Discovering Hidden Analogies in an Online Humanities Database.

ERIC Educational Resources Information Center

Cory, Kenneth A.

1999-01-01

Drawing upon an efficacious method for discovering previously unknown causes of medical syndromes and searching in the Humanities Index, an illuminating new humanities analogy between the epistemological ideas of Robert Frost and the ancient Greek philosopher Carneades was found by constructing a search statement in which proper names were coupled…

Hidden Expert Knowledge: The Knowledge That Counts for the Small School-District Superintendent

ERIC Educational Resources Information Center

Hyle, Adrienne E.; Ivory, Gary; McClellan, Rhonda L.

2010-01-01

Using Bereiter and Scardamalia's (1993) hidden expert knowledge, we explored what knowledge counts from the perspectives of working small school-district superintendents and the ways in which they gain that knowledge. This qualitative study used focus groups as its primary data collection method. Participants were 37 superintendents of districts…

A New Chaotic Flow with Hidden Attractor: The First Hyperjerk System with No Equilibrium

NASA Astrophysics Data System (ADS)

Ren, Shuili; Panahi, Shirin; Rajagopal, Karthikeyan; Akgul, Akif; Pham, Viet-Thanh; Jafari, Sajad

2018-02-01

Discovering unknown aspects of non-equilibrium systems with hidden strange attractors is an attractive research topic. A novel quadratic hyperjerk system is introduced in this paper. It is noteworthy that this non-equilibrium system can generate hidden chaotic attractors. The essential properties of such systems are investigated by means of equilibrium points, phase portrait, bifurcation diagram, and Lyapunov exponents. In addition, a fractional-order differential equation of this new system is presented. Moreover, an electronic circuit is also designed and implemented to verify the feasibility of the theoretical model.

Protein painting reveals solvent-excluded drug targets hidden within native protein–protein interfaces

PubMed Central

Luchini, Alessandra; Espina, Virginia; Liotta, Lance A.

2014-01-01

Identifying the contact regions between a protein and its binding partners is essential for creating therapies that block the interaction. Unfortunately, such contact regions are extremely difficult to characterize because they are hidden inside the binding interface. Here we introduce protein painting as a new tool that employs small molecules as molecular paints to tightly coat the surface of protein–protein complexes. The molecular paints, which block trypsin cleavage sites, are excluded from the binding interface. Following mass spectrometry, only peptides hidden in the interface emerge as positive hits, revealing the functional contact regions that are drug targets. We use protein painting to discover contact regions between the three-way interaction of IL1β ligand, the receptor IL1RI and the accessory protein IL1RAcP. We then use this information to create peptides and monoclonal antibodies that block the interaction and abolish IL1β cell signalling. The technology is broadly applicable to discover protein interaction drug targets. PMID:25048602

Mining Rare Associations between Biological Ontologies

PubMed Central

Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

2014-01-01

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations. PMID:24404165

Mining rare associations between biological ontologies.

PubMed

Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

2014-01-01

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

BioEve Search: A Novel Framework to Facilitate Interactive Literature Search

PubMed Central

Ahmed, Syed Toufeeq; Davulcu, Hasan; Tikves, Sukru; Nair, Radhika; Zhao, Zhongming

2012-01-01

Background. Recent advances in computational and biological methods in last two decades have remarkably changed the scale of biomedical research and with it began the unprecedented growth in both the production of biomedical data and amount of published literature discussing it. An automated extraction system coupled with a cognitive search and navigation service over these document collections would not only save time and effort, but also pave the way to discover hitherto unknown information implicitly conveyed in the texts. Results. We developed a novel framework (named “BioEve”) that seamlessly integrates Faceted Search (Information Retrieval) with Information Extraction module to provide an interactive search experience for the researchers in life sciences. It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and diseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover related concepts and keywords to search while information seeking. Conclusions. The BioEve Search framework makes it easier to enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of biomedical literature articles with ease. PMID:22693501

The digital library: an oxymoron?

PubMed Central

Guédon, J C

1999-01-01

"Virtual libraries" and "digital libraries" have become stock phrases of our times. But what do they really mean? While digital refers to a new form of document encoding and must be approached from that perspective, virtual resonates with aspects that modern philosophy treats with benign neglect at best. The word virtual harbors the notion of potential, and therein lies its hidden strength. Although strong commercial interests try to use the shift to a digital environment to redefine the political economy of knowledge, and thus virtualize libraries into a state of almost complete impotence, all hope is not lost. Librarians of virtualized libraries may well discover that they have re-empowered institutions if they place human interaction at the heart of their operations. In other words, rather than envisioning themselves as knowledge bankers sitting on treasure vaults of knowledge, they should see themselves as "hearts" dynamizing human communities. They should also see themselves as an essential part of these communities, and not as external repositories of knowledge. In this fashion, they will avoid the fate of becoming an oxymoron. PMID:9934524

Detecting hidden particles with MATHUSLA

NASA Astrophysics Data System (ADS)

Evans, Jared A.

2018-03-01

A hidden sector containing light long-lived particles provides a well-motivated place to find new physics. The recently proposed MATHUSLA experiment has the potential to be extremely sensitive to light particles originating from rare meson decays in the very long lifetime region. In this work, we illustrate this strength with the specific example of a light scalar mixed with the standard model-like Higgs boson, a model where MATHUSLA can further probe unexplored parameter space from exotic Higgs decays. Design augmentations should be considered in order to maximize the ability of MATHUSLA to discover very light hidden sector particles.

Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases

PubMed Central

Frijters, Raoul; van Vugt, Marianne; Smeets, Ruben; van Schaik, René; de Vlieg, Jacob; Alkema, Wynand

2010-01-01

The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs. PMID:20885778

Knowledge discovery from patients' behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services.

PubMed

Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

2016-01-01

The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers.

Knowledge discovery from patients’ behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services

PubMed Central

Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

2016-01-01

The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers. PMID:27610177

Modular representation of layered neural networks.

PubMed

Watanabe, Chihiro; Hiramatsu, Kaoru; Kashino, Kunio

2018-01-01

Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its internal representation has many nonlinear and complex parameters embedded in hierarchical layers. Therefore, it becomes important to establish a new methodology by which layered neural networks can be understood. In this paper, we propose a new method for extracting a global and simplified structure from a layered neural network. Based on network analysis, the proposed method detects communities or clusters of units with similar connection patterns. We show its effectiveness by applying it to three use cases. (1) Network decomposition: it can decompose a trained neural network into multiple small independent networks thus dividing the problem and reducing the computation time. (2) Training assessment: the appropriateness of a trained result with a given hyperparameter or randomly chosen initial parameters can be evaluated by using a modularity index. And (3) data analysis: in practical data it reveals the community structure in the input, hidden, and output layers, which serves as a clue for discovering knowledge from a trained neural network. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

"Core Knowledges": A Dissociation between Spatiotemporal Knowledge and Contact-Mechanics in a Non-Human Primate?

ERIC Educational Resources Information Center

Santos, Laurie R.

2004-01-01

Human toddlers demonstrate striking failures when searching for hidden objects that interact with other objects, yet successfully locate hidden objects that do not undergo mechanical interactions. This pattern hints at a developmental dissociation between contact-mechanical and spatiotemporal knowledge. Recent studies suggest that adult non-human…

Discovering Hidden Connections among Diseases, Genes and Drugs Based on Microarray Expression Profiles with Negative-Term Filtering

PubMed Central

2014-01-01

Microarrays based on gene expression profiles (GEPs) can be tailored specifically for a variety of topics to provide a precise and efficient means with which to discover hidden information. This study proposes a novel means of employing existing GEPs to reveal hidden relationships among diseases, genes, and drugs within a rich biomedical database, PubMed. Unlike the co-occurrence method, which considers only the appearance of keywords, the proposed method also takes into account negative relationships and non-relationships among keywords, the importance of which has been demonstrated in previous studies. Three scenarios were conducted to verify the efficacy of the proposed method. In Scenario 1, disease and drug GEPs (disease: lymphoma cancer, lymph node cancer, and drug: cyclophosphamide) were used to obtain lists of disease- and drug-related genes. Fifteen hidden connections were identified between the diseases and the drug. In Scenario 2, we adopted different diseases and drug GEPs (disease: AML-ALL dataset and drug: Gefitinib) to obtain lists of important diseases and drug-related genes. In this case, ten hidden connections were identified. In Scenario 3, we obtained a list of disease-related genes from the disease-related GEP (liver cancer) and the drug (Capecitabine) on the PharmGKB website, resulting in twenty-two hidden connections. Experimental results demonstrate the efficacy of the proposed method in uncovering hidden connections among diseases, genes, and drugs. Following implementation of the weight function in the proposed method, a large number of the documents obtained in each of the scenarios were judged to be related: 834 of 4028 documents, 789 of 1216 documents, and 1928 of 3791 documents in Scenarios 1, 2, and 3, respectively. The negative-term filtering scheme also uncovered a large number of negative relationships as well as non-relationships among these connections: 97 of 834, 38 of 789, and 202 of 1928 in Scenarios 1, 2, and 3, respectively. PMID:24915461

Look at my Arms!

NASA Image and Video Library

2005-07-25

This image shows the hidden spiral arms that were discovered around the galaxy called NGC 4625 top by the ultraviolet eyes of NASA Galaxy Evolution Explorer. An armless companion galaxy called NGC 4618 is pictured below.

What Is Going on Inside the Arrows? Discovering the Hidden Springs in Causal Models

PubMed Central

Murray-Watters, Alexander; Glymour, Clark

2016-01-01

Using Gebharter's (2014) representation, we consider aspects of the problem of discovering the structure of unmeasured sub-mechanisms when the variables in those sub-mechanisms have not been measured. Exploiting an early insight of Sober's (1998), we provide a correct algorithm for identifying latent, endogenous structure—sub-mechanisms—for a restricted class of structures. The algorithm can be merged with other methods for discovering causal relations among unmeasured variables, and feedback relations between measured variables and unobserved causes can sometimes be learned. PMID:27313331

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.

Finding your next core business.

PubMed

Zook, Chris

2007-04-01

How do you know when your core needs to change? And how do you determine what should replace it? From an in-depth study of 25 companies, the author, a strategy consultant, has discovered that it's possible to measure the vitality of a business's core. If it needs reinvention, he says, the best course is to mine hidden assets. Some of the 25 companies were in deep crisis when they began the process of redefining themselves. But, says Zook, management teams can learn to recognize early signs of erosion. He offers five diagnostic questions with which to evaluate the customers, key sources of differentiation, profit pools, capabilities, and organizational culture of your core business. The next step is strategic regeneration. In four-fifths of the companies Zook examined, a hidden asset was the centerpiece of the new strategy. He provides a map for identifying the hidden assets in your midst, which tend to fall into three categories: undervalued business platforms, untapped insights into customers, and underexploited capabilities. The Swedish company Dometic, for example, was manufacturing small absorption refrigerators for boats and RVs when it discovered a hidden asset: its understanding of, and access to, customers in the RV market. The company took advantage of a boom in that market to refocus on complete systems for live-in vehicles. The Danish company Novozymes, which produced relatively low-tech commodity enzymes such as those used in detergents, realized that its underutilized biochemical capability in genetic and protein engineering was a hidden asset and successfully refocused on creating bioengineered specialty enzymes. Your next core business is not likely to announce itself with fanfare. Use the author's tools to conduct an internal audit of possibilities and pinpoint your new focus.

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.

DNA barcodes, species delimitation, and bioassessment: issues of diversity, analysis, and standardization

EPA Science Inventory

DNA barcoding has the capability to uncover cryptic diversity otherwise undetectable using morphology alone. For aquatic bioassessment, this opportunity to discover hidden biodiversity presents new data for incorporation into environmental monitoring programs. Unfortunately, the ...

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…

Data Mining of NASA Boeing 737 Flight Data: Frequency Analysis of In-Flight Recorded Data

NASA Technical Reports Server (NTRS)

Butterfield, Ansel J.

2001-01-01

Data recorded during flights of the NASA Trailblazer Boeing 737 have been analyzed to ascertain the presence of aircraft structural responses from various excitations such as the engine, aerodynamic effects, wind gusts, and control system operations. The NASA Trailblazer Boeing 737 was chosen as a focus of the study because of a large quantity of its flight data records. The goal of this study was to determine if any aircraft structural characteristics could be identified from flight data collected for measuring non-structural phenomena. A number of such data were examined for spatial and frequency correlation as a means of discovering hidden knowledge of the dynamic behavior of the aircraft. Data recorded from on-board dynamic sensors over a range of flight conditions showed consistently appearing frequencies. Those frequencies were attributed to aircraft structural vibrations.

Nanotechnology drives a paradigm shift on protein misfolding diseases and amyloidosis

NASA Astrophysics Data System (ADS)

Bellotti, Vittorio; Stoppini, Monica

2012-06-01

In almost a century of scientific work on the mechanism of amyloid diseases much of the attention has been focused on the amyloid fibrils, which still represent the diagnostic hallmark of the disease and are easily identified in affected organs for their peculiar tinctorial properties and the fibrillar shape. However, it has been lately discovered that the seeds of the pathogenesis are deeply hidden in the structure and folding dynamics of proteins at the monomeric state which almost indistinguishable from the normal counterpart through classical biochemical approaches. In the recent years soluble oligomeric/prefibrillar species, putatively cytotoxic, were discovered and even more recently polymorphisms of shape and structure of fibrils was emerging as a property that could dictate the bioactivity of amyloid as well as the specificity of its tissue localization. Nanotechnology through the biophysical analysis of the single molecules (monomers or oligomers or fibrils) is the propulsive disciplines in the transformation of our knowledge on the molecular mechanism of this disease. It will provide, in the forthcoming years, precious analytical devices mimicking the biological microenvironment where the molecular events causing the amyloid formation will be monitored and possibly modulated in a real time frame.

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…

Exhibitions in Sight.

ERIC Educational Resources Information Center

Wasserman, Burton

1978-01-01

Early in the eighteenth century, Pompeii was discovered, a city that had been hidden for sixteen centuries by volcanic lava. There is a traveling exhibition of the sculptures, friezes, mosaics, and paintings being shown around the United States. Described is the history and contents of "Pompeii--A.D. 79." (RK)

Cross-modal learning to rank via latent joint representation.

PubMed

Wu, Fei; Jiang, Xinyang; Li, Xi; Tang, Siliang; Lu, Weiming; Zhang, Zhongfei; Zhuang, Yueting

2015-05-01

Cross-modal ranking is a research topic that is imperative to many applications involving multimodal data. Discovering a joint representation for multimodal data and learning a ranking function are essential in order to boost the cross-media retrieval (i.e., image-query-text or text-query-image). In this paper, we propose an approach to discover the latent joint representation of pairs of multimodal data (e.g., pairs of an image query and a text document) via a conditional random field and structural learning in a listwise ranking manner. We call this approach cross-modal learning to rank via latent joint representation (CML²R). In CML²R, the correlations between multimodal data are captured in terms of their sharing hidden variables (e.g., topics), and a hidden-topic-driven discriminative ranking function is learned in a listwise ranking manner. The experiments show that the proposed approach achieves a good performance in cross-media retrieval and meanwhile has the capability to learn the discriminative representation of multimodal data.

Object Permanence After a 24-Hr Delay and Leaving the Locale of Disappearance: The Role of Memory, Space, and Identity

PubMed Central

Moore, M. Keith; Meltzoff, Andrew N.

2005-01-01

Fourteen-month-old infants saw an object hidden inside a container and were removed from the disappearance locale for 24 hr. Upon their return, they searched correctly for the hidden object, demonstrating object permanence and long-term memory. Control infants who saw no disappearance did not search. In Experiment 2, infants returned to see the container either in the same or a different room. Performance by room-change infants dropped to baseline levels, suggesting that infant search for hidden objects is guided by numerical identity. Infants seek the individual object that disappeared, which exists in its original location, not in a different room. A new behavior, identity-verifying search, was discovered and quantified. Implications are drawn for memory, spatial understanding, object permanence, and object identity. PMID:15238047

Object permanence after a 24-hr delay and leaving the locale of disappearance: the role of memory, space, and identity.

PubMed

Moore, M Keith; Meltzoff, Andrew N

2004-07-01

Fourteen-month-old infants saw an object hidden inside a container and were removed from the disappearance locale for 24 hr. Upon their return, they searched correctly for the hidden object, demonstrating object permanence and long-term memory. Control infants who saw no disappearance did not search. In Experiment 2, infants returned to see the container either in the same or a different room. Performance by room-change infants dropped to baseline levels, suggesting that infant search for hidden objects is guided by numerical identity. Infants seek the individual object that disappeared, which exists in its original location, not in a different room. A new behavior, identity-verifying search, was discovered and quantified. Implications are drawn for memory, spatial understanding, object permanence, and object identity. Copyright 2004 APA, all rights reserved

Young children's (Homo sapiens) understanding of knowledge formation in themselves and others.

PubMed

Povinelli, D J; deBlois, S

1992-09-01

Three- and 4-year-old children (Homo sapiens) were tested for comprehension of knowledge formation. In Experiment 1, 34 subjects watched as a surprise was hidden under 1 of 4 obscured cups. The experimenter then pointed to the cup. All children searched under the correct cup, but no 3-year-olds (in contrast to most 4-year-olds) could explain how they knew where to look. Subjects then discriminated between simultaneous pointing by 2 adults, one who had hidden a surprise and one who had left the room before the surprise was hidden. Most 4-year-olds (but no 3-year-olds) showed clear discrimination between the adults. In Experiment 2, 16 subjects were tested with procedures designed to make the source of their own knowledge more obvious, but this had no effect on performance. We conclude that studies using very similar procedures with chimpanzees and rhesus macaques were measuring an ability (or inability) to understand how knowledge states form.

Overcoming Stereotypes, Discovering Hidden Capitals

ERIC Educational Resources Information Center

Beckett, Lori; Wrigley, Terry

2014-01-01

This article presents a model of teacher research supported by academic partners to develop a better understanding of the barriers to education faced by young people growing up in poverty. It critiques politicians' demands for teachers to "close the gap" for ignoring the cumulative intergenerational effects of deprivation. The authors…

Experimental evolution reveals hidden diversity in evolutionary pathways.

PubMed

Lind, Peter A; Farr, Andrew D; Rainey, Paul B

2015-03-25

Replicate populations of natural and experimental organisms often show evidence of parallel genetic evolution, but the causes are unclear. The wrinkly spreader morph of Pseudomonas fluorescens arises repeatedly during experimental evolution. The mutational causes reside exclusively within three pathways. By eliminating these, 13 new mutational pathways were discovered with the newly arising WS types having fitnesses similar to those arising from the commonly passaged routes. Our findings show that parallel genetic evolution is strongly biased by constraints and we reveal the genetic bases. From such knowledge, and in instances where new phenotypes arise via gene activation, we suggest a set of principles: evolution proceeds firstly via pathways subject to negative regulation, then via promoter mutations and gene fusions, and finally via activation by intragenic gain-of-function mutations. These principles inform evolutionary forecasting and have relevance to interpreting the diverse array of mutations associated with clinically identical instances of disease in humans.

Discovering Hidden Resources: Assistive Technology Recycling, Refurbishing, and Redistribution. RESNA Technical Assistance Project.

ERIC Educational Resources Information Center

RESNA: Association for the Advancement of Rehabilitation Technology, Arlington, VA.

This monograph discusses the benefits of recycling and reusing assistive technology for students with disabilities. It begins by discussing the benefits of recycled assistive technology for suppliers, students, and consumers, and then profiles programmatic models for assistive technology recycling programs. The advantages and disadvantages for…

Geocaching: 21st-Century Hide-and-Seek

ERIC Educational Resources Information Center

Schlatter, Barbara Elwood; Hurd, Amy R.

2005-01-01

Looking for a new adventure that combines technology and physical activity with nature? Try geocaching (pronounced geocashing)! Geocachers use Global Positioning System (GPS) receivers and satellite data to search and find hidden treasures (or caches) around the world. Enthusiasts visit web sites (e.g., www.geocaching.com) to discover the…

Mining the Values in the Curriculum.

ERIC Educational Resources Information Center

Ryan, Kevin

1993-01-01

Schools must provide opportunities for students to discover what is most worth knowing, as they prepare to be citizens, good workers, good private individuals. Formal curriculum is one vehicle for teaching Tao (universal path to becoming a good person). Hidden curriculum can also convey profound teachings, if a spirit of fairness predominates,…

Hidden sketches by Leonardo da Vinci revealed

NASA Astrophysics Data System (ADS)

Dumé, Belle

2009-02-01

Three drawings on the back of Leonardo da Vinci's The Virgin and Child with St Anne (circa 1508) have been discovered by researchers led by Michel Menu from the Centre de Recherche et de Restauration des Musées de France (C2RMF) and the Louvre Museum in Paris.

When Stones Teach.

ERIC Educational Resources Information Center

Lucier, Todd

2001-01-01

Creating towers of balanced stones is a versatile outdoor learning activity that can be experienced in the classroom, school yard, forest, or parking lot. Students discover hidden talents, learn to work and communicate clearly with others, and reconnect with the natural world. Several variations on the exercise are given, along with principles of…

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

On some dynamical chameleon systems

NASA Astrophysics Data System (ADS)

Burkin, I. M.; Kuznetsova, O. I.

2018-03-01

It is now well known that dynamical systems can be categorized into systems with self-excited attractors and systems with hidden attractors. A self-excited attractor has a basin of attraction that is associated with an unstable equilibrium, while a hidden attractor has a basin of attraction that does not intersect with small neighborhoods of any equilibrium points. Hidden attractors play the important role in engineering applications because they allow unexpected and potentially disastrous responses to perturbations in a structure like a bridge or an airplane wing. In addition, complex behaviors of chaotic systems have been applied in various areas from image watermarking, audio encryption scheme, asymmetric color pathological image encryption, chaotic masking communication to random number generator. Recently, researchers have discovered the so-called “chameleon systems”. These systems were so named because they demonstrate self-excited or hidden oscillations depending on the value of parameters. The present paper offers a simple algorithm of synthesizing one-parameter chameleon systems. The authors trace the evolution of Lyapunov exponents and the Kaplan-Yorke dimension of such systems which occur when parameters change.

Hidden correlations entailed by q-non additivity render the q-monoatomic gas highly non trivial

NASA Astrophysics Data System (ADS)

Plastino, A.; Rocca, M. C.

2018-01-01

It ts known that Tsallis' q-non-additivity entails hidden correlations. It has also been shown that even for a monoatomic gas, both the q-partition function Z and the mean energy 〈 U 〉 diverge and, in particular, exhibit poles for certain values of the Tsallis non additivity parameter q. This happens because Z and 〈 U 〉 both depend on a Γ-function. This Γ, in turn, depends upon the spatial dimension ν. We encounter three different regimes according to the argument A of the Γ-function. (1) A > 0, (2) A < 0 and Γ > 0 outside the poles. (3) A displays poles and the physics is obtained via dimensional regularization. In cases (2) and (3) one discovers gravitational effects and quartets of particles. Moreover, bound states and gravitational effects emerge as a consequence of the hidden q-correlations.

Multi-agents and learning: Implications for Webusage mining.

PubMed

Lotfy, Hewayda M S; Khamis, Soheir M S; Aboghazalah, Maie M

2016-03-01

Characterization of user activities is an important issue in the design and maintenance of websites. Server weblog files have abundant information about the user's current interests. This information can be mined and analyzed therefore the administrators may be able to guide the users in their browsing activity so they may obtain relevant information in a shorter span of time to obtain user satisfaction. Web-based technology facilitates the creation of personally meaningful and socially useful knowledge through supportive interactions, communication and collaboration among educators, learners and information. This paper suggests a new methodology based on learning techniques for a Web-based Multiagent-based application to discover the hidden patterns in the user's visited links. It presents a new approach that involves unsupervised, reinforcement learning, and cooperation between agents. It is utilized to discover patterns that represent the user's profiles in a sample website into specific categories of materials using significance percentages. These profiles are used to make recommendations of interesting links and categories to the user. The experimental results of the approach showed successful user pattern recognition, and cooperative learning among agents to obtain user profiles. It indicates that combining different learning algorithms is capable of improving user satisfaction indicated by the percentage of precision, recall, the progressive category weight and F 1-measure.

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

Multi-agents and learning: Implications for Webusage mining

PubMed Central

Lotfy, Hewayda M.S.; Khamis, Soheir M.S.; Aboghazalah, Maie M.

