeed, U.; Ahmad, S.; Alsadi, J.; Ross, D.; Rizvi, G.

2014-05-01

In present paper, the applicability of artificial neural networks (ANN) is investigated for color properties of plastics. The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. An optimal design is completed for 10, 12, 14,16,18 & 20 hidden neurons on single hidden layer with five different algorithms: batch gradient descent (GD), batch variable learning rate (GDX), resilient back-propagation (RP), scaled conjugate gradient (SCG), levenberg-marquardt (LM) in the feed forward back-propagation neural network model. The training data for ANN is obtained from experimental measurements. There were twenty two inputs including resins, additives & pigments while three tristimulus color values L*, a* and b* were used as output layer. Statistical analysis in terms of Root-Mean-Squared (RMS), absolute fraction of variance (R squared), as well as mean square error is used to investigate the performance of ANN. LM algorithm with fourteen neurons on hidden layer in Feed Forward Back-Propagation of ANN model has shown best result in the present study. The degree of accuracy of the ANN model in reduction of errors is proven acceptable in all statistical analysis and shown in results. However, it was concluded that ANN provides a feasible method in error reduction in specific color tristimulus values.

Photoacoustic imaging of hidden dental caries by using a fiber-based probing system

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2017-04-01

Photoacoustic method to detect hidden dental caries is proposed. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating laser light to occlusal surface of model tooth. By making a map of intensity of these high frequency components, photoacoustic images of hidden caries were successfully obtained. A photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for using clinical application, and clear photoacoustic image of hidden caries was also obtained by this system.

--No Title--

Science.gov Websites

;height:auto;overflow:hidden}.poc_table .top_row{background-color:#eee;height:auto;overflow:hidden}.poc_table ;background-color:#FFF;height:auto;overflow:hidden;border-top:1px solid #ccc}.poc_table .main_row .name :200px;padding:5px;height:auto;overflow:hidden}.tli_grey_box{background-color:#eaeaea;text-align:center

N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes.

PubMed

Li, Qike; Schissler, A Grant; Gardeux, Vincent; Achour, Ikbel; Kenost, Colleen; Berghout, Joanne; Li, Haiquan; Zhang, Hao Helen; Lussier, Yves A

2017-05-24

Transcriptome analytic tools are commonly used across patient cohorts to develop drugs and predict clinical outcomes. However, as precision medicine pursues more accurate and individualized treatment decisions, these methods are not designed to address single-patient transcriptome analyses. We previously developed and validated the N-of-1-pathways framework using two methods, Wilcoxon and Mahalanobis Distance (MD), for personal transcriptome analysis derived from a pair of samples of a single patient. Although, both methods uncover concordantly dysregulated pathways, they are not designed to detect dysregulated pathways with up- and down-regulated genes (bidirectional dysregulation) that are ubiquitous in biological systems. We developed N-of-1-pathways MixEnrich, a mixture model followed by a gene set enrichment test, to uncover bidirectional and concordantly dysregulated pathways one patient at a time. We assess its accuracy in a comprehensive simulation study and in a RNA-Seq data analysis of head and neck squamous cell carcinomas (HNSCCs). In presence of bidirectionally dysregulated genes in the pathway or in presence of high background noise, MixEnrich substantially outperforms previous single-subject transcriptome analysis methods, both in the simulation study and the HNSCCs data analysis (ROC Curves; higher true positive rates; lower false positive rates). Bidirectional and concordant dysregulated pathways uncovered by MixEnrich in each patient largely overlapped with the quasi-gold standard compared to other single-subject and cohort-based transcriptome analyses. The greater performance of MixEnrich presents an advantage over previous methods to meet the promise of providing accurate personal transcriptome analysis to support precision medicine at point of care.

Natural hidden antibodies reacting with DNA or cardiolipin bind to thymocytes and evoke their death.

PubMed

Zamulaeva, I A; Lekakh, I V; Kiseleva, V I; Gabai, V L; Saenko, A S; Shevchenko, A S; Poverenny, A M

1997-08-18

Both free and hidden natural antibodies to DNA or cardiolipin were obtained from immunoglobulins of a normal donor. The free antibodies reacting with DNA or cardiolipin were isolated by means of affinity chromatography. Antibodies occurring in an hidden state were disengaged from the depleted immunoglobulins by ion-exchange chromatography and were then affinity-isolated on DNA or cardiolipin sorbents. We used flow cytometry to study the ability of free and hidden antibodies to bind to rat thymocytes. Simultaneously, plasma membrane integrity was tested by propidium iodide (PI) exclusion. The hidden antibodies reacted with 65.2 +/- 10.9% of the thymocytes and caused a fast plasma membrane disruption. Cells (28.7 +/- 7.1%) were stained with PI after incubation with the hidden antibodies for 1 h. The free antibodies bound to a very small fraction of the thymocytes and did not evoke death as compared to control without antibodies. The possible reason for the observed effects is difference in reactivity of the free and hidden antibodies to phospholipids. While free antibodies reacted preferentially with phosphotidylcholine, hidden antibodies reacted with cardiolipin and phosphotidylserine.

Raising awareness of the hidden curriculum in veterinary medical education: a review and call for research.

PubMed

Whitcomb, Tiffany L

2014-01-01

The hidden curriculum is characterized by information that is tacitly conveyed to and among students about the cultural and moral environment in which they find themselves. Although the hidden curriculum is often defined as a distinct entity, tacit information is conveyed to students throughout all aspects of formal and informal curricula. This unconsciously communicated knowledge has been identified across a wide spectrum of educational environments and is known to have lasting and powerful impacts, both positive and negative. Recently, medical education research on the hidden curriculum of becoming a doctor has come to the forefront as institutions struggle with inconsistencies between formal and hidden curricula that hinder the practice of patient-centered medicine. Similarly, the complex ethical questions that arise during the practice and teaching of veterinary medicine have the potential to cause disagreement between what the institution sets out to teach and what is actually learned. However, the hidden curriculum remains largely unexplored for this field. Because the hidden curriculum is retained effectively by students, elucidating its underlying messages can be a key component of program refinement. A review of recent literature about the hidden curriculum in a variety of fields, including medical education, will be used to explore potential hidden curricula in veterinary medicine and draw attention to the need for further investigation.

A hidden Markov model approach to neuron firing patterns.

PubMed

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-11-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

PubMed Central

Friedman, Alexander; Slocum, Joshua F.; Tyulmankov, Danil; Gibb, Leif G.; Altshuler, Alex; Ruangwises, Suthee; Shi, Qinru; Toro Arana, Sebastian E.; Beck, Dirk W.; Sholes, Jacquelyn E. C.; Graybiel, Ann M.

2016-01-01

A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamically interact to bring about thought and action. Granger causality is a powerful tool for identifying linear interactions, but handling nonlinear interactions remains an unmet challenge. We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction strength analysis and decoding of networks with nonlinear interactions by including latent state variables for each node in the network. We compare NMHS to Granger causality in analyzing neural circuit recordings and simulations, improvised music, and sociodemographic data. We conclude that NMHS significantly extends the scope of analyses of multidimensional, nonlinear networks, notably in coping with the complexity of the brain. PMID:27222584

Under-reported data analysis with INAR-hidden Markov chains.

PubMed

Fernández-Fontelo, Amanda; Cabaña, Alejandra; Puig, Pedro; Moriña, David

2016-11-20

In this work, we deal with correlated under-reported data through INAR(1)-hidden Markov chain models. These models are very flexible and can be identified through its autocorrelation function, which has a very simple form. A naïve method of parameter estimation is proposed, jointly with the maximum likelihood method based on a revised version of the forward algorithm. The most-probable unobserved time series is reconstructed by means of the Viterbi algorithm. Several examples of application in the field of public health are discussed illustrating the utility of the models. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

The perception of the hidden curriculum on medical education: an exploratory study

PubMed Central

2009-01-01

Background Major curriculum reform of undergraduate medical education occurred during the past decades in the United Kingdom (UK); however, the effects of the hidden curriculum, which influence the choice of primary care as a career, have not been sufficiently recognized. While Japan, where traditionally few institutions systematically foster primary care physicians and very few have truly embraced family medicine as their guiding discipline, has also experienced meaningful curriculum reform, the effect of the hidden curriculum is not well known. The aim of this study is to identify themes pertaining to the students' perceptions of the hidden curriculum affecting undergraduate medical education in bedside learning in Japan. Methods Semi-structured interviews with thematic content analysis were implemented. Undergraduate year-5 students from a Japanese medical school at a Japanese teaching hospital were recruited. Interview were planned to last between 30 to 60 minutes each, over an 8-month period in 2007. The interviewees' perceptions concerning the quality of teaching in their bedside learning and related experiences were collected and analysed thematically. Results Twenty five medical students (18 males and 7 females, mean age 25 years old) consented to participate in the interviews, and seven main themes emerged: "the perception of education as having a low priority," "the prevalence of positive/negative role models," "the persistence of hierarchy and exclusivity," "the existence of gender issues," "an overburdened medical knowledge," "human relationships with colleagues and medical team members," and "first experience from the practical wards and their patients." Conclusions Both similarities and differences were found when comparing the results to those of previous studies in the UK. Some effects of the hidden curriculum in medical education likely exist in common between the UK and Japan, despite the differences in their demographic backgrounds, cultures and philosophies. PMID:20003462

A Computational Network Biology Approach to Uncover Novel Genes Related to Alzheimer's Disease.

PubMed

Zanzoni, Andreas

2016-01-01

Recent advances in the fields of genetics and genomics have enabled the identification of numerous Alzheimer's disease (AD) candidate genes, although for many of them the role in AD pathophysiology has not been uncovered yet. Concomitantly, network biology studies have shown a strong link between protein network connectivity and disease. In this chapter I describe a computational approach that, by combining local and global network analysis strategies, allows the formulation of novel hypotheses on the molecular mechanisms involved in AD and prioritizes candidate genes for further functional studies.

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks

PubMed Central

Jang, Hojin; Plis, Sergey M.; Calhoun, Vince D.; Lee, Jong-Hwan

2016-01-01

Feedforward deep neural networks (DNN), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean ± standard deviation; %) of 6.9 (± 3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4 ± 4.6) and the two-layer network (7.4 ± 4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. PMID:27079534

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

PubMed

Jang, Hojin; Plis, Sergey M; Calhoun, Vince D; Lee, Jong-Hwan

2017-01-15

Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. Copyright © 2016 Elsevier Inc. All rights reserved.

Heating up the Galaxy with hidden photons

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

Dubovsky, Sergei; Hernández-Chifflet, Guzmán, E-mail: dubovsky@nyu.edu, E-mail: ghc236@nyu.edu

2015-12-01

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Heating up the Galaxy with hidden photons

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

Dubovsky, Sergei; Hernández-Chifflet, Guzmán; Instituto de Física, Facultad de Ingeniería, Universidad de la República,Montevideo, 11300

2015-12-29

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Schools in Ethnolinguistic Minorities.

ERIC Educational Resources Information Center

Byram, Michael

1986-01-01

Discusses the school's contribution to the transmission of cultural heritage, focusing on curriculum content rather than on language issues. The kind of conceptual framework within which overt and hidden curriculum analysis might be carried out is suggested. (SED)

Artificial Intelligence Assists Ultrasonic Inspection

NASA Technical Reports Server (NTRS)

Schaefer, Lloyd A.; Willenberg, James D.

1992-01-01

Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

"Invisible" conformers of an antifungal disulfide protein revealed by constrained cold and heat unfolding, CEST-NMR experiments, and molecular dynamics calculations.

PubMed

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-03-23

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20-40 % at 298 K in a disulfide-rich protein. In addition, sensitive (15) N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR "dark matter". Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-01-01

Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS's hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs' spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets.

An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents

ERIC Educational Resources Information Center

Hwang, Heungsun; Montreal, Hec; Dillon, William R.; Takane, Yoshio

2006-01-01

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

"It's Not Always What It Seems": Exploring the Hidden Curriculum within a Doctoral Program

ERIC Educational Resources Information Center

Foot, Rachel Elizabeth

2017-01-01

The purpose of this qualitative, naturalistic study was to explore the ways in which hidden curriculum might influence doctoral student success. Two questions guided the study: (a) How do doctoral students experience the hidden curriculum? (b) What forms of hidden curricula can be identified in a PhD program? Data were collected from twelve…

Hidden Farmworker Labor Camps in North Carolina: An Indicator of Structural Vulnerability

PubMed Central

Summers, Phillip; Quandt, Sara A.; Talton, Jennifer W.; Galván, Leonardo

2015-01-01

Objectives. We used geographic information systems (GIS) to delineate whether farmworker labor camps were hidden and to determine whether hidden camps differed from visible camps in terms of physical and resident characteristics. Methods. We collected data using observation, interview, and public domain GIS data for 180 farmworker labor camps in east central North Carolina. A hidden camp was defined as one that was at least 0.15 miles from an all-weather road or located behind natural or manufactured objects. Hidden camps were compared with visible camps in terms of physical and resident characteristics. Results. More than one third (37.8%) of the farmworker labor camps were hidden. Hidden camps were significantly larger (42.7% vs 17.0% with 21 or more residents; P ≤ .001; and 29.4% vs 13.5% with 3 or more dwellings; P = .002) and were more likely to include barracks (50% vs 19.6%; P ≤ .001) than were visible camps. Conclusions. Poor housing conditions in farmworker labor camps often go unnoticed because they are hidden in the rural landscape, increasing farmworker vulnerability. Policies that promote greater community engagement with farmworker labor camp residents to reduce structural vulnerability should be considered. PMID:26469658

Community perceptions of the social determinants of child health in Western Cape, South Africa: neglect as a major indicator of child health and wellness.

PubMed

Kadir, Ayesha; Marais, Frederick; Desmond, Nicola

2013-11-01

Worldwide, neglect is the most common form of child maltreatment. Data on neglect are scarce in low- and middle-income countries, and almost no qualitative research includes the voices of children. The main objective was to understand community perceptions of the social determinants of child health. The study was also intended to test the feasibility of health professionals undertaking qualitative studies of the social determinants of child health which can be used to inform clinical care and policy. The target population was people living in deprived circumstances in rural South Africa. Data collected included focus group discussions with children and adults, children's drawings, semi-structured in-depth interviews, documentary review and transect drives. Purposive sampling of poorer households was done. Recurring themes were explored using a continuous repetitive process. Data were examined using framework analysis. The main finding was that neglect owing to substance abuse was a major predictor of poor child health and wellness. This sensitive topic was introduced by children, who created a platform for discussion with and among adult participants. Adults attributed neglect to a breakdown in family structure and changing norms regarding the responsibilities of parents. Community programmes were cited by children as a source of support, while some adults felt they undermined parental responsibility. Understanding social arrangements and community support structures is best achieved at community level through a participatory, qualitative approach. These methods also enable the views of children to inform the findings. Children's input will help uncover neglect and other hidden predictors of challenges to child health, and promote a rights-based approach to care and research.

Identification and reassessment of the specific status of some tropical freshwater midges (Diptera: Chironomidae) using DNA barcode data.