2015-01-01

Characterization of user activities is an important issue in the design and maintenance of websites. Server weblog files have abundant information about the user’s current interests. This information can be mined and analyzed therefore the administrators may be able to guide the users in their browsing activity so they may obtain relevant information in a shorter span of time to obtain user satisfaction. Web-based technology facilitates the creation of personally meaningful and socially useful knowledge through supportive interactions, communication and collaboration among educators, learners and information. This paper suggests a new methodology based on learning techniques for a Web-based Multiagent-based application to discover the hidden patterns in the user’s visited links. It presents a new approach that involves unsupervised, reinforcement learning, and cooperation between agents. It is utilized to discover patterns that represent the user’s profiles in a sample website into specific categories of materials using significance percentages. These profiles are used to make recommendations of interesting links and categories to the user. The experimental results of the approach showed successful user pattern recognition, and cooperative learning among agents to obtain user profiles. It indicates that combining different learning algorithms is capable of improving user satisfaction indicated by the percentage of precision, recall, the progressive category weight and F1-measure. PMID:26966569

Efficiently Exploring Multilevel Data with Recursive Partitioning

ERIC Educational Resources Information Center

Martin, Daniel P.; von Oertzen, Timo; Rimm-Kaufman, Sara E.

2015-01-01

There is an increasing number of datasets with many participants, variables, or both, in education and other fields that often deal with large, multilevel data structures. Once initial confirmatory hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform…

The Jossey-Bass Reader on Gender in Education. The Jossey-Bass Education Series.

ERIC Educational Resources Information Center

2002

These papers examine various perspectives on the gender debate in education: (1) "'Too Strong for a Woman': The Five Words That Created Title IX" (Bernice R. Sandler); (2) "Feminists Discover the Hidden Injuries of Coeducation" (David Tyack and Elisabeth Hansot); (3) "Images of Relationship" (Carol Gilligan); (4)…

The Implicit Association Test as a Class Assignment: Student Affective and Attitudinal Reactions

ERIC Educational Resources Information Center

Morris, Kathryn A.; Ashburn-Nardo, Leslie

2010-01-01

The Implicit Association Test (IAT) is a popular means of examining "hidden" biases. However, some express concerns about classroom use of the IAT, citing students' potentially negative affective reactions to taking the IAT and discovering their implicit biases. To investigate the validity of this criticism, 35 social psychology students completed…

Exploring the Integration of Data Mining and Data Visualization

ERIC Educational Resources Information Center

Zhang, Yi

2011-01-01

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be…

Ontology-Based Empirical Knowledge Verification for Professional Virtual Community

ERIC Educational Resources Information Center

Chen, Yuh-Jen

2011-01-01

A professional virtual community provides an interactive platform for enterprise experts to create and share their empirical knowledge cooperatively, and the platform contains a tremendous amount of hidden empirical knowledge that knowledge experts have preserved in the discussion process. Therefore, enterprise knowledge management highly…

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

Accelerating the discovery of hidden two-dimensional magnets using machine learning and first principle calculations

NASA Astrophysics Data System (ADS)

Miyazato, Itsuki; Tanaka, Yuzuru; Takahashi, Keisuke

2018-02-01

Two-dimensional (2D) magnets are explored in terms of data science and first principle calculations. Machine learning determines four descriptors for predicting the magnetic moments of 2D materials within reported 216 2D materials data. With the trained machine, 254 2D materials are predicted to have high magnetic moments. First principle calculations are performed to evaluate the predicted 254 2D materials where eight undiscovered stable 2D materials with high magnetic moments are revealed. The approach taken in this work indicates that undiscovered materials can be surfaced by utilizing data science and materials data, leading to an innovative way of discovering hidden materials.

Using "1 = 2" to Inspire and Learn

ERIC Educational Resources Information Center

Premadasa, Kirthi; Samaranayake, Geetha

2012-01-01

Mathematical fallacies have an embedded sense of awe and mystery that can be used effectively in a classroom to inspire students to tackle a fallacy and find the "hidden" violation. In doing so, the student may discover the consequence of a rule violation in a stimulating manner, thus making a lasting impact of the rule as well as providing the…

Writing to Survive: How Teachers and Teens Negotiate the Effects of Abuse, Violence, and Disaster

ERIC Educational Resources Information Center

Alvarez, Deborah M.

2010-01-01

This ethnographic research investigates how adolescents use writing. Deborah M. Alvarez uncovers the hidden abuses and violence that adolescents bore with each school day. In two different research sites, the author follows adolescents through their academic and personal lives to discover how they use writing only to uncover the impact the public…

The Use of Tetrads in the Analysis of Arts-Based Media

ERIC Educational Resources Information Center

Gouzouasis, Peter; LaMonde, Anne-Marie

2005-01-01

In this article, we chose the musical form of a sonata to examine tetrads, a simple four-fold structure that Marshall McLuhan coined and employed to describe various technologies. Tetrads, as cognitive models, are used to refine, focus, or discover entities in cultures and technologies, which are hidden from view in the psyche. Tetradic logic…

Training, Sharing or Cheating? Gamer Strategies to Get a Digital Upper Hand

ERIC Educational Resources Information Center

Mortensen, Torill Elvira

2010-01-01

Digital game-players devote a large amount of their time to discovering rules hidden in the code and discoverable through empirical study, experiments, and developing or rediscovering the mathematical formulae governing the code. They do this through their own independent play as they test areas, gear and abilities, through data mining using…

Analysis and Design of Complex Networks

DTIC Science & Technology

2014-12-02

systems. 08-NOV-10, . : , Barlas Oguz, Venkat Anantharam. Long range dependent Markov chains with applications , Information Theory and Applications ...JUL-12, . : , Michael Krishnan, Ehsan Haghani, Avideh Zakhor. Packet Length Adaptation in WLANs with Hidden Nodes and Time-Varying Channels, IEEE... WLAN networks with multi-antenna beam-forming nodes. VII. Use of busy/idle signals for discovering optimum AP association VIII

The Hidden Curriculum, Ethics Teaching, and the Structure of Medical Education.

ERIC Educational Resources Information Center

Hafferty, Frederic W.; Franks, Ronald

1994-01-01

Issues concerning inclusion of ethics instruction in the medical school curriculum are discussed, including whether ethics should be presented as a body of knowledge or matter of professional identity and the "hidden curriculum" of medicine as a form of socialization. Recommendations for the structuring of an ethics curriculum are…

Francis Bacon's behavioral psychology.

PubMed

MacDonald, Paul S

2007-01-01

Francis Bacon offers two accounts of the nature and function of the human mind: one is a medical-physical account of the composition and operation of spirits specific to human beings, the other is a behavioral account of the character and activities of individual persons. The medical-physical account is a run-of-the-mill version of the late Renaissance model of elemental constituents and humoral temperaments. The other, less well-known, behavioral account represents an unusual position in early modern philosophy. This theory espouses a form of behavioral psychology according to which (a) supposed mental properties are "hidden forms" best described in dispositional terms, (b) the true character of an individual can be discovered in his observable behavior, and (c) an "informed" understanding of these properties permits the prediction and control of human behavior. Both of Bacon's theories of human nature fall under his general notion of systematic science: his medical-physical theory of vital spirits is theoretical natural philosophy and his behavioral theory of disposition and expression is operative natural philosophy. Because natural philosophy as a whole is "the inquiry of causes and the production of effects," knowledge of human nature falls under the same two-part definition. It is an inquisition of forms that pertains to the patterns of minute motions in the vital spirits and the production of effects that pertains both to the way these hidden motions produce behavioral effects and to the way in which a skillful agent is able to produce desired effects in other persons' behavior. (c) 2007 Wiley Periodicals, Inc.

Experimental evolution reveals hidden diversity in evolutionary pathways

PubMed Central

Lind, Peter A; Farr, Andrew D; Rainey, Paul B

2015-01-01

Replicate populations of natural and experimental organisms often show evidence of parallel genetic evolution, but the causes are unclear. The wrinkly spreader morph of Pseudomonas fluorescens arises repeatedly during experimental evolution. The mutational causes reside exclusively within three pathways. By eliminating these, 13 new mutational pathways were discovered with the newly arising WS types having fitnesses similar to those arising from the commonly passaged routes. Our findings show that parallel genetic evolution is strongly biased by constraints and we reveal the genetic bases. From such knowledge, and in instances where new phenotypes arise via gene activation, we suggest a set of principles: evolution proceeds firstly via pathways subject to negative regulation, then via promoter mutations and gene fusions, and finally via activation by intragenic gain-of-function mutations. These principles inform evolutionary forecasting and have relevance to interpreting the diverse array of mutations associated with clinically identical instances of disease in humans. DOI: http://dx.doi.org/10.7554/eLife.07074.001 PMID:25806684

Implications of Emerging Data Mining

NASA Astrophysics Data System (ADS)

Kulathuramaiyer, Narayanan; Maurer, Hermann

Data Mining describes a technology that discovers non-trivial hidden patterns in a large collection of data. Although this technology has a tremendous impact on our lives, the invaluable contributions of this invisible technology often go unnoticed. This paper discusses advances in data mining while focusing on the emerging data mining capability. Such data mining applications perform multidimensional mining on a wide variety of heterogeneous data sources, providing solutions to many unresolved problems. This paper also highlights the advantages and disadvantages arising from the ever-expanding scope of data mining. Data Mining augments human intelligence by equipping us with a wealth of knowledge and by empowering us to perform our daily tasks better. As the mining scope and capacity increases, users and organizations become more willing to compromise privacy. The huge data stores of the ‚master miners` allow them to gain deep insights into individual lifestyles and their social and behavioural patterns. Data integration and analysis capability of combining business and financial trends together with the ability to deterministically track market changes will drastically affect our lives.

The Hidden Diversity of Zanclea Associated with Scleractinians Revealed by Molecular Data

PubMed Central

Montano, Simone; Maggioni, Davide; Arrigoni, Roberto; Seveso, Davide; Puce, Stefania; Galli, Paolo

2015-01-01

Scleractinian reef corals have recently been acknowledged as the most numerous host group found in association with hydroids belonging to the Zanclea genus. However, knowledge of the molecular phylogenetic relationships among Zanclea species associated with scleractinians is just beginning. This study, using the nuclear 28S rDNA region and the fast-evolving mitochondrial 16S rRNA and COI genes, provides the most comprehensive phylogenetic reconstruction of the genus Zanclea with a particular focus on the genetic diversity among Zanclea specimens associated with 13 scleractinian genera. The monophyly of Zanclea associated with scleractinians was strongly supported in all nuclear and mitochondrial phylogenetic reconstructions. Furthermore, a combined mitochondrial 16S and COI phylogenetic tree revealed a multitude of hidden molecular lineages within this group (Clades I, II, III, V, VI, VII, and VIII), suggesting the existence of both host-generalist and genus-specific lineages of Zanclea associated with scleractinians. In addition to Z. gallii living in association with the genus Acropora, we discovered four well-supported lineages (Clades I, II, III, and VII), each one forming a strict association with a single scleractinian genus, including sequences of Zanclea associated with Montipora from two geographically separated areas (Maldives and Taiwan). Two host-generalist Zanclea lineages were also observed, and one of them was formed by Zanclea specimens symbiotic with seven scleractinian genera (Clade VIII). We also found that the COI gene allows the recognition of separated hidden lineages in agreement with the commonly recommended mitochondrial 16S as a DNA barcoding gene for Hydrozoa and shows reasonable potential for phylogenetic and evolutionary analyses in the genus Zanclea. Finally, as no DNA sequences are available for the majority of the nominal Zanclea species known, we note that they will be necessary to elucidate the diversity of the Zanclea-scleractinian association. PMID:26207903

Ethical violations in the clinical setting: the hidden curriculum learning experience of Pakistani nurses.

PubMed

Jafree, Sara Rizvi; Zakar, Rubeena; Fischer, Florian; Zakar, Muhammad Zakria

2015-03-19

The importance of the hidden curriculum is recognised as a practical training ground for the absorption of medical ethics by healthcare professionals. Pakistan's healthcare sector is hampered by the exclusion of ethics from medical and nursing education curricula and the absence of monitoring of ethical violations in the clinical setting. Nurses have significant knowledge of the hidden curriculum taught during clinical practice, due to long working hours in the clinic and front-line interaction with patients and other practitioners. The means of inquiry for this study was qualitative, with 20 interviews and four focus group discussions used to identify nurses' clinical experiences of ethical violations. Content analysis was used to discover sub-categories of ethical violations, as perceived by nurses, within four pre-defined categories of nursing codes of ethics: 1) professional guidelines and integrity, 2) patient informed consent, 3) patient rights, and 4) co-worker coordination for competency, learning and patient safety. Ten sub-categories of ethical violations were found: nursing students being used as adjunct staff, nurses having to face frequent violence in the hospital setting, patient reluctance to receive treatment from nurses, the near-absence of consent taken from patients for most non-surgical medical procedures, the absence of patient consent taking for receiving treatment from student nurses, the practice of patient discrimination on the basis of a patient's socio-demographic status, nurses withdrawing treatment out of fear for their safety, a non-learning culture and, finally, blame-shifting and non-reportage of errors. Immediate and urgent attention is required to reduce ethical violations in the healthcare sector in Pakistan through collaborative efforts by the government, the healthcare sector, and ethics regulatory bodies. Also, changes in socio-cultural values in hospital organisation, public awareness of how to conveniently report ethical violations by practitioners and public perceptions of nurse identity are needed.

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.

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.

Stable heavy pentaquarks in constituent models

NASA Astrophysics Data System (ADS)

Richard, J.-M.; Valcarce, A.; Vijande, J.

2017-11-01

It is shown that standard constituent quark models produce (c bar cqqq) hidden-charm pentaquarks, where c denotes the charmed quark and q a light quark, which lie below the lowest threshold for spontaneous dissociation and thus are stable in the limit where the internal c bar c annihilation is neglected. The binding is a cooperative effect of the chromoelectric and chromomagnetic components of the interaction, and it disappears in the static limit with a pure chromoelectric potential. Their wave function contains color sextet and color octet configurations for the subsystems and can hardly be reduced to a molecular state made of two interacting hadrons. These pentaquark states could be searched for in the experiments having discovered or confirmed the hidden-charm meson and baryon resonances.

Discovering the Science Hidden behind Real Objects

ERIC Educational Resources Information Center

Desforges, Ruth

2018-01-01

The Zoological Society of London (ZSL) has a huge collection of unique and curious objects from the natural world that have been loaned to us by HM Revenue and Customs after being seized at the UK border. Among the turtle shells and snake skins, the strangest of these is perhaps the freestanding rhino-foot ash tray. This single object can open up…

Alvarez, Luis Walter (1911-88)

NASA Astrophysics Data System (ADS)

Murdin, P.

2000-11-01

Physicist and astronomer, born in San Francisco, CA, professor at the University of California, Nobel prizewinner (1968) for his discoveries in particle physics. Used cosmic rays to `x-ray' the pyramids of Egypt, finding in particular that the tombs in the Great Pyramid at Giza had no hidden rooms. Alvarez (and his son) discovered globally distributed iridium at the Cretaceous/Tertiary boundary i...

Openness--A Way Forward: Development Education Research Centre

ERIC Educational Resources Information Center

Hare-Heremia, Mahora

2014-01-01

Education is a vital aspect in the lives of humankind. It contributes and shapes our future as citizens of the world. To understand it is to discover the many hidden talents the world has in store for all. The Development Education Research Centre (DERC) holds many resources that aid in the development of education at a global level. With the…

External Dependencies-Driven Architecture Discovery and Analysis of Implemented Systems

NASA Technical Reports Server (NTRS)

Ganesan, Dharmalingam; Lindvall, Mikael; Ron, Monica

2014-01-01

A method for architecture discovery and analysis of implemented systems (AIS) is disclosed. The premise of the method is that architecture decisions are inspired and influenced by the external entities that the software system makes use of. Examples of such external entities are COTS components, frameworks, and ultimately even the programming language itself and its libraries. Traces of these architecture decisions can thus be found in the implemented software and is manifested in the way software systems use such external entities. While this fact is often ignored in contemporary reverse engineering methods, the AIS method actively leverages and makes use of the dependencies to external entities as a starting point for the architecture discovery. The AIS method is demonstrated using the NASA's Space Network Access System (SNAS). The results show that, with abundant evidence, the method offers reusable and repeatable guidelines for discovering the architecture and locating potential risks (e.g. low testability, decreased performance) that are hidden deep in the implementation. The analysis is conducted by using external dependencies to identify, classify and review a minimal set of key source code files. Given the benefits of analyzing external dependencies as a way to discover architectures, it is argued that external dependencies deserve to be treated as first-class citizens during reverse engineering. The current structure of a knowledge base of external entities and analysis questions with strategies for getting answers is also discussed.

Probabilistic reasoning over seismic RMS time series: volcano monitoring through HMMs and SAX technique

NASA Astrophysics Data System (ADS)

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

2014-12-01

During the last years, volcanic activity at Mt. Etna was often characterized by cyclic occurrences of fountains. In the period between January 2011 and June 2013, 38 episodes of lava fountains has been observed. Automatic recognition of the volcano's states related to lava fountain episodes (Quiet, Pre-Fountaining, Fountaining, Post-Fountaining) is very useful for monitoring purposes. We discovered that such states are strongly related to the trend of RMS (Root Mean Square) of the seismic signal recorded in the summit area. In the framework of the project PON SIGMA (Integrated Cloud-Sensor System for Advanced Multirisk Management) work, we tried to model the system generating its sampled values (assuming to be a Markov process and assuming that RMS time series is a stochastic process), by using Hidden Markov models (HMMs), that are a powerful tool for modeling any time-varying series. HMMs analysis seeks to discover the sequence of hidden states from the observed emissions. In our framework, observed emissions are characters generated by SAX (Symbolic Aggregate approXimation) technique. SAX is able to map RMS time series values with discrete literal emissions. Our experiments showed how to predict volcano states by means of SAX and HMMs.

"mysterium Cosmographicum", for Orchestra, Narrator/actor, and Computer Music on Tape. (with Original Composition)

NASA Astrophysics Data System (ADS)

Keefe, Robert Michael

Mysterium Cosmographicum is a musical chronicle of an astronomy treatise by the German astronomer Johannes Kepler (1571-1630). Kepler's Mysterium Cosmographicum (Tubingen, 1596), or "Secret of the Universe," was a means by which he justified the existence of the six planets discovered during his lifetime. Kepler, through flawless a priori reasoning, goes to great lengths to explain that the reason there are six and only six planets (Mercury, Venus, Earth, Mars, Jupiter, and Saturn) is because God had placed one of the five regular solids (tetrahedron, cube, octa-, dodeca-, and icosahedron) around each orbiting body. Needless to say, the publication was not very successful, nor did it gain much comment from Kepler's peers, Galileo Galilei (1564-1642) and Tycho Brahe (1546-1601). But hidden within the Mysterium Cosmographicum, almost like a new planet waiting to be discovered, is one of Kepler's three laws of planetary motion, a law that held true for planets discovered long after Kepler's lifetime. Mysterium Cosmographicum is a monologue with music in three parts for orchestra, narrator/actor, and computer music on tape. All musical data structures are generated via an interactive Pascal computer program that computes latitudinal and longitudinal coordinates for each of the nine planets as seen from a fixed point on Earth for any given time frame. These coordinates are then mapped onto selected musical parameters as determined by the composer. Whenever Kepler reads from his treatise or from a lecture or correspondence, the monologue is supported by orchestral planetary data generated from the exact place, date, and time of the treatise, lecture, or correspondence. To the best of my knowledge, Mysterium Cosmographicum is the first composition ever written that employs planetary data as a supporting chronology to action and monologue.

Hidden Markov models for character recognition.

PubMed

Vlontzos, J A; Kung, S Y

1992-01-01

A hierarchical system for character recognition with hidden Markov model knowledge sources which solve both the context sensitivity problem and the character instantiation problem is presented. The system achieves 97-99% accuracy using a two-level architecture and has been implemented using a systolic array, thus permitting real-time (1 ms per character) multifont and multisize printed character recognition as well as handwriting recognition.

Informatics in neurocritical care: new ideas for Big Data.

PubMed

Flechet, Marine; Grandas, Fabian Güiza; Meyfroidt, Geert

2016-04-01

Big data is the new hype in business and healthcare. Data storage and processing has become cheap, fast, and easy. Business analysts and scientists are trying to design methods to mine these data for hidden knowledge. Neurocritical care is a field that typically produces large amounts of patient-related data, and these data are increasingly being digitized and stored. This review will try to look beyond the hype, and focus on possible applications in neurointensive care amenable to Big Data research that can potentially improve patient care. The first challenge in Big Data research will be the development of large, multicenter, and high-quality databases. These databases could be used to further investigate recent findings from mathematical models, developed in smaller datasets. Randomized clinical trials and Big Data research are complementary. Big Data research might be used to identify subgroups of patients that could benefit most from a certain intervention, or can be an alternative in areas where randomized clinical trials are not possible. The processing and the analysis of the large amount of patient-related information stored in clinical databases is beyond normal human cognitive ability. Big Data research applications have the potential to discover new medical knowledge, and improve care in the neurointensive care unit.

I Learned More than I Taught: The Hidden Dimension of Learning in Intercultural Knowledge Transfer

ERIC Educational Resources Information Center

Chen, Fang; Bapuji, Hari; Dyck, Bruno; Wang, Xiaoyun

2012-01-01

Purpose: Although knowledge transfer is generally conceived as a two-way process in which knowledge is transferred to and from the knowledge source, research has tended to focus on the first part of the process and neglect the second part. This study aims to examine the feedback loop and how knowledge is transferred from the knowledge receiver to…

Did You Remember to DID

DTIC Science & Technology

2010-04-01

threats (also known as a SWOT analysis) is a very useful method in identifying potential issues, hidden agendas, and competing egos. • Defining a...comprehensive communications plan uses what’s been defined and informs (the second key component to DID) government and con - tractor teams of the essential...program execution strategies. Inform Inform means communicating to internal and external stake- holders what was defined, expected, discovered, con

Nuclear scissors modes and hidden angular momenta

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

Balbutsev, E. B., E-mail: balbuts@theor.jinr.ru; Molodtsova, I. V.; Schuck, P.

The coupled dynamics of low-lying modes and various giant resonances are studied with the help of the Wigner Function Moments method generalized to take into account spin degrees of freedom and pair correlations simultaneously. The method is based on Time-Dependent Hartree–Fock–Bogoliubov equations. The model of the harmonic oscillator including spin–orbit potential plus quadrupole–quadrupole and spin–spin interactions is considered. New low-lying spin-dependent modes are analyzed. Special attention is paid to the scissors modes. A new source of nuclear magnetism, connected with counter-rotation of spins up and down around the symmetry axis (hidden angular momenta), is discovered. Its inclusion into the theorymore » allows one to improve substantially the agreement with experimental data in the description of energies and transition probabilities of scissors modes.« less

Topological data analysis (TDA) applied to reveal pedogenetic principles of European topsoil system.

PubMed

Savic, Aleksandar; Toth, Gergely; Duponchel, Ludovic

2017-05-15

Recent developments in applied mathematics are bringing new tools that are capable to synthesize knowledge in various disciplines, and help in finding hidden relationships between variables. One such technique is topological data analysis (TDA), a fusion of classical exploration techniques such as principal component analysis (PCA), and a topological point of view applied to clustering of results. Various phenomena have already received new interpretations thanks to TDA, from the proper choice of sport teams to cancer treatments. For the first time, this technique has been applied in soil science, to show the interaction between physical and chemical soil attributes and main soil-forming factors, such as climate and land use. The topsoil data set of the Land Use/Land Cover Area Frame survey (LUCAS) was used as a comprehensive database that consists of approximately 20,000 samples, each described by 12 physical and chemical parameters. After the application of TDA, results obtained were cross-checked against known grouping parameters including five types of land cover, nine types of climate and the organic carbon content of soil. Some of the grouping characteristics observed using standard approaches were confirmed by TDA (e.g., organic carbon content) but novel subtle relationships (e.g., magnitude of anthropogenic effect in soil formation), were discovered as well. The importance of this finding is that TDA is a unique mathematical technique capable of extracting complex relations hidden in soil science data sets, giving the opportunity to see the influence of physicochemical, biotic and abiotic factors on topsoil formation through fresh eyes. Copyright © 2017 Elsevier B.V. All rights reserved.

A review on computational systems biology of pathogen–host interactions

PubMed Central

Durmuş, Saliha; Çakır, Tunahan; Özgür, Arzucan; Guthke, Reinhard

2015-01-01

Pathogens manipulate the cellular mechanisms of host organisms via pathogen–host interactions (PHIs) in order to take advantage of the capabilities of host cells, leading to infections. The crucial role of these interspecies molecular interactions in initiating and sustaining infections necessitates a thorough understanding of the corresponding mechanisms. Unlike the traditional approach of considering the host or pathogen separately, a systems-level approach, considering the PHI system as a whole is indispensable to elucidate the mechanisms of infection. Following the technological advances in the post-genomic era, PHI data have been produced in large-scale within the last decade. Systems biology-based methods for the inference and analysis of PHI regulatory, metabolic, and protein–protein networks to shed light on infection mechanisms are gaining increasing demand thanks to the availability of omics data. The knowledge derived from the PHIs may largely contribute to the identification of new and more efficient therapeutics to prevent or cure infections. There are recent efforts for the detailed documentation of these experimentally verified PHI data through Web-based databases. Despite these advances in data archiving, there are still large amounts of PHI data in the biomedical literature yet to be discovered, and novel text mining methods are in development to unearth such hidden data. Here, we review a collection of recent studies on computational systems biology of PHIs with a special focus on the methods for the inference and analysis of PHI networks, covering also the Web-based databases and text-mining efforts to unravel the data hidden in the literature. PMID:25914674

The Development of Knowledge of an External Retrieval Cue Strategy.

ERIC Educational Resources Information Center

Ritter, Kenneth

1978-01-01

Investigated preschool and third grade children's metamnemonic knowledge that in order to serve as an efficient retrieval cue of the location of a hidden object, an external marker sign must differentiate it from other locations. (JMB)

Properties of the Bayesian Knowledge Tracing Model

ERIC Educational Resources Information Center

van de Sande, Brett

2013-01-01

Bayesian Knowledge Tracing is used very widely to model student learning. It comes in two different forms: The first form is the Bayesian Knowledge Tracing "hidden Markov model" which predicts the probability of correct application of a skill as a function of the number of previous opportunities to apply that skill and the model…

The Hidden Strand of Mathematical Proficiency: Defining and Assessing for Productive Disposition in Elementary School Teachers' Mathematical Content Knowledge

ERIC Educational Resources Information Center

Siegfried, John Zig Michael

2012-01-01

Teachers' mathematical content knowledge is one of the most important constructs considered by researchers studying elementary mathematics education (Fennema & Franke, 1992). One component of mathematical content knowledge that is complicated, ill-defined, and oft-ignored is "productive disposition," defined as the…

Reflection on the Role of Artists: A Case Study on the Hidden Visual Curriculum of the School of the Art Institute of Chicago

ERIC Educational Resources Information Center

Baker, Marissa H.; Ng-He, Carol; Lopez-Bosch, Maria Acaso

2008-01-01

In 2005, Maria Acaso, professor in Art Education at the Universidad Complutense Madrid in Spain and a co-author of this article, conducted a comparative research project on visual configurations at different art schools in Europe and the United States. The study of hidden visual curriculum examines how knowledge and cultural/political/social…

What if Finding Data was as Easy as Subscribing to the News?

NASA Astrophysics Data System (ADS)

Duerr, R. E.

2011-12-01

Data are the "common wealth of humanity," the fuel that drives the sciences; but much of the data that exist are inaccessible, buried in one of numerous stove-piped data systems, or entirely hidden unless you have direct knowledge of and contact with the investigator that acquired them. Much of the "wealth" is squandered and overall scientific progress inhibited, a situation that is becoming increasingly untenable with the openness required by data-driven science. What are needed are simple interoperability protocols and advertising mechanisms that allow data from disparate data systems to be easily discovered, explored, and accessed. The tools must be simple enough that individual investigators can use them without IT support. The tools cannot rely on centralized repositories or registries but must enable the development of ad-hoc or special purpose aggregations of data and services tailored to individual community needs. In addition, the protocols must scale to support the discovery of and access to the holdings of the global, interdisciplinary community, be they individual investigators or major data centers. NSIDC, in conjunction with other members of the Federation of Earth Science Information Partners and the Polar Information Commons, are working on just such a suite of tools and protocols. In this talk, I discuss data and service casting, aggregation, data badging, and OpenSearch - a suite of tools and protocols which, when used in conjunction with each other, have the potential of completely changing the way that data and services worldwide are discovered and used.

Galactic optical cloaking of visible baryonic matter

NASA Astrophysics Data System (ADS)

Smolyaninov, Igor I.

2018-05-01

Three-dimensional gravitational cloaking is known to require exotic matter and energy sources, which makes it arguably physically unrealizable. On the other hand, typical astronomical observations are performed using one-dimensional paraxial line of sight geometries. We demonstrate that unidirectional line of sight gravitational cloaking does not require exotic matter, and it may occur in multiple natural astronomical scenarios that involve gravitational lensing. In particular, recently discovered double gravitational lens SDSSJ 0 9 4 6 +1 0 0 6 together with the Milky Way appear to form a natural paraxial cloak. A natural question to ask, then, is how much matter in the Universe may be hidden from view by such natural gravitational cloaks? It is estimated that the total volume hidden from an observer by gravitational cloaking may reach about 1% of the total volume of the visible Universe.

Evolutionary neural networks for anomaly detection based on the behavior of a program.

PubMed

Han, Sang-Jun; Cho, Sung-Bae

2006-06-01

The process of learning the behavior of a given program by using machine-learning techniques (based on system-call audit data) is effective to detect intrusions. Rule learning, neural networks, statistics, and hidden Markov models (HMMs) are some of the kinds of representative methods for intrusion detection. Among them, neural networks are known for good performance in learning system-call sequences. In order to apply this knowledge to real-world problems successfully, it is important to determine the structures and weights of these call sequences. However, finding the appropriate structures requires very long time periods because there are no suitable analytical solutions. In this paper, a novel intrusion-detection technique based on evolutionary neural networks (ENNs) is proposed. One advantage of using ENNs is that it takes less time to obtain superior neural networks than when using conventional approaches. This is because they discover the structures and weights of the neural networks simultaneously. Experimental results with the 1999 Defense Advanced Research Projects Agency (DARPA) Intrusion Detection Evaluation (IDEVAL) data confirm that ENNs are promising tools for intrusion detection.

Discovering Knowledge from AIS Database for Application in VTS

NASA Astrophysics Data System (ADS)

Tsou, Ming-Cheng

The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

Graph processing platforms at scale: practices and experiences

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

Lim, Seung-Hwan; Lee, Sangkeun; Brown, Tyler C

2015-01-01

Graph analysis unveils hidden associations of data in many phenomena and artifacts, such as road network, social networks, genomic information, and scientific collaboration. Unfortunately, a wide diversity in the characteristics of graphs and graph operations make it challenging to find a right combination of tools and implementation of algorithms to discover desired knowledge from the target data set. This study presents an extensive empirical study of three representative graph processing platforms: Pegasus, GraphX, and Urika. Each system represents a combination of options in data model, processing paradigm, and infrastructure. We benchmarked each platform using three popular graph operations, degree distribution,more » connected components, and PageRank over a variety of real-world graphs. Our experiments show that each graph processing platform shows different strength, depending the type of graph operations. While Urika performs the best in non-iterative operations like degree distribution, GraphX outputforms iterative operations like connected components and PageRank. In addition, we discuss challenges to optimize the performance of each platform over large scale real world graphs.« less

Hidden hyperchaos and electronic circuit application in a 5D self-exciting homopolar disc dynamo

NASA Astrophysics Data System (ADS)

Wei, Zhouchao; Moroz, Irene; Sprott, J. C.; Akgul, Akif; Zhang, Wei

2017-03-01

We report on the finding of hidden hyperchaos in a 5D extension to a known 3D self-exciting homopolar disc dynamo. The hidden hyperchaos is identified through three positive Lyapunov exponents under the condition that the proposed model has just two stable equilibrium states in certain regions of parameter space. The new 5D hyperchaotic self-exciting homopolar disc dynamo has multiple attractors including point attractors, limit cycles, quasi-periodic dynamics, hidden chaos or hyperchaos, as well as coexisting attractors. We use numerical integrations to create the phase plane trajectories, produce bifurcation diagram, and compute Lyapunov exponents to verify the hidden attractors. Because no unstable equilibria exist in two parameter regions, the system has a multistability and six kinds of complex dynamic behaviors. To the best of our knowledge, this feature has not been previously reported in any other high-dimensional system. Moreover, 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 integrations. Both Matlab and the oscilloscope outputs produce similar phase portraits. Such implementations in real time represent a new type of hidden attractor with important consequences for engineering applications.

Hidden hyperchaos and electronic circuit application in a 5D self-exciting homopolar disc dynamo.

PubMed

Wei, Zhouchao; Moroz, Irene; Sprott, J C; Akgul, Akif; Zhang, Wei

2017-03-01

We report on the finding of hidden hyperchaos in a 5D extension to a known 3D self-exciting homopolar disc dynamo. The hidden hyperchaos is identified through three positive Lyapunov exponents under the condition that the proposed model has just two stable equilibrium states in certain regions of parameter space. The new 5D hyperchaotic self-exciting homopolar disc dynamo has multiple attractors including point attractors, limit cycles, quasi-periodic dynamics, hidden chaos or hyperchaos, as well as coexisting attractors. We use numerical integrations to create the phase plane trajectories, produce bifurcation diagram, and compute Lyapunov exponents to verify the hidden attractors. Because no unstable equilibria exist in two parameter regions, the system has a multistability and six kinds of complex dynamic behaviors. To the best of our knowledge, this feature has not been previously reported in any other high-dimensional system. Moreover, 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 integrations. Both Matlab and the oscilloscope outputs produce similar phase portraits. Such implementations in real time represent a new type of hidden attractor with important consequences for engineering applications.

Recognition of Tacit Skills and Knowledge: Sustaining Learning Outcomes in Workplace Environments

ERIC Educational Resources Information Center

Evans, Karen; Kersh, Natasha

2004-01-01

The part played by tacit skills and knowledge in work performance is well recognised but not well understood. These implicit or hidden dimensions of knowledge and skill are key elements of "mastery," which experienced workers draw upon in everyday activities and continuously expand in tackling new or unexpected situations. This paper,…

Working with Data: Discovering Knowledge through Mining and Analysis; Systematic Knowledge Management and Knowledge Discovery; Text Mining; Methodological Approach in Discovering User Search Patterns through Web Log Analysis; Knowledge Discovery in Databases Using Formal Concept Analysis; Knowledge Discovery with a Little Perspective.

ERIC Educational Resources Information Center

Qin, Jian; Jurisica, Igor; Liddy, Elizabeth D.; Jansen, Bernard J; Spink, Amanda; Priss, Uta; Norton, Melanie J.

2000-01-01

These six articles discuss knowledge discovery in databases (KDD). Topics include data mining; knowledge management systems; applications of knowledge discovery; text and Web mining; text mining and information retrieval; user search patterns through Web log analysis; concept analysis; data collection; and data structure inconsistency. (LRW)

Study on real-time elevator brake failure predictive system

NASA Astrophysics Data System (ADS)

Guo, Jun; Fan, Jinwei

2013-10-01

This paper presented a real-time failure predictive system of the elevator brake. Through inspecting the running state of the coil by a high precision long range laser triangulation non-contact measurement sensor, the displacement curve of the coil is gathered without interfering the original system. By analyzing the displacement data using the diagnostic algorithm, the hidden danger of the brake system can be discovered in time and thus avoid the according accident.

Cache-Cache Comparison for Supporting Meaningful Learning

ERIC Educational Resources Information Center

Wang, Jingyun; Fujino, Seiji

2015-01-01

The paper presents a meaningful discovery learning environment called "cache-cache comparison" for a personalized learning support system. The processing of seeking hidden relations or concepts in "cache-cache comparison" is intended to encourage learners to actively locate new knowledge in their knowledge framework and check…

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.

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.

Bayesian structural inference for hidden processes.

PubMed

Strelioff, Christopher C; Crutchfield, James P

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ε-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ε-machines, irrespective of estimated transition probabilities. Properties of ε-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

Bayesian structural inference for hidden processes

NASA Astrophysics Data System (ADS)

Strelioff, Christopher C.; Crutchfield, James P.

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ɛ-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ɛ-machines, irrespective of estimated transition probabilities. Properties of ɛ-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

Bridging the Gap Between Earth Science Open Data Producers and Consumers Using a Standards based approach

NASA Astrophysics Data System (ADS)

Stephan, E.; Sivaraman, C.

2016-12-01

The Web brought together science communities creating collaborative opportunities that were previously unimaginable. This was due to the novel ways technology enabled users to share information that would otherwise not be available. This means that data and software that previously could not be discovered without direct contact with data or software creators can now be downloaded with the click of a mouse button, and the same products can now outlive the lifespan of their research projects. While in many ways these technological advancements provide benefit to collaborating scientists, a critical producer-consumer knowledge gap is created when collaborating scientists rely solely on web sites, web browsers, or similar technology to exchange services, software, and data. Without some best practices and common approaches from Web publishers, collaborating scientific consumers have no inherent way to trust the results or other products being shared, producers have no way to convey their scientific credibility, and publishers risk obscurity where data is hidden in the deep Web. By leveraging recommendations from the W3C Data Activity, scientific communities can adopt best practices for data publication enabling consumers to explore, reuse, reproduce, and contribute their knowledge about the data. This talk will discuss the application of W3C Data on the Web Best Practices in support of published earth science data and feature the Data Usage Vocabulary.

Increased Alpha (8-12 Hz) Activity during Slow Wave Sleep as a Marker for the Transition from Implicit Knowledge to Explicit Insight

ERIC Educational Resources Information Center

Yordanova, Juliana; Kolev, Vasil; Wagner, Ullrich; Born, Jan; Verleger, Rolf

2012-01-01

The number reduction task (NRT) allows us to study the transition from implicit knowledge of hidden task regularities to explicit insight into these regularities. To identify sleep-associated neurophysiological indicators of this restructuring of knowledge representations, we measured frequency-specific power of EEG while participants slept during…

ArtArctic Science: a polarTREC effort to educate about Antarctica through art

NASA Astrophysics Data System (ADS)

Botella, J.; Racette, B.

2013-12-01

Formal scientific education is as important as ever for raising awarness about Antarctic issues, but some people resistance to learning about scienctific issues demands novel approaches for reaching people who are not in the classroom. ArtArctic Science is an interactive exhibit of photography and paintings presented at the Overture Center for the Arts, in Madison, WI by Monona Grove High School students and a science teacher that attempts to educate the general audience about Antarctic science. The exhibit explores art as a form of perceiving and understanding the world around us, and as a way of igniting the spark of curiosity that can lead to scientific inquiries. Antarctica has inspired explorers and scientists for over 100 years, and we add our work to efforts that share scientific results with common people. Antarctica offers stunning views of amazing geometric ice structures complemented and contrasted by the organisms that inhabit it that fascinate most everyone. We probe these scenes through photography and paintings knowing that there is more in each image than what the eye can 'see'. We invite the viewer to discover these secrets by engaging the observer in a mimicking of the scientific method (observation, questioning, finding an explanation, revising the explanation). Each art piece has a question and a scientific explanation hidden under a wooden lid. The observer is invited to explore the scene, involve itself with the scientific query, come up with an answer, and compare his or her idea with the hidden explanation. The exhibit is inspired by an Antarctic PolarTREC expedition in which our science teacher participated as a member of a scientific research team. In this presentation we share the knowledge acquired through this experience in hopes that it will help others attempting a similar Project.

Federal Geothermal Research Program Update, FY 2000

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

Renner, Joel Lawrence

2001-08-01

The Department of Energy's Geothermal Program serves two broad purposes: 1) to assist industry in overcoming near-term barriers by conducting cost-shared research and field verification that allows geothermal energy to compete in today's aggressive energy markets; and 2) to undertake fundamental research with potentially large economic payoffs. The four categories of work used to distinguish the research activities of the Geothermal Program during FY 2000 reflect the main components of real-world geothermal projects. These categories form the main sections of the project descriptions in this Research Update. Exploration Technology research focuses on developing instruments and techniques to discover hidden hydrothermalmore » systems and to explore the deep portions of known systems. Research in geophysical and geochemical methods is expected to yield increased knowledge of hidden geothermal systems. Reservoir Technology research combines laboratory and analytical investigations with equipment development and field testing to establish practical tools for resource development and management for both hydrothermal reservoirs and enhanced geothermal systems. Research in various reservoir analysis techniques is generating a wide range of information that facilitates development of improved reservoir management tools. Drilling Technology focuses on developing improved, economic drilling and completion technology for geothermal wells. Ongoing research to avert lost circulation episodes in geothermal drilling is yielding positive results. Conversion Technology research focuses on reducing costs and improving binary conversion cycle efficiency, to permit greater use of the more abundant moderate-temperature geothermal resource, and on the development of materials that will improve the operating characteristics of many types of geothermal energy equipment. Increased output and improved performance of binary cycles will result from investigations in heat cycle research.« less

Federal Geothermal Research Program Update Fiscal Year 2000

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

Renner, J.L.

2001-08-15

The Department of Energy's Geothermal Program serves two broad purposes: (1) to assist industry in overcoming near-term barriers by conducting cost-shared research and field verification that allows geothermal energy to compete in today's aggressive energy markets; and (2) to undertake fundamental research with potentially large economic payoffs. The four categories of work used to distinguish the research activities of the Geothermal Program during FY 2000 reflect the main components of real-world geothermal projects. These categories form the main sections of the project descriptions in this Research Update. Exploration Technology research focuses on developing instruments and techniques to discover hidden hydrothermalmore » systems and to explore the deep portions of known systems. Research in geophysical and geochemical methods is expected to yield increased knowledge of hidden geothermal systems. Reservoir Technology research combines laboratory and analytical investigations with equipment development and field testing to establish practical tools for resource development and management for both hydrothermal reservoirs and enhanced geothermal systems. Research in various reservoir analysis techniques is generating a wide range of information that facilitates development of improved reservoir management tools. Drilling Technology focuses on developing improved, economic drilling and completion technology for geothermal wells. Ongoing research to avert lost circulation episodes in geothermal drilling is yielding positive results. Conversion Technology research focuses on reducing costs and improving binary conversion cycle efficiency, to permit greater use of the more abundant moderate-temperature geothermal resource, and on the development of materials that will improve the operating characteristics of many types of geothermal energy equipment. Increased output and improved performance of binary cycles will result from investigations in heat cycle research.« less

Efficient discovery of overlapping communities in massive networks

PubMed Central

Gopalan, Prem K.; Blei, David M.

2013-01-01

Detecting overlapping communities is essential to analyzing and exploring natural networks such as social networks, biological networks, and citation networks. However, most existing approaches do not scale to the size of networks that we regularly observe in the real world. In this paper, we develop a scalable approach to community detection that discovers overlapping communities in massive real-world networks. Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities. We demonstrate how we can discover the hidden community structure of several real-world networks, including 3.7 million US patents, 575,000 physics articles from the arXiv preprint server, and 875,000 connected Web pages from the Internet. Furthermore, we demonstrate on large simulated networks that our algorithm accurately discovers the true community structure. This paper opens the door to using sophisticated statistical models to analyze massive networks. PMID:23950224

Advocacy: The Early Childhood Historian's Not-So-Hidden Agenda.

ERIC Educational Resources Information Center

Ranck, Edna Runnels

To examine how knowledge of history and politics informs the early education and child care field, this paper identifies sources of historical knowledge and unexamined underlying presuppositions frequently held by early childhood professionals which, if allowed to remain unchallenged, contribute to professional burn-out, repeated frustration at…

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-10-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e. , internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature.

A Hybrid of Deep Network and Hidden Markov Model for MCI Identification with Resting-State fMRI

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2015-01-01

In this paper, we propose a novel method for modelling functional dynamics in resting-state fMRI (rs-fMRI) for Mild Cognitive Impairment (MCI) identification. Specifically, we devise a hybrid architecture by combining Deep Auto-Encoder (DAE) and Hidden Markov Model (HMM). The roles of DAE and HMM are, respectively, to discover hierarchical non-linear relations among features, by which we transform the original features into a lower dimension space, and to model dynamic characteristics inherent in rs-fMRI, i.e., internal state changes. By building a generative model with HMMs for each class individually, we estimate the data likelihood of a test subject as MCI or normal healthy control, based on which we identify the clinical label. In our experiments, we achieved the maximal accuracy of 81.08% with the proposed method, outperforming state-of-the-art methods in the literature. PMID:27054199

Hidden Anemias in the Critically Ill.

PubMed

O'Malley, Patricia

2017-09-01

With increasing knowledge of the risks associated with receiving blood transfusions, a new paradigm of bloodless medicine is needed. Principles of bloodless medicine include careful monitoring for obvious and hidden anemias, rapid intervention, minimizing blood losses from laboratory testing and procedures, and careful management of bleeding diatheses. As evidence is revealed and refined, standard treatment of anemia in the intensive care unit will include erythropoietin-stimulating agents, iron, folate, and vitamin B12, which will reduce risks associated with blood transfusions. Copyright © 2017 Elsevier Inc. All rights reserved.

Early Knowledge of Object Motion: Continuity and Inertia.

ERIC Educational Resources Information Center

Spelke, Elizabeth; And Others

1994-01-01

Investigated whether infants infer that a hidden, freely moving object will move continuously and smoothly. Six- to 10- month olds inferred that the object's path would be connected and unobstructed, in accord with continuity. Younger infants did not infer this, in accord with inertia. At 8 and 10 months, knowledge of inertia emerged but remained…

A Generative Approach to the Development of Hidden-Figure Items.

ERIC Educational Resources Information Center

Bejar, Issac I.; Yocom, Peter

This report explores an approach to item development and psychometric modeling which explicitly incorporates knowledge about the mental models used by examinees in the solution of items into a psychometric model that characterize performances on a test, as well as incorporating that knowledge into the item development process. The paper focuses on…

Discover the Hidden Jewels in Your Library and Sharing the Wealth through Collaboration. Selected Papers from PIALA 2011, Pacific Islands Association of Libraries, Archives, and Museums Annual Conference (21st, Kosrae, Federated States of Micronesia, November 14-17, 2011)

ERIC Educational Resources Information Center

Drake, Paul B., Ed.

2012-01-01

This publication follows the tradition of publishing selected papers from Pacific Islands Association of Libraries, Archives and Museums (PIALA) annual conferences. This 21st annual conference was held in Kosrae, Federated States of Micronesia, November 14-17, 2011. The volume begins with a listing of the members of the PIALA 2011 Planning…

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

Hidden MHC genetic diversity in the Iberian ibex (Capra pyrenaica).

PubMed

Angelone, Samer; Jowers, Michael J; Molinar Min, Anna Rita; Fandos, Paulino; Prieto, Paloma; Pasquetti, Mario; Cano-Manuel, Francisco Javier; Mentaberre, Gregorio; Olvera, Jorge Ramón López; Ráez-Bravo, Arián; Espinosa, José; Pérez, Jesús M; Soriguer, Ramón C; Rossi, Luca; Granados, José Enrique

2018-05-08

Defining hidden genetic diversity within species is of great significance when attempting to maintain the evolutionary potential of natural populations and conduct appropriate management. Our hypothesis is that isolated (and eventually small) wild animal populations hide unexpected genetic diversity due to their maintenance of ancient polymorphisms or introgressions. We tested this hypothesis using the Iberian ibex (Capra pyrenaica) as an example. Previous studies based on large sample sizes taken from its principal populations have revealed that the Iberian ibex has a remarkably small MHC DRB1 diversity (only six remnant alleles) as a result of recent population bottlenecks and a marked demographic decline that has led to the extinction of two recognized subspecies. Extending on the geographic range to include non-studied isolated Iberian ibex populations, we sequenced a new MHC DRB1 in what seemed three small isolated populations in Southern Spain (n = 132). The findings indicate a higher genetic diversity than previously reported in this important gene. The newly discovered allele, MHC DRB1*7, is identical to one reported in the domestic goat C. aegagrus hircus. Whether or not this is the result of ancient polymorphisms maintained by balancing selection or, alternatively, introgressions from domestic goats through hybridization needs to be clarified in future studies. However, hybridization between Iberian ibex and domestic goats has been reported in Spain and the fact that the newly discovered allele is only present in one of the small isolated populations and not in the others suggests introgression. The new discovered allele is not expected to increase fitness in C. pyrenaica since it generates the same protein as the existing MHC DRB1*6. Analysis of a microsatellite locus (OLADRB1) near the new MHC DRB1*7 gene reveals a linkage disequilibrium between these two loci. The allele OLADRB1, 187 bp in length, was unambiguously linked to the MHC DRB1*7 allele. This enabled us to perform a DRB-STR matching method for the recently discovered MHC allele. This finding is critical for the conservation of the Iberian ibex since it directly affects the identification of the units of this species that should be managed and conserved separately (Evolutionarily Significant Units).