PubMed

Pramual, Pairot; Simwisat, Kusumart; Martin, Jon

2016-01-28

Chironomidae are a highly diverse group of insects. Members of this family are often included in programs monitoring the health of freshwater ecosystems. However, a difficulty in morphological identification, particularly of larval stages is the major obstacle to this application. In this study, we tested the efficiency of mitochondrial cytochrome c oxidase I (COI) sequences as the DNA barcoding region for species identification of Chironomidae in Thailand. The results revealed 14 species with a high success rate (>90%) for the correct species identification, which suggests the potential usefulness of the technique. However, some morphological species possess high (>3%) intraspecific genetic divergence that suggests these species could be species complexes and need further morphological or cytological examination. Sequence-based species delimitation analyses indicated that most specimens identified as Chironomus kiiensis, Tokunaga 1936, in Japan are conspecific with C. striatipennis, Kieffer 1912, although a small number form a separate cluster. A review of the descriptions of Kiefferulus tainanus (Kieffer 1912) and its junior synonym, K. biroi (Kieffer 1918), following our results, suggests that this synonymy is probably not correct and that K. tainanus occurs in Japan, China and Singapore, while K. biroi occurs in India and Thailand. Our results therefore revealed the usefulness of DNA barcoding for correct species identification of Chironomidae, particularly the immature stages. In addition, DNA barcodes could also uncover hidden diversity that can guide further taxonomic study, and offer a more efficient way to identify species than morphological analysis where large numbers of specimens are involved, provided the identifications of DNA barcodes in the databases are correct. Our studies indicate that this is not the case, and we identify cases of misidentifications for C. flaviplumus, Tokunaga 1940 and K. tainanus.

Global gamesmanship.

PubMed

MacMillan, Ian C; van Putten, Alexander B; McGrath, Rita Gunther

2003-05-01

Competition among multinationals these days is likely to be a three-dimensional game of global chess: The moves an organization makes in one market are designed to achieve goals in another in ways that aren't immediately apparent to its rivals. The authors--all management professors-call this approach "competing under strategic interdependence," or CSI. And where this interdependence exists, the complexity of the situation can quickly overwhelm ordinary analysis. Indeed, most business strategists are terrible at anticipating the consequences of interdependent choices, and they're even worse at using interdependency to their advantage. In this article, the authors offer a process for mapping the competitive landscape and anticipating how your company's moves in one market can influence its competitive interactions in others. They outline the six types of CSI campaigns--onslaughts, contests, guerrilla campaigns, feints, gambits, and harvesting--available to any multiproduct or multimarket corporation that wants to compete skillfully. They cite real-world examples such as the U.S. pricing battle Philip Morris waged with R.J. Reynolds--not to gain market share in the domestic cigarette market but to divert R.J. Reynolds's resources and attention from the opportunities Philip Morris was pursuing in Eastern Europe. And, using data they collected from their studies of consumer-products companies Procter & Gamble and Unilever, the authors describe how to create CSI tables and bubble charts that present a graphical look at the competitive landscape and that may uncover previously hidden opportunities. The CSI mapping process isn't just for global corporations, the authors explain. Smaller organizations that compete with a portfolio of products in just one national or regional market may find it just as useful for planning their next business moves.

A case study of an unknown mass grave - Hostages killed 70 years ago by a Nazi firing squad identified thanks to genetics.

PubMed

Ossowski, Andrzej; Diepenbroek, Marta; Zwolski, Marcin; Falis, Adam; Wróbel, Maria; Bykowska-Witowska, Milena; Zielińska, Grażyna; Szargut, Maria; Kupiec, Tomasz

2017-09-01

Almost 6 million people died in Poland during the Nazi occupation and about 570 thousand during the Soviet occupation. But the end of the war was not the end of the trauma. Historians estimate that at least 30 thousand people were killed during the Stalinist regime in Poland. In 2012 the Institute of National Remembrance started to search for hidden burials of victims of communism. Many exhumations were carried out under the project. One of them took place in Białystok, eastern Poland. According to information gathered by local historians, a detention centre in the heart of city was the place of secret burials of victims of the communist regime. During the exhumation work a burial pit with the remains of 24 victims was found. It's characteristics supported the hypothesis that these people were shot on the spot, in a mass execution during the Nazi occupation. Historians knew of only one such execution, but its victims - according to the available records - were supposed to have been exhumed at the end of the war. Exhumation works and the discovery of the discussed mass grave put in question the events of 1944, which would have been impossible without the field work. The first identifications confirmed the doubts of historians, since both the results of genetic profiling and the conducted anthropological analysis revealed that at the end of the war a mistake was made, and bodies other than those suspected had been exhumed. Having established this fact, the mass grave created at that time should be investigated to reveal the identity of the remains uncovered then. Copyright © 2017 Elsevier B.V. All rights reserved.

Psychiatry and emergency medicine: medical student and physician attitudes toward homeless persons.

PubMed

Morrison, Ann; Roman, Brenda; Borges, Nicole

2012-05-01

The purpose of the study was to explore changes in medical students' attitudes toward homeless persons during the Psychiatry and Emergency Medicine clerkships. Simultaneously, this study explored attitudes toward homeless persons held by Psychiatry and Emergency Medicine residents and faculty in an attempt to uncover the "hidden curriculum" in medical education, in which values are communicated from teacher to student outside of the formal instruction. A group of 79 students on Psychiatry and 66 on Emergency Medicine clerkships were surveyed at the beginning and end of their rotation regarding their attitudes toward homeless persons by use of the Health Professionals' Attitudes Toward the Homeless Inventory (HPATHI). The HPATHI was also administered to 31 Psychiatry residents and faculty and 41 Emergency Medicine residents and faculty one time during the course of this study. For Psychiatry clerks, t-tests showed significant differences pre- and post-clerkship experiences on 2 of the 23 items on the HPATHI. No statistically significant differences were noted for the Emergency Medicine students. An analysis of variance revealed statistically significant differences on 7 out of the 23 survey questions for residents and faculty in Psychiatry, as compared with those in Emergency Medicine. Results suggest that medical students showed small differences in their attitudes toward homeless people following clerkships in Psychiatry but not in Emergency Medicine. Regarding resident and faculty results, significant differences between specialties were noted, with Psychiatry residents and faculty exhibiting more favorable attitudes toward homeless persons than residents and faculty in Emergency Medicine. Given that medical student competencies should be addressing the broader social issues of homelessness, medical schools need to first understand the attitudes of medical students to such issues, and then develop curricula to overcome inaccurate or stigmatizing beliefs.

Mapping the emotional face. How individual face parts contribute to successful emotion recognition.

PubMed

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation.

Mapping the emotional face. How individual face parts contribute to successful emotion recognition

PubMed Central

Wegrzyn, Martin; Vogt, Maria; Kireclioglu, Berna; Schneider, Julia; Kissler, Johanna

2017-01-01

Which facial features allow human observers to successfully recognize expressions of emotion? While the eyes and mouth have been frequently shown to be of high importance, research on facial action units has made more precise predictions about the areas involved in displaying each emotion. The present research investigated on a fine-grained level, which physical features are most relied on when decoding facial expressions. In the experiment, individual faces expressing the basic emotions according to Ekman were hidden behind a mask of 48 tiles, which was sequentially uncovered. Participants were instructed to stop the sequence as soon as they recognized the facial expression and assign it the correct label. For each part of the face, its contribution to successful recognition was computed, allowing to visualize the importance of different face areas for each expression. Overall, observers were mostly relying on the eye and mouth regions when successfully recognizing an emotion. Furthermore, the difference in the importance of eyes and mouth allowed to group the expressions in a continuous space, ranging from sadness and fear (reliance on the eyes) to disgust and happiness (mouth). The face parts with highest diagnostic value for expression identification were typically located in areas corresponding to action units from the facial action coding system. A similarity analysis of the usefulness of different face parts for expression recognition demonstrated that faces cluster according to the emotion they express, rather than by low-level physical features. Also, expressions relying more on the eyes or mouth region were in close proximity in the constructed similarity space. These analyses help to better understand how human observers process expressions of emotion, by delineating the mapping from facial features to psychological representation. PMID:28493921

Look beyond one's own nose: combination of information from publicly available sources reveals an association of GATA4 polymorphisms with plasma triglycerides.

PubMed

Lamina, Claudia; Coassin, Stefan; Illig, Thomas; Kronenberg, Florian

2011-12-01

GATA4iKO mice exhibit impeded triglyceride absorption from intestine and decreased plasma triglyceride levels. Data in humans are lacking. We hypothesized that triglyceride levels might also be regulated by polymorphisms in the GATA4 gene in humans. We used publicly available data from different sources to evaluate this hypothesis. Our approach is a more often applicable advance to uncover associations and their functional implications which would have been otherwise missed by standard genome-wide association studies (GWAS). We used the publicly available GWAS results from 137 SNPs in the GATA4 region for triglyceride levels. We embedded these results into the comprehensive functional genomics data provided in the UCSC Genome Browser including among others information on regulatory elements and interspecies conservation. A concise graphical presentation is proposed together with an R function for automatic data preparation. This process is presented in an educational manner using a screencast to become most useful for other researchers. We observed several polymorphisms in and around the GATA4 gene which have a significant influence on plasma triglyceride levels with the lowest p-value at SNP rs1466785 (Bonferroni-corrected p-value = 1.76e-5). The bioinformatic evaluation of this locus in publicly available functional genomics data provided converging evidence for the presence of a transcriptional regulator downstream of GATA4. The combination of different sources of data has revealed an association of GATA4 with triglyceride levels in humans. Our evaluation exemplifies how an integrative analysis including both statistical and biological perspectives can shed new light on available association data and reveals novel candidate genes, which are otherwise hidden in the noisy region below genome-wide significance. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

NASA Technical Reports Server (NTRS)

Kempler, Steven; Barbieri, Lindsay

2016-01-01

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

Zipf exponent of trajectory distribution in the hidden Markov model

NASA Astrophysics Data System (ADS)

Bochkarev, V. V.; Lerner, E. Yu

2014-03-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.

Moving beyond "Shut up and Learn"

ERIC Educational Resources Information Center

Watkins, Chris

2016-01-01

This article analyses the sort of classroom talk that leads to effective learning, and some of the forces which operate against such practices. It starts with an analysis of the classroom context and the dominant patterns of interaction. These cause processes of learning to be hidden. It then develops by an analysis of effective learning,…

CT scanning analysis of Megantereon whitei (Carnivora, Machairodontinae) from Monte Argentario (Early Pleistocene, central Italy): evidence of atavistic teeth

NASA Astrophysics Data System (ADS)

Iurino, Dawid Adam; Sardella, Raffaele

2014-12-01

CT scanning analysis applied to vertebrate palaeontology is providing an increasing number of data of great interest. This method can be used in many branches of palaeontology such as the investigation of all the fossilized elements in a hard matrix and the hidden structures in the bones. A large number of pathologies are "hidden", completely or partially invisible on the external surface of the bones because their development took place within the bones. However, the study of these diseases and abnormalities plays a crucial role in our understanding of evolutionary and adaptive processes of extinct taxa. The analysis of a partial skeleton of the sabre-toothed felid Megantereon whitei from the Early Pleistocene karst filling deposits of Monte Argentario (Tuscany, Italy) has been carried out. The CT scanning analysis put in evidence the presence of supernumerary teeth (P2) and the absence of P3 in the mandible. The occurrence of P2 can be considered as an evidence of atavism. Such an archaic feature is recorded for the first time in Megantereon.

Economic cycles and their synchronization: Spectral analysis of macroeconomic series from Italy, The Netherlands, and the UK

NASA Astrophysics Data System (ADS)

Sella, Lisa; Vivaldo, Gianna; Ghil, Michael; Groth, Andreas

2010-05-01

The present work applies several advanced spectral methods (Ghil et al., Rev. Geophys., 2002) to the analysis of macroeconomic fluctuations in Italy, The Netherlands, and the United Kingdom. These methods provide valuable time-and-frequency-domain tools that complement traditional time-domain analysis, and are thus fairly well known by now in the geosciences and life sciences, but not yet widespread in quantitative economics. In particular, they enable the identification and characterization of nonlinear trends and dominant cycles --- including low-frequency and seasonal components --- that characterize the behavior of each time series. We explore five fundamental indicators of the real (i.e., non-monetary), aggregate economy --- namely gross domestic product (GDP), consumption, fixed investments, exports and imports --- in a univariate as well as multivariate setting. A single-channel analysis by means of three independent spectral methods --- singular spectrum analysis (SSA), the multi-taper method (MTM), and the maximum-entropy method (MEM) --- reveals very similar near-annual cycles, as well as several longer periodicities, in the macroeconomic indicators of all the countries analyzed. Since each indicator represents different features of an economic system, we combine them to infer if common oscillatory modes are present, either among different indicators within the same country or among the same indicators across different countries. Multichannel-SSA (M-SSA) reinforces the previous results, and shows that the common modes agree in character with solutions of a non-equilibrium dynamic model (NEDyM) that produces endogenous business cycles (Hallegatte et al., JEBO, 2008). The presence of these modes in NEDyM results from adjustment delays and other nonequilibrium effects that were added to a neoclassical Solow (Q. J. Econ., 1956) growth model. Their confirmation by the present analysis has important consequences for the net impact of natural disasters on the economy of a country: Hallegatte and Ghil (Ecol. Econ., 2008) have shown that the presence of business cycles modifies substantially this impact with respect to their impact on an economy in or near equilibrium. The present work concludes with a study of the synchronization of economic fluctuations, which follows a similar study of macroeconomic indicators for the United States, presented in a nearby poster. Since business cycles are not country-specific phenomena, but show common characteristics across countries, our aim is to uncover hidden global behavior across the European economies (cf. Mazzi and Savio, Macmillan, 2006).

Adaptive distributed source coding.

PubMed

Varodayan, David; Lin, Yao-Chung; Girod, Bernd

2012-05-01

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.

Tracking problem solving by multivariate pattern analysis and Hidden Markov Model algorithms.

PubMed

Anderson, John R

2012-03-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application involves using fMRI activity to track what students are doing as they solve a sequence of algebra problems. The methodology achieves considerable accuracy at determining both what problem-solving step the students are taking and whether they are performing that step correctly. The second "model discovery" application involves using statistical model evaluation to determine how many substates are involved in performing a step of algebraic problem solving. This research indicates that different steps involve different numbers of substates and these substates are associated with different fluency in algebra problem solving. Copyright © 2011 Elsevier Ltd. All rights reserved.

Hidden corrosion detection in aircraft aluminum structures using laser ultrasonics and wavelet transform signal analysis.

PubMed

Silva, M Z; Gouyon, R; Lepoutre, F

2003-06-01

Preliminary results of hidden corrosion detection in aircraft aluminum structures using a noncontact laser based ultrasonic technique are presented. A short laser pulse focused to a line spot is used as a broadband source of ultrasonic guided waves in an aluminum 2024 sample cut from an aircraft structure and prepared with artificially corroded circular areas on its back surface. The out of plane surface displacements produced by the propagating ultrasonic waves were detected with a heterodyne Mach-Zehnder interferometer. Time-frequency analysis of the signals using a continuous wavelet transform allowed the identification of the generated Lamb modes by comparison with the calculated dispersion curves. The presence of back surface corrosion was detected by noting the loss of the S(1) mode near its cutoff frequency. This method is applicable to fast scanning inspection techniques and it is particularly suited for early corrosion detection.

A hidden Markov model approach to neuron firing patterns.

PubMed Central

Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G

1996-01-01

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing. Images FIGURE 3 PMID:8913581

Complementary Proteomic and Biochemical Analysis of Peptidases in Lobster Gastric Juice Uncovers the Functional Role of Individual Enzymes in Food Digestion.