Relational Network for Knowledge Discovery through Heterogeneous Biomedical and Clinical Features

PubMed Central

Chen, Huaidong; Chen, Wei; Liu, Chenglin; Zhang, Le; Su, Jing; Zhou, Xiaobo

2016-01-01

Biomedical big data, as a whole, covers numerous features, while each dataset specifically delineates part of them. “Full feature spectrum” knowledge discovery across heterogeneous data sources remains a major challenge. We developed a method called bootstrapping for unified feature association measurement (BUFAM) for pairwise association analysis, and relational dependency network (RDN) modeling for global module detection on features across breast cancer cohorts. Discovered knowledge was cross-validated using data from Wake Forest Baptist Medical Center’s electronic medical records and annotated with BioCarta signaling signatures. The clinical potential of the discovered modules was exhibited by stratifying patients for drug responses. A series of discovered associations provided new insights into breast cancer, such as the effects of patient’s cultural background on preferences for surgical procedure. We also discovered two groups of highly associated features, the HER2 and the ER modules, each of which described how phenotypes were associated with molecular signatures, diagnostic features, and clinical decisions. The discovered “ER module”, which was dominated by cancer immunity, was used as an example for patient stratification and prediction of drug responses to tamoxifen and chemotherapy. BUFAM-derived RDN modeling demonstrated unique ability to discover clinically meaningful and actionable knowledge across highly heterogeneous biomedical big data sets. PMID:27427091

Relational Network for Knowledge Discovery through Heterogeneous Biomedical and Clinical Features

NASA Astrophysics Data System (ADS)

Chen, Huaidong; Chen, Wei; Liu, Chenglin; Zhang, Le; Su, Jing; Zhou, Xiaobo

2016-07-01

Biomedical big data, as a whole, covers numerous features, while each dataset specifically delineates part of them. “Full feature spectrum” knowledge discovery across heterogeneous data sources remains a major challenge. We developed a method called bootstrapping for unified feature association measurement (BUFAM) for pairwise association analysis, and relational dependency network (RDN) modeling for global module detection on features across breast cancer cohorts. Discovered knowledge was cross-validated using data from Wake Forest Baptist Medical Center’s electronic medical records and annotated with BioCarta signaling signatures. The clinical potential of the discovered modules was exhibited by stratifying patients for drug responses. A series of discovered associations provided new insights into breast cancer, such as the effects of patient’s cultural background on preferences for surgical procedure. We also discovered two groups of highly associated features, the HER2 and the ER modules, each of which described how phenotypes were associated with molecular signatures, diagnostic features, and clinical decisions. The discovered “ER module”, which was dominated by cancer immunity, was used as an example for patient stratification and prediction of drug responses to tamoxifen and chemotherapy. BUFAM-derived RDN modeling demonstrated unique ability to discover clinically meaningful and actionable knowledge across highly heterogeneous biomedical big data sets.

What if Indigenous Knowledge Contradicts Accepted Scientific Findings?--The Hidden Agenda: Respect, Caring and Passion towards Aboriginal Research in the Context of Applying Western Academic Rules

ERIC Educational Resources Information Center

Witt, Norbert

2007-01-01

The statement in the title, what if Indigenous Knowledge contradicts accepted scientific findings (Fowler, 2000), is an expression of the dilemma people who research Indigenous Knowledge think they find themselves in when they are confronted with different interpretations of what it means to be human, or, as I may summarize it, with different…

Rethinking infant knowledge: toward an adaptive process account of successes and failures in object permanence tasks.

PubMed

Munakata, Y; McClelland, J L; Johnson, M H; Siegler, R S

1997-10-01

Infants seem sensitive to hidden objects in habituation tasks at 3.5 months but fail to retrieve hidden objects until 8 months. The authors first consider principle-based accounts of these successes and failures, in which early successes imply knowledge of principles and failures are attributed to ancillary deficits. One account is that infants younger than 8 months have the object permanence principle but lack means-ends abilities. To test this, 7-month-olds were trained on means-ends behaviors and were tested on retrieval of visible and occluded toys. Means-ends demands were the same, yet infants made more toy-guided retrievals in the visible case. The authors offer an adaptive process account in which knowledge is graded and embedded in specific behavioral processes. Simulation models that learn gradually to represent occluded objects show how this approach can account for success and failure in object permanence tasks without assuming principles and ancillary deficits.

Exploring the Hidden Barriers in Knowledge Translation: A Case Study Within an Academic Community.

PubMed

Harvey, Gill; Marshall, Rhianon J; Jordan, Zoe; Kitson, Alison L

2015-11-01

Debates about knowledge translation (KT) typically focus on the research-practice gap, which appears to be premised on the assumption that academics are a homogeneous collective, sharing a common view. We argue that a number of hidden barriers need to be addressed related to the understanding, interpretation, ability, and commitment to translate knowledge within academic communities. We explore this by presenting a qualitative case study in a health sciences faculty. Applying organizational and management theory, we discuss different types of boundaries and the resultant barriers generated, ranging from diversity in understanding and perceptions of KT to varying motivations and incentives to engage in translational activity. We illustrate how we are using the empirical findings to inform the development of a KT strategy that targets the identified barriers. Investing in this internal KT-focused activity is an important step to maximize the potential of future collaborations between producers and users of research in health care. © The Author(s) 2015.

The Medawar Lecture 2001 Knowledge for vision: vision for knowledge

PubMed Central

Gregory, Richard L

2005-01-01

An evolutionary development of perception is suggested—from passive reception to active perception to explicit conception—earlier stages being largely retained and incorporated in later species. A key is innate and then individually learned knowledge, giving meaning to sensory signals. Inappropriate or misapplied knowledge produces rich cognitive phenomena of illusions, revealing normally hidden processes of vision, tentatively classified here in a ‘peeriodic table’. Phenomena of physiology are distinguished from phenomena of general rules and specific object knowledge. It is concluded that vision uses implicit knowledge, and provides knowledge for intelligent behaviour and for explicit conceptual understanding including science. PMID:16147519

The Hidden Diversity of Flagellated Protists in Soil.

PubMed

Venter, Paul Christiaan; Nitsche, Frank; Arndt, Hartmut

2018-07-01

Protists are among the most diverse and abundant eukaryotes in soil. However, gaps between described and sequenced protist morphospecies still present a pending problem when surveying environmental samples for known species using molecular methods. The number of sequences in the molecular PR 2 database (∼130,000) is limited compared to the species richness expected (>1 million protist species) - limiting the recovery rate. This is important, since high throughput sequencing (HTS) methods are used to find associative patterns between functional traits, taxa and environmental parameters. We performed HTS to survey soil flagellates in 150 grasslands of central Europe, and tested the recovery rate of ten previously isolated and cultivated cercomonad species, among locally found diversity. We recovered sequences for reference soil flagellate species, but also a great number of their phylogenetically evaluated genetic variants, among rare and dominant taxa with presumably own biogeography. This was recorded among dominant (cercozoans, Sandona), rare (apusozoans) and a large hidden diversity of predominantly aquatic protists in soil (choanoflagellates, bicosoecids) often forming novel clades associated with uncultured environmental sequences. Evaluating the reads, instead of the OTUs that individual reads are usually clustered into, we discovered that much of this hidden diversity may be lost due to clustering. Copyright © 2018 Elsevier GmbH. All rights reserved.

Gaining Insights on Nasopharyngeal Carcinoma Treatment Outcome Using Clinical Data Mining Techniques.

PubMed

Ghaibeh, A Ammar; Kasem, Asem; Ng, Xun Jin; Nair, Hema Latha Krishna; Hirose, Jun; Thiruchelvam, Vinesh

2018-01-01

The analysis of Electronic Health Records (EHRs) is attracting a lot of research attention in the medical informatics domain. Hospitals and medical institutes started to use data mining techniques to gain new insights from the massive amounts of data that can be made available through EHRs. Researchers in the medical field have often used descriptive statistics and classical statistical methods to prove assumed medical hypotheses. However, discovering new insights from large amounts of data solely based on experts' observations is difficult. Using data mining techniques and visualizations, practitioners can find hidden knowledge, identify interesting patterns, or formulate new hypotheses to be further investigated. This paper describes a work in progress on using data mining methods to analyze clinical data of Nasopharyngeal Carcinoma (NPC) cancer patients. NPC is the fifth most common cancer among Malaysians, and the data analyzed in this study was collected from three states in Malaysia (Kuala Lumpur, Sabah and Sarawak), and is considered to be the largest up-to-date dataset of its kind. This research is addressing the issue of cancer recurrence after the completion of radiotherapy and chemotherapy treatment. We describe the procedure, problems, and insights gained during the process.

Conformation-dependent restraints for polynucleotides: I. Clustering of the geometry of the phosphodiester group

PubMed Central

Kowiel, Marcin; Brzezinski, Dariusz; Jaskolski, Mariusz

2016-01-01

The refinement of macromolecular structures is usually aided by prior stereochemical knowledge in the form of geometrical restraints. Such restraints are also used for the flexible sugar-phosphate backbones of nucleic acids. However, recent highly accurate structural studies of DNA suggest that the phosphate bond angles may have inadequate description in the existing stereochemical dictionaries. In this paper, we analyze the bonding deformations of the phosphodiester groups in the Cambridge Structural Database, cluster the studied fragments into six conformation-related categories and propose a revised set of restraints for the O-P-O bond angles and distances. The proposed restraints have been positively validated against data from the Nucleic Acid Database and an ultrahigh-resolution Z-DNA structure in the Protein Data Bank. Additionally, the manual classification of PO4 geometry is compared with geometrical clusters automatically discovered by machine learning methods. The machine learning cluster analysis provides useful insights and a practical example for general applications of clustering algorithms for automatic discovery of hidden patterns of molecular geometry. Finally, we describe the implementation and application of a public-domain web server for automatic generation of the proposed restraints. PMID:27521371

The Nash Equilibrium Revisited: Chaos and Complexity Hidden in Simplicity

NASA Astrophysics Data System (ADS)

Fellman, Philip V.

The Nash Equilibrium is a much discussed, deceptively complex, method for the analysis of non-cooperative games (McLennan and Berg, 2005). If one reads many of the commonly available definitions the description of the Nash Equilibrium is deceptively simple in appearance. Modern research has discovered a number of new and important complex properties of the Nash Equilibrium, some of which remain as contemporary conundrums of extraordinary difficulty and complexity (Quint and Shubik, 1997). Among the recently discovered features which the Nash Equilibrium exhibits under various conditions are heteroclinic Hamiltonian dynamics, a very complex asymptotic structure in the context of two-player bi-matrix games and a number of computationally complex or computationally intractable features in other settings (Sato, Akiyama and Farmer, 2002). This paper reviews those findings and then suggests how they may inform various market prediction strategies.

Geodetic imaging: A new tool for Mesoamerican archaeology

NASA Astrophysics Data System (ADS)

Carter, William E.; Shrestha, Ramesh L.; Fisher, Christopher; Leisz, Stephen

2012-10-01

On 15 May 2012, Honduran President Porfirio Lobo convened a press conference to announce that researchers mapping areas of the Mosquitia region of Honduras, using airborne light detection and ranging (lidar), had discovered what appeared to be an extensive complex of archaeological ruins hidden beneath the dense canopy of rain forest that shrouds the terrain [UTL Scientific, LLC, 2012]. President Lobo released preliminary images of the ruins derived from the airborne lidar observations (Figure 1a) but withheld information about their precise location so that measures could be taken to protect and preserve this newly discovered cultural heritage. The coordinates of the ruins, determined from the lidar observations with an accuracy of a few decimeters, will enable archaeological teams to use the Global Positioning System to navigate through the dense forest directly to features of interest.

Discovering Sentinel Rules for Business Intelligence

NASA Astrophysics Data System (ADS)

Middelfart, Morten; Pedersen, Torben Bach

This paper proposes the concept of sentinel rules for multi-dimensional data that warns users when measure data concerning the external environment changes. For instance, a surge in negative blogging about a company could trigger a sentinel rule warning that revenue will decrease within two months, so a new course of action can be taken. Hereby, we expand the window of opportunity for organizations and facilitate successful navigation even though the world behaves chaotically. Since sentinel rules are at the schema level as opposed to the data level, and operate on data changes as opposed to absolute data values, we are able to discover strong and useful sentinel rules that would otherwise be hidden when using sequential pattern mining or correlation techniques. We present a method for sentinel rule discovery and an implementation of this method that scales linearly on large data volumes.

A hidden pygmy devil from the Philippines: Arulenus miae sp. nov.-a new species serendipitously discovered in an amateur Facebook post
(Tetrigidae: Discotettiginae).

PubMed

Skejo, Josip; Caballero, Joy Honezza S

2016-01-21

Arulenus miae Skejo & Caballero sp. nov. is described from Buknidon and Davao, Mindanao, the Philippines. The species was serendipitously found in an amateur photo posted in Orthoptera Facebook group by Leif Gabrielsen. Holotype and paratype are deposited in Nederlands Centrum voor Biodiversiteit in Leiden, the Netherlands. Detailed comparison with Arulenus validispinus Stål, 1877 is given. A new diagnosis of the genus and A. validispinus is given. The paper is part of the revision of the subfamily Discotettiginae. This study provides a good example of how social networks can be used as a modern tool of discovering biodiversity if the regulations of the International Code of the Zoological Nomenclature are followed. A brief insight into habitat and ecology of this rainforest and mountainous species is presented.

Reading Readiness Deficiency in Children: Causes and Ways of Improvement

ERIC Educational Resources Information Center

Akubuilo, Francis; Okorie, Eugene U.; Onwuka, Gloria; Uloh-Bethels, Annah Chinyeaka

2015-01-01

Reading is one of the important skills of language. It is a basic tool of education whether formal or informal. Reading is a receptive skill, which involves the ability to meaningfully interpret or decode written or graphic symbols of language. Through reading, the hidden treasure of knowledge is unfolded; knowledge is gained thereby empowering…

Application of Knowledge Discovery in Databases Methodologies for Predictive Models for Pregnancy Adverse Events

ERIC Educational Resources Information Center

Taft, Laritza M.

2010-01-01

In its report "To Err is Human", The Institute of Medicine recommended the implementation of internal and external voluntary and mandatory automatic reporting systems to increase detection of adverse events. Knowledge Discovery in Databases (KDD) allows the detection of patterns and trends that would be hidden or less detectable if analyzed by…

Young Children's Recognition of How and when Knowledge Was Acquired

ERIC Educational Resources Information Center

Tang, Connie M.; Bartsch, Karen

2012-01-01

Two experiments investigated young children's understanding of how and when knowledge was acquired. In Experiment 1, thirty 4- and 5-year-olds were shown or told about various toys hidden in distinctive containers in two sessions a week apart. In the second session, children were asked how and when they learned the containers' contents. They more…

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

PubMed Central

Shah, Abhik; Woolf, Peter

2009-01-01

Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

Discovering hidden biodiversity: the use of complementary monitoring of fish diet based on DNA barcoding in freshwater ecosystems.

PubMed

Jo, Hyunbin; Ventura, Marc; Vidal, Nicolas; Gim, Jeong-Soo; Buchaca, Teresa; Barmuta, Leon A; Jeppesen, Erik; Joo, Gea-Jae

2016-01-01

Ecological monitoring contributes to the understanding of complex ecosystem functions. The diets of fish reflect the surrounding environment and habitats and may, therefore, act as useful integrating indicators of environmental status. It is, however, often difficult to visually identify items in gut contents to species level due to digestion of soft-bodied prey beyond visual recognition, but new tools rendering this possible are now becoming available. We used a molecular approach to determine the species identities of consumed diet items of an introduced generalist feeder, brown trout (Salmo trutta), in 10 Tasmanian lakes and compared the results with those obtained from visual quantification of stomach contents. We obtained 44 unique taxa (OTUs) belonging to five phyla, including seven classes, using the barcode of life approach from cytochrome oxidase I (COI). Compared with visual quantification, DNA analysis showed greater accuracy, yielding a 1.4-fold higher number of OTUs. Rarefaction curve analysis showed saturation of visually inspected taxa, while the curves from the DNA barcode did not saturate. The OTUs with the highest proportions of haplotypes were the families of terrestrial insects Formicidae, Chrysomelidae, and Torbidae and the freshwater Chironomidae. Haplotype occurrence per lake was negatively correlated with lake depth and transparency. Nearly all haplotypes were only found in one fish gut from a single lake. Our results indicate that DNA barcoding of fish diets is a useful and complementary method for discovering hidden biodiversity.

Hidden in plain sight: the formal, informal, and hidden curricula of a psychiatry clerkship.

PubMed

Wear, Delese; Skillicorn, Jodie

2009-04-01

To examine perceptions of the formal, informal, and hidden curricula in psychiatry as they are observed and experienced by (1) attending physicians who have teaching responsibilities for residents and medical students, (2) residents who are taught by those same physicians and who have teaching responsibilities for medical students, and (3) medical students who are taught by attendings and residents during their psychiatry rotation. From June to November 2007, the authors conducted focus groups with attendings, residents, and students in one midwestern academic setting. The sessions were audiotaped, transcribed, and analyzed for themes surrounding the formal, informal, and hidden curricula. All three groups offered a similar belief that the knowledge, skills, and values of the formal curriculum focused on building relationships. Similarly, all three suggested that elements of the informal and hidden curricula were expressed primarily as the values arising from attendings' role modeling, as the nature and amount of time attendings spend with patients, and as attendings' advice arising from experience and intuition versus "textbook learning." Whereas students and residents offered negative values arising from the informal and hidden curricula, attendings did not, offering instead the more positive values they intended to encourage through the informal and hidden curricula. The process described here has great potential in local settings across all disciplines. Asking teachers and learners in any setting to think about how they experience the educational environment and what sense they make of all curricular efforts can provide a reality check for educators and a values check for learners as they critically reflect on the meanings of what they are learning.

Tapping into the "Hidden" Home and Community Resources of Students

ERIC Educational Resources Information Center

Moll, Luis C.

2015-01-01

The author provides an overview of a "funds of knowledge" approach and presents three different adaptations of the approach with a common theme of expanding teachers' and students' resources for learning.

Phenomenology of pure-gauge hidden valleys at hadron colliders

NASA Astrophysics Data System (ADS)

Juknevich, Jose E.

Expectations for new physics at the LHC have been greatly influenced by the Hierarchy problem of electroweak symmetry breaking. However, there are reasons to believe that the LHC may still discover new physics, but not directly related to the resolution of the Hierarchy problem. To ensure that such a physics does not go undiscovered requires precise understanding of how new phenomena will reveal themselves in the current and future generation of particle-physics experiments. Given this fact it seems sensible to explore other approaches to this problem; we study three alternatives here. In this thesis I argue for the plausibility that the standard model is coupled, through new massive charged or colored particles, to a hidden sector whose low energy dynamics is controlled by a pure Yang-Mills theory, with no light matter. Such a sector would have numerous metastable "hidden glueballs" built from the hidden gluons. These states would decay to particles of the standard model. I consider the phenomenology of this scenario, and find formulas for the lifetimes and branching ratios of the most important of these states. The dominant decays are to two standard model gauge bosons or to fermion-antifermion pairs, or by radiative decays with photon or Higgs emission, leading to jet- and photon-rich signals, and some occasional leptons. The presence of effective operators of different mass dimensions, often competing with each other, together with a great diversity of states, leads to a great variability in the lifetimes and decay modes of the hidden glueballs. I find that most of the operators considered in this work are not heavily constrained by precision electroweak physics, therefore leaving plenty of room in the parameter space to be explored by the future experiments at the LHC. Finally, I discuss several issues on the phenomenology of the new massive particles as well as an outlook for experimental searches.

Hamiltonian dynamics of a quantum of space: hidden symmetries and spectrum of the volume operator, and discrete orthogonal polynomials

NASA Astrophysics Data System (ADS)

Aquilanti, Vincenzo; Marinelli, Dimitri; Marzuoli, Annalisa

2013-05-01

The action of the quantum mechanical volume operator, introduced in connection with a symmetric representation of the three-body problem and recently recognized to play a fundamental role in discretized quantum gravity models, can be given as a second-order difference equation which, by a complex phase change, we turn into a discrete Schrödinger-like equation. The introduction of discrete potential-like functions reveals the surprising crucial role here of hidden symmetries, first discovered by Regge for the quantum mechanical 6j symbols; insight is provided into the underlying geometric features. The spectrum and wavefunctions of the volume operator are discussed from the viewpoint of the Hamiltonian evolution of an elementary ‘quantum of space’, and a transparent asymptotic picture of the semiclassical and classical regimes emerges. The definition of coordinates adapted to the Regge symmetry is exploited for the construction of a novel set of discrete orthogonal polynomials, characterizing the oscillatory components of torsion-like modes.

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.

Conserved patterns hidden within group A Streptococcus M protein hypervariability recognize human C4b-binding protein

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

Buffalo, Cosmo Z.; Bahn-Suh, Adrian J.; Hirakis, Sophia P.

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ~90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteinsmore » in complexes with C4BP. The structures revealed a uniform and tolerant ‘reading head’ in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M–C4BP interaction, and also inform a path towards vaccine design.« less

Intercultural PhD Supervision: Exploring the Hidden Curriculum in a Social Science Faculty Doctoral Programme

ERIC Educational Resources Information Center

Kidman, Joanna; Manathunga, Catherine; Cornforth, Sue

2017-01-01

International knowledge markets rely heavily on a ready supply of highly mobile doctoral students, many of whom are from the global South, to bring in revenue. The supervision of these PhD students, however, can reproduce neo-colonial knowledge relations, often in subtle ways. In settler nations, international PhD students may find that they are…

Form-Focused Discovery Activities in English Classes

ERIC Educational Resources Information Center

Ogeyik, Muhlise Cosgun

2011-01-01

Form-focused discovery activities allow language learners to grasp various aspects of a target language by contributing implicit knowledge by using discovered explicit knowledge. Moreover, such activities can assist learners to perceive and discover the features of their language input. In foreign language teaching environments, they can be used…

Decoding the learning environment of medical education: a hidden curriculum perspective for faculty development.

PubMed

Hafler, Janet P; Ownby, Allison R; Thompson, Britta M; Fasser, Carl E; Grigsby, Kevin; Haidet, Paul; Kahn, Marc J; Hafferty, Frederic W

2011-04-01

Medical student literature has broadly established the importance of differentiating between formal-explicit and hidden-tacit dimensions of the physician education process. The hidden curriculum refers to cultural mores that are transmitted, but not openly acknowledged, through formal and informal educational endeavors. The authors extend the concept of the hidden curriculum from students to faculty, and in so doing, they frame the acquisition by faculty of knowledge, skills, and values as a more global process of identity formation. This process includes a subset of formal, formative activities labeled "faculty development programs" that target specific faculty skills such as teaching effectiveness or leadership; however, it also includes informal, tacit messages that faculty absorb. As faculty members are socialized into faculty life, they often encounter conflicting messages about their role. In this article, the authors examine how faculty development programs have functioned as a source of conflict, and they ask how these programs might be retooled to assist faculty in understanding the tacit institutional culture shaping effective socialization and in managing the inconsistencies that so often dominate faculty life. © by the Association of American Medical Colleges.

Intuitive optics: what great apes infer from mirrors and shadows.

PubMed

Völter, Christoph J; Call, Josep

2018-05-02

There is ongoing debate about the extent to which nonhuman animals, like humans, can go beyond first-order perceptual information to abstract structural information from their environment. To provide more empirical evidence regarding this question, we examined what type of information great apes (chimpanzees, bonobos, and orangutans) gain from optical effects such as shadows and mirror images. In an initial experiment, we investigated whether apes would use mirror images and shadows to locate hidden food. We found that all examined ape species used these cues to find the food. Follow-up experiments showed that apes neither confused these optical effects with the food rewards nor did they merely associate cues with food. First, naïve chimpanzees used the shadow of the hidden food to locate it but they did not learn within the same number of trials to use a perceptually similar rubber patch as indicator of the hidden food reward. Second, apes made use of the mirror images to estimate the distance of the hidden food from their own body. Depending on the distance, apes either pointed into the direction of the food or tried to access the hidden food directly. Third, apes showed some sensitivity to the geometrical relation between mirror orientation and mirrored objects when searching hidden food. Fourth, apes tended to interpret mirror images and pictures of these mirror images differently depending on their prior knowledge. Together, these findings suggest that apes are sensitive to the optical relation between mirror images and shadows and their physical referents.

Hidden messenger revealed in Hawking radiation: A resolution to the paradox of black hole information loss

NASA Astrophysics Data System (ADS)

Zhang, Baocheng; Cai, Qing-yu; You, Li; Zhan, Ming-sheng

2009-05-01

Using standard statistical method, we discover the existence of correlations among Hawking radiations (of tunneled particles) from a black hole. The information carried by such correlations is quantified by mutual information between sequential emissions. Through a careful counting of the entropy taken out by the emitted particles, we show that the black hole radiation as tunneling is an entropy conservation process. While information is leaked out through the radiation, the total entropy is conserved. Thus, we conclude the black hole evaporation process is unitary.

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.

An Exploration of Latent Structure in Observational Huntington’s Disease Studies

PubMed Central

Ghosh, Soumya; Sun, Zhaonan; Li, Ying; Cheng, Yu; Mohan, Amrita; Sampaio, Cristina; Hu, Jianying

2017-01-01

Huntington’s disease (HD) is a monogenic neurodegenerative disorder characterized by the progressive decay of motor and cognitive abilities accompanied by psychiatric episodes. Tracking and modeling the progression of the multi-faceted clinical symptoms of HD is a challenging problem that has important implications for staging of HD patients and the development of improved enrollment criteria for future HD studies and trials. In this paper, we describe the first steps towards this goal. We begin by curating data from four recent observational HD studies, each containing a diverse collection of clinical assessments. The resulting dataset is unprecedented in size and contains data from 19,269 study participants. By analyzing this large dataset, we are able to discover hidden low dimensional structure in the data that correlates well with surrogate measures of HD progression. The discovered structures are promising candidates for future consumption by downstream statistical HD progression models. PMID:28815114

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

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.

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

PubMed

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

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.

Domestic horses send signals to humans when they face with an unsolvable task.

PubMed

Ringhofer, Monamie; Yamamoto, Shinya

2017-05-01

Some domestic animals are thought to be skilled at social communication with humans due to the process of domestication. Horses, being in close relationship with humans, similar to dogs, might be skilled at communication with humans. Previous studies have indicated that they are sensitive to bodily signals and the attentional state of humans; however, there are few studies that investigate communication with humans and responses to the knowledge state of humans. Our first question was whether and how horses send signals to their potentially helpful but ignorant caretakers in a problem-solving situation where a food item was hidden in a bucket that was accessible only to the caretakers. We then examined whether horses alter their behaviours on the basis of the caretakers' knowledge of where the food was hidden. We found that horses communicated to their caretakers using visual and tactile signals. The signalling behaviour of the horses significantly increased in conditions where the caretakers had not seen the hiding of the food. These results suggest that horses alter their communicative behaviour towards humans in accordance with humans' knowledge state.

Hidden lesions of the posterior horn of the medial meniscus: a systematic arthroscopic exploration of the concealed portion of the knee.

PubMed

Sonnery-Cottet, Bertrand; Conteduca, Jacopo; Thaunat, Mathieu; Gunepin, François Xavier; Seil, Romain

2014-04-01

Anterior cruciate ligament (ACL) tears are frequently associated with meniscal lesions. Despite improvements in meniscal repair techniques, failure rates remain significant, especially for the posterior horn of the medial meniscus. To determine whether a systematic arthroscopic exploration of the posterior horn of the medial meniscus with an additional posteromedial portal is useful to identify otherwise unrecognized lesions. Case series; Level of evidence, 4. In a consecutive series of 302 ACL reconstructions, a systematic arthroscopic exploration of the posterior horn of the medial meniscus was performed. The first stage of the exploration was achieved through anterior visualization via a standard anterolateral portal. In the second stage, the posterior horn of the medial meniscus was visualized posteriorly via the anterolateral portal with the scope positioned deep in the notch. In the third stage, the posterior horn was probed through an additional posteromedial portal. A χ2 test and logistic regression analysis were performed to determine if the time from injury to surgery was associated with the meniscal tear pattern. A medial meniscal tear was diagnosed in 125 of the 302 patients (41.4%). Seventy-five lesions (60%) located in the meniscal body were diagnosed at the first stage of the arthroscopic exploration. Fifty lesions located in the ramp area were diagnosed: 29 (23.2%) at the second stage and 21 lesions (16.8%) at the third stage after minimal debridement of the superficial soft tissue layer. The latter type of lesion is called a "hidden lesion." Altogether, the prevalence of ramp lesions in this population was 40%. Meniscal body lesions (odds ratio, 2.6; 95% confidence interval, 1.18-5.18; P < .02) were found to be significantly correlated with a longer delay between injury and surgery. Posterior visualization and posteromedial probing of the posterior horn of the medial meniscus can help in discovering a higher rate of lesions that could be easily missed through a standard anterior exploration. In numerous cases, these lesions were "hidden" under a membrane-like tissue and were discovered after minimal debridement through a posteromedial portal.

Stream-Dashboard: A Big Data Stream Clustering Framework with Applications to Social Media Streams

ERIC Educational Resources Information Center

Hawwash, Basheer

2013-01-01

Data mining is concerned with detecting patterns of data in raw datasets, which are then used to unearth knowledge that might not have been discovered using conventional querying or statistical methods. This discovered knowledge has been used to empower decision makers in countless applications spanning across many multi-disciplinary areas…

SemaTyP: a knowledge graph based literature mining method for drug discovery.

PubMed

Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

2018-05-30

Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

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.

Discovering System Health Anomalies Using Data Mining Techniques

NASA Technical Reports Server (NTRS)

Sriastava, Ashok, N.

2005-01-01

We present a data mining framework for the analysis and discovery of anomalies in high-dimensional time series of sensor measurements that would be found in an Integrated System Health Monitoring system. We specifically treat the problem of discovering anomalous features in the time series that may be indicative of a system anomaly, or in the case of a manned system, an anomaly due to the human. Identification of these anomalies is crucial to building stable, reusable, and cost-efficient systems. The framework consists of an analysis platform and new algorithms that can scale to thousands of sensor streams to discovers temporal anomalies. We discuss the mathematical framework that underlies the system and also describe in detail how this framework is general enough to encompass both discrete and continuous sensor measurements. We also describe a new set of data mining algorithms based on kernel methods and hidden Markov models that allow for the rapid assimilation, analysis, and discovery of system anomalies. We then describe the performance of the system on a real-world problem in the aircraft domain where we analyze the cockpit data from aircraft as well as data from the aircraft propulsion, control, and guidance systems. These data are discrete and continuous sensor measurements and are dealt with seamlessly in order to discover anomalous flights. We conclude with recommendations that describe the tradeoffs in building an integrated scalable platform for robust anomaly detection in ISHM applications.

What are patients with Rett syndrome interested in?

PubMed

Hirano, Daisuke; Taniguchi, Takamichi

2018-02-01

[Purpose] Rett syndrome is a severe neurodevelopmental disease; individuals typically have no verbal skills or purposeful hand movements. In clinical settings, knowledge of their interests would be helpful for therapy. Therefore, we investigated the interests of Rett syndrome patients. [Subjects and Methods] In 2016, we sent a questionnaire regarding the interests of individuals with Rett syndrome to 1,016 directors of schools for special needs education and 204 directors of rehabilitation departments (130 facilities for persons with severe motor and intellectual disabilities, 73 wards for patients with severe motor and intellectual disabilities, and the National Hospital Organization and National Center Hospital, and the National Center of Neurology and Psychiatry) in Japan. We used descriptive statistics and content analysis to examine the answers to the questionnaires. [Results] Information was acquired from 216 individuals (3-53 years old) with Rett syndrome. 92.9% of the individuals were reported to have some interests (e.g., in people, music, things to see, animation, or books). [Conclusion] Individuals with Rett syndrome were observed to be interested in various things despite their having severe motor and intellectual disabilities. These findings suggest that family members and care staff might facilitate various changes or developments of these individuals and discover their hidden strengths by focusing on their interests.

Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique

NASA Astrophysics Data System (ADS)

Bandaru, Sunith; Deb, Kalyanmoy

2011-09-01

In this article, a methodology is proposed for automatically extracting innovative design principles which make a system or process (subject to conflicting objectives) optimal using its Pareto-optimal dataset. Such 'higher knowledge' would not only help designers to execute the system better, but also enable them to predict how changes in one variable would affect other variables if the system has to retain its optimal behaviour. This in turn would help solve other similar systems with different parameter settings easily without the need to perform a fresh optimization task. The proposed methodology uses a clustering-based optimization technique and is capable of discovering hidden functional relationships between the variables, objective and constraint functions and any other function that the designer wishes to include as a 'basis function'. A number of engineering design problems are considered for which the mathematical structure of these explicit relationships exists and has been revealed by a previous study. A comparison with the multivariate adaptive regression splines (MARS) approach reveals the practicality of the proposed approach due to its ability to find meaningful design principles. The success of this procedure for automated innovization is highly encouraging and indicates its suitability for further development in tackling more complex design scenarios.

Clustering Algorithms: Their Application to Gene Expression Data

PubMed Central

Oyelade, Jelili; Isewon, Itunuoluwa; Oladipupo, Funke; Aromolaran, Olufemi; Uwoghiren, Efosa; Ameh, Faridah; Achas, Moses; Adebiyi, Ezekiel

2016-01-01

Gene expression data hide vital information required to understand the biological process that takes place in a particular organism in relation to its environment. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks and the volume of genes present increase the challenges of comprehending and interpretation of the resulting mass of data, which consists of millions of measurements; these data also inhibit vagueness, imprecision, and noise. Therefore, the use of clustering techniques is a first step toward addressing these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding gene functions, cellular processes, and subtypes of cells, mining useful information from noisy data, and understanding gene regulation. The other benefit of clustering gene expression data is the identification of homology, which is very important in vaccine design. This review examines the various clustering algorithms applicable to the gene expression data in order to discover and provide useful knowledge of the appropriate clustering technique that will guarantee stability and high degree of accuracy in its analysis procedure. PMID:27932867

A novel water quality data analysis framework based on time-series data mining.

PubMed

Deng, Weihui; Wang, Guoyin

2017-07-01

The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Universities as Moral Communities.

ERIC Educational Resources Information Center

Kovac, Jeffrey; Coppola, Brian P.

2000-01-01

Explores what morally reflective educational practice might look like, focusing on education as a relational human activity that has a moral dimension. Discusses: (1) instructional goals (development of character, cognitive skills, and disciplinary skills, and reintegration of knowledge); (2) pedagogy (for example, the hidden curriculum in…

Ecological approaches to human nutrition.

PubMed

DeClerck, Fabrice A J; Fanzo, Jessica; Palm, Cheryl; Remans, Roseline

2011-03-01

Malnutrition affects a large number of people throughout the developing world. Approaches to reducing malnutrition rarely focus on ecology and agriculture to simultaneously improve human nutrition and environmental sustainability. However, evidence suggests that interdisciplinary approaches that combine the knowledge bases of these disciplines can serve as a central strategy in alleviating hidden hunger for the world's poorest. To describe the role that ecological knowledge plays in alleviating hidden hunger, considering human nutrition as an overlooked ecosystem service. We review existing literature and propose a framework that expands on earlier work on econutrition. We provide novel evidence from case studies conducted by the authors in western Kenya and propose a framework for interdisciplinary collaboration to alleviate hidden hunger, increase agricultural productivity, and improve environmental sustainability. Our review supports the concept that an integrated approach will impact human nutrition. We provide evidence that increased functional agrobiodiversity can alleviate anemia, and interventions that contribute to environmental sustainability can have both direct and indirect effects on human health and nutritional well-being. Integrated and interdisciplinary approaches are critical to reaching development goals. Ecologists must begin to consider not only how their field can contribute to biodiversity conservation, but also, the relationship between biodiversity and provisioning of nontraditional ecosystem services such as human health. Likewise, nutritionists and agronomists must recognize that many of the solutions to increasing human wellbeing and health can best be achieved by focusing on a healthy environment and the conservation of ecosystem services.

Ultrafast photo-induced hidden phases in strained manganite thin films

NASA Astrophysics Data System (ADS)

Zhang, Jingdi; McLeod, A. S.; Zhang, Gu-Feng; Stoica, Vladimir; Jin, Feng; Gu, Mingqiang; Gopalan, Venkatraman; Freeland, John W.; Wu, Wenbin; Rondinelli, James; Wen, Haidan; Basov, D. N.; Averitt, R. D.

Correlated transition metal oxides (TMOs) are particularly sensitive to external control because of energy degeneracy in a complex energy landscape that promote a plethora of metastable states. However, it remains a grand challenge to actively control and fully explore the rich landscape of TMOs. Dynamic control with pulsed photons can overcome energetic barriers, enabling access to transient or metastable states that are not thermally accessible. In the past, we have demonstrated that mode-selective single-laser-pulse excitation of a strained manganite thin film La2/3Ca1/3MnO3 initiates a persistent phase transition from an emergent antiferromagnetic insulating ground state to a ferromagnetic metallic metastable state. Beyond the photo-induced insulator to metal transition, we recently discovered a new peculiar photo-induced hidden phase, identified by an experimental approach that combines ultrafast pump-probe spectroscopy, THz spectroscopy, X-ray diffraction, cryogenic near-field spectroscopy and SHG probe. This work is funded by the DOE, Office of Science, Office of Basic Energy Science under Award Numbers DE-SC0012375 and DE-SC0012592.

Reverse engineering a social agent-based hidden markov model--visage.

PubMed

Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

2008-12-01

We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

Reproductive isolation and patterns of genetic differentiation in a cryptic butterfly species complex

PubMed Central

Dincâ, V; Wiklund, C; Lukhtanov, V A; Kodandaramaiah, U; Norén, K; Dapporto, L; Wahlberg, N; Vila, R; Friberg, M

2013-01-01

Molecular studies of natural populations are often designed to detect and categorize hidden layers of cryptic diversity, and an emerging pattern suggests that cryptic species are more common and more widely distributed than previously thought. However, these studies are often decoupled from ecological and behavioural studies of species divergence. Thus, the mechanisms by which the cryptic diversity is distributed and maintained across large spatial scales are often unknown. In 1988, it was discovered that the common Eurasian Wood White butterfly consisted of two species (Leptidea sinapis and Leptidea reali), and the pair became an emerging model for the study of speciation and chromosomal evolution. In 2011, the existence of a third cryptic species (Leptidea juvernica) was proposed. This unexpected discovery raises questions about the mechanisms preventing gene flow and about the potential existence of additional species hidden in the complex. Here, we compare patterns of genetic divergence across western Eurasia in an extensive data set of mitochondrial and nuclear DNA sequences with behavioural data on inter- and intraspecific reproductive isolation in courtship experiments. We show that three species exist in accordance with both the phylogenetic and biological species concepts and that additional hidden diversity is unlikely to occur in Europe. The Leptidea species are now the best studied cryptic complex of butterflies in Europe and a promising model system for understanding the formation of cryptic species and the roles of local processes, colonization patterns and heterospecific interactions for ecological and evolutionary divergence. PMID:23909947

A Community-Driven Workflow Recommendations and Reuse Infrastructure

NASA Astrophysics Data System (ADS)

Zhang, J.; Votava, P.; Lee, T. J.; Lee, C.; Xiao, S.; Nemani, R. R.; Foster, I.

2013-12-01

Aiming to connect the Earth science community to accelerate the rate of discovery, NASA Earth Exchange (NEX) has established an online repository and platform, so that researchers can publish and share their tools and models with colleagues. In recent years, workflow has become a popular technique at NEX for Earth scientists to define executable multi-step procedures for data processing and analysis. The ability to discover and reuse knowledge (sharable workflows or workflow) is critical to the future advancement of science. However, as reported in our earlier study, the reusability of scientific artifacts at current time is very low. Scientists often do not feel confident in using other researchers' tools and utilities. One major reason is that researchers are often unaware of the existence of others' data preprocessing processes. Meanwhile, researchers often do not have time to fully document the processes and expose them to others in a standard way. These issues cannot be overcome by the existing workflow search technologies used in NEX and other data projects. Therefore, this project aims to develop a proactive recommendation technology based on collective NEX user behaviors. In this way, we aim to promote and encourage process and workflow reuse within NEX. Particularly, we focus on leveraging peer scientists' best practices to support the recommendation of artifacts developed by others. Our underlying theoretical foundation is rooted in the social cognitive theory, which declares people learn by watching what others do. Our fundamental hypothesis is that sharable artifacts have network properties, much like humans in social networks. More generally, reusable artifacts form various types of social relationships (ties), and may be viewed as forming what organizational sociologists who use network analysis to study human interactions call a 'knowledge network.' In particular, we will tackle two research questions: R1: What hidden knowledge may be extracted from usage history to help Earth scientists better understand existing artifacts and how to use them in a proper manner? R2: Informed by insights derived from their computing contexts, how could such hidden knowledge be used to facilitate artifact reuse by Earth scientists? Our study of the two research questions will provide answers to three technical questions aiming to assist NEX users during workflow development: 1) How to determine what topics interest the researcher? 2) How to find appropriate artifacts? and 3) How to advise the researcher in artifact reuse? In this paper, we report our on-going efforts of leveraging social networking theory and analysis techniques to provide dynamic advice on artifact reuse to NEX users based on their surrounding contexts. As a proof of concept, we have designed and developed a plug-in to the VisTrails workflow design tool. When users develop workflows using VisTrails, our plug-in will proactively recommend most relevant sub-workflows to the users.

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.

Selections from 2016: Hidden Galaxies Found Behind the Milky Way

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2016-01-01

Editors note:In these last two weeks of 2016, well be looking at a few selections that we havent yet discussed on AAS Nova from among the most-downloaded paperspublished in AAS journals this year. The usual posting schedule will resume after the AAS winter meeting.The Parkes H I Zone of Avoidance SurveyPublished February2016Main takeaway:883 galaxies have been discoveredwithin a few hundredmillion light-years of us, hiding behind the Milky Way. The galaxies were found by a team led by Lister Staveley-Smith (International Center for Radio Astronomy Research, University of Western Australia) using the 64-m Parkes radio telescope in Australia.Distribution of the galaxies discovered in the Zone of Avoidance. Radial distance is measured by the recessional velocities of the galaxies. [Staveley-Smith et al. 2016]Why its interesting:These new galaxies were discovered in whats known as the Zone of Avoidance, a gap that extends roughly 5 above and 5 below the galactic plane. The Zone of Avoidance has been excluded from many past surveys because the stars and dust of the Milky Way prevent us from being able to identify background galaxies in this region. But the Parkes radio telescope equipped with an innovative new receiver was able to peer through the foreground of the Milky Way to detect the hidden galaxies behind it.What this could teach us:The discovery of hundreds of new galaxies may help explain the gravitational anomaly known as the Great Attractor region, a diffuse concentration of mass roughly 250 million light-years away that is pulling the Milky Way and hundreds of thousands of other galaxies toward it.CitationL. Staveley-Smith et al 2016 AJ 151 52. doi:10.3847/0004-6256/151/3/52

Careers in Psychology: Creating Customized Learning to Expose the Invisible Curriculum

ERIC Educational Resources Information Center

Case, Kim A.; Miller, Angela; Hensley, Rachel; Jackson, Shaprie

2014-01-01

Invisible knowledge or the hidden curriculum, the informal education some students get from faculty mentors, is a privilege not afforded to all students. Many universities have instituted psychology careers courses to assist undergraduate psychology students with academic and career advisement. Designed to share this invisible curriculum with all…

Uncovering the wisdom hidden between the lines: the Collaborative Reflexive Deliberative Approach.

PubMed

Crabtree, Benjamin F; Miller, William L; Gunn, Jane M; Hogg, William E; Scott, Cathie M; Levesque, Jean-Frederic; Harris, Mark F; Chase, Sabrina M; Advocat, Jenny R; Halma, Lisa M; Russell, Grant M

2018-05-23

Meta-analysis and meta-synthesis have been developed to synthesize results across published studies; however, they are still largely grounded in what is already published, missing the tacit 'between the lines' knowledge generated during many research projects that are not intrinsic to the main objectives of studies. To develop a novel approach to expand and deepen meta-syntheses using researchers' experience, tacit knowledge and relevant unpublished materials. We established new collaborations among primary health care researchers from different contexts based on common interests in reforming primary care service delivery and a diversity of perspectives. Over 2 years, the team met face-to-face and via tele- and video-conferences to employ the Collaborative Reflexive Deliberative Approach (CRDA) to discuss and reflect on published and unpublished results from participants' studies to identify new patterns and insights. CRDA focuses on uncovering critical insights, interpretations hidden within multiple research contexts. For the process to work, careful attention must be paid to ensure sufficient diversity among participants while also having people who are able to collaborate effectively. Ensuring there are enough studies for contextual variation also matters. It is necessary to balance rigorous facilitation techniques with the creation of safe space for diverse contributions. The CRDA requires large commitments of investigator time, the expense of convening facilitated retreats, considerable coordination, and strong leadership. The process creates an environment where interactions among diverse participants can illuminate hidden information within the contexts of studies, effectively enhancing theory development and generating new research questions and strategies.

Invisible Brain: Knowledge in Research Works and Neuron Activity.

PubMed

Segev, Aviv; Curtis, Dorothy; Jung, Sukhwan; Chae, Suhyun

2016-01-01

If the market has an invisible hand, does knowledge creation and representation have an "invisible brain"? While knowledge is viewed as a product of neuron activity in the brain, can we identify knowledge that is outside the brain but reflects the activity of neurons in the brain? This work suggests that the patterns of neuron activity in the brain can be seen in the representation of knowledge-related activity. Here we show that the neuron activity mechanism seems to represent much of the knowledge learned in the past decades based on published articles, in what can be viewed as an "invisible brain" or collective hidden neural networks. Similar results appear when analyzing knowledge activity in patents. Our work also tries to characterize knowledge increase as neuron network activity growth. The results propose that knowledge-related activity can be seen outside of the neuron activity mechanism. Consequently, knowledge might exist as an independent mechanism.

Invisible Brain: Knowledge in Research Works and Neuron Activity

PubMed Central

Segev, Aviv; Curtis, Dorothy; Jung, Sukhwan; Chae, Suhyun

2016-01-01

If the market has an invisible hand, does knowledge creation and representation have an “invisible brain”? While knowledge is viewed as a product of neuron activity in the brain, can we identify knowledge that is outside the brain but reflects the activity of neurons in the brain? This work suggests that the patterns of neuron activity in the brain can be seen in the representation of knowledge-related activity. Here we show that the neuron activity mechanism seems to represent much of the knowledge learned in the past decades based on published articles, in what can be viewed as an “invisible brain” or collective hidden neural networks. Similar results appear when analyzing knowledge activity in patents. Our work also tries to characterize knowledge increase as neuron network activity growth. The results propose that knowledge-related activity can be seen outside of the neuron activity mechanism. Consequently, knowledge might exist as an independent mechanism. PMID:27439199

How transfer flights shape the structure of the airline network.

PubMed

Ryczkowski, Tomasz; Fronczak, Agata; Fronczak, Piotr

2017-07-17

In this paper, we analyse the gravity model in the global passenger air-transport network. We show that in the standard form, the model is inadequate for correctly describing the relationship between passenger flows and typical geo-economic variables that characterize connected countries. We propose a model for transfer flights that allows exploitation of these discrepancies in order to discover hidden subflows in the network. We illustrate its usefulness by retrieving the distance coefficient in the gravity model, which is one of the determinants of the globalization process. Finally, we discuss the correctness of the presented approach by comparing the distance coefficient to several well-known economic events.

Checklists, safety, my culture and me.