PubMed

Bibo-Verdugo, Betsaida; O'Donoghue, Anthony J; Rojo-Arreola, Liliana; Craik, Charles S; García-Carreño, Fernando

2016-04-01

Crustaceans are a diverse group, distributed in widely variable environmental conditions for which they show an equally extensive range of biochemical adaptations. Some digestive enzymes have been studied by purification/characterization approaches. However, global analysis is crucial to understand how digestive enzymes interplay. Here, we present the first proteomic analysis of the digestive fluid from a crustacean (Homarus americanus) and identify glycosidases and peptidases as the most abundant classes of hydrolytic enzymes. The digestion pathway of complex carbohydrates was predicted by comparing the lobster enzymes to similar enzymes from other crustaceans. A novel and unbiased substrate profiling approach was used to uncover the global proteolytic specificity of gastric juice and determine the contribution of cysteine and aspartic acid peptidases. These enzymes were separated by gel electrophoresis and their individual substrate specificities uncovered from the resulting gel bands. This new technique is called zymoMSP. Each cysteine peptidase cleaves a set of unique peptide bonds and the S2 pocket determines their substrate specificity. Finally, affinity chromatography was used to enrich for a digestive cathepsin D1 to compare its substrate specificity and cold-adapted enzymatic properties to mammalian enzymes. We conclude that the H. americanus digestive peptidases may have useful therapeutic applications, due to their cold-adaptation properties and ability to hydrolyze collagen.

A composite model for the 750 GeV diphoton excess

DOE PAGES

Harigaya, Keisuke; Nomura, Yasunori

2016-03-14

We study a simple model in which the recently reported 750 GeV diphoton excess arises from a composite pseudo Nambu-Goldstone boson — hidden pion — produced by gluon fusion and decaying into two photons. The model only introduces an extra hidden gauge group at the TeV scale with a vectorlike quark in the bifundamental representation of the hidden and standard model gauge groups. We calculate the masses of all the hidden pions and analyze their experimental signatures and constraints. We find that two colored hidden pions must be near the current experimental limits, and hence are probed in the nearmore » future. We study physics of would-be stable particles — the composite states that do not decay purely by the hidden and standard model gauge dynamics — in detail, including constraints from cosmology. We discuss possible theoretical structures above the TeV scale, e.g. conformal dynamics and supersymmetry, and their phenomenological implications. We also discuss an extension of the minimal model in which there is an extra hidden quark that is singlet under the standard model and has a mass smaller than the hidden dynamical scale. This provides two standard model singlet hidden pions that can both be viewed as diphoton/diboson resonances produced by gluon fusion. We discuss several scenarios in which these (and other) resonances can be used to explain various excesses seen in the LHC data.« less

Hidden pattern discovery on epileptic EEG with 1-D local binary patterns and epileptic seizures detection by grey relational analysis.

PubMed

Kaya, Yılmaz

2015-09-01

This paper proposes a novel approach to detect epilepsy seizures by using Electroencephalography (EEG), which is one of the most common methods for the diagnosis of epilepsy, based on 1-Dimension Local Binary Pattern (1D-LBP) and grey relational analysis (GRA) methods. The main aim of this paper is to evaluate and validate a novel approach, which is a computer-based quantitative EEG analyzing method and based on grey systems, aimed to help decision-maker. In this study, 1D-LBP, which utilizes all data points, was employed for extracting features in raw EEG signals, Fisher score (FS) was employed to select the representative features, which can also be determined as hidden patterns. Additionally, GRA is performed to classify EEG signals through these Fisher scored features. The experimental results of the proposed approach, which was employed in a public dataset for validation, showed that it has a high accuracy in identifying epileptic EEG signals. For various combinations of epileptic EEG, such as A-E, B-E, C-E, D-E, and A-D clusters, 100, 96, 100, 99.00 and 100% were achieved, respectively. Also, this work presents an attempt to develop a new general-purpose hidden pattern determination scheme, which can be utilized for different categories of time-varying signals.

Radio for hidden-photon dark matter detection

DOE PAGES

Chaudhuri, Saptarshi; Graham, Peter W.; Irwin, Kent; ...

2015-10-08

We propose a resonant electromagnetic detector to search for hidden-photon dark matter over an extensive range of masses. Hidden-photon dark matter can be described as a weakly coupled “hidden electric field,” oscillating at a frequency fixed by the mass, and able to penetrate any shielding. At low frequencies (compared to the inverse size of the shielding), we find that the observable effect of the hidden photon inside any shielding is a real, oscillating magnetic field. We outline experimental setups designed to search for hidden-photon dark matter, using a tunable, resonant LC circuit designed to couple to this magnetic field. Ourmore » “straw man” setups take into consideration resonator design, readout architecture and noise estimates. At high frequencies, there is an upper limit to the useful size of a single resonator set by 1/ν. However, many resonators may be multiplexed within a hidden-photon coherence length to increase the sensitivity in this regime. Hidden-photon dark matter has an enormous range of possible frequencies, but current experiments search only over a few narrow pieces of that range. As a result, we find the potential sensitivity of our proposal is many orders of magnitude beyond current limits over an extensive range of frequencies, from 100 Hz up to 700 GHz and potentially higher.« less

Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data

PubMed Central

2017-01-01

Mapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into consideration hidden confounders and weak regulations. Findr outperformed existing methods on the DREAM5 Systems Genetics challenge and on the prediction of microRNA and transcription factor targets in human lymphoblastoid cells, while being nearly a million times faster. Findr is publicly available at https://github.com/lingfeiwang/findr. PMID:28821014

Pitowsky's Kolmogorovian Models and Super-determinism.

PubMed

Kellner, Jakob

2017-01-01

In an attempt to demonstrate that local hidden variables are mathematically possible, Pitowsky constructed "spin-[Formula: see text] functions" and later "Kolmogorovian models", which employs a nonstandard notion of probability. We describe Pitowsky's analysis and argue (with the benefit of hindsight) that his notion of hidden variables is in fact just super-determinism (and accordingly physically not relevant). Pitowsky's first construction uses the Continuum Hypothesis. Farah and Magidor took this as an indication that at some stage physics might give arguments for or against adopting specific new axioms of set theory. We would rather argue that it supports the opposing view, i.e., the widespread intuition "if you need a non-measurable function, it is physically irrelevant".

Molecular analysis reveals hidden diversity in Zungaro (Siluriformes: Pimelodidade): a genus of giant South American catfish.

PubMed

Pires, Antonio A; Ramirez, Jorge L; Galetti, Pedro M; Troy, Waldo P; Freitas, Patricia D

2017-06-01

The genus Zungaro contains some of the largest catfish in South America. Two valid species are currently recognized: Zungaro jahu, inhabiting the Paraná and Paraguay basins, and Zungaro zungaro, occurring in the Amazonas and Orinoco basins. Analysing Zungaro specimens from the Amazonas, Orinoco, Paraguay and Paraná basins, based on the sequencing of COI and D-loop, we found at least three MOTUs, indicating the existence of hidden diversity within this fish group. Considering the ecological and economic values of this fish, our results are surely welcomed for its conservation, disclosing new findings on its diversity and pointing out the necessity for a detailed taxonomic revision.

Use of Partial Least Squares improves the efficacy of removing unwanted variability in differential expression analyses based on RNA-Seq data.

PubMed

Chakraborty, Sutirtha

2018-05-26

RNA-Seq technology has revolutionized the face of gene expression profiling by generating read count data measuring the transcript abundances for each queried gene on multiple experimental subjects. But on the downside, the underlying technical artefacts and hidden biological profiles of the samples generate a wide variety of latent effects that may potentially distort the actual transcript/gene expression signals. Standard normalization techniques fail to correct for these hidden variables and lead to flawed downstream analyses. In this work I demonstrate the use of Partial Least Squares (built as an R package 'SVAPLSseq') to correct for the traces of extraneous variability in RNA-Seq data. A novel and thorough comparative analysis of the PLS based method is presented along with some of the other popularly used approaches for latent variable correction in RNA-Seq. Overall, the method is found to achieve a substantially improved estimation of the hidden effect signatures in the RNA-Seq transcriptome expression landscape compared to other available techniques. Copyright © 2017. Published by Elsevier Inc.

PCSYS: The optimal design integration system picture drawing system with hidden line algorithm capability for aerospace vehicle configurations

NASA Technical Reports Server (NTRS)

Hague, D. S.; Vanderburg, J. D.

1977-01-01

A vehicle geometric definition based upon quadrilateral surface elements to produce realistic pictures of an aerospace vehicle. The PCSYS programs can be used to visually check geometric data input, monitor geometric perturbations, and to visualize the complex spatial inter-relationships between the internal and external vehicle components. PCSYS has two major component programs. The between program, IMAGE, draws a complex aerospace vehicle pictorial representation based on either an approximate but rapid hidden line algorithm or without any hidden line algorithm. The second program, HIDDEN, draws a vehicle representation using an accurate but time consuming hidden line algorithm.

Text Analysis of Chemistry Thesis and Dissertation Titles

ERIC Educational Resources Information Center

Scalfani, Vincent F.

2017-01-01

Programmatic text analysis can be used to understand patterns and reveal trends in data that would otherwise be difficult or impossible to uncover with manual coding methods. This work uses programmatic text analysis, specifically term frequency counts, to study nearly 10,000 chemistry thesis and dissertation titles from 1911-2015. The thesis and…

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

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

Phases of cannibal dark matter

NASA Astrophysics Data System (ADS)

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; Trevisan, Gabriele

2016-12-01

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector is cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.

Phases of cannibal dark matter

DOE PAGES

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; ...

2016-12-13

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

What Can We Learn about Mental Health Needs from Tweets Mentioning Dementia on World Alzheimer’s Day?

PubMed Central

Yoon, Sunmoo

2017-01-01

Background Twitter can address the mental health challenges of dementia care. The aims of this study is to explore the contents and user interactions of tweets mentioning dementia to gain insights for dementia care. Methods We collected 35,260 tweets mentioning Alzheimer’s or dementia on World Alzheimer’s Day, September 21st in 2015. Topic modeling and social network analysis were applied to uncover content and structure of user communication. Results Global users generated keywords related to mental health and care including #psychology and #mental health. There were similarities and differences between the UK and the US in tweet content. The macro-level analysis uncovered substantial public interest on dementia. The meso-level network analysis revealed that top leaders of communities were spiritual organizations and traditional media. Conclusions The application of topic modeling and multi-level network analysis while incorporating visualization techniques can promote a global level understanding regarding public attention, interests, and insights regarding dementia care and mental health. PMID:27803262

Evaluation of chronic lymphocytic leukemia by oligonucleotide-based microarray analysis uncovers novel aberrations not detected by FISH or cytogenetic analysis

PubMed Central

2011-01-01

Background Cytogenetic evaluation is a key component of the diagnosis and prognosis of chronic lymphocytic leukemia (CLL). We performed oligonucleotide-based comparative genomic hybridization microarray analysis on 34 samples with CLL and known abnormal karyotypes previously determined by cytogenetics and/or fluorescence in situ hybridization (FISH). Results Using a custom designed microarray that targets >1800 genes involved in hematologic disease and other malignancies, we identified additional cryptic aberrations and novel findings in 59% of cases. These included gains and losses of genes associated with cell cycle regulation, apoptosis and susceptibility loci on 3p21.31, 5q35.2q35.3, 10q23.31q23.33, 11q22.3, and 22q11.23. Conclusions Our results show that microarray analysis will detect known aberrations, including microscopic and cryptic alterations. In addition, novel genomic changes will be uncovered that may become important prognostic predictors or treatment targets for CLL in the future. PMID:22087757

Out of Reach, Out of Mind? Infants' Comprehension of References to Hidden Inaccessible Objects.

PubMed

Osina, Maria A; Saylor, Megan M; Ganea, Patricia A

2017-09-01

This study investigated the nature of infants' difficulty understanding references to hidden inaccessible objects. Twelve-month-old infants (N = 32) responded to the mention of objects by looking at, pointing at, or approaching them when the referents were visible or accessible, but not when they were hidden and inaccessible (Experiment I). Twelve-month-olds (N = 16) responded robustly when a container with the hidden referent was moved from a previously inaccessible position to an accessible position before the request, but failed to respond when the reverse occurred (Experiment II). This suggests that infants might be able to track the hidden object's dislocations and update its accessibility as it changes. Knowing the hidden object is currently inaccessible inhibits their responding. Older, 16-month-old (N = 17) infants' performance was not affected by object accessibility. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Automatic classification of animal vocalizations

NASA Astrophysics Data System (ADS)

Clemins, Patrick J.

2005-11-01

Bioacoustics, the study of animal vocalizations, has begun to use increasingly sophisticated analysis techniques in recent years. Some common tasks in bioacoustics are repertoire determination, call detection, individual identification, stress detection, and behavior correlation. Each research study, however, uses a wide variety of different measured variables, called features, and classification systems to accomplish these tasks. The well-established field of human speech processing has developed a number of different techniques to perform many of the aforementioned bioacoustics tasks. Melfrequency cepstral coefficients (MFCCs) and perceptual linear prediction (PLP) coefficients are two popular feature sets. The hidden Markov model (HMM), a statistical model similar to a finite autonoma machine, is the most commonly used supervised classification model and is capable of modeling both temporal and spectral variations. This research designs a framework that applies models from human speech processing for bioacoustic analysis tasks. The development of the generalized perceptual linear prediction (gPLP) feature extraction model is one of the more important novel contributions of the framework. Perceptual information from the species under study can be incorporated into the gPLP feature extraction model to represent the vocalizations as the animals might perceive them. By including this perceptual information and modifying parameters of the HMM classification system, this framework can be applied to a wide range of species. The effectiveness of the framework is shown by analyzing African elephant and beluga whale vocalizations. The features extracted from the African elephant data are used as input to a supervised classification system and compared to results from traditional statistical tests. The gPLP features extracted from the beluga whale data are used in an unsupervised classification system and the results are compared to labels assigned by experts. The development of a framework from which to build animal vocalization classifiers will provide bioacoustics researchers with a consistent platform to analyze and classify vocalizations. A common framework will also allow studies to compare results across species and institutions. In addition, the use of automated classification techniques can speed analysis and uncover behavioral correlations not readily apparent using traditional techniques.

Acoustic tomography for decay detection in red oak trees

Treesearch

Xiping Wang; R. Bruce Allison; Lihai Wang; Robert J. Ross

2007-01-01

The science of tree stability analysis uses both biological and engineering principles in attempting to rate a tree’s structural soundness and make reasonable predictions of potential for failure. In such analysis, arborists are often challenged by internal structural defects hidden from view within the trunks. This paper reports the results of an investigation using...

Greenpeace Greenspeak: A Transcultural Discourse Analysis

ERIC Educational Resources Information Center

Heinz, Bettina; Cheng, Hsin-I; Inuzuka, Ako

2007-01-01

This cross-cultural discourse analysis examines the construction of environmental issues on Greenpeace web pages in China, Japan and Germany. To uncover the semantic representation of environmental activism on these sites, the authors sought to identify discursive homogeneity and divergence and to bring to light embedded cultural assumptions. The…

Mean Comparison: Manifest Variable versus Latent Variable

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Bentler, Peter M.

2006-01-01

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

Development and Psychometric Evaluation of the Interpersonal Sexual Objectification Scale

ERIC Educational Resources Information Center

Kozee, Holly B.; Tylka, Tracy L.; Augustus-Horvath, Casey L.; Denchik, Angela

2007-01-01

This study reports on the development and psychometric evaluation of the Interpersonal Sexual Objectification Scale (ISOS). Data from 576 college women were collected in three studies. Exploratory factor analysis uncovered two factors: Body Evaluation and Unwanted Explicit Sexual Advances; confirmatory factor analysis supported this factor…

Learning and inference in a nonequilibrium Ising model with hidden nodes.

PubMed

Dunn, Benjamin; Roudi, Yasser

2013-02-01

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations of the hidden ones. This, as we show, can be represented as a path integral. Using this representation, we demonstrate that systematic approximate inference and learning rules can be derived using dynamical mean-field theory. Although naive mean-field theory leads to an unstable learning rule, taking into account Gaussian corrections allows learning the couplings involving hidden nodes. It also improves learning of the couplings between the observed nodes compared to when hidden nodes are ignored.

Preliminary analysis of loss-of-coolant accident in Fukushima nuclear accident

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

Su'ud, Zaki; Anshari, Rio

Loss-of-Coolant Accident (LOCA) in Boiling Water Reactor (BWR) especially on Fukushima Nuclear Accident will be discussed in this paper. The Tohoku earthquake triggered the shutdown of nuclear power reactors at Fukushima Nuclear Power station. Though shutdown process has been completely performed, cooling process, at much smaller level than in normal operation, is needed to remove decay heat from the reactor core until the reactor reach cold-shutdown condition. If LOCA happen at this condition, it will cause the increase of reactor fuel and other core temperatures and can lead to reactor core meltdown and exposure of radioactive material to the environmentmore » such as in the Fukushima Dai Ichi nuclear accident case. In this study numerical simulation has been performed to calculate pressure composition, water level and temperature distribution on reactor during this accident. There are two coolant regulating system that operational on reactor unit 1 at this accident, Isolation Condensers (IC) system and Safety Relief Valves (SRV) system. Average mass flow of steam to the IC system in this event is 10 kg/s and could keep reactor core from uncovered about 3,2 hours and fully uncovered in 4,7 hours later. There are two coolant regulating system at operational on reactor unit 2, Reactor Core Isolation Condenser (RCIC) System and Safety Relief Valves (SRV). Average mass flow of coolant that correspond this event is 20 kg/s and could keep reactor core from uncovered about 73 hours and fully uncovered in 75 hours later. There are three coolant regulating system at operational on reactor unit 3, Reactor Core Isolation Condenser (RCIC) system, High Pressure Coolant Injection (HPCI) system and Safety Relief Valves (SRV). Average mass flow of water that correspond this event is 15 kg/s and could keep reactor core from uncovered about 37 hours and fully uncovered in 40 hours later.« less

Preliminary analysis of loss-of-coolant accident in Fukushima nuclear accident

NASA Astrophysics Data System (ADS)

Su'ud, Zaki; Anshari, Rio

2012-06-01

Loss-of-Coolant Accident (LOCA) in Boiling Water Reactor (BWR) especially on Fukushima Nuclear Accident will be discussed in this paper. The Tohoku earthquake triggered the shutdown of nuclear power reactors at Fukushima Nuclear Power station. Though shutdown process has been completely performed, cooling process, at much smaller level than in normal operation, is needed to remove decay heat from the reactor core until the reactor reach cold-shutdown condition. If LOCA happen at this condition, it will cause the increase of reactor fuel and other core temperatures and can lead to reactor core meltdown and exposure of radioactive material to the environment such as in the Fukushima Dai Ichi nuclear accident case. In this study numerical simulation has been performed to calculate pressure composition, water level and temperature distribution on reactor during this accident. There are two coolant regulating system that operational on reactor unit 1 at this accident, Isolation Condensers (IC) system and Safety Relief Valves (SRV) system. Average mass flow of steam to the IC system in this event is 10 kg/s and could keep reactor core from uncovered about 3,2 hours and fully uncovered in 4,7 hours later. There are two coolant regulating system at operational on reactor unit 2, Reactor Core Isolation Condenser (RCIC) System and Safety Relief Valves (SRV). Average mass flow of coolant that correspond this event is 20 kg/s and could keep reactor core from uncovered about 73 hours and fully uncovered in 75 hours later. There are three coolant regulating system at operational on reactor unit 3, Reactor Core Isolation Condenser (RCIC) system, High Pressure Coolant Injection (HPCI) system and Safety Relief Valves (SRV). Average mass flow of water that correspond this event is 15 kg/s and could keep reactor core from uncovered about 37 hours and fully uncovered in 40 hours later.

A True Training Needs Analysis.

ERIC Educational Resources Information Center

Nowack, Kenneth M.

1991-01-01

Employees often want training in areas that are irrelevant to their jobs or inconsistent with organizational objectives. A well-designed questionnaire can weed out training wants to uncover an employee's true training needs. (Author)

Conjoint Analysis of Study Abroad Preferences: Key Attributes, Segments and Implications for Increasing Student Participation

ERIC Educational Resources Information Center

Garver, Michael S.; Divine, Richard L.

2008-01-01

An adaptive conjoint analysis was performed on the study abroad preferences of a sample of undergraduate college students. The results indicate that trip location, cost, and time spent abroad are the three most important determinants of student preference for different study abroad trip scenarios. The analysis also uncovered four different study…

The Politics of the Hidden Curriculum

ERIC Educational Resources Information Center

Giroux, Henry A.

1977-01-01

Schools teach much more than the traditional curriculum. They also teach a "hidden curriculum"--those unstated norms, values, and beliefs promoting hierarchic and authoritarian social relations that are transmitted to students through the underlying educational structure. Discusses the effects of the "hidden curriculum" on the…

Birefringence and hidden photons

NASA Astrophysics Data System (ADS)

Arza, Ariel; Gamboa, J.

2018-05-01

We study a model where photons interact with hidden photons and millicharged particles through a kinetic mixing term. Particularly, we focus on vacuum birefringence effects and we find a bound for the millicharged parameter assuming that hidden photons are a piece of the local dark matter density.

Like a Hurricane: A Citation Analysis of Emergency Management Scholarly Literature

ERIC Educational Resources Information Center

Noe, Jennifer; Furay, Julia

2013-01-01

This bibliometric study used citation analysis to uncover citing characteristics in the burgeoning academic field of emergency management. Of the 281 degree programs listed by the Federal Emergency Management Agency nationwide, those at community colleges accounted for 17% of the total. Using the interdisciplinary database of Academic Search…

Extreme negotiations.

PubMed

Weiss, Jeff; Donigian, Aram; Hughes, Jonathan

2010-11-01

CEOs and other senior executives must make countless complex, high-stakes deals across functional areas and divisions, with alliance partners and critical suppliers, and with customers and regulators. The pressure of such negotiations may make them feel a lot like U.S. military officers in an Afghan village, fending off enemy fire while trying to win trust and get intelligence from the local populace. Both civilian and military leaders face what the authors call "dangerous negotiations," in which the traps are many and good advice is scarce. Although the sources of danger are quite different for executives and officers, they resort to the same kinds of behaviors. Both feel pressure to make quick progress, project strength and control (particularly when they have neither), rely on force rather than collaboration, trade resources for cooperation rather than build trust, and make unwanted compromises to minimize potential damage. The authors outline five core strategies that "in extremis" military negotiators use to resolve conflicts and influence others: maintaining a big-picture perspective; uncovering hidden agendas to improve collaboration; using facts and fairness to get buy-in; building trust; and focusing on process as well as outcomes. These strategies provide an effective framework that business executives can use to prepare for a negotiation and guide their moves at the bargaining table.

The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

PubMed

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J; Inzé, Dirk; Van de Peer, Yves

2013-03-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.

First-principles approach to the dynamic magnetoelectric couplings for the non-reciprocal directional dichroism in BiFeO 3

DOE PAGES

Kezsmarki, I.; Fishman, Randy Scott

2016-04-18

Due to the complicated magnetic and crystallographic structures of BiFeO 3, its magnetoelectric (ME) couplings and microscopic model Hamiltonian remain poorly understood. By employing a firstprinciples approach, we uncover all possibleMEcouplings associated with the spin-current (SC) and exchange-striction (ES) polarizations, and construct an appropriate Hamiltonian for the long-range spin-cycloid in BiFeO 3. First-principles calculations are used to understand the microscopic origins of theMEcouplings.Wefind that inversion symmetries broken by ferroelectric and antiferroelectric distortions induce the SC and the ES polarizations, which cooperatively produce the dynamicME effects in BiFeO 3. A model motivated by first principles reproduces the absorption difference of counter-propagatingmore » light beams called non-reciprocal directional dichroism. The current paper focuses on the spin-driven (SD) polarizations produced by a dynamic electric field, i.e. the dynamic MEcouplings. Due to the inertial properties of Fe, the dynamic SD polarizations differ significantly from the static SD polarizations. Our systematic approach can be generally applied to any multiferroic material, laying the foundation for revealing hiddenMEcouplings on the atomic scale and for exploiting opticalMEeffects in the next generation of technological devices such as optical diodes.« less

Genetic signatures of ecological diversity along an urbanization gradient.

PubMed

Kelly, Ryan P; O'Donnell, James L; Lowell, Natalie C; Shelton, Andrew O; Samhouri, Jameal F; Hennessey, Shannon M; Feist, Blake E; Williams, Gregory D

2016-01-01

Despite decades of work in environmental science and ecology, estimating human influences on ecosystems remains challenging. This is partly due to complex chains of causation among ecosystem elements, exacerbated by the difficulty of collecting biological data at sufficient spatial, temporal, and taxonomic scales. Here, we demonstrate the utility of environmental DNA (eDNA) for quantifying associations between human land use and changes in an adjacent ecosystem. We analyze metazoan eDNA sequences from water sampled in nearshore marine eelgrass communities and assess the relationship between these ecological communities and the degree of urbanization in the surrounding watershed. Counter to conventional wisdom, we find strongly increasing richness and decreasing beta diversity with greater urbanization, and similar trends in the diversity of life histories with urbanization. We also find evidence that urbanization influences nearshore communities at local (hundreds of meters) rather than regional (tens of km) scales. Given that different survey methods sample different components of an ecosystem, we then discuss the advantages of eDNA-which we use here to detect hundreds of taxa simultaneously-as a complement to traditional ecological sampling, particularly in the context of broad ecological assessments where exhaustive manual sampling is impractical. Genetic data are a powerful means of uncovering human-ecosystem interactions that might otherwise remain hidden; nevertheless, no sampling method reveals the whole of a biological community.

Phylogenomics and species delimitation of a complex radiation of Neotropical suboscine birds (Pachyramphus).

PubMed

Musher, Lukas J; Cracraft, Joel

2018-01-01

Phylogeographic studies within the Neotropics continue to uncover hidden diversity, the extent of which remains poorly known. In birds, molecular studies are producing evidence that species-level diversity is substantially underestimated. Many avian taxa comprise large complexes of subspecies that often represent species-level taxa by various criteria. One such group of Neotropical suboscine birds, the becards (Pachyramphus), ranges from Argentina through northern Mexico. Their taxonomic limits have been complex and controversial as the genus has bounced around a number of suboscine families. Additionally, the phylogenetic relationships within Pachyramphus are unresolved due to insufficient sampling of taxa and populations across species' ranges. We used target capture of ultraconserved elements for 62 individuals representing 42 taxa, and sequenced two mitochondrial genes and two nuclear introns covering 265 individuals of 51 taxa, including all recognized species, resulting in the most densely and completely sampled phylogenetic hypothesis for Pachyramphus to date. We delimited species using a traditional taxonomic approach and then tested them under a Bayesian multi-species coalescent framework. In doing so, we provide evidence for multiple young, previously undetected evolutionary lineages within Pachyramphus. Deep, well-supported branches and a high number of intraspecific lineages across the tree suggest that at least 50% of species diversity may be unrecognized. Copyright © 2017 Elsevier Inc. All rights reserved.

Professionalism in global, personalized cancer care: restoring authenticity and integrity.

PubMed

Surbone, Antonella

2013-01-01

Personalized medicine is revolutionizing cancer care and creating new expectations among oncologists and patients. At present the benefit is still marginal, however, and must be understood as incremental. In addition, cultural and resource disparities limit the sustainability of new cancer therapies on a global scale. Adequate instruments are needed to enable our exercise of sound and honest judgment in distinguishing breakthrough treatments from those that yield only marginal or doubtful improvements, and to develop strategies for formulation and correct application of balanced guidelines for sustainable cancer care. Professionalism requires that the acquisition of knowledge and skills go hand in hand with moral education in the intellectual virtues of humility, perseverance, adaptability, communicativeness, and commitment to resist self-deception or conflicts of interest. Hidden curricula undermine the moral values of medicine: these must be understood and uncovered. We should possess a special body of knowledge, skills, and values that allow us to change our practices when appropriate and to be stewards of society's limited resources through proper communication with our patients and families. In the era of personalized oncology and global issues of sustainability, professional authenticity and integrity in cancer clinical practice are key to bridging the gaps between true and false expectations of patients and the public.

Natural Products from Marine Fungi—Still an Underrepresented Resource

PubMed Central

Imhoff, Johannes F.

2016-01-01

Marine fungi represent a huge potential for new natural products and an increased number of new metabolites have become known over the past years, while much of the hidden potential still needs to be uncovered. Representative examples of biodiversity studies of marine fungi and of natural products from a diverse selection of marine fungi from the author’s lab are highlighting important aspects of this research. If one considers the huge phylogenetic diversity of marine fungi and their almost ubiquitous distribution, and realizes that most of the published work on secondary metabolites of marine fungi has focused on just a few genera, strictly speaking Penicillium, Aspergillus and maybe also Fusarium and Cladosporium, the diversity of marine fungi is not adequately represented in investigations on their secondary metabolites and the less studied species deserve special attention. In addition to results on recently discovered new secondary metabolites of Penicillium species, the diversity of fungi in selected marine habitats is highlighted and examples of groups of secondary metabolites produced by representatives of a variety of different genera and their bioactivities are presented. Special focus is given to the production of groups of derivatives of metabolites by the fungi and to significant differences in biological activities due to small structural changes. PMID:26784209

Novel Insights into the Transcriptome of Dirofilaria immitis

PubMed Central

Zhang, Zhihe; Hou, Rong; Wu, Xuhang; Yang, Deying; Zhang, Runhui; Zheng, Wanpeng; Nie, Huaming; Xie, Yue; Yan, Ning; Yang, Zhi; Wang, Chengdong; Luo, Li; Liu, Li; Gu, Xiaobin; Wang, Shuxian; Peng, Xuerong; Yang, Guangyou

2012-01-01

Background The heartworm Dirofilaria immitis is the causal agent of cardiopulmonary dirofilariosis in dogs and cats, and also infects a wide range of wild mammals as well as humans. One bottleneck for the design of fundamentally new intervention and management strategies against D. immitis may be the currently limited knowledge of fundamental molecular aspects of D. immitis. Methodology/Principal Findings A next-generation sequencing platform combining computational approaches was employed to assess a global view of the heartworm transcriptome. A total of 20,810 unigenes (mean length  = 1,270 bp) were assembled from 22.3 million clean reads. From these, 15,698 coding sequences (CDS) were inferred, and about 85% of the unigenes had orthologs/homologs in public databases. Comparative transcriptomic study uncovered 4,157 filarial-specific genes as well as 3,795 genes potentially involved in filarial-Wolbachia symbiosis. In addition, the potential intestine transcriptome of D. immitis (1,101 genes) was mined for the first time, which might help to discover ‘hidden antigens’. Conclusions/Significance This study provides novel insights into the transcriptome of D. immitis and sheds light on its molecular processes and survival mechanisms. Furthermore, it provides a platform to discover new vaccine candidates and potential targets for new drugs against dirofilariosis. PMID:22911833

Implications of the measured angular anisotropy at the hidden order transition of URu2Si2

NASA Astrophysics Data System (ADS)

Chandra, P.; Coleman, P.; Flint, R.; Trinh, J.; Ramirez, A. P.

2018-05-01

The heavy fermion compound URu2Si2 continues to attract great interest due to the long-unidentified nature of the hidden order that develops below 17.5 K. Here we discuss the implications of an angular survey of the linear and nonlinear susceptibility of URu2Si2 in the vicinity of the hidden order transition [1]. While the anisotropic nature of spin fluctuations and low-temperature quasiparticles was previously established, our recent results suggest that the order parameter itself has intrinsic Ising anisotropy, and that moreover this anisotropy extends far above the hidden order transition. Consistency checks and subsequent questions for future experimental and theoretical studies of hidden order are discussed.