PubMed

Raghunathan, Karthik

2012-07-01

The world is not flat. Hierarchy is a fact of life in society and in healthcare institutions. National, specialty-specific and institutional cultures may play an important role in shaping today's patient-safety climate. The influence of power distance on safety interventions is under-studied. Checklists may make power distance-hampered negotiations easier by providing a standardised aviation-like framework for communications and by democratising the environment. By using surveys and simulation, we might discover patterns of potentially hidden yet problematic interactions that might foster maintenance of the error swamp. We need to understand how people interact as members of a group as this is crucial for the development of generalisable safety interventions.

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.

A semi-supervised learning framework for biomedical event extraction based on hidden topics.

PubMed

Zhou, Deyu; Zhong, Dayou

2015-05-01

Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, due to the lack of explicit structure, literature in life science, one of the most important sources of this information, prevents computer-based systems from accessing. Therefore, biomedical event extraction, automatically acquiring knowledge of molecular events in research articles, has attracted community-wide efforts recently. Most approaches are based on statistical models, requiring large-scale annotated corpora to precisely estimate models' parameters. However, it is usually difficult to obtain in practice. Therefore, employing un-annotated data based on semi-supervised learning for biomedical event extraction is a feasible solution and attracts more interests. In this paper, a semi-supervised learning framework based on hidden topics for biomedical event extraction is presented. In this framework, sentences in the un-annotated corpus are elaborately and automatically assigned with event annotations based on their distances to these sentences in the annotated corpus. More specifically, not only the structures of the sentences, but also the hidden topics embedded in the sentences are used for describing the distance. The sentences and newly assigned event annotations, together with the annotated corpus, are employed for training. Experiments were conducted on the multi-level event extraction corpus, a golden standard corpus. Experimental results show that more than 2.2% improvement on F-score on biomedical event extraction is achieved by the proposed framework when compared to the state-of-the-art approach. The results suggest that by incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely described by hidden topics and structures of the sentences. Copyright © 2015 Elsevier B.V. All rights reserved.

Motion Recognition and Modifying Motion Generation for Imitation Robot Based on Motion Knowledge Formation

NASA Astrophysics Data System (ADS)

Okuzawa, Yuki; Kato, Shohei; Kanoh, Masayoshi; Itoh, Hidenori

A knowledge-based approach to imitation learning of motion generation for humanoid robots and an imitative motion generation system based on motion knowledge learning and modification are described. The system has three parts: recognizing, learning, and modifying parts. The first part recognizes an instructed motion distinguishing it from the motion knowledge database by the continuous hidden markov model. When the motion is recognized as being unfamiliar, the second part learns it using locally weighted regression and acquires a knowledge of the motion. When a robot recognizes the instructed motion as familiar or judges that its acquired knowledge is applicable to the motion generation, the third part imitates the instructed motion by modifying a learned motion. This paper reports some performance results: the motion imitation of several radio gymnastics motions.

Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study

PubMed Central

2014-01-01

Background Given the significant impact on public health and drug development, drug safety has been a focal point and research emphasis across multiple disciplines in addition to scientific investigation, including consumer advocates, drug developers and regulators. Such a concern and effort has led numerous databases with drug safety information available in the public domain and the majority of them contain substantial textual data. Text mining offers an opportunity to leverage the hidden knowledge within these textual data for the enhanced understanding of drug safety and thus improving public health. Methods In this proof-of-concept study, topic modeling, an unsupervised text mining approach, was performed on the LiverTox database developed by National Institutes of Health (NIH). The LiverTox structured one document per drug that contains multiple sections summarizing clinical information on drug-induced liver injury (DILI). We hypothesized that these documents might contain specific textual patterns that could be used to address key DILI issues. We placed the study on drug-induced acute liver failure (ALF) which was a severe form of DILI with limited treatment options. Results After topic modeling of the "Hepatotoxicity" sections of the LiverTox across 478 drug documents, we identified a hidden topic relevant to Hy's law that was a widely-accepted rule incriminating drugs with high risk of causing ALF in humans. Using this topic, a total of 127 drugs were further implicated, 77 of which had clear ALF relevant terms in the "Outcome and management" sections of the LiverTox. For the rest of 50 drugs, evidence supporting risk of ALF was found for 42 drugs from other public databases. Conclusion In this case study, the knowledge buried in the textual data was extracted for identification of drugs with potential of causing ALF by applying topic modeling to the LiverTox database. The knowledge further guided identification of drugs with the similar potential and most of them could be verified and confirmed. This study highlights the utility of topic modeling to leverage information within textual drug safety databases, which provides new opportunities in the big data era to assess drug safety. PMID:25559675

Mining hidden knowledge for drug safety assessment: topic modeling of LiverTox as a case study.

PubMed

Yu, Ke; Zhang, Jie; Chen, Minjun; Xu, Xiaowei; Suzuki, Ayako; Ilic, Katarina; Tong, Weida

2014-01-01

Given the significant impact on public health and drug development, drug safety has been a focal point and research emphasis across multiple disciplines in addition to scientific investigation, including consumer advocates, drug developers and regulators. Such a concern and effort has led numerous databases with drug safety information available in the public domain and the majority of them contain substantial textual data. Text mining offers an opportunity to leverage the hidden knowledge within these textual data for the enhanced understanding of drug safety and thus improving public health. In this proof-of-concept study, topic modeling, an unsupervised text mining approach, was performed on the LiverTox database developed by National Institutes of Health (NIH). The LiverTox structured one document per drug that contains multiple sections summarizing clinical information on drug-induced liver injury (DILI). We hypothesized that these documents might contain specific textual patterns that could be used to address key DILI issues. We placed the study on drug-induced acute liver failure (ALF) which was a severe form of DILI with limited treatment options. After topic modeling of the "Hepatotoxicity" sections of the LiverTox across 478 drug documents, we identified a hidden topic relevant to Hy's law that was a widely-accepted rule incriminating drugs with high risk of causing ALF in humans. Using this topic, a total of 127 drugs were further implicated, 77 of which had clear ALF relevant terms in the "Outcome and management" sections of the LiverTox. For the rest of 50 drugs, evidence supporting risk of ALF was found for 42 drugs from other public databases. In this case study, the knowledge buried in the textual data was extracted for identification of drugs with potential of causing ALF by applying topic modeling to the LiverTox database. The knowledge further guided identification of drugs with the similar potential and most of them could be verified and confirmed. This study highlights the utility of topic modeling to leverage information within textual drug safety databases, which provides new opportunities in the big data era to assess drug safety.

Heavy-flavor production and medium properties in high-energy nuclear collisions --What next?

DOE PAGES

Aarts, G.; Aichelin, J.; Allton, C.; ...

2017-05-16

Open and hidden heavy-flavor physics in high-energy nuclear collisions are entering a new and exciting stage towards reaching a clearer understanding of the new experimental results with the possibility to link them directly to the advancement in lattice Quantum Chromo-Dynamics (QCD). Some recent results from experiments and theoretical developments regarding open and hidden heavy-flavor dynamics have been debated at the Lorentz Workshop Tomography of the Quark-Gluon Plasma with Heavy Quarks, which was held in October 2016 in Leiden, The Netherlands. Here, we summarize identified common understandings and developed strategies for the upcoming five years, which aim at achieving a profoundmore » knowledge of the dynamical properties of the quark-gluon plasma.« less

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.

Novel aspects in diagnostic approach to respiratory patients: is it the time for a new semiotics?

PubMed

Soldati, Gino; Smargiassi, Andrea; Mariani, Alberto A; Inchingolo, Riccardo

2017-01-01

Medical approach to patients is a fundamental step to get the correct diagnosis. The aim of this paper is to analyze some aspects of the reasoning process inherent in medical diagnosis in our era. Pathologic signs (anamnestic data, symptoms, semiotics, laboratory and strumental findings) represent informative phenomena to be integrated for inferring a diagnosis. Thus, diagnosis begins with "signs" and finishes in a probability of disease. The abductive reasoning process is the generation of a hypothesis to explain one or more observations (signs) in order to decide between alternative explanations searching the best one. This process is iterative during the diagnostic activity while collecting further observations and it could be creative generating new knowledge about what has not been experienced before. In the clinical setting the abductive process is not only theoretical, conversely the physical exploitation of the patient (palpation, percussion, auscultation) is always crucial. Through this manipulative abduction, new and still unexpressed information is discovered and evaluated and physicians are able "to think through doing" to get the correct diagnosis. Abductive inferential path originates with an emotional reaction (discovery of the signs), step by step explanations are formed and it ends with another emotional reaction (diagnosis). Few bedside instruments are allowed to physicians to amplify their ability to search for signs. Stethoscope is an example. Similarities between ultrasound exploration and percussion can be found. Bedside ultrasonography can be considered an external amplifier of signs, a particular kind of percussion and represents a valid example of abductive manipulation. In this searching for signs doctors act like detectives and sometimes the discovering of a strategic, unsuspected sign during abductive manipulation could represent the key point for the correct diagnosis. This condition is called serendipity. Ultrasound is a powerful tool for detecting soft, hidden, unexpected and strategic signs.

Geophysical techniques in detection to river embankments - A case study: To locate sites of potential leaks using surface-wave and electrical methods

USGS Publications Warehouse

Chen, C.; Liu, J.; Xu, S.; Xia, J.; ,

2004-01-01

Geophysical technologies are very effective in environmental, engineering and groundwater applications. Parameters of delineating nature of near-surface materials such as compressional-wave velocity, shear-wave velocity can be obtained using shallow seismic methods. Electric methods are primary approaches for investigating groundwater and detecting leakage. Both of methods are applied to detect embankment in hope of obtaining evidences of the strength and moisture inside the body. A technological experiment has done for detecting and discovering the hidden troubles in the embankment of Yangtze River, Songzi, Hubei, China in 2003. Surface-wave and DC multi-channel array resistivity sounding techniques were used to detect hidden trouble inside and under dike like pipe-seeps. This paper discusses the exploration strategy and the effect of geological characteristics. A practical approach of combining seismic and electric resistivity measurements was applied to locate potential pipe-seeps in embankment in the experiment. The method presents a potential leak factor based on the shear-wave velocity and the resistivity of the medium to evaluate anomalies. An anomaly found in a segment of embankment detected was verified, where occurred a pipe-seep during the 98' flooding.

Hidden phase in parent Fe-pnictide superconductors

NASA Astrophysics Data System (ADS)

Ali, Khadiza; Adhikary, Ganesh; Thakur, Sangeeta; Patil, Swapnil; Mahatha, Sanjoy K.; Thamizhavel, A.; De Ninno, Giovanni; Moras, Paolo; Sheverdyaeva, Polina M.; Carbone, Carlo; Petaccia, Luca; Maiti, Kalobaran

2018-02-01

We investigate the origin of exoticity in Fe-based systems via studying the fermiology of CaFe2As2 employing angle-resolved photoemission spectroscopy. While the Fermi surfaces (FSs) at 200 K and 31 K are observed to exhibit two-dimensional and three-dimensional (3D) topology, respectively, the FSs at intermediate temperatures reveal the emergence of the 3D topology at a temperature much lower than the structural and magnetic phase transition temperature (170 K, for the sample under scrutiny). This leads to the conclusion that the evolution of FS topology is not directly driven by the structural transition. In addition, we discover the existence in ambient conditions of energy bands related to the cT phase. These bands are distinctly resolved in the high-photon energy spectra exhibiting strong Fe 3 d character. They gradually move to higher binding energies due to thermal compression with cooling, leading to the emergence of 3D topology in the Fermi surface. These results reveal the so-far hidden existence of a cT phase under ambient conditions, which is argued to lead to quantum fluctuations responsible for the exotic electronic properties in Fe-pnictide superconductors.

Student profiling on university co-curriculum activities using data visualization tools

NASA Astrophysics Data System (ADS)

Jamil, Jastini Mohd.; Shaharanee, Izwan Nizal Mohd

2017-11-01

Co-curricular activities are playing a vital role in the development of a holistic student. Co-curriculum can be described as an extension of the formal learning experiences in a course or academic program. There are many co-curriculum activities such as students' participation in sports, volunteerism, leadership, entrepreneurship, uniform body, student council, and other social events. The number of student involves in co-curriculum activities are large, thus creating an enormous volume of data including their demographic facts, academic performance and co-curriculum types. The task for discovering and analyzing these information becomes increasingly difficult and hard to comprehend. Data visualization offer a better ways in handling with large volume of information. The need for an understanding of these various co-curriculum activities and their effect towards student performance are essential. Visualizing these information can help related stakeholders to become aware of hidden and interesting information from large amount of data drowning in their student data. The main objective of this study is to provide a clearer understanding of the different trends hidden in the student co-curriculum activities data with related to their activities and academic performances. The data visualization software was used to help visualize the data extracted from the database.

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

A quality by design approach using artificial intelligence techniques to control the critical quality attributes of ramipril tablets manufactured by wet granulation.

PubMed

Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Özer, Özgen; Güneri, Tamer; York, Peter

2013-02-01

Quality by design (QbD) is an essential part of the modern approach to pharmaceutical quality. This study was conducted in the framework of a QbD project involving ramipril tablets. Preliminary work included identification of the critical quality attributes (CQAs) and critical process parameters (CPPs) based on the quality target product profiles (QTPPs) using the historical data and risk assessment method failure mode and effect analysis (FMEA). Compendial and in-house specifications were selected as QTPPs for ramipril tablets. CPPs that affected the product and process were used to establish an experimental design. The results thus obtained can be used to facilitate definition of the design space using tools such as design of experiments (DoE), the response surface method (RSM) and artificial neural networks (ANNs). The project was aimed at discovering hidden knowledge associated with the manufacture of ramipril tablets using a range of artificial intelligence-based software, with the intention of establishing a multi-dimensional design space that ensures consistent product quality. At the end of the study, a design space was developed based on the study data and specifications, and a new formulation was optimized. On the basis of this formulation, a new laboratory batch formulation was prepared and tested. It was confirmed that the explored formulation was within the design space.

Missions to Venus

NASA Astrophysics Data System (ADS)

Titov, D. V.; Baines, K. H.; Basilevsky, A. T.; Chassefiere, E.; Chin, G.; Crisp, D.; Esposito, L. W.; Lebreton, J.-P.; Lellouch, E.; Moroz, V. I.; Nagy, A. F.; Owen, T. C.; Oyama, K.-I.; Russell, C. T.; Taylor, F. W.; Young, R. E.

2002-10-01

Venus has always been a fascinating objective for planetary studies. At the beginning of the space era Venus became one of the first targets for spacecraft missions. Our neighbour in the solar system and, in size, the twin sister of Earth, Venus was expected to be very similar to our planet. However, the first phase of Venus spacecraft exploration in 1962-1992 by the family of Soviet Venera and Vega spacecraft and US Mariner, Pioneer Venus, and Magellan missions discovered an entirely different, exotic world hidden behind a curtain of dense clouds. These studies gave us a basic knowledge of the conditions on the planet, but generated many more questions concerning the atmospheric composition, chemistry, structure, dynamics, surface-atmosphere interactions, atmospheric and geological evolution, and the plasma environment. Despite all of this exploration by more than 20 spacecraft, the "morning star" still remains a mysterious world. But for more than a decade Venus has been a "forgotten" planet with no new missions featuring in the plans of the world space agencies. Now we are witnessing the revival of interest in this planet: the Venus Orbiter mission is approved in Japan, Venus Express - a European orbiter mission - has successfully passed the selection procedure in ESA, and several Venus Discovery proposals are knocking at the doors of NASA. The paper presents an exciting story of Venus spacecraft exploration, summarizes open scientific problems, and builds a bridge to the future missions.

Forgotten public health impacts of cancer - an overview.

PubMed

Viegas, Susana; Ladeira, Carina; Costa-Veiga, Ana; Perelman, Julian; Gajski, Goran

2017-12-20

Cancer is one of the diseases of greatest concern in developed countries and much effort has been invested in discovering and developing therapeutics for curing cancer. Despite the improvements in antineoplastic therapeutics in the last decades, cancer is still one of the most harmful diseases worldwide. The global burden of cancer also implies financial costs: these can be direct costs, such as those related to treatment, care, and rehabilitation and indirect, which include the loss of economic output due to missed work (morbidity costs) and premature death (mortality costs). There are also hidden costs such as health insurance premiums and nonmedical expenses that are worth noting. This paper intends to present an overview of the generally forgotten impacts that the increasing number of cancer cases can have on the environment, workers who handle antineoplastic drugs, and health services. The knowledge available of each of the impacts will be addressed and discussed regarding the expected development. Overall, lessons learnt reflect on the impact of cancer through aspects not commonly evidenced in the literature or even considered in socio-economic analysis, in part due to the fact that these are difficult to contemplate in direct and indirect cancer costs already defined. Attention may be drawn to the need of continuous investment in prevention to reduce the negative impact on the environment, and in the health of workers who handle antineoplastic drugs for patients' treatment.

Coaching as Caring (The Smiling Gallery): Accessing Hidden Knowledge

ERIC Educational Resources Information Center

Jones, Robyn L.

2009-01-01

Background: Recent research into coaching has been critical of much previous work, particularly in terms of the tendency to paint a rather unproblematic portrayal of the activity. The criticism has focussed on the erroneous supposition that method can be substituted for individuals, thus giving a synthetic account of a most messy of jobs.…

Values Education and the Board of Education for the City of Hamilton.

ERIC Educational Resources Information Center

Kocmarek, Ivan; Barrs, Steve

1988-01-01

Describes a values education program developed in the city of Hamilton, Ontario. Advocates removing values education from the realm of the hidden curriculum as found in the traditional school model of knowledge of facts, mastery of technical skills, and awareness of attitudes. Emphasizes the importance of continual interaction between school and…

Political Power of New Mexico Public School Superintendents: A Qualitative Exploratory Study

ERIC Educational Resources Information Center

Romero, Arsenio

2013-01-01

The purpose of this study is to identify how superintendents use political power, examine the characteristics used by superintendents to function politically, and to define the hidden knowledge of managing politically charged situations. Based on this informative literature and conducted research, I answered the following research questions: 1.…

Preschool as an Arena for Developing Teacher Knowledge Concerning Children's Language Learning

ERIC Educational Resources Information Center

Sheridan, Sonja; Gjems, Liv

2017-01-01

The most important benefits of international comparisons are the indications that make hidden national characteristics visible and shed new light on the system in each country. From a comparative perspective, this article explores what Swedish and Norwegian preschool teachers emphasise as important to preschool student teachers about preschool as…

What do Two-Year-Olds Understand about Hidden-Object Events?

ERIC Educational Resources Information Center

Mash, Clay; Novak, Elizabeth; Berthier, Neil E.; Keen, Rachel

2006-01-01

Preferential-looking studies suggest that by 2 months of age, infants may have knowledge about some object properties, such as solidity. Manual search studies of toddlers examining these same concepts, however, have failed to provide evidence for the same understanding. Investigators have recently attempted to reconcile this disparity but failed…

False Reality or Hidden Messages: Reading Graphs Obtained in Computerized Biological Experiments

ERIC Educational Resources Information Center

Sorgo, Andrej; Kocijancic, Slavko

2012-01-01

Information and communication technology (ICT) has become an inseparable part of schoolwork and a goal of education to prepare scientifically literate and digitally competent citizens. Yet the introduction of computers into school work has been much slower than its introduction in other spheres of life. Teachers' lack of knowledge/skills and…

The Development of Preschoolers' Appreciation of Communicative Ambiguity

ERIC Educational Resources Information Center

Nilsen, Elizabeth S.; Graham, Susan A.

2012-01-01

Using a longitudinal design, preschoolers' appreciation of a listener's knowledge of the location of a hidden sticker after the listener was provided with an ambiguous or unambiguous description was assessed. Preschoolers (N = 34) were tested at 3 time points, each 6 months apart (4, 4 1/2, and 5 years). Eye gaze measures demonstrated that…

Hidden Treasures for Science Teaching: United States Patents.

ERIC Educational Resources Information Center

Anderson, Norman D.

United States patents are a source of historical information with many implications for science teaching. Using patents as science teaching devices has been largely ignored by science educators. Some of these devices can be easily modified for use in today's classrooms; in addition, patents serve as great examples of how our knowledge of science…

International Content as Hidden Curriculum in Business Statistics: An Overlooked Opportunity

ERIC Educational Resources Information Center

Sebastianelli, Rose; Trussler, Susan

2006-01-01

We revisit the issue of internationalizing the required course in business statistics as a means for introducing international subject matter earlier in the undergraduate business curriculum. A survey of sophomore business students indicates that their level of international knowledge is poor. The results are strikingly similar to a decade ago.…

[A brief history of the anatomy and physiology of a mysterious and hidden gland called the pancreas].

PubMed

Navarro, Salvador

2014-11-01

Because of its retrogastric location and appearance, which is similar to mesenteric fat, for centuries the pancreas has been a mysterious, hidden organ that has received little attention. However, its importance was intuited and described by Herophilus, Ruphos of Ephesus and Galen. This gland began to appearin distinct medical treatises from the 16th century. There are two important scientists in the history of the pancreas. The fist, Johann Georg Wirsung, described the main pancreatic duct in 1642, a date considered by many to be the start of Pancreatology. The second, Claude Bernard, described pancreatic exocrine function between 1849 and 1856 and is considered the father of pancreatic physiology. Besides these two outstanding figures, there is a constellation of personalities who contributed to improving knowledge of this enigmatic gland with the results of their studies. The aim of this article is to call attention to some of the most notable findings that have enhanced knowledge of this gland over the years. Copyright © 2014 Elsevier España, S.L.U. and AEEH y AEG. All rights reserved.

Photoproduction of hidden-charm states in the reaction near threshold

NASA Astrophysics Data System (ADS)

Huang, Yin; Xie, Ju-Jun; He, Jun; Chen, Xurong; Zhang, Hong-Fei

2016-12-01

We report on a theoretical study of the hidden charm states in the reaction near threshold within an effective Lagrangian approach. In addition to the contributions from the s-channel nucleon pole, the t-channel D0 exchange, the u-channel exchange and the contact term, we study the contributions from the states with spin-parity JP = 1/2- and 3/2-. The total and differential cross sections of the reaction are predicted. It is found that the contributions of these states give clear peak structures in the total cross sections. Thus, this reaction is another new platform to study the hidden-charm states. It is expected that our model calculation may be tested by future experiments. Supported by Major State Basic Research Development Program in China (2014CB845400), National Natural Science Foundation of China (11475227, 11275235, 11035006) and Chinese Academy of Sciences (Knowledge Innovation Project (KJCX2-EW-N01), Youth Innovation Promotion Association CAS (2016367), Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China (Y5KF151CJ1)

The "hidden diversity" of medicinal plants in northeastern Brazil: diagnosis and prospects for conservation and biological prospecting.

PubMed

Cavalcanti, Deyvson Rodrigues; Albuquerque, Ulysses Paulino

2013-01-01

Increases in ethnobotanical studies and knowledge in recent decades have led to a greater and more accurate interpretation of the overall patterns related to the use of medicinal plants, allowing for a clear identification of some ecological and cultural phenomena. "Hidden diversity" of medicinal plants refers in the present study to the existence of several species of medicinal plants known by the same vernacular name in a given region. Although this phenomenon has previously been observed in a localized and sporadic manner, its full dimensions have not yet been established. In the present study, we sought to assess the hidden diversity of medicinal plants in northeastern Brazil based on the ethnospecies catalogued by local studies. The results indicate that there are an average of at least 2.78 different species per cataloged ethnospecies in the region. Phylogenetic proximity and its attendant morphological similarity favor the interchangeable use of these species, resulting in serious ecological and sanitary implications as well as a wide range of options for conservation and bioprospecting.

The “Hidden Diversity” of Medicinal Plants in Northeastern Brazil: Diagnosis and Prospects for Conservation and Biological Prospecting

PubMed Central

Cavalcanti, Deyvson Rodrigues; Albuquerque, Ulysses Paulino

2013-01-01

Increases in ethnobotanical studies and knowledge in recent decades have led to a greater and more accurate interpretation of the overall patterns related to the use of medicinal plants, allowing for a clear identification of some ecological and cultural phenomena. “Hidden diversity” of medicinal plants refers in the present study to the existence of several species of medicinal plants known by the same vernacular name in a given region. Although this phenomenon has previously been observed in a localized and sporadic manner, its full dimensions have not yet been established. In the present study, we sought to assess the hidden diversity of medicinal plants in northeastern Brazil based on the ethnospecies catalogued by local studies. The results indicate that there are an average of at least 2.78 different species per cataloged ethnospecies in the region. Phylogenetic proximity and its attendant morphological similarity favor the interchangeable use of these species, resulting in serious ecological and sanitary implications as well as a wide range of options for conservation and bioprospecting. PMID:24228056

A method for exploring implicit concept relatedness in biomedical knowledge network.