A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State

PubMed Central

2016-01-01

Identifying the hidden state is important for solving problems with hidden state. We prove any deterministic partially observable Markov decision processes (POMDP) can be represented by a minimal, looping hidden state transition model and propose a heuristic state transition model constructing algorithm. A new spatiotemporal associative memory network (STAMN) is proposed to realize the minimal, looping hidden state transition model. STAMN utilizes the neuroactivity decay to realize the short-term memory, connection weights between different nodes to represent long-term memory, presynaptic potentials, and synchronized activation mechanism to complete identifying and recalling simultaneously. Finally, we give the empirical illustrations of the STAMN and compare the performance of the STAMN model with that of other methods. PMID:27891146

Optimizing Likelihood Models for Particle Trajectory Segmentation in Multi-State Systems.

PubMed

Young, Dylan Christopher; Scrimgeour, Jan

2018-06-19

Particle tracking offers significant insight into the molecular mechanics that govern the behav- ior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule's environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of the likelihood models used to describe the states of the system and for characterization of the technique's failure mechanisms. This analysis was made pos- sible by the implementation of parallelized adaptive direct search algorithm on a Nvidia graphics processing unit. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states. © 2018 IOP Publishing Ltd.

Analyzing hidden populations online: topic, emotion, and social network of HIV-related users in the largest Chinese online community.

PubMed

Liu, Chuchu; Lu, Xin

2018-01-05

Traditional survey methods are limited in the study of hidden populations due to the hard to access properties, including lack of a sampling frame, sensitivity issue, reporting error, small sample size, etc. The rapid increase of online communities, of which members interact with others via the Internet, have generated large amounts of data, offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. In this study, we try to understand the multidimensional characteristics of a hidden population by analyzing the massive data generated in the online community. By elaborately designing crawlers, we retrieved a complete dataset from the "HIV bar," the largest bar related to HIV on the Baidu Tieba platform, for all records from January 2005 to August 2016. Through natural language processing and social network analysis, we explored the psychology, behavior and demand of online HIV population and examined the network community structure. In HIV communities, the average topic similarity among members is positively correlated to network efficiency (r = 0.70, p < 0.001), indicating that the closer the social distance between members of the community, the more similar their topics. The proportion of negative users in each community is around 60%, weakly correlated with community size (r = 0.25, p = 0.002). It is found that users suspecting initial HIV infection or first in contact with high-risk behaviors tend to seek help and advice on the social networking platform, rather than immediately going to a hospital for blood tests. Online communities have generated copious amounts of data offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. It is recommended that support through online services for HIV/AIDS consultation and diagnosis be improved to avoid privacy concerns and social discrimination in China.

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

Hidden attractors in dynamical models of phase-locked loop circuits: Limitations of simulation in MATLAB and SPICE

NASA Astrophysics Data System (ADS)

Kuznetsov, N. V.; Leonov, G. A.; Yuldashev, M. V.; Yuldashev, R. V.

2017-10-01

During recent years it has been shown that hidden oscillations, whose basin of attraction does not overlap with small neighborhoods of equilibria, may significantly complicate simulation of dynamical models, lead to unreliable results and wrong conclusions, and cause serious damage in drilling systems, aircrafts control systems, electromechanical systems, and other applications. This article provides a survey of various phase-locked loop based circuits (used in satellite navigation systems, optical, and digital communication), where such difficulties take place in MATLAB and SPICE. Considered examples can be used for testing other phase-locked loop based circuits and simulation tools, and motivate the development and application of rigorous analytical methods for the global analysis of phase-locked loop based circuits.

Tissue multifractality and hidden Markov model based integrated framework for optimum precancer detection

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sabyasachi; Das, Nandan K.; Kurmi, Indrajit; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-10-01

We report the application of a hidden Markov model (HMM) on multifractal tissue optical properties derived via the Born approximation-based inverse light scattering method for effective discrimination of precancerous human cervical tissue sites from the normal ones. Two global fractal parameters, generalized Hurst exponent and the corresponding singularity spectrum width, computed by multifractal detrended fluctuation analysis (MFDFA), are used here as potential biomarkers. We develop a methodology that makes use of these multifractal parameters by integrating with different statistical classifiers like the HMM and support vector machine (SVM). It is shown that the MFDFA-HMM integrated model achieves significantly better discrimination between normal and different grades of cancer as compared to the MFDFA-SVM integrated model.

Analysis of single ion channel data incorporating time-interval omission and sampling

PubMed Central

The, Yu-Kai; Timmer, Jens

2005-01-01

Hidden Markov models are widely used to describe single channel currents from patch-clamp experiments. The inevitable anti-aliasing filter limits the time resolution of the measurements and therefore the standard hidden Markov model is not adequate anymore. The notion of time-interval omission has been introduced where brief events are not detected. The developed, exact solutions to this problem do not take into account that the measured intervals are limited by the sampling time. In this case the dead-time that specifies the minimal detectable interval length is not defined unambiguously. We show that a wrong choice of the dead-time leads to considerably biased estimates and present the appropriate equations to describe sampled data. PMID:16849220

Parametric inference for biological sequence analysis.

PubMed

Pachter, Lior; Sturmfels, Bernd

2004-11-16

One of the major successes in computational biology has been the unification, by using the graphical model formalism, of a multitude of algorithms for annotating and comparing biological sequences. Graphical models that have been applied to these problems include hidden Markov models for annotation, tree models for phylogenetics, and pair hidden Markov models for alignment. A single algorithm, the sum-product algorithm, solves many of the inference problems that are associated with different statistical models. This article introduces the polytope propagation algorithm for computing the Newton polytope of an observation from a graphical model. This algorithm is a geometric version of the sum-product algorithm and is used to analyze the parametric behavior of maximum a posteriori inference calculations for graphical models.

Supersymmetric leptogenesis with a light hidden sector

NASA Astrophysics Data System (ADS)

De Simone, Andrea; Garny, Mathias; Ibarra, Alejandro; Weniger, Christoph

2010-07-01

Supersymmetric scenarios incorporating thermal leptogenesis as the origin of the observed matter-antimatter asymmetry generically predict abundances of the primordial elements which are in conflict with observations. In this paper we propose a simple way to circumvent this tension and accommodate naturally thermal leptogenesis and primordial nucleosynthesis. We postulate the existence of a light hidden sector, coupled very weakly to the Minimal Supersymmetric Standard Model, which opens up new decay channels for the next-to-lightest supersymmetric particle, thus diluting its abundance during nucleosynthesis. We present a general model-independent analysis of this mechanism as well as two concrete realizations, and describe the relevant cosmological and astrophysical bounds and implications for this dark matter scenario. Possible experimental signatures at colliders and in cosmic-ray observations are also discussed.

Sustained response with ixekizumab treatment of moderate-to-severe psoriasis with scalp involvement: results from three phase 3 trials (UNCOVER-1, UNCOVER-2, UNCOVER-3).

PubMed

Reich, Kristian; Leonardi, Craig; Lebwohl, Mark; Kerdel, Francisco; Okubo, Yukari; Romiti, Ricardo; Goldblum, Orin; Dennehy, Ellen B; Kerr, Lisa; Sofen, Howard

2017-06-01

Scalp is a frequently affected and difficult-to-treat area in psoriasis patients. We assessed the efficacy of ixekizumab in the treatment of patients with scalp psoriasis over 60 weeks using the Psoriasis Scalp Severity Index (PSSI). In three Phase 3, multicenter, double-blind, placebo-controlled trials, patients with moderate-to-severe psoriasis in UNCOVER-1 (N = 1296), UNCOVER-2 (N = 1224) and UNCOVER-3 (N = 1346) were randomized to subcutaneous 80 mg ixekizumab every two weeks (Q2W) or every four weeks (Q4W) after a 160 mg starting dose, or placebo through Week 12. Additional UNCOVER-2 and UNCOVER-3 cohorts were randomized to 50 mg bi-weekly etanercept through Week 12. Patients entering the open-label long-term extension (LTE) (UNCOVER-3) received ixekizumab Q4W; UNCOVER-1 and UNCOVER-2 included a blinded maintenance period in which static physician global assessment (sPGA) 0/1 responders were re-randomized to placebo, ixekizumab Q4W, or 80 mg ixekizumab every 12 weeks (Q12W) through Week 60. In patients with moderate-to-severe psoriasis with baseline scalp involvement, PSSI 90 and 100 were achieved at Week 12 in higher percentages of patients treated with ixekizumab Q2W (81.7% and 74.6%) or ixekizumab Q4W (75.6% and 68.9%) compared with patients treated with placebo (7.6% and 6.7%; p < .001 each ixekizumab arm versus placebo) or etanercept (55.5% and 48.1%; p < .001 each ixekizumab arm versus etanercept). These outcomes were maintained through Week 60 of the maintenance (UNCOVER-1 and UNCOVER-2) and LTE (UNCOVER-3) period in patients who continued on ixekizumab Q4W. Ixekizumab was efficacious in treating scalp psoriasis in patients with moderate-to-severe psoriasis, with most patients achieving complete or near-complete resolution of scalp psoriasis and maintaining this response over 60 weeks.

Gender Neutralities, Dichotomies and Hidden Inequalities: Analysis of Vocational Teachers' Reflections on Gender in the Profession

ERIC Educational Resources Information Center

Lappalainen, Sirpa; Lahelma, Elina; Pehkonen, Leila; Isopahkala-Bouret, Ulpukka

2012-01-01

This article analyses how Finnish vocational teachers make sense of the meanings of gender in their work. The context of the study consists of the two most gender segregated environments of vocational education: the female-dominated Sector of Health and Social Services and the male-dominated Sector of Technology and Transport. Our analysis draws…

Bell's theorem and the problem of decidability between the views of Einstein and Bohr.

PubMed

Hess, K; Philipp, W

2001-12-04

Einstein, Podolsky, and Rosen (EPR) have designed a gedanken experiment that suggested a theory that was more complete than quantum mechanics. The EPR design was later realized in various forms, with experimental results close to the quantum mechanical prediction. The experimental results by themselves have no bearing on the EPR claim that quantum mechanics must be incomplete nor on the existence of hidden parameters. However, the well known inequalities of Bell are based on the assumption that local hidden parameters exist and, when combined with conflicting experimental results, do appear to prove that local hidden parameters cannot exist. This fact leaves only instantaneous actions at a distance (called "spooky" by Einstein) to explain the experiments. The Bell inequalities are based on a mathematical model of the EPR experiments. They have no experimental confirmation, because they contradict the results of all EPR experiments. In addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions; for instance, he assumes that the hidden parameters are governed by a single probability measure independent of the analyzer settings. We argue that the mathematical model of Bell excludes a large set of local hidden variables and a large variety of probability densities. Our set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does permit derivation of the quantum result and is consistent with all known experiments.

Hidden attractors in dynamical systems

NASA Astrophysics Data System (ADS)

Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh

2016-06-01

Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.

Cascade Error Projection: A Learning Algorithm for Hardware Implementation

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher

1996-01-01

In this paper, we workout a detailed mathematical analysis for a new learning algorithm termed Cascade Error Projection (CEP) and a general learning frame work. This frame work can be used to obtain the cascade correlation learning algorithm by choosing a particular set of parameters. Furthermore, CEP learning algorithm is operated only on one layer, whereas the other set of weights can be calculated deterministically. In association with the dynamical stepsize change concept to convert the weight update from infinite space into a finite space, the relation between the current stepsize and the previous energy level is also given and the estimation procedure for optimal stepsize is used for validation of our proposed technique. The weight values of zero are used for starting the learning for every layer, and a single hidden unit is applied instead of using a pool of candidate hidden units similar to cascade correlation scheme. Therefore, simplicity in hardware implementation is also obtained. Furthermore, this analysis allows us to select from other methods (such as the conjugate gradient descent or the Newton's second order) one of which will be a good candidate for the learning technique. The choice of learning technique depends on the constraints of the problem (e.g., speed, performance, and hardware implementation); one technique may be more suitable than others. Moreover, for a discrete weight space, the theoretical analysis presents the capability of learning with limited weight quantization. Finally, 5- to 8-bit parity and chaotic time series prediction problems are investigated; the simulation results demonstrate that 4-bit or more weight quantization is sufficient for learning neural network using CEP. In addition, it is demonstrated that this technique is able to compensate for less bit weight resolution by incorporating additional hidden units. However, generation result may suffer somewhat with lower bit weight quantization.

Partially Covered Metal Stents May Not Prolong Stent Patency Compared to Uncovered Stents in Unresectable Malignant Distal Biliary Obstruction.

PubMed

Kim, Jae Yun; Ko, Gyu Bong; Lee, Tae Hoon; Park, Sang-Heum; Lee, Yun Nah; Cho, Young Sin; Jung, Yunho; Chung, Il-Kwun; Choi, Hyun Jong; Cha, Sang-Woo; Moon, Jong Ho; Cho, Young Deok; Kim, Sun-Joo

2017-05-15

Controversy still exists regarding the benefits of covered self-expandable metal stents (SEMSs) compared to uncovered SEMSs. We aimed to compare the patency and stent-related adverse events of partially covered SEMSs (PC-SEMSs) and uncovered SEMSs in unresectable malignant distal biliary obstruction. A total of 134 patients who received a PC-SEMS or uncovered SEMS for palliation of unresectable malignant distal biliary obstruction were reviewed retrospectively. The main outcome measures were stent patency, stent-related adverse events, and overall survival. The median stent patency was 118 days (range, 3 to 802 days) with PC-SEMSs and 105 days (range, 2 to 485 days) with uncovered SEMSs (p=0.718). The overall endoscopic revision rate due to stent dysfunction was 36.6% (26/71) with PC-SEMSs and 36.5% (23/63) with uncovered SEMSs (p=0.589). Tumor ingrowth was more frequent with uncovered SEMSs (4.2% vs 19.1%, p=0.013), but migration was more frequent with PC-SEMSs (11.2% vs 1.5%, p=0.04). The incidence of stent-related adverse events was 2.8% (2/71) with PC-SEMSs and 9.5% (6/63) with uncovered SEMSs (p=0.224). The median overall survival was 166 days with PC-SEMSs and 168 days with uncovered SEMSs (p=0.189). Compared to uncovered SEMSs, PC-SEMSs did not prolong stent patency in unresectable malignant distal biliary obstruction. Stent migration was more frequent with PC-SEMSs. However, tumor ingrowth was less frequent with PC-SEMSs compared to uncovered SEMSs.

Partially Covered Metal Stents May Not Prolong Stent Patency Compared to Uncovered Stents in Unresectable Malignant Distal Biliary Obstruction

PubMed Central

Kim, Jae Yun; Ko, Gyu Bong; Lee, Tae Hoon; Park, Sang-Heum; Lee, Yun Nah; Cho, Young Sin; Jung, Yunho; Chung, Il-Kwun; Choi, Hyun Jong; Cha, Sang-Woo; Moon, Jong Ho; Cho, Young Deok; Kim, Sun-Joo

2017-01-01

Background/Aims Controversy still exists regarding the benefits of covered self-expandable metal stents (SEMSs) compared to uncovered SEMSs. We aimed to compare the patency and stent-related adverse events of partially covered SEMSs (PC-SEMSs) and uncovered SEMSs in unresectable malignant distal biliary obstruction. Methods A total of 134 patients who received a PC-SEMS or uncovered SEMS for palliation of unresectable malignant distal biliary obstruction were reviewed retrospectively. The main outcome measures were stent patency, stent-related adverse events, and overall survival. Results The median stent patency was 118 days (range, 3 to 802 days) with PC-SEMSs and 105 days (range, 2 to 485 days) with uncovered SEMSs (p=0.718). The overall endoscopic revision rate due to stent dysfunction was 36.6% (26/71) with PC-SEMSs and 36.5% (23/63) with uncovered SEMSs (p=0.589). Tumor ingrowth was more frequent with uncovered SEMSs (4.2% vs 19.1%, p=0.013), but migration was more frequent with PC-SEMSs (11.2% vs 1.5%, p=0.04). The incidence of stent-related adverse events was 2.8% (2/71) with PC-SEMSs and 9.5% (6/63) with uncovered SEMSs (p=0.224). The median overall survival was 166 days with PC-SEMSs and 168 days with uncovered SEMSs (p=0.189). Conclusions Compared to uncovered SEMSs, PC-SEMSs did not prolong stent patency in unresectable malignant distal biliary obstruction. Stent migration was more frequent with PC-SEMSs. However, tumor ingrowth was less frequent with PC-SEMSs compared to uncovered SEMSs. PMID:28208003

77 FR 12227 - Long Term 2 Enhanced Surface Water Treatment Rule: Uncovered Finished Water Reservoirs; Public...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-29

... Water Treatment Rule: Uncovered Finished Water Reservoirs; Public Meeting AGENCY: Environmental... review of the uncovered finished water reservoir requirement in the Long Term 2 Enhanced Surface Water... uncovered finished water reservoir requirement and the agency's Six Year Review process. EPA also plans to...

The Hidden Curriculum in Distance Education: An Updated View.

ERIC Educational Resources Information Center

Anderson, Terry

2001-01-01

Addressing recent criticism of distance education, explores the distinctive hidden curriculum (supposed "real" agenda) of distance education, focusing on both its positive and negative expressions. Also offers an updated view of the hidden curriculum of traditional, campus-based education, grounded in an emerging worldwide context of broadening…

77 FR 8253 - Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... ENVIRONMENTAL PROTECTION AGENCY [FRL-9631-3] Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill Superfund Site ACTION: Notice. SUMMARY: In accordance... (``DOJ'') on behalf of EPA, in connection with the Hidden Lane Landfill Superfund Site, Sterling, Loudoun...

Hidden Curriculum as One of Current Issue of Curriculum

ERIC Educational Resources Information Center

Alsubaie, Merfat Ayesh

2015-01-01

There are several issues in the education system, especially in the curriculum field that affect education. Hidden curriculum is one of current controversial curriculum issues. Many hidden curricular issues are the result of assumptions and expectations that are not formally communicated, established, or conveyed within the learning environment.…

Hidden Variable Theories and Quantum Nonlocality

ERIC Educational Resources Information Center

Boozer, A. D.

2009-01-01

We clarify the meaning of Bell's theorem and its implications for the construction of hidden variable theories by considering an example system consisting of two entangled spin-1/2 particles. Using this example, we present a simplified version of Bell's theorem and describe several hidden variable theories that agree with the predictions of…

Building Simple Hidden Markov Models. Classroom Notes

ERIC Educational Resources Information Center

Ching, Wai-Ki; Ng, Michael K.

2004-01-01

Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

Seuss's Butter Battle Book: Is There Hidden Harm?

ERIC Educational Resources Information Center

Van Cleaf, David W.; Martin, Rita J.

1986-01-01

Examines whether elementary school children relate to the "harmful hidden message" about nuclear war in Dr. Seuss's THE BUTTER BATTLE BOOK. After ascertaining the children's cognitive level, they participated in activities to find hidden meanings in stories, including Seuss's book. Students failed to identify the nuclear war message in…

Comment on 'All quantum observables in a hidden-variable model must commute simultaneously'

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

Nagata, Koji

Malley discussed [Phys. Rev. A 69, 022118 (2004)] that all quantum observables in a hidden-variable model for quantum events must commute simultaneously. In this comment, we discuss that Malley's theorem is indeed valid for the hidden-variable theoretical assumptions, which were introduced by Kochen and Specker. However, we give an example that the local hidden-variable (LHV) model for quantum events preserves noncommutativity of quantum observables. It turns out that Malley's theorem is not related to the LHV model for quantum events, in general.

Inference for dynamics of continuous variables: the extended Plefka expansion with hidden nodes

NASA Astrophysics Data System (ADS)

Bravi, B.; Sollich, P.

2017-06-01

We consider the problem of a subnetwork of observed nodes embedded into a larger bulk of unknown (i.e. hidden) nodes, where the aim is to infer these hidden states given information about the subnetwork dynamics. The biochemical networks underlying many cellular and metabolic processes are important realizations of such a scenario as typically one is interested in reconstructing the time evolution of unobserved chemical concentrations starting from the experimentally more accessible ones. We present an application to this problem of a novel dynamical mean field approximation, the extended Plefka expansion, which is based on a path integral description of the stochastic dynamics. As a paradigmatic model we study the stochastic linear dynamics of continuous degrees of freedom interacting via random Gaussian couplings. The resulting joint distribution is known to be Gaussian and this allows us to fully characterize the posterior statistics of the hidden nodes. In particular the equal-time hidden-to-hidden variance—conditioned on observations—gives the expected error at each node when the hidden time courses are predicted based on the observations. We assess the accuracy of the extended Plefka expansion in predicting these single node variances as well as error correlations over time, focussing on the role of the system size and the number of observed nodes.

A CFD Analysis of Steam Flow in the Two-Stage Experimental Impulse Turbine with the Drum Rotor Arrangement

NASA Astrophysics Data System (ADS)

Yun, Kukchol; Tajč, L.; Kolovratník, M.

2016-03-01

The aim of the paper is to present the CFD analysis of the steam flow in the two-stage turbine with a drum rotor and balancing slots. The balancing slot is a part of every rotor blade and it can be used in the same way as balancing holes on the classical rotor disc. The main attention is focused on the explanation of the experimental knowledge about the impact of the slot covering and uncovering on the efficiency of the individual stages and the entire turbine. The pressure and temperature fields and the mass steam flows through the shaft seals, slots and blade cascades are calculated. The impact of the balancing slots covering or uncovering on the reaction and velocity conditions in the stages is evaluated according to the pressure and temperature fields. We have also concentrated on the analysis of the seal steam flow through the balancing slots. The optimized design of the balancing slots has been suggested.

The phylogeny of swimming kinematics: The environment controls flagellar waveforms in sperm motility

NASA Astrophysics Data System (ADS)

Guasto, Jeffrey; Burton, Lisa; Zimmer, Richard; Hosoi, Anette; Stocker, Roman

2013-11-01

In recent years, phylogenetic and molecular analyses have dominated the study of ecology and evolution. However, physical interactions between organisms and their environment, a fundamental determinant of organism ecology and evolution, are mediated by organism form and function, highlighting the need to understand the mechanics of basic survival strategies, including locomotion. Focusing on spermatozoa, we combined high-speed video microscopy and singular value decomposition analysis to quantitatively compare the flagellar waveforms of eight species, ranging from marine invertebrates to humans. We found striking similarities in sperm swimming kinematics between genetically dissimilar organisms, which could not be uncovered by phylogenetic analysis. The emergence of dominant waveform patterns across species are suggestive of biological optimization for flagellar locomotion and point toward environmental cues as drivers of this convergence. These results reinforce the power of quantitative kinematic analysis to understand the physical drivers of evolution and as an approach to uncover new solutions for engineering applications, such as micro-robotics.

Strategic Planning for Cardiac Services

DTIC Science & Technology

2008-04-13

Support Delivery Strategies 38 8. Action Plan 40 CT Strategy Plan List of Tables Table 1. CT program SWOT analysis Table 2. Critical strengths and...activities will give an overview to form a thorough SWOT (strengths, weaknesses, opportunities and threats) analysis by uncovering crucial elements...Potential Strategies To understand potential strategies available to DDEAMC and Augusta VAMC, a SWOT analysis was completed to clearly identify

Results from the Solar Hidden Photon Search (SHIPS)

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

Schwarz, Matthias; Schneide, Magnus; Susol, Jaroslaw

We present the results of a search for transversely polarised hidden photons (HPs) with ∼ 3 eV energies emitted from the Sun. These hypothetical particles, known also as paraphotons or dark sector photons, are theoretically well motivated for example by string theory inspired extensions of the Standard Model. Solar HPs of sub-eV mass can convert into photons of the same energy (photon ↔ HP oscillations are similar to neutrino flavour oscillations). At SHIPS this would take place inside a long light-tight high-vacuum tube, which tracks the Sun. The generated photons would then be focused into a low-noise photomultiplier at the far end ofmore » the tube. Our analysis of 330 h of data (and 330 h of background characterisation) reveals no signal of photons from solar hidden photon conversion. We estimate the rate of newly generated photons due to this conversion to be smaller than 25 mHz/m{sup 2} at the 95% C.L . Using this and a recent model of solar HP emission, we set stringent constraints on χ, the coupling constant between HPs and photons, as a function of the HP mass.« less

Results from the Solar Hidden Photon Search (SHIPS)

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

Schwarz, Matthias; Knabbe, Ernst-Axel; Lindner, Axel

We present the results of a search for transversely polarised hidden photons (HPs) with ∼3 eV energies emitted from the Sun. These hypothetical particles, known also as paraphotons or dark sector photons, are theoretically well motivated for example by string theory inspired extensions of the Standard Model. Solar HPs of sub-eV mass can convert into photons of the same energy (photon ↔ HP oscillations are similar to neutrino flavour oscillations). At SHIPS this would take place inside a long light-tight high-vacuum tube, which tracks the Sun. The generated photons would then be focused into a low-noise photomultiplier at the farmore » end of the tube. Our analysis of 330 h of data (and 330 h of background characterisation) reveals no signal of photons from solar hidden photon conversion. We estimate the rate of newly generated photons due to this conversion to be smaller than 25 mHz/m{sup 2} at the 95% C.L. Using this and a recent model of solar HP emission, we set stringent constraints on χ, the coupling constant between HPs and photons, as a function of the HP mass.« less

Antibiotic pharmacoeconomics: an attempt to find the real cost of hospital antibiotic prescribing.

PubMed Central

Kerr, J. R.; Barr, J. G.; Smyth, E. T.; O'Hare, J.; Bell, P. M.; Callender, M. E.

1993-01-01

Antibiotics account for a large part of all hospital pharmacy budgets, but the actual cost of their prescription is unknown. These costs include intravenous administration, labour, serum antibiotic assay, monitoring of haematological and biochemical indices, disposal of sharps and adverse effects. An in-house method of costing antibiotic therapy is presented, to quantify these hidden expenses. Since not only an awareness, but an accurate quantification, of hidden costs is required, a study of various hospital procedures relating directly to antibiotic therapy was undertaken in an acute medical ward; this involved the identification of particular staff members performing various procedures, consumables used and time taken. The cost of five-day courses of gentamicin, penicillin G, ampicillin, flucloxacillin, cefuroxime, ceftotaxime and erythromycin has been calculated; drug and hidden costs for each are presented graphically for comparison. The breakdown cost for gentamicin is presented to illustrate the method. The costing of adverse effects has not been attempted. We suggest that costings of this sort are used in cost-benefit analysis of antibiotic use. These calculations have been incorporated into a computer spreadsheet and this costing service will be offered to clinical areas of our hospital. PMID:8516976

Single photon and nonlocality

NASA Astrophysics Data System (ADS)

Drezet, Aurelien

2007-03-01

In a paper by Home and Agarwal [1], it is claimed that quantum nonlocality can be revealed in a simple interferometry experiment using only single particles. A critical analysis of the concept of hidden variable used by the authors of [1] shows that the reasoning is not correct.

A New Wave in Applied Mathematics.

ERIC Educational Resources Information Center

Cipra, Barry A.

1990-01-01

Discussed is wavelet theory, which provides ways to rearrange data to reveal features of a physical or mathematical system which might otherwise be hidden. This theory is compared to fourier analysis and the advantages of wavelet theory are stressed. Applications of this technique are suggested. (CW)

Searching for Hidden Costs: Presentation made at the University of Michigan Energy Institute’s Conference on Transportation, Economics, Energy, and the Environment (TE3)

EPA Pesticide Factsheets

This presentation contains research on consumer issues, including an assessment of vehicle affordability, a study of willingness-to-pay for various vehicle attributes, and content analysis of auto reviews.

Follow that fish: Uncovering the hidden blue economy in coral reef fisheries

PubMed Central

Teneva, Lida; Kittinger, John N.

2017-01-01

Despite their importance for human well-being, nearshore fisheries are often data poor, undervalued, and underappreciated in policy and development programs. We assess the value chain for nearshore Hawaiian coral reef fisheries, mapping post-catch distribution and disposition, and quantifying associated monetary, food security, and cultural values. We estimate that the total annual value of the nearshore fishery in Hawaiʻi is $10.3-$16.4 million, composed of non-commercial ($7.2-$12.9 million) and commercial ($2.97 million licensed + $148,500-$445,500 unlicensed) catch. Hawaii’s nearshore fisheries provide >7 million meals annually, with most (>5 million) from the non-commercial sector. Over a third (36%) of meals were planktivores, 26% piscivores, 21% primary consumers, and 18% secondary consumers. Only 62% of licensed commercial catch is accounted for in purchase reports, leaving 38% of landings unreported in sales. Value chains are complex, with major buyers for the commercial fishery including grocery stores (66%), retailers (19%), wholesalers (14%), and restaurants (<1%), who also trade and sell amongst themselves. The bulk of total nearshore catch (72–74%) follows a short value chain, with non-commercial fishers keeping catch for household consumption or community sharing. A small amount (~37,000kg) of reef fish—the equivalent of 1.8% of local catch—is imported annually into Hawaiʻi, 23,000kg of which arrives as passenger luggage on commercial flights from Micronesia. Evidence of exports to the US mainland exists, but is unquantifiable given existing data. Hawaiian nearshore fisheries support fundamental cultural values including subsistence, activity, traditional knowledge, and social cohesion. These small-scale coral reef fisheries provide large-scale benefits to the economy, food security, and cultural practices of Hawaiʻi, underscoring the need for sustainable management. This research highlights the value of information on the value chain for small-scale production systems, making the hidden economy of these fisheries visible and illuminating a range of conservation interventions applicable to Hawaiʻi and beyond. PMID:28771508

Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation.

PubMed

Yang, Hongyu; Huang, Di; Wang, Yunhong; Wang, Heng; Tang, Yuanyan

2016-06-01

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue using hidden factor analysis joint sparse representation. In contrast to the majority of tasks in the literature that integrally handle the facial texture, the proposed aging approach separately models the person-specific facial properties that tend to be stable in a relatively long period and the age-specific clues that gradually change over time. It then transforms the age component to a target age group via sparse reconstruction, yielding aging effects, which is finally combined with the identity component to achieve the aged face. Experiments are carried out on three face aging databases, and the results achieved clearly demonstrate the effectiveness and robustness of the proposed method in rendering a face with aging effects. In addition, a series of evaluations prove its validity with respect to identity preservation and aging effect generation.

Multi-cultural Wikipedia mining of geopolitics interactions leveraging reduced Google matrix analysis

NASA Astrophysics Data System (ADS)

Frahm, Klaus M.; El Zant, Samer; Jaffrès-Runser, Katia; Shepelyansky, Dima L.

2017-09-01

Geopolitics focuses on political power in relation to geographic space. Interactions among world countries have been widely studied at various scales, observing economic exchanges, world history or international politics among others. This work exhibits the potential of Wikipedia mining for such studies. Indeed, Wikipedia stores valuable fine-grained dependencies among countries by linking webpages together for diverse types of interactions (not only related to economical, political or historical facts). We mine herein the Wikipedia networks of several language editions using the recently proposed method of reduced Google matrix analysis. This approach allows to establish direct and hidden links between a subset of nodes that belong to a much larger directed network. Our study concentrates on 40 major countries chosen worldwide. Our aim is to offer a multicultural perspective on their interactions by comparing networks extracted from five different Wikipedia language editions, emphasizing English, Russian and Arabic ones. We demonstrate that this approach allows to recover meaningful direct and hidden links among the 40 countries of interest.