PubMed

Bai, Tian; Gong, Leiguang; Wang, Ye; Wang, Yan; Kulikowski, Casimir A; Huang, Lan

2016-07-19

Biomedical information and knowledge, structural and non-structural, stored in different repositories can be semantically connected to form a hybrid knowledge network. How to compute relatedness between concepts and discover valuable but implicit information or knowledge from it effectively and efficiently is of paramount importance for precision medicine, and a major challenge facing the biomedical research community. In this study, a hybrid biomedical knowledge network is constructed by linking concepts across multiple biomedical ontologies as well as non-structural biomedical knowledge sources. To discover implicit relatedness between concepts in ontologies for which potentially valuable relationships (implicit knowledge) may exist, we developed a Multi-Ontology Relatedness Model (MORM) within the knowledge network, for which a relatedness network (RN) is defined and computed across multiple ontologies using a formal inference mechanism of set-theoretic operations. Semantic constraints are designed and implemented to prune the search space of the relatedness network. Experiments to test examples of several biomedical applications have been carried out, and the evaluation of the results showed an encouraging potential of the proposed approach to biomedical knowledge discovery.

Uncovering the wisdom hidden between the lines: the Collaborative Reflexive Deliberative Approach

PubMed Central

Crabtree, Benjamin F; Miller, William L; Gunn, Jane M; Hogg, William E; Scott, Cathie M; Levesque, Jean-Frederic; Harris, Mark F; Chase, Sabrina M; Advocat, Jenny R; Halma, Lisa M; Russell, Grant M

2018-01-01

Abstract Background Meta-analysis and meta-synthesis have been developed to synthesize results across published studies; however, they are still largely grounded in what is already published, missing the tacit ‘between the lines’ knowledge generated during many research projects that are not intrinsic to the main objectives of studies. Objective To develop a novel approach to expand and deepen meta-syntheses using researchers’ experience, tacit knowledge and relevant unpublished materials. Methods We established new collaborations among primary health care researchers from different contexts based on common interests in reforming primary care service delivery and a diversity of perspectives. Over 2 years, the team met face-to-face and via tele- and video-conferences to employ the Collaborative Reflexive Deliberative Approach (CRDA) to discuss and reflect on published and unpublished results from participants’ studies to identify new patterns and insights. Results CRDA focuses on uncovering critical insights, interpretations hidden within multiple research contexts. For the process to work, careful attention must be paid to ensure sufficient diversity among participants while also having people who are able to collaborate effectively. Ensuring there are enough studies for contextual variation also matters. It is necessary to balance rigorous facilitation techniques with the creation of safe space for diverse contributions. Conclusions The CRDA requires large commitments of investigator time, the expense of convening facilitated retreats, considerable coordination, and strong leadership. The process creates an environment where interactions among diverse participants can illuminate hidden information within the contexts of studies, effectively enhancing theory development and generating new research questions and strategies. PMID:29069335

Sleep facilitates learning a new linguistic rule

PubMed Central

Batterink, Laura J.; Oudiette, Delphine; Reber, Paul J.; Paller, Ken A.

2014-01-01

Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input. PMID:25447376

Religion, Spirituality, and the Hidden Curriculum: Medical Student and Faculty Reflections.

PubMed

Balboni, Michael J; Bandini, Julia; Mitchell, Christine; Epstein-Peterson, Zachary D; Amobi, Ada; Cahill, Jonathan; Enzinger, Andrea C; Peteet, John; Balboni, Tracy

2015-10-01

Religion and spirituality play an important role in physicians' medical practice, but little research has examined their influence within the socialization of medical trainees and the hidden curriculum. The objective is to explore the role of religion and spirituality as they intersect with aspects of medicine's hidden curriculum. Semiscripted, one-on-one interviews and focus groups (n = 33 respondents) were conducted to assess Harvard Medical School student and faculty experiences of religion/spirituality and the professionalization process during medical training. Using grounded theory, theme extraction was performed with interdisciplinary input (medicine, sociology, and theology), yielding a high inter-rater reliability score (kappa = 0.75). Three domains emerged where religion and spirituality appear as a factor in medical training. First, religion/spirituality may present unique challenges and benefits in relation to the hidden curriculum. Religious/spiritual respondents more often reported to struggle with issues of personal identity, increased self-doubt, and perceived medical knowledge inadequacy. However, religious/spiritual participants less often described relationship conflicts within the medical team, work-life imbalance, and emotional stress arising from patient suffering. Second, religion/spirituality may influence coping strategies during encounters with patient suffering. Religious/spiritual trainees described using prayer, faith, and compassion as means for coping whereas nonreligious/nonspiritual trainees discussed compartmentalization and emotional repression. Third, levels of religion/spirituality appear to fluctuate in relation to medical training, with many trainees experiencing an increase in religiousness/spirituality during training. Religion/spirituality has a largely unstudied but possibly influential role in medical student socialization. Future study is needed to characterize its function within the hidden curriculum. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Religion, Spirituality, and the Hidden Curriculum: Medical Student and Faculty Reflections

PubMed Central

Balboni, Michael J.; Bandini, Julia; Mitchell, Christine; Epstein-Peterson, Zachary D.; Amobi, Ada; Cahill, Jonathan; Enzinger, Andrea C.; Peteet, John; Balboni, Tracy

2017-01-01

Context Religion and spirituality play an important role in physicians’ medical practice, but little research has examined their influence within the socialization of medical trainees and the hidden curriculum. Objectives The objective is to explore the role of religion and spirituality as they intersect with aspects of medicine’s hidden curriculum. Methods Semiscripted, one-on-one interviews and focus groups (n = 33 respondents) were conducted to assess Harvard Medical School student and faculty experiences of religion/spirituality and the professionalization process during medical training. Using grounded theory, theme extraction was performed with interdisciplinary input (medicine, sociology, and theology), yielding a high inter-rater reliability score (kappa = 0.75). Results Three domains emerged where religion and spirituality appear as a factor in medical training. First, religion/spirituality may present unique challenges and benefits in relation to the hidden curriculum. Religious/spiritual respondents more often reported to struggle with issues of personal identity, increased self-doubt, and perceived medical knowledge inadequacy. However, religious/spiritual participants less often described relationship conflicts within the medical team, work-life imbalance, and emotional stress arising from patient suffering. Second, religion/spirituality may influence coping strategies during encounters with patient suffering. Religious/spiritual trainees described using prayer, faith, and compassion as means for coping whereas nonreligious/nonspiritual trainees discussed compartmentalization and emotional repression. Third, levels of religion/spirituality appear to fluctuate in relation to medical training, with many trainees experiencing an increase in religiousness/spirituality during training. Conclusion Religion/spirituality has a largely unstudied but possibly influential role in medical student socialization. Future study is needed to characterize its function within the hidden curriculum. PMID:26025271

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

Knowledge.

PubMed

Jost, Jürgen

2017-06-01

We investigate the basic principles of structural knowledge. Structural knowledge underlies cognition, and it organizes, selects and assigns meaning to information. It is the result of evolutionary, cultural and developmental processes. Because of its own constraints, it needs to discover and exploit regularities and thereby achieve a complexity reduction.

Topic Model for Graph Mining.

PubMed

Xuan, Junyu; Lu, Jie; Zhang, Guangquan; Luo, Xiangfeng

2015-12-01

Graph mining has been a popular research area because of its numerous application scenarios. Many unstructured and structured data can be represented as graphs, such as, documents, chemical molecular structures, and images. However, an issue in relation to current research on graphs is that they cannot adequately discover the topics hidden in graph-structured data which can be beneficial for both the unsupervised learning and supervised learning of the graphs. Although topic models have proved to be very successful in discovering latent topics, the standard topic models cannot be directly applied to graph-structured data due to the "bag-of-word" assumption. In this paper, an innovative graph topic model (GTM) is proposed to address this issue, which uses Bernoulli distributions to model the edges between nodes in a graph. It can, therefore, make the edges in a graph contribute to latent topic discovery and further improve the accuracy of the supervised and unsupervised learning of graphs. The experimental results on two different types of graph datasets show that the proposed GTM outperforms the latent Dirichlet allocation on classification by using the unveiled topics of these two models to represent graphs.

Cocaine addiction: the hidden dimension.

PubMed

Oswald, L M

1989-06-01

There is growing awareness within the nursing profession that nurses need to expand their knowledge about addiction and develop expertise in providing care for substance abusing clients. This report presents a discussion about cocaine abuse that is focused on evolving knowledge about the physiology of addiction. Researchers have recently described cocaine-induced neurochemical changes in the brain that may form the underpinnings for the behavioral manifestations and symptomatology that have been associated with cocaine addiction. These neurochemical alterations are described at the cellular level, and treatment implications for nurses are presented.

Reflection on Theory: Whose Knowledge, and the Hidden Curriculum

ERIC Educational Resources Information Center

Hartlep, Nicholas D.

2009-01-01

This opinion paper intends to elucidate the author's theoretical framework towards education and the goals of curriculum. The author utilizes various scholars' work to help form a silhouette of his beliefs and of what he feels a P-12 school curriculum should provide to students, as well as to outline how his theoretical disposition has shaped his…

A Gay Immigrant Student's Perspective: Unspeakable Acts in the Language Class

ERIC Educational Resources Information Center

Nelson, Cynthia D.

2010-01-01

This article focuses on a subset of the student cohort that has, until recently, been largely hidden from view in the literature of language education: gay immigrants. Little is known about what sorts of classroom experiences gay immigrant students find engaging or alienating, or why this sort of knowledge is needed. This case study uses interview…

Hidden Dangers of Computer Modelling: Remarks on Sokolik and Smith's Connectionist Learning Model of French Gender.

ERIC Educational Resources Information Center

Carroll, Susanne E.

1995-01-01

Criticizes the computer modelling experiments conducted by Sokolik and Smith (1992), which involved the learning of French gender attribution using connectionist architecture. The article argues that the experiments greatly oversimplified the complexity of gender learning, in that they were designed in such a way that knowledge that must be…

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…

Accounting for Slipping and Other False Negatives in Logistic Models of Student Learning

ERIC Educational Resources Information Center

MacLellan, Christopher J.; Liu, Ran; Koedinger, Kenneth R.

2015-01-01

Additive Factors Model (AFM) and Performance Factors Analysis (PFA) are two popular models of student learning that employ logistic regression to estimate parameters and predict performance. This is in contrast to Bayesian Knowledge Tracing (BKT) which uses a Hidden Markov Model formalism. While all three models tend to make similar predictions,…

Effect of Frequency and Idiomaticity on Second Language Reading Comprehension

ERIC Educational Resources Information Center

Martinez, Ron; Murphy, Victoria A.

2011-01-01

A number of studies claim that knowledge of 5,000-8,000 of the most frequent words should provide at least 95% coverage of most unsimplified texts in English, arguably enough to guess or ignore most unknown words while reading (Hirsh & Nation, 1992; Hu & Nation, 2000; Laufer, 1991; Nation, 2006). However, perhaps hidden in that 95% figure…

Generalization in Place Learning and Geometry Knowledge in Rats

ERIC Educational Resources Information Center

Tommasi, Luca; Thinus-Blanc, Catherine

2004-01-01

Rats were trained to search for a food reward hidden under sawdust in the center of a square-shaped enclosure designed to force orientation on the basis of the overall geometry of the environment. They were then tested in a number of enclosures differing in shape and in size (rectangular-, double-side square-, and equilateral triangle-shaped…

The Impact of Hidden Grades on Student Decision-Making and Academic Performance: An Examination of a Policy Change at MIT

ERIC Educational Resources Information Center

Harris, Gregory A.

2010-01-01

Colleges and universities work hard to create environments that encourage student learning, and they develop grading policies, in part, to motivate their students to perform well. Grades provide two kinds of information about a student's abilities and learned knowledge: "internal" information that informs the students themselves about…

Featured Article: Genotation: Actionable knowledge for the scientific reader

PubMed Central

Willis, Ethan; Sakauye, Mark; Jose, Rony; Chen, Hao; Davis, Robert L

2016-01-01

We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org. The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug–gene relationships, 5981 gene–disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge. PMID:26900164

Featured Article: Genotation: Actionable knowledge for the scientific reader.

PubMed

Nagahawatte, Panduka; Willis, Ethan; Sakauye, Mark; Jose, Rony; Chen, Hao; Davis, Robert L

2016-06-01

We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug-gene relationships, 5981 gene-disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge. © 2016 by the Society for Experimental Biology and Medicine.

A planetary nervous system for social mining and collective awareness

NASA Astrophysics Data System (ADS)

Giannotti, F.; Pedreschi, D.; Pentland, A.; Lukowicz, P.; Kossmann, D.; Crowley, J.; Helbing, D.

2012-11-01

We present a research roadmap of a Planetary Nervous System (PNS), capable of sensing and mining the digital breadcrumbs of human activities and unveiling the knowledge hidden in the big data for addressing the big questions about social complexity. We envision the PNS as a globally distributed, self-organizing, techno-social system for answering analytical questions about the status of world-wide society, based on three pillars: social sensing, social mining and the idea of trust networks and privacy-aware social mining. We discuss the ingredients of a science and a technology necessary to build the PNS upon the three mentioned pillars, beyond the limitations of their respective state-of-art. Social sensing is aimed at developing better methods for harvesting the big data from the techno-social ecosystem and make them available for mining, learning and analysis at a properly high abstraction level. Social mining is the problem of discovering patterns and models of human behaviour from the sensed data across the various social dimensions by data mining, machine learning and social network analysis. Trusted networks and privacy-aware social mining is aimed at creating a new deal around the questions of privacy and data ownership empowering individual persons with full awareness and control on own personal data, so that users may allow access and use of their data for their own good and the common good. The PNS will provide a goal-oriented knowledge discovery framework, made of technology and people, able to configure itself to the aim of answering questions about the pulse of global society. Given an analytical request, the PNS activates a process composed by a variety of interconnected tasks exploiting the social sensing and mining methods within the transparent ecosystem provided by the trusted network. The PNS we foresee is the key tool for individual and collective awareness for the knowledge society. We need such a tool for everyone to become fully aware of how powerful is the knowledge of our society we can achieve by leveraging our wisdom as a crowd, and how important is that everybody participates both as a consumer and as a producer of the social knowledge, for it to become a trustable, accessible, safe and useful public good.

Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

NASA Astrophysics Data System (ADS)

Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

2010-11-01

The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

The Knowledge Bluff

ERIC Educational Resources Information Center

Vanderburg, Willem H.

2007-01-01

Our knowledge "system" is built up from disciplines and specialties as its components, which are "wired" by patterns of collaboration that constitute its organization. The intellectual autonomy of these components prevents this knowledge system from adequately accounting for what we have gradually discovered during the past 50 years: In human…

The De-Genderization of Knowledge Production: The Case of Sor Juana Ines de la Cruz.

ERIC Educational Resources Information Center

Salazar, Norma

1994-01-01

All societies have official knowledge. Life of Sor Juana Ines de la Cruz, 17th-century nun and literary genius, illustrates who discovers knowledge is more important than what knowledge is promulgated. Real issue was not what Sor Juana wrote but whether nun or woman should engage in producing and publishing knowledge. Her efforts have inspired…

Knowledge discovery from structured mammography reports using inductive logic programming.

PubMed

Burnside, Elizabeth S; Davis, Jesse; Costa, Victor Santos; Dutra, Inês de Castro; Kahn, Charles E; Fine, Jason; Page, David

2005-01-01

The development of large mammography databases provides an opportunity for knowledge discovery and data mining techniques to recognize patterns not previously appreciated. Using a database from a breast imaging practice containing patient risk factors, imaging findings, and biopsy results, we tested whether inductive logic programming (ILP) could discover interesting hypotheses that could subsequently be tested and validated. The ILP algorithm discovered two hypotheses from the data that were 1) judged as interesting by a subspecialty trained mammographer and 2) validated by analysis of the data itself.

STRUCTURAL AND HIDDEN BARRIERS TO A LOCAL PRIMARY HEALTH CARE INFRASTRUCTURE: AUTONOMY, DECISIONS ABOUT PRIMARY HEALTH CARE, AND THE CENTRALITY AND SIGNIFICANCE OF POWER.

PubMed

Freed, Christopher R; Hansberry, Shantisha T; Arrieta, Martha I

2013-09-01

To examine a local primary health care infrastructure and the reality of primary health care from the perspective of residents of a small, urban community in the southern United States. Data derive from 13 semi-structured focus groups, plus three semi-structured interviews, and were analyzed inductively consistent with a grounded theory approach. Structural barriers to the local primary health care infrastructure include transportation, clinic and appointment wait time, and co-payments and health insurance. Hidden barriers consist of knowledge about local health care services, non-physician gatekeepers, and fear of medical care. Community residents have used home remedies and the emergency department at the local academic medical center to manage these structural and hidden barriers. Findings might not generalize to primary health care infrastructures in other communities, respondent perspectives can be biased, and the data are subject to various interpretations and conceptual and thematic frameworks. Nevertheless, the structural and hidden barriers to the local primary health care infrastructure have considerably diminished the autonomy community residents have been able to exercise over their decisions about primary health care, ultimately suggesting that efforts concerned with increasing the access of medically underserved groups to primary health care in local communities should recognize the centrality and significance of power. This study addresses a gap in the sociological literature regarding the impact of specific barriers to primary health care among medically underserved groups.

Learning a single-hidden layer feedforward neural network using a rank correlation-based strategy with application to high dimensional gene expression and proteomic spectra datasets in cancer detection.

PubMed

Belciug, Smaranda; Gorunescu, Florin

2018-06-08

Methods based on microarrays (MA), mass spectrometry (MS), and machine learning (ML) algorithms have evolved rapidly in recent years, allowing for early detection of several types of cancer. A pitfall of these approaches, however, is the overfitting of data due to large number of attributes and small number of instances -- a phenomenon known as the 'curse of dimensionality'. A potentially fruitful idea to avoid this drawback is to develop algorithms that combine fast computation with a filtering module for the attributes. The goal of this paper is to propose a statistical strategy to initiate the hidden nodes of a single-hidden layer feedforward neural network (SLFN) by using both the knowledge embedded in data and a filtering mechanism for attribute relevance. In order to attest its feasibility, the proposed model has been tested on five publicly available high-dimensional datasets: breast, lung, colon, and ovarian cancer regarding gene expression and proteomic spectra provided by cDNA arrays, DNA microarray, and MS. The novel algorithm, called adaptive SLFN (aSLFN), has been compared with four major classification algorithms: traditional ELM, radial basis function network (RBF), single-hidden layer feedforward neural network trained by backpropagation algorithm (BP-SLFN), and support vector-machine (SVM). Experimental results showed that the classification performance of aSLFN is competitive with the comparison models. Copyright © 2018. Published by Elsevier Inc.

Biological engineering applications of feedforward neural networks designed and parameterized by genetic algorithms.

PubMed

Ferentinos, Konstantinos P

2005-09-01

Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.

The Front and Back Stages of Swedish School Inspection: Opening the Black Box of Judgment

ERIC Educational Resources Information Center

Lindgren, Joakim

2015-01-01

This article provides results from a study of the hidden processes of consensus formation that precede and make possible official judgments and decisions of the Swedish Schools Inspectorate (SI). The research question for the study was: How is knowledge negotiated on the back stage of school inspection and presented on the front stage? The article…

Surfacing a Hidden Literature: A Systematic Review of Research on Educational Leadership and Management in Africa

ERIC Educational Resources Information Center

Hallinger, Philip

2018-01-01

Scholars throughout the world are working to diversify the knowledge base in educational leadership and management (EDLM). In concert with this effort, this article reports the results of a systematic review of research on EDLM in Africa. The goals of the review were to describe trends with respect to the volume of journal publications, national…

From Candy Girls to Cyber Sista-Cipher: Narrating Black Females' Color-Consciousness and Counterstories in "and" out "of School"

ERIC Educational Resources Information Center

Kynard, Carmen

2010-01-01

In this article, Carmen Kynard provides a window into a present-day "hush harbor," a site where a group of black women build generative virtual spaces for counterstories that fight institutional racism. Hidden in plain view, these intentional communities have historically allowed African American participants to share and create knowledge and find…

Substance Abuse: A Hidden Problem within the D/deaf and Hard of Hearing Communities

ERIC Educational Resources Information Center

Guthmann, Debra; Graham, Vicki

2004-01-01

Current research indicates that D/deaf and hard of hearing clients seeking treatment for substance abuse often encounter obstacles in receiving the help they need. Many of these obstacles are the result of a lack of knowledge and experience with regard to treating D/deaf and hard of hearing people. Programs designed for hearing people that attempt…

The Impact of Hidden Grades on Student Decision-Making and Academic Performance: An Examination of a Policy Change at MIT

ERIC Educational Resources Information Center

Harris, Gregory A.

2011-01-01

Colleges and universities work hard to create environments that encourage student learning, and they develop grading policies, in part, to motivate their students to perform well. Grades provide two kinds of information about a student's abilities and learned knowledge: "internal" information that informs the students themselves about the…

Preliminary clinical nursing leadership competency model: a qualitative study from Thailand.

PubMed

Supamanee, Treeyaphan; Krairiksh, Marisa; Singhakhumfu, Laddawan; Turale, Sue

2011-12-01

This qualitative study explored the clinical nursing leadership competency perspectives of Thai nurses working in a university hospital. To collect data, in-depth interviews were undertaken with 23 nurse administrators, and focus groups were used with 31 registered nurses. Data were analyzed using content analysis, and theory development was guided by the Iceberg model. Nurses' clinical leadership competencies emerged, comprising hidden characteristics and surface characteristics. The hidden characteristics composed three elements: motive (respect from the nursing and healthcare team and being secure in life), self-concept (representing positive attitudes and values), and traits (personal qualities necessary for leadership). The surface characteristics comprised specific knowledge of nurse leaders about clinical leadership, management and nursing informatics, and clinical skills, such as coordination, effective communication, problem solving, and clinical decision-making. The study findings help nursing to gain greater knowledge of the essence of clinical nursing leadership competencies, a matter critical for theory development in leadership. This study's results later led to the instigation of a training program for registered nurse leaders at the study site, and the formation of a preliminary clinical nursing leadership competency model. © 2011 Blackwell Publishing Asia Pty Ltd.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Dissociable influences of opiates and expectations on pain

PubMed Central

Atlas, Lauren Y.; Whittington, Robert A.; Lindquist, Martin A.; Wielgosz, Joe; Sonty, Nomita; Wager, Tor D.

2012-01-01

Placebo treatments and opiate drugs are thought to have common effects on the opioid system and pain-related brain processes. This has created excitement about the potential for expectations to modulate drug effects themselves. If drug effects differ as a function of belief, this would challenge the assumptions underlying the standard clinical trial. We conducted two studies to directly examine the relationship between expectations and opioid analgesia. We administered the opioid agonist remifentanil to human subjects during experimental thermal pain and manipulated participants’ knowledge of drug delivery using an open-hidden design. This allowed us to test drug effects, expectancy (knowledge) effects, and their interactions on pain reports and pain-related responses in the brain. Remifentanil and expectancy both reduced pain, but drug effects on pain reports and fMRI activity did not interact with expectancy. Regions associated with pain processing showed drug-induced modulation during both Open and Hidden conditions, with no differences in drug effects as a function of expectation. Instead, expectancy modulated activity in frontal cortex, with a separable time course from drug effects. These findings reveal that opiates and placebo treatments both influence clinically relevant outcomes and operate without mutual interference. PMID:22674280

JournalMap: Discovering location-relevant knowledge from published studies for sustainable land use, preventing degradation, and restoring landscapes

USDA-ARS?s Scientific Manuscript database

Finding relevant knowledge and information to prevent land degradation and support restoration has historically involved researchers working from their own knowledge, querying people they know, and tediously searching topical literature reviews.To address this need we created JournalMap (http://www....

Improving Collaborative Learning by Supporting Casual Encounters in Distance Learning.