The Factors That Influence and Protect Against Power Imbalance in Covert Bullying Among Preadolescent Children at School: A Thematic Analysis.

PubMed

Nelson, Helen J; Burns, Sharyn K; Kendall, Garth E; Schonert-Reichl, Kimberly A

2017-01-01

In this article, the perceptions of preadolescent children (ages 9-11) regarding factors that influence and protect against power imbalance associated with covert aggression and bullying are explored. In aggression research, the term covert has been typically used to describe relational, indirect, and social acts of aggression that are hidden. These behaviors contrast with overt physical and verbal aggression. Children have previously conveyed their belief that covert aggression is harmful because adults do not see it even though children, themselves, are aware. We used focus groups to explore children's understanding of covert aggression and to identify children's experience and perception of adult support in relation to bullying. Thematic analysis supported the definition of covert aggression as that which is intentionally hidden from adults. Friendship, social exclusion, and secret from teacher were identified as factors that influence power imbalance, while support from friends and adult support protected against power imbalance.

Analysis of world terror networks from the reduced Google matrix of Wikipedia

NASA Astrophysics Data System (ADS)

El Zant, Samer; Frahm, Klaus M.; Jaffrès-Runser, Katia; Shepelyansky, Dima L.

2018-01-01

We apply the reduced Google matrix method to analyze interactions between 95 terrorist groups and determine their relationships and influence on 64 world countries. This is done on the basis of the Google matrix of the English Wikipedia (2017) composed of 5 416 537 articles which accumulate a great part of global human knowledge. The reduced Google matrix takes into account the direct and hidden links between a selection of 159 nodes (articles) appearing due to all paths of a random surfer moving over the whole network. As a result we obtain the network structure of terrorist groups and their relations with selected countries including hidden indirect links. Using the sensitivity of PageRank to a weight variation of specific links we determine the geopolitical sensitivity and influence of specific terrorist groups on world countries. The world maps of the sensitivity of various countries to influence of specific terrorist groups are obtained. We argue that this approach can find useful application for more extensive and detailed data bases analysis.

Analyzing Hidden Semantics in Social Bookmarking of Open Educational Resources

NASA Astrophysics Data System (ADS)

Minguillón, Julià

Web 2.0 services such as social bookmarking allow users to manage and share the links they find interesting, adding their own tags for describing them. This is especially interesting in the field of open educational resources, as delicious is a simple way to bridge the institutional point of view (i.e. learning object repositories) with the individual one (i.e. personal collections), thus promoting the discovering and sharing of such resources by other users. In this paper we propose a methodology for analyzing such tags in order to discover hidden semantics (i.e. taxonomies and vocabularies) that can be used to improve descriptions of learning objects and make learning object repositories more visible and discoverable. We propose the use of a simple statistical analysis tool such as principal component analysis to discover which tags create clusters that can be semantically interpreted. We will compare the obtained results with a collection of resources related to open educational resources, in order to better understand the real needs of people searching for open educational resources.

Data Envelopment Analysis for steel production with the use of Total Material Requirement

NASA Astrophysics Data System (ADS)

Oyaizu, Akira; Cravioto, Jordi; Yamasue, Eiji; Daigo, Ichiro

2018-06-01

High properties of stainless steels can be achieved by adding alloying elements and/or by structure control through complex heat treatments. Evaluations of such processes have so far been made in terms of the carbon dioxide emissions emitted or the energy consumption, but less attention has been given to resource intensity and "hidden flows". Using Data Envelopment Analysis (DEA), this study evaluates the efficiency of the environmental impact, characterised through Total Material Requirement (TMR), a measurement of hidden flows, and three properties (two mechanical and one chemical) of the materials obtained after manufacturing. Out of sample of 72 stainless steels it was found that seven (SUS312L, SUS836L, SUS447J1, SUSXM27, SUS410, SUS420F2, and SUS329J4L) showed the highest comparative efficiency, and that, when classifying the sample into four groups, the production of martensitic steels showed the highest efficiency (88%), followed by ferritic and duplex (82.6% each) and lastly austenitic (43.3%).

The importance of situation-specific encodings: analysis of a simple connectionist model of letter transposition effects

NASA Astrophysics Data System (ADS)

Fang, Shin-Yi; Smith, Garrett; Tabor, Whitney

2018-04-01

This paper analyses a three-layer connectionist network that solves a translation-invariance problem, offering a novel explanation for transposed letter effects in word reading. Analysis of the hidden unit encodings provides insight into two central issues in cognitive science: (1) What is the novelty of claims of "modality-specific" encodings? and (2) How can a learning system establish a complex internal structure needed to solve a problem? Although these topics (embodied cognition and learnability) are often treated separately, we find a close relationship between them: modality-specific features help the network discover an abstract encoding by causing it to break the initial symmetries of the hidden units in an effective way. While this neural model is extremely simple compared to the human brain, our results suggest that neural networks need not be black boxes and that carefully examining their encoding behaviours may reveal how they differ from classical ideas about the mind-world relationship.

Topic Time Series Analysis of Microblogs

DTIC Science & Technology

2014-10-01

network, may be closer to a media distribution site, where the media is user produced [14]. Analysis of the text content includes both general models as...is generated by Instagram . Topic 80, Distance: 143.2101 Top words: 1. rawr 2. ˆ0ˆ 3. kill 4. jurassic 5. dinosaur Analysis: This topic is quite...data, lack of reliable event information, hidden temporal trends, and the vastly diverse nature of content . In the present work, we examine spatio

ResStock Analysis Tool | Buildings | NREL

Science.gov Websites

Energy and Cost Savings for U.S. Homes Contact Eric Wilson to learn how ResStock can benefit your approach to large-scale residential energy analysis by combining: Large public and private data sources uncovered $49 billion in potential annual utility bill savings through cost-effective energy efficiency

The Pedagogical Foundations of Primary School Inspector Leonor Serrano (1914-1939)

ERIC Educational Resources Information Center

Ortells Roca, Miguel; Traver Martí, Juan

2018-01-01

This article aims to reconstruct the pedagogy of Leonor Serrano, a Spanish school inspector working and developing her theories between 1914 and 1939. We use an interrogative-analytical methodology based on content analysis of her texts to reconstruct her educational theory. The theoretical deductive elements are uncovered in the analysis of the…

Increased taxon sampling reveals thousands of hidden orthologs in flatworms

PubMed Central

2017-01-01

Gains and losses shape the gene complement of animal lineages and are a fundamental aspect of genomic evolution. Acquiring a comprehensive view of the evolution of gene repertoires is limited by the intrinsic limitations of common sequence similarity searches and available databases. Thus, a subset of the gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology to sequenced animal lineages—mistakenly considered new genes—but actually representing rapidly evolving orthologs or undetected paralogs. Here, we describe Leapfrog, a simple automated BLAST pipeline that leverages increased taxon sampling to overcome long evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by transitive homology. As a case study, we used 35 transcriptomes of 29 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and HaMStR, two common orthogroup inference algorithms. Unexpectedly, we do not observe a correlation between the number of putative hidden orthologs in a lineage and its “average” evolutionary rate. Hidden orthologs do not show unusual sequence composition biases that might account for systematic errors in sequence similarity searches. Instead, gene duplication with divergence of one paralog and weak positive selection appear to underlie hidden orthology in Platyhelminthes. By using Leapfrog, we identify key centrosome-related genes and homeodomain classes previously reported as absent in free-living flatworms, e.g., planarians. Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of the gene repertoire in flatworms, qualifying the impact of gene losses and gains in gene complement evolution. PMID:28400424

A Rose By Other Names: Some General Musings on Lawrence and Colleagues' Hidden Curriculum Scoping Review.

PubMed

Hafferty, Frederic W; Martimianakis, Maria Athina

2017-11-07

In this Commentary, the authors explore the scoping review by Lawrence and colleagues by challenging their conclusion that with over 25 years' worth of "ambiguous and seemingly ubiquitous use" of the hidden curriculum construct in health professions education scholarship, it is time to either move to a more uniform definitional foundation or abandon the term altogether. The commentary authors counter these remedial propositions by foregrounding the importance of theoretical diversity and the conceptual richness afforded when the hidden curriculum construct is used as an entry point for studying the interstitial space between the formal and a range of other-than-formal domains of learning. Further, they document how tightly-delimited scoping strategies fail to capture the wealth of educational scholarship that operates within a hidden curriculum framework, including "hidden" hidden curriculum articles, studies that employ alternative constructs, and investigations that target important tacit socio-cultural influences on learners and faculty without formally deploying the term. They offer examples of how the hidden curriculum construct, while undergoing significant transformation in its application within the field of health professions education, has created the conceptual foundation for the application of a number of critical perspectives that make visible the field's political investments in particular forms of knowing and associated practices. Finally, the commentary authors invite readers to consider the methodological promise afforded by conceptual heterogeneity, particularly strands of scholarship that resituate the hidden curriculum concept within the magically expansive dance of social relationships, social learning, and social life that form the learning environments of health professions education.

FIMP dark matter freeze-in gauge mediation and hidden sector

NASA Astrophysics Data System (ADS)

Tsao, Kuo-Hsing

2018-07-01

We explore the dark matter freeze-in mechanism within the gauge mediation framework, which involves a hidden feebly interacting massive particle (FIMP) coupling feebly with the messenger fields while the messengers are still in the thermal bath. The FIMP is the fermionic component of the pseudo-moduli in a generic metastable supersymmetry (SUSY) breaking model and resides in the hidden sector. The relic abundance and the mass of the FIMP are determined by the SUSY breaking scale and the feeble coupling. The gravitino, which is the canonical dark matter candidate in the gauge mediation framework, contributes to the dark matter relic abundance along with the freeze-in of the FIMP. The hidden sector thus becomes two-component with both the FIMP and gravitino lodging in the SUSY breaking hidden sector. We point out that the ratio between the FIMP and the gravitino is determined by how SUSY breaking is communicated to the messengers. In particular when the FIMP dominates the hidden sector, the gravitino becomes the minor contributor in the hidden sector. Meanwhile, the neutralino is assumed to be both the weakly interacting massive particle dark matter candidate in the freeze-out mechanism and the lightest observable SUSY particle. We further find out the neutralino has the sub-leading contribution to the current dark matter relic density in the parameter space of our freeze-in gauge mediation model. Our result links the SUSY breaking scale in the gauge mediation framework with the FIMP freeze-in production rate leading to a natural and predicting scenario for the studies of the dark matter in the hidden sector.

What Should We Do With a Hidden Curriculum When We Fine One?

ERIC Educational Resources Information Center

Martin, Jane R.

1976-01-01

A hidden curriculum consists of those learning states of a setting that are either unintended or intended but not openly acknowledged to the learners in the setting unless the learners are aware of them. Consciousness-raising may be the best weapon of individuals who are subject to hidden curricula. (Author/MLF)

Manifestations of Hidden Curriculum in a Community College Online Opticianry Program: An Ecological Approach

ERIC Educational Resources Information Center

Hubbard, Barry

2010-01-01

Understanding the influential factors at work within an online learning environment is a growing area of interest. Hidden or implicit expectations, skill sets, knowledge, and social process can help or hinder student achievement, belief systems, and persistence. This qualitative study investigated how hidden curricular issues transpired in an…

The Hidden Reason Behind Children's Misbehavior.

ERIC Educational Resources Information Center

Nystul, Michael S.

1986-01-01

Discusses hidden reason theory based on the assumptions that: (1) the nature of people is positive; (2) a child's most basic psychological need is involvement; and (3) a child has four possible choices in life (good somebody, good nobody, bad somebody, or severely mentally ill.) A three step approach for implementing hidden reason theory is…

Student Teaching: A Hidden Wholeness

ERIC Educational Resources Information Center

Bowman, Richard F.

2007-01-01

Productive student teachers lead learning by emergently sensing and honoring the hidden wholeness of life in classrooms. That hidden wholeness mirrors seven contextual concerns which learners reflect upon in the everydayness of classroom life: What are we going to do in class today? What am I going to have to do in class? What counts in today's…

Environmental Assessment for the Expansion of Permitted Land and Operations at the 9940 Complex and Thunder Range at Sandia National Laboratories/New Mexico

DTIC Science & Technology

2008-03-01

vivipara Hidden flower Cryptantha crassisepala Hidden flower Cryptantha fulvocanescens James’s hidden flower Cryptantha jamesii Buffalo gourd...pumila Bigbract verbena ta Verbena bractea Banana yucca ta Yucca bacca Soapweed yucca Yucca glauca Rocky Mountain zinnia Zinnia grandiflora A-9

Hidden Agendas in Marriage: Affective and Longitudinal Dimensions.

ERIC Educational Resources Information Center

Krokoff, Lowell J.

1990-01-01

Examines how couples' discussions of troublesome problems reveal hidden agendas (issues not directly discussed or explored). Finds disgust and contempt are at the core of both love and respect agendas for husbands and wives. Finds that wives' more than husbands' hidden agendas are directly predictive of how negatively they argue at home. (SR)

Driving style recognition method using braking characteristics based on hidden Markov model

PubMed Central

Wu, Chaozhong; Lyu, Nengchao; Huang, Zhen

2017-01-01

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced. Thirdly, the maximum likelihood logarithm could be implied from the observable parameters. The recognition accuracy of algorithm is verified through experiments and two common pattern recognition algorithms. The results showed that the driving style discrimination based on hidden Markov model algorithm could realize effective discriminant of driving style. PMID:28837580

A possible loophole in the theorem of Bell.

PubMed

Hess, K; Philipp, W

2001-12-04

The celebrated inequalities of Bell are based on the assumption that local hidden parameters exist. When combined with conflicting experimental results, these inequalities appear to prove that local hidden parameters cannot exist. This contradiction suggests to many that only instantaneous action at a distance can explain the Einstein, Podolsky, and Rosen type of experiments. We show that, in addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions that contribute to his being able to obtain the desired contradiction. For instance, Bell assumes that the hidden parameters do not depend on time and are governed by a single probability measure independent of the analyzer settings. We argue that the exclusion of time has neither a physical nor a mathematical basis but is based on Bell's translation of the concept of Einstein locality into the language of probability theory. Our additional set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does not permit Bell-type proofs to go forward.

Reputation and Competition in a Hidden Action Model

PubMed Central

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium. PMID:25329387

Reputation and competition in a hidden action model.

PubMed

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium.

Photoacoustic imaging of hidden dental caries by using a bundle of hollow optical fibers

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2018-02-01

Photoacoustic imaging system using a bundle of hollow-optical fibers to detect hidden dental caries is proposed. Firstly, we fabricated a hidden caries model with a brown pigment simulating a common color of caries lesion. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating Nd:YAG laser light with a 532 nm wavelength to occlusal surface of model tooth. We calculated by Fourier transform and found that the waveform from the carious part provides frequency components of approximately from 0.5 to 1.2 MHz. Then a photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for clinical applications. From intensity map of frequency components in 0.5-1.2 MHz, photoacoustic images of hidden caries in the simulated samples were successfully obtained.

On the LHC sensitivity for non-thermalised hidden sectors

NASA Astrophysics Data System (ADS)

Kahlhoefer, Felix

2018-04-01

We show under rather general assumptions that hidden sectors that never reach thermal equilibrium in the early Universe are also inaccessible for the LHC. In other words, any particle that can be produced at the LHC must either have been in thermal equilibrium with the Standard Model at some point or must be produced via the decays of another hidden sector particle that has been in thermal equilibrium. To reach this conclusion, we parametrise the cross section connecting the Standard Model to the hidden sector in a very general way and use methods from linear programming to calculate the largest possible number of LHC events compatible with the requirement of non-thermalisation. We find that even the HL-LHC cannot possibly produce more than a few events with energy above 10 GeV involving states from a non-thermalised hidden sector.

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

Using a voice-centered relational method of data analysis in a feminist study exploring the working world of nursing unit managers.

PubMed

Paliadelis, Penny; Cruickshank, Mary

2008-10-01

In this article, we discuss the application of a data analysis method used in a feminist study that explored the working world of nursing unit managers in Australia. The decision to use a voice-centered relational approach to the data was based on a desire to delve into the working world of nursing unit managers and uncover the layers within the narratives that specifically related to their perceptions of themselves, their world, and the context in which they work. Throughout this article, the focus is on how this method was applied to uncover multiple layers of meaning within the data, rather than on the researchers' and participants' roles in the coconstruction of interview data. An excerpt from an interview transcript is used to illustrate how the stories of the participants were explored using this method.

Hidden charged dark matter and chiral dark radiation

NASA Astrophysics Data System (ADS)

Ko, P.; Nagata, Natsumi; Tang, Yong

2017-10-01

In the light of recent possible tensions in the Hubble constant H0 and the structure growth rate σ8 between the Planck and other measurements, we investigate a hidden-charged dark matter (DM) model where DM interacts with hidden chiral fermions, which are charged under the hidden SU(N) and U(1) gauge interactions. The symmetries in this model assure these fermions to be massless. The DM in this model, which is a Dirac fermion and singlet under the hidden SU(N), is also assumed to be charged under the U(1) gauge symmetry, through which it can interact with the chiral fermions. Below the confinement scale of SU(N), the hidden quark condensate spontaneously breaks the U(1) gauge symmetry such that there remains a discrete symmetry, which accounts for the stability of DM. This condensate also breaks a flavor symmetry in this model and Nambu-Goldstone bosons associated with this flavor symmetry appear below the confinement scale. The hidden U(1) gauge boson and hidden quarks/Nambu-Goldstone bosons are components of dark radiation (DR) above/below the confinement scale. These light fields increase the effective number of neutrinos by δNeff ≃ 0.59 above the confinement scale for N = 2, resolving the tension in the measurements of the Hubble constant by Planck and Hubble Space Telescope if the confinement scale is ≲1 eV. DM and DR continuously scatter with each other via the hidden U(1) gauge interaction, which suppresses the matter power spectrum and results in a smaller structure growth rate. The DM sector couples to the Standard Model sector through the exchange of a real singlet scalar mixing with the Higgs boson, which makes it possible to probe our model in DM direct detection experiments. Variants of this model are also discussed, which may offer alternative ways to investigate this scenario.

Nonparametric model validations for hidden Markov models with applications in financial econometrics.

PubMed

Zhao, Zhibiao

2011-06-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise.

Cryptic diversity in Ptyodactylus (Reptilia: Gekkonidae) from the northern Hajar Mountains of Oman and the United Arab Emirates uncovered by an integrative taxonomic approach

PubMed Central

Simó-Riudalbas, Marc; de Pous, Philip; Els, Johannes; Jayasinghe, Sithum; Péntek-Zakar, Erika; Wilms, Thomas; Al-Saadi, Saleh

2017-01-01

The Hajar Mountains of south-eastern Arabia form an isolated massif surrounded by the sea to the east and by a large desert to the west. As a result of their old geological origin, geographical isolation, complex topography and local climate, these mountains provide an important refuge for endemic and relict species of plants and animals. With 19 species restricted to the Hajar Mountains, reptiles are the vertebrate group with the highest level of endemicity, becoming an excellent model for understanding the patterns and processes that generate and shape diversity in this arid mountain range. The geckos of the Ptyodactylus hasselquistii species complex are the largest geckos in Arabia and are found widely distributed across the Arabian Mountains, constituting a very important component of the reptile mountain fauna. Preliminary analyses suggested that their diversity in the Hajar Mountains may be higher than expected and that their systematics should be revised. In order to tackle these questions, we inferred a nearly complete calibrated phylogeny of the genus Ptyodactylus to identify the origin of the Hajar Mountains lineages using information from two mitochondrial and four nuclear genes. Genetic variability within the Hajar Mountains was further investigated using 68 specimens of Ptyodactylus from 46 localities distributed across the entire mountain range and sequenced for the same genes as above. The molecular phylogenies and morphological analyses as well as niche comparisons indicate the presence of two very old sister cryptic species living in allopatry: one restricted to the extreme northern Hajar Mountains and described as a new species herein; the other distributed across the rest of the Hajar Mountains that can be confidently assigned to the species P. orlovi. Similar to recent findings in the geckos of the genus Asaccus, the results of the present study uncover more hidden diversity in the northern Hajar Mountains and stress once again the importance of this unique mountain range as a hot spot of biodiversity and a priority focal point for reptile conservation in Arabia. PMID:28767644

What Makes You Tick? An Empirical Study of Space Science Related Social Media Communications Using Machine Learning

NASA Astrophysics Data System (ADS)

Hwong, Y. L.; Oliver, C.; Van Kranendonk, M. J.

2016-12-01

The rise of social media has transformed the way the public engages with scientists and science organisations. `Retweet', `Like', `Share' and `Comment' are a few ways users engage with messages on Twitter and Facebook, two of the most popular social media platforms. Despite the availability of big data from these digital footprints, research into social media science communication is scant. This paper presents the results of an empirical study into the processes and outcomes of space science related social media communications using machine learning. The study is divided into two main parts. The first part is dedicated to the use of supervised learning methods to investigate the features of highly engaging messages., e.g. highly retweeted tweets and shared Facebook posts. It is hypothesised that these messages contain certain psycholinguistic features that are unique to the field of space science. We built a predictive model to forecast the engagement levels of social media posts. By using four feature sets (n-grams, psycholinguistics, grammar and social media), we were able to achieve prediction accuracies in the vicinity of 90% using three supervised learning algorithms (Naive Bayes, linear classifier and decision tree). We conducted the same experiments on social media messages from three other fields (politics, business and non-profit) and discovered several features that are exclusive to space science communications: anger, authenticity, hashtags, visual descriptions and a tentative tone. The second part of the study focuses on the extraction of topics from a corpus of texts using topic modelling. This part of the study is exploratory in nature and uses an unsupervised method called Latent Dirichlet Allocation (LDA) to uncover previously unknown topics within a large body of documents. Preliminary results indicate a strong potential of topic model algorithms to automatically uncover themes hidden within social media chatters on space related issues, with keywords such as `exoplanet', `water' and `life' being clustered together forming a topic (i.e. 'Astrobiology'). Results also demonstrate the freewheeling nature of social media conversations, while providing evidence for the role of these platforms in facilitating meaningful exchanges among science audience.

Memetic algorithms for de novo motif-finding in biomedical sequences.

PubMed

Bi, Chengpeng

2012-09-01

The objectives of this study are to design and implement a new memetic algorithm for de novo motif discovery, which is then applied to detect important signals hidden in various biomedical molecular sequences. In this paper, memetic algorithms are developed and tested in de novo motif-finding problems. Several strategies in the algorithm design are employed that are to not only efficiently explore the multiple sequence local alignment space, but also effectively uncover the molecular signals. As a result, there are a number of key features in the implementation of the memetic motif-finding algorithm (MaMotif), including a chromosome replacement operator, a chromosome alteration-aware local search operator, a truncated local search strategy, and a stochastic operation of local search imposed on individual learning. To test the new algorithm, we compare MaMotif with a few of other similar algorithms using simulated and experimental data including genomic DNA, primary microRNA sequences (let-7 family), and transmembrane protein sequences. The new memetic motif-finding algorithm is successfully implemented in C++, and exhaustively tested with various simulated and real biological sequences. In the simulation, it shows that MaMotif is the most time-efficient algorithm compared with others, that is, it runs 2 times faster than the expectation maximization (EM) method and 16 times faster than the genetic algorithm-based EM hybrid. In both simulated and experimental testing, results show that the new algorithm is compared favorably or superior to other algorithms. Notably, MaMotif is able to successfully discover the transcription factors' binding sites in the chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) data, correctly uncover the RNA splicing signals in gene expression, and precisely find the highly conserved helix motif in the transmembrane protein sequences, as well as rightly detect the palindromic segments in the primary microRNA sequences. The memetic motif-finding algorithm is effectively designed and implemented, and its applications demonstrate it is not only time-efficient, but also exhibits excellent performance while compared with other popular algorithms. Copyright © 2012 Elsevier B.V. All rights reserved.

Cryptic diversity in Ptyodactylus (Reptilia: Gekkonidae) from the northern Hajar Mountains of Oman and the United Arab Emirates uncovered by an integrative taxonomic approach.

PubMed

Simó-Riudalbas, Marc; Metallinou, Margarita; de Pous, Philip; Els, Johannes; Jayasinghe, Sithum; Péntek-Zakar, Erika; Wilms, Thomas; Al-Saadi, Saleh; Carranza, Salvador

2017-01-01

The Hajar Mountains of south-eastern Arabia form an isolated massif surrounded by the sea to the east and by a large desert to the west. As a result of their old geological origin, geographical isolation, complex topography and local climate, these mountains provide an important refuge for endemic and relict species of plants and animals. With 19 species restricted to the Hajar Mountains, reptiles are the vertebrate group with the highest level of endemicity, becoming an excellent model for understanding the patterns and processes that generate and shape diversity in this arid mountain range. The geckos of the Ptyodactylus hasselquistii species complex are the largest geckos in Arabia and are found widely distributed across the Arabian Mountains, constituting a very important component of the reptile mountain fauna. Preliminary analyses suggested that their diversity in the Hajar Mountains may be higher than expected and that their systematics should be revised. In order to tackle these questions, we inferred a nearly complete calibrated phylogeny of the genus Ptyodactylus to identify the origin of the Hajar Mountains lineages using information from two mitochondrial and four nuclear genes. Genetic variability within the Hajar Mountains was further investigated using 68 specimens of Ptyodactylus from 46 localities distributed across the entire mountain range and sequenced for the same genes as above. The molecular phylogenies and morphological analyses as well as niche comparisons indicate the presence of two very old sister cryptic species living in allopatry: one restricted to the extreme northern Hajar Mountains and described as a new species herein; the other distributed across the rest of the Hajar Mountains that can be confidently assigned to the species P. orlovi. Similar to recent findings in the geckos of the genus Asaccus, the results of the present study uncover more hidden diversity in the northern Hajar Mountains and stress once again the importance of this unique mountain range as a hot spot of biodiversity and a priority focal point for reptile conservation in Arabia.

Global gene expression analysis using RNA-seq uncovered a new role for SR1/CAMTA3 transcription factor in salt stress

PubMed Central

Prasad, Kasavajhala V. S. K.; Abdel-Hameed, Amira A. E.; Xing, Denghui; Reddy, Anireddy S. N.

2016-01-01

Abiotic and biotic stresses cause significant yield losses in all crops. Acquisition of stress tolerance in plants requires rapid reprogramming of gene expression. SR1/CAMTA3, a member of signal responsive transcription factors (TFs), functions both as a positive and a negative regulator of biotic stress responses and as a positive regulator of cold stress-induced gene expression. Using high throughput RNA-seq, we identified ~3000 SR1-regulated genes. Promoters of about 60% of the differentially expressed genes have a known DNA binding site for SR1, suggesting that they are likely direct targets. Gene ontology analysis of SR1-regulated genes confirmed previously known functions of SR1 and uncovered a potential role for this TF in salt stress. Our results showed that SR1 mutant is more tolerant to salt stress than the wild type and complemented line. Improved tolerance of sr1 seedlings to salt is accompanied with the induction of salt-responsive genes. Furthermore, ChIP-PCR results showed that SR1 binds to promoters of several salt-responsive genes. These results suggest that SR1 acts as a negative regulator of salt tolerance by directly repressing the expression of salt-responsive genes. Overall, this study identified SR1-regulated genes globally and uncovered a previously uncharacterized role for SR1 in salt stress response. PMID:27251464

The Hidden Curriculum of Youth Policy: A Dutch Example

ERIC Educational Resources Information Center

Hopman, Marit; de Winter, Micha; Koops, Willem

2014-01-01

Youth policy is more than a mere response to the actual behavior of children, but it is equally influenced by values and beliefs of policy makers. These values are however rarely made explicit and, therefore, the authors refer to them as "the hidden curriculum" of youth policy. The study investigation explicates this hidden curriculum by…

Hidden School Dropout among Immigrant Students: A Cross-Sectional Study

ERIC Educational Resources Information Center

Makarova, Elena; Herzog, Walter

2013-01-01

Actual school dropout among immigrant youth has been addressed in a number of studies, but research on hidden school dropout among immigrant students is rare. Thus, the objective of this paper is to analyze hidden school dropout among primary school students with an immigrant background. The analyses were performed using survey data of 1186…

Secret Codes: The Hidden Curriculum of Semantic Web Technologies

ERIC Educational Resources Information Center

Edwards, Richard; Carmichael, Patrick

2012-01-01

There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate…

Hidden Costs of Hospital Based Delivery from Two Tertiary Hospitals in Western Nepal.

PubMed

Acharya, Jeevan; Kaehler, Nils; Marahatta, Sujan Babu; Mishra, Shiva Raj; Subedi, Sudarshan; Adhikari, Bipin

2016-01-01

Hospital based delivery has been an expensive experience for poor households because of hidden costs which are usually unaccounted in hospital costs. The main aim of this study was to estimate the hidden costs of hospital based delivery and determine the factors associated with the hidden costs. A hospital based cross-sectional study was conducted among 384 post-partum mothers with their husbands/house heads during the discharge time in Manipal Teaching Hospital and Western Regional Hospital, Pokhara, Nepal. A face to face interview with each respondent was conducted using a structured questionnaire. Hidden costs were calculated based on the price rate of the market during the time of the study. The total hidden costs for normal delivery and C-section delivery were 243.4 USD (US Dollar) and 321.6 USD respectively. Of the total maternity care expenditures; higher mean expenditures were found for food & drinking (53.07%), clothes (9.8%) and transport (7.3%). For postpartum women with their husband or house head, the total mean opportunity cost of "days of work loss" were 84.1 USD and 81.9 USD for normal delivery and C-section respectively. Factors such as literate mother (p = 0.007), employed house head (p = 0.011), monthly family income more than 25,000 NRs (Nepalese Rupees) (p = 0.014), private hospital as a place of delivery (p = 0.0001), C-section as a mode of delivery (p = 0.0001), longer duration (>5days) of stay in hospital (p = 0.0001), longer distance (>15km) from house to hospital (p = 0.0001) and longer travel time (>240 minutes) from house to hospital (p = 0.007) showed a significant association with the higher hidden costs (>25000 NRs). Experiences of hidden costs on hospital based delivery and opportunity costs of days of work loss were found high. Several socio-demographic factors, delivery related factors (place and mode of delivery, length of stay, distance from hospital and travel time) were associated with hidden costs. Hidden costs can be a critical factor for many poor and remote households who attend the hospital for delivery. Current remuneration (10-15 USD for normal delivery, 30 USD for complicated delivery and 70 USD for caesarean section delivery) for maternity incentive needs to account the hidden costs by increasing it to 250 USD for normal delivery and 350 USD for C-section. Decentralization of the obstetric care to remote and under-privileged population might reduce the economic burden of pregnant women and can facilitate their attendance at the health care centers.