ERIC Educational Resources Information Center

Contreras, Juan; Llamas, Rafael; Vizcaino, Aurora; Vavela, Jesus

Casual encounters in a learning environment are very useful in reinforcing previous knowledge and acquiring new knowledge. Such encounters are very common in traditional learning environments and can be used successfully in social environments in which students can discover and construct knowledge through a process of dialogue, negotiation, or…

Authentic, Dialogical Knowledge Construction: A Blended and Mobile Teacher Education Programme

ERIC Educational Resources Information Center

Ruhalahti, Sanna; Korhonen, Anne-Maria; Rasi, Päivi

2017-01-01

Background: Knowledge construction and technology have been identified as critical for an understanding of the future of teacher education. Knowledge is discovered, applied and created collaboratively from authentic starting points. Today's new mobile and blended learning environments create increased opportunities for such processes, including…

Sleep facilitates learning a new linguistic rule.

PubMed

Batterink, Laura J; Oudiette, Delphine; Reber, Paul J; Paller, Ken A

2014-12-01

Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input. Copyright © 2014 Elsevier Ltd. All rights reserved.

Agent based simulation on the process of human flesh search-From perspective of knowledge and emotion

NASA Astrophysics Data System (ADS)

Zhu, Hou; Hu, Bin

2017-03-01

Human flesh search as a new net crowed behavior, on the one hand can help us to find some special information, on the other hand may lead to privacy leaking and offending human right. In order to study the mechanism of human flesh search, this paper proposes a simulation model based on agent-based model and complex networks. The computational experiments show some useful results. Discovered information quantity and involved personal ratio are highly correlated, and most of net citizens will take part in the human flesh search or will not take part in the human flesh search. Knowledge quantity does not influence involved personal ratio, but influences whether HFS can find out the target human. When the knowledge concentrates on hub nodes, the discovered information quantity is either perfect or almost zero. Emotion of net citizens influences both discovered information quantity and involved personal ratio. Concretely, when net citizens are calm to face the search topic, it will be hardly to find out the target; But when net citizens are agitated, the target will be found out easily.

Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

NASA Astrophysics Data System (ADS)

Khoshahval, S.; Farnaghi, M.; Taleai, M.

2017-09-01

Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

A facility to search for hidden particles at the CERN SPS: the SHiP physics case.

PubMed

Alekhin, Sergey; Altmannshofer, Wolfgang; Asaka, Takehiko; Batell, Brian; Bezrukov, Fedor; Bondarenko, Kyrylo; Boyarsky, Alexey; Choi, Ki-Young; Corral, Cristóbal; Craig, Nathaniel; Curtin, David; Davidson, Sacha; de Gouvêa, André; Dell'Oro, Stefano; deNiverville, Patrick; Bhupal Dev, P S; Dreiner, Herbi; Drewes, Marco; Eijima, Shintaro; Essig, Rouven; Fradette, Anthony; Garbrecht, Björn; Gavela, Belen; Giudice, Gian F; Goodsell, Mark D; Gorbunov, Dmitry; Gori, Stefania; Grojean, Christophe; Guffanti, Alberto; Hambye, Thomas; Hansen, Steen H; Helo, Juan Carlos; Hernandez, Pilar; Ibarra, Alejandro; Ivashko, Artem; Izaguirre, Eder; Jaeckel, Joerg; Jeong, Yu Seon; Kahlhoefer, Felix; Kahn, Yonatan; Katz, Andrey; Kim, Choong Sun; Kovalenko, Sergey; Krnjaic, Gordan; Lyubovitskij, Valery E; Marcocci, Simone; Mccullough, Matthew; McKeen, David; Mitselmakher, Guenakh; Moch, Sven-Olaf; Mohapatra, Rabindra N; Morrissey, David E; Ovchynnikov, Maksym; Paschos, Emmanuel; Pilaftsis, Apostolos; Pospelov, Maxim; Reno, Mary Hall; Ringwald, Andreas; Ritz, Adam; Roszkowski, Leszek; Rubakov, Valery; Ruchayskiy, Oleg; Schienbein, Ingo; Schmeier, Daniel; Schmidt-Hoberg, Kai; Schwaller, Pedro; Senjanovic, Goran; Seto, Osamu; Shaposhnikov, Mikhail; Shchutska, Lesya; Shelton, Jessie; Shrock, Robert; Shuve, Brian; Spannowsky, Michael; Spray, Andy; Staub, Florian; Stolarski, Daniel; Strassler, Matt; Tello, Vladimir; Tramontano, Francesco; Tripathi, Anurag; Tulin, Sean; Vissani, Francesco; Winkler, Martin W; Zurek, Kathryn M

2016-12-01

This paper describes the physics case for a new fixed target facility at CERN SPS. The SHiP (search for hidden particles) experiment is intended to hunt for new physics in the largely unexplored domain of very weakly interacting particles with masses below the Fermi scale, inaccessible to the LHC experiments, and to study tau neutrino physics. The same proton beam setup can be used later to look for decays of tau-leptons with lepton flavour number non-conservation, [Formula: see text] and to search for weakly-interacting sub-GeV dark matter candidates. We discuss the evidence for physics beyond the standard model and describe interactions between new particles and four different portals-scalars, vectors, fermions or axion-like particles. We discuss motivations for different models, manifesting themselves via these interactions, and how they can be probed with the SHiP experiment and present several case studies. The prospects to search for relatively light SUSY and composite particles at SHiP are also discussed. We demonstrate that the SHiP experiment has a unique potential to discover new physics and can directly probe a number of solutions of beyond the standard model puzzles, such as neutrino masses, baryon asymmetry of the Universe, dark matter, and inflation.

Anaphylaxis after eating Italian pizza containing buckwheat as the hidden food allergen.

PubMed

Heffler, E; Guida, G; Badiu, I; Nebiolo, F; Rolla, G

2007-01-01

A 20-year-old woman developed anaphylaxis after eating pizza on 4 different occasions in 2 restaurants. Both restaurants made their pizza dough with a mixture of wheat and buckwheat flours. A prick-to-prick test with buckwheat flour was positive. Skin prick tests and specific immunoglobulin E responses to soybean and peanut were weakly positive while the response to buckwheat was negative. We ruled out a pathogenic role for peanut and soybean because the patient usually eats both with no signs of allergic reaction. Double-blind, placebo-controlled food challenges with buckwheat flour were positive after the administration of a cumulative dose of 2.3 g of the culprit flour. To our knowledge, our report describes the first case of anaphylaxis after intake of buckwheat flour as the hidden allergen in pizza dough.

Discovering functional modules by topic modeling RNA-Seq based toxicogenomic data.

PubMed

Yu, Ke; Gong, Binsheng; Lee, Mikyung; Liu, Zhichao; Xu, Joshua; Perkins, Roger; Tong, Weida

2014-09-15

Toxicogenomics (TGx) endeavors to elucidate the underlying molecular mechanisms through exploring gene expression profiles in response to toxic substances. Recently, RNA-Seq is increasingly regarded as a more powerful alternative to microarrays in TGx studies. However, realizing RNA-Seq's full potential requires novel approaches to extracting information from the complex TGx data. Considering read counts as the number of times a word occurs in a document, gene expression profiles from RNA-Seq are analogous to a word by document matrix used in text mining. Topic modeling aiming at to discover the latent structures in text corpora would be helpful to explore RNA-Seq based TGx data. In this study, topic modeling was applied on a typical RNA-Seq based TGx data set to discover hidden functional modules. The RNA-Seq based gene expression profiles were transformed into "documents", on which latent Dirichlet allocation (LDA) was used to build a topic model. We found samples treated by the compounds with the same modes of actions (MoAs) could be clustered based on topic similarities. The topic most relevant to each cluster was identified as a "marker" topic, which was interpreted by gene enrichment analysis with MoAs then confirmed by compound and pathways associations mined from literature. To further validate the "marker" topics, we tested topic transferability from RNA-Seq to microarrays. The RNA-Seq based gene expression profile of a topic specifically associated with peroxisome proliferator-activated receptors (PPAR) signaling pathway was used to query samples with similar expression profiles in two different microarray data sets, yielding accuracy of about 85%. This proof-of-concept study demonstrates the applicability of topic modeling to discover functional modules in RNA-Seq data and suggests a valuable computational tool for leveraging information within TGx data in RNA-Seq era.

Asymmetric threat data mining and knowledge discovery

NASA Astrophysics Data System (ADS)

Gilmore, John F.; Pagels, Michael A.; Palk, Justin

2001-03-01

Asymmetric threats differ from the conventional force-on- force military encounters that the Defense Department has historically been trained to engage. Terrorism by its nature is now an operational activity that is neither easily detected or countered as its very existence depends on small covert attacks exploiting the element of surprise. But terrorism does have defined forms, motivations, tactics and organizational structure. Exploiting a terrorism taxonomy provides the opportunity to discover and assess knowledge of terrorist operations. This paper describes the Asymmetric Threat Terrorist Assessment, Countering, and Knowledge (ATTACK) system. ATTACK has been developed to (a) data mine open source intelligence (OSINT) information from web-based newspaper sources, video news web casts, and actual terrorist web sites, (b) evaluate this information against a terrorism taxonomy, (c) exploit country/region specific social, economic, political, and religious knowledge, and (d) discover and predict potential terrorist activities and association links. Details of the asymmetric threat structure and the ATTACK system architecture are presented with results of an actual terrorist data mining and knowledge discovery test case shown.

Discovering, Supporting, and Promoting Young Children's Passions and Interests: One Teacher's Reflections.

ERIC Educational Resources Information Center

Ferguson, Christine

2001-01-01

Describes the journey of one kindergarten teacher as she discovered, supported, and promoted the passions and interests of an at-risk kindergarten student, and shared in his joys of learning. Details an inquiry project about snakes, initiated by the student's knowledge about snakes, involving field trips, class discussion, learning centers, and…

A Novel Method for Discovering Fuzzy Sequential Patterns Using the Simple Fuzzy Partition Method.

ERIC Educational Resources Information Center

Chen, Ruey-Shun; Hu, Yi-Chung

2003-01-01

Discusses sequential patterns, data mining, knowledge acquisition, and fuzzy sequential patterns described by natural language. Proposes a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method which allows the linguistic interpretation of each fuzzy set to be easily obtained. (Author/LRW)

One Crystal, Two Temperatures: Cryocooling Penalties Alter Ligand Binding to Transient Protein Sites

DOE PAGES

Fischer, Marcus; Shoichet, Brian K.; Fraser, James S.

2015-05-28

Interrogating fragment libraries by X-ray crystallography is a powerful strategy for discovering allosteric ligands for protein targets. Cryocooling of crystals should theoretically increase the fraction of occupied binding sites and decrease radiation damage. However, it might also perturb protein conformations that can be accessed at room temperature. Using data from crystals measured consecutively at room temperature and at cryogenic temperature, we found that transient binding sites could be abolished at the cryogenic temperatures employed by standard approaches. Finally, changing the temperature at which the crystallographic data was collected could provide a deliberate perturbation to the equilibrium of protein conformations andmore » help to visualize hidden sites with great potential to allosterically modulate protein function.« less

Blood libel rebooted: traditional scapegoats, online media, and the H1N1 epidemic.

PubMed

Atlani-Duault, L; Mercier, A; Rousseau, C; Guyot, P; Moatti, J P

2015-03-01

This study of comments posted on major French print and TV media websites during the H1N1 epidemic illustrates the relationship between the traditional media and social media in responding to an emerging disease. A disturbing "geography of blame" was observed suggesting the metamorphosis of the folk-devil phenomenon to the Internet. We discovered a subterranean discourse about the putative origins and "objectives" of the H1N1 virus, which was absent from the discussions in mainstream television channels and large-circulation print media. These online rumours attributed hidden motives to governments, pharmaceutical companies, and figures of Otherness that were scapegoated in the social history of previous European epidemics, notably Freemasons and Jews.

Beyond the Fermi liquid paradigm: Hidden Fermi liquids

PubMed Central

Jain, J. K.; Anderson, P. W.

2009-01-01

An intense investigation of possible non-Fermi liquid states of matter has been inspired by two of the most intriguing phenomena discovered in the past quarter century, namely, high-temperature superconductivity and the fractional quantum Hall effect. Despite enormous conceptual strides, these two fields have developed largely along separate paths. Two widely employed theories are the resonating valence bond theory for high-temperature superconductivity and the composite fermion theory for the fractional quantum Hall effect. The goal of this perspective article is to note that they subscribe to a common underlying paradigm: They both connect these exotic quantum liquids to certain ordinary Fermi liquids residing in unphysical Hilbert spaces. Such a relation yields numerous nontrivial experimental consequences, exposing these theories to rigorous and definitive tests. PMID:19506260

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

Lapidus, Alla L.

From the date its role in heredity was discovered, DNA has been generating interest among scientists from different fields of knowledge: physicists have studied the three dimensional structure of the DNA molecule, biologists tried to decode the secrets of life hidden within these long molecules, and technologists invent and improve methods of DNA analysis. The analysis of the nucleotide sequence of DNA occupies a special place among the methods developed. Thanks to the variety of sequencing technologies available, the process of decoding the sequence of genomic DNA (or whole genome sequencing) has become robust and inexpensive. Meanwhile the assembly ofmore » whole genome sequences remains a challenging task. In addition to the need to assemble millions of DNA fragments of different length (from 35 bp (Solexa) to 800 bp (Sanger)), great interest in analysis of microbial communities (metagenomes) of different complexities raises new problems and pushes some new requirements for sequence assembly tools to the forefront. The genome assembly process can be divided into two steps: draft assembly and assembly improvement (finishing). Despite the fact that automatically performed assembly (or draft assembly) is capable of covering up to 98% of the genome, in most cases, it still contains incorrectly assembled reads. The error rate of the consensus sequence produced at this stage is about 1/2000 bp. A finished genome represents the genome assembly of much higher accuracy (with no gaps or incorrectly assembled areas) and quality ({approx}1 error/10,000 bp), validated through a number of computer and laboratory experiments.« less

An investigation of prior knowledge in Automatic Music Transcription systems.

PubMed

Cazau, Dorian; Revillon, Guillaume; Krywyk, Julien; Adam, Olivier

2015-10-01

Automatic transcription of music is a long-studied research field with many operational systems available commercially. In this paper, a generic transcription system able to host various prior knowledge parameters has been developed, followed by an in-depth investigation of their impact on music transcription. Explicit links between musical knowledge and algorithmic formalism have been made. Musical knowledge covers classes of timbre, musicology, and playing style of an instrument repertoire. An evaluation sound corpus gathering musical pieces played by human performers from three different instrument repertoires, namely, classical piano, steel-string acoustic guitar, and the marovany zither from Madagascar, has been developed. The different components of musical knowledge have been successively incorporated in a complete transcription system, consisting mainly of a Probabilistic Latent Component Analysis algorithm post-processed with a Hidden Markov Model, and their impact on transcription results have been comparatively evaluated.

Escape from Metaignorance: How Children Develop an Understanding of Their Own Lack of Knowledge

ERIC Educational Resources Information Center

Rohwer, Michael; Kloo, Daniela; Perner, Josef

2012-01-01

Previous research yielded conflicting results about when children can accurately assess their epistemic states in different hiding tasks. In Experiment 1, ninety-two 3- to 7-year-olds were either shown which object was hidden inside a box, were totally ignorant about what it could be, or were presented with two objects one of which was being put…

A Hidden History: A Survey of the Teaching of Eugenics in Health, Social Care and Pedagogical Education and Training Courses in Europe

ERIC Educational Resources Information Center

Atherton, H. L.; Steels, S. L.

2016-01-01

Knowledge and understanding of how eugenics has historically affected the lives of people with intellectual disabilities is vital if professionals are to mount an effective defence against its contemporary influences. An online survey of European providers of health, social care and pedagogical education and training courses was undertaken to find…

Two-Year-Old Children's Understanding of Visual Perception and Knowledge Formation in Others

ERIC Educational Resources Information Center

Teufel, Christoph; Clayton, Nicola S.; Russell, James

2013-01-01

A landmark study by O'Neill (1996), in which 2-year-old children were found to be more likely to point toward a hidden object to help an adult who was unsighted during the hiding event than to point helpfully for an adult who had been sighted, seems to undermine the conventional assumption that children this young do not understand the…

Beliefs about Thought Probability: Evidence for Persistent Errors in Mindreading and Links to Executive Control

ERIC Educational Resources Information Center

Lagattuta, Kristin Hansen; Sayfan, Liat; Harvey, Christina

2014-01-01

Four- to 10-year-olds' and adults' (N = 263) ability to inhibit privileged knowledge and simulate a naïve perspective were examined. Participants viewed pictures that were then occluded aside from a small ambiguous part. They offered suggestions for how a naïve person might interpret the hidden pictures, as well as rated the probability…

Prior knowledge driven Granger causality analysis on gene regulatory network discovery

DOE PAGES

Yao, Shun; Yoo, Shinjae; Yu, Dantong

2015-08-28

Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

2010-01-01

Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103

Discovering motion primitives for unsupervised grouping and one-shot learning of human actions, gestures, and expressions.

PubMed

Yang, Yang; Saleemi, Imran; Shah, Mubarak

2013-07-01

This paper proposes a novel representation of articulated human actions and gestures and facial expressions. The main goals of the proposed approach are: 1) to enable recognition using very few examples, i.e., one or k-shot learning, and 2) meaningful organization of unlabeled datasets by unsupervised clustering. Our proposed representation is obtained by automatically discovering high-level subactions or motion primitives, by hierarchical clustering of observed optical flow in four-dimensional, spatial, and motion flow space. The completely unsupervised proposed method, in contrast to state-of-the-art representations like bag of video words, provides a meaningful representation conducive to visual interpretation and textual labeling. Each primitive action depicts an atomic subaction, like directional motion of limb or torso, and is represented by a mixture of four-dimensional Gaussian distributions. For one--shot and k-shot learning, the sequence of primitive labels discovered in a test video are labeled using KL divergence, and can then be represented as a string and matched against similar strings of training videos. The same sequence can also be collapsed into a histogram of primitives or be used to learn a Hidden Markov model to represent classes. We have performed extensive experiments on recognition by one and k-shot learning as well as unsupervised action clustering on six human actions and gesture datasets, a composite dataset, and a database of facial expressions. These experiments confirm the validity and discriminative nature of the proposed representation.

Discovering Science through Art-Based Activities

ERIC Educational Resources Information Center

Alberts, Rebecca

2010-01-01

Art and science are intrinsically linked; the essence of art and science is discovery. Both artists and scientists work in a systematic but creative way--knowledge and understanding are built up through pieces of art or a series of labs. In the classroom, integrating science and visual art can provide students with the latitude to think, discover,…

Passive Acoustic Leak Detection for Sodium Cooled Fast Reactors Using Hidden Markov Models

NASA Astrophysics Data System (ADS)

Marklund, A. Riber; Kishore, S.; Prakash, V.; Rajan, K. K.; Michel, F.

2016-06-01

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970s and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), the proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control.

Behind the scenes of a research and training collaboration: power, privilege, and the hidden transcript of race.

PubMed

Carpenter-Song, Elizabeth; Whitley, Rob

2013-06-01

This paper examines a federally funded research and training collaboration between an Ivy League psychiatric research center and a historically Black university and medical center. This collaboration focuses on issues of psychiatric recovery and rehabilitation among African Americans. In addition, this multidisciplinary collaboration aims to build the research capacity at both institutions and to contribute to the tradition of research in culture and mental health within the medical social sciences and cultural psychiatry. This article provides a window into the complex, often messy, dynamics of a collaboration that cross cuts institutional, disciplinary, and demographic boundaries. Taking an auto-ethnographic approach, we intend to illustrate how collaborative relationships unfold and are constructed through ongoing reciprocal flows of knowledge and experience. Central to this aim is a consideration of how issues of power, privilege, and the hidden transcript of race shape the nature of our research and training efforts.

Failure monitoring in dynamic systems: Model construction without fault training data

NASA Technical Reports Server (NTRS)

Smyth, P.; Mellstrom, J.

1993-01-01

Advances in the use of autoregressive models, pattern recognition methods, and hidden Markov models for on-line health monitoring of dynamic systems (such as DSN antennas) have recently been reported. However, the algorithms described in previous work have the significant drawback that data acquired under fault conditions are assumed to be available in order to train the model used for monitoring the system under observation. This article reports that this assumption can be relaxed and that hidden Markov monitoring models can be constructed using only data acquired under normal conditions and prior knowledge of the system characteristics being measured. The method is described and evaluated on data from the DSS 13 34-m beam wave guide antenna. The primary conclusion from the experimental results is that the method is indeed practical and holds considerable promise for application at the 70-m antenna sites where acquisition of fault data under controlled conditions is not realistic.

Epistemic View of Quantum States and Communication Complexity of Quantum Channels

NASA Astrophysics Data System (ADS)

Montina, Alberto

2012-09-01

The communication complexity of a quantum channel is the minimal amount of classical communication required for classically simulating a process of state preparation, transmission through the channel and subsequent measurement. It establishes a limit on the power of quantum communication in terms of classical resources. We show that classical simulations employing a finite amount of communication can be derived from a special class of hidden variable theories where quantum states represent statistical knowledge about the classical state and not an element of reality. This special class has attracted strong interest very recently. The communication cost of each derived simulation is given by the mutual information between the quantum state and the classical state of the parent hidden variable theory. Finally, we find that the communication complexity for single qubits is smaller than 1.28 bits. The previous known upper bound was 1.85 bits.

A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles.

PubMed

Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng

2016-05-01

In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.

Spread spectrum image steganography.

PubMed

Marvel, L M; Boncelet, C R; Retter, C T

1999-01-01

In this paper, we present a new method of digital steganography, entitled spread spectrum image steganography (SSIS). Steganography, which means "covered writing" in Greek, is the science of communicating in a hidden manner. Following a discussion of steganographic communication theory and review of existing techniques, the new method, SSIS, is introduced. This system hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range. The hidden message can be recovered using appropriate keys without any knowledge of the original image. Image restoration, error-control coding, and techniques similar to spread spectrum are described, and the performance of the system is illustrated. A message embedded by this method can be in the form of text, imagery, or any other digital signal. Applications for such a data-hiding scheme include in-band captioning, covert communication, image tamperproofing, authentication, embedded control, and revision tracking.

Collaborative mining of graph patterns from multiple sources

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Colonna-Romanoa, John

2016-05-01

Intelligence analysts require automated tools to mine multi-source data, including answering queries, learning patterns of life, and discovering malicious or anomalous activities. Graph mining algorithms have recently attracted significant attention in intelligence community, because the text-derived knowledge can be efficiently represented as graphs of entities and relationships. However, graph mining models are limited to use-cases involving collocated data, and often make restrictive assumptions about the types of patterns that need to be discovered, the relationships between individual sources, and availability of accurate data segmentation. In this paper we present a model to learn the graph patterns from multiple relational data sources, when each source might have only a fragment (or subgraph) of the knowledge that needs to be discovered, and segmentation of data into training or testing instances is not available. Our model is based on distributed collaborative graph learning, and is effective in situations when the data is kept locally and cannot be moved to a centralized location. Our experiments show that proposed collaborative learning achieves learning quality better than aggregated centralized graph learning, and has learning time comparable to traditional distributed learning in which a knowledge of data segmentation is needed.

An interactive visualization tool for mobile objects

NASA Astrophysics Data System (ADS)

Kobayashi, Tetsuo

Recent advancements in mobile devices---such as Global Positioning System (GPS), cellular phones, car navigation system, and radio-frequency identification (RFID)---have greatly influenced the nature and volume of data about individual-based movement in space and time. Due to the prevalence of mobile devices, vast amounts of mobile objects data are being produced and stored in databases, overwhelming the capacity of traditional spatial analytical methods. There is a growing need for discovering unexpected patterns, trends, and relationships that are hidden in the massive mobile objects data. Geographic visualization (GVis) and knowledge discovery in databases (KDD) are two major research fields that are associated with knowledge discovery and construction. Their major research challenges are the integration of GVis and KDD, enhancing the ability to handle large volume mobile objects data, and high interactivity between the computer and users of GVis and KDD tools. This dissertation proposes a visualization toolkit to enable highly interactive visual data exploration for mobile objects datasets. Vector algebraic representation and online analytical processing (OLAP) are utilized for managing and querying the mobile object data to accomplish high interactivity of the visualization tool. In addition, reconstructing trajectories at user-defined levels of temporal granularity with time aggregation methods allows exploration of the individual objects at different levels of movement generality. At a given level of generality, individual paths can be combined into synthetic summary paths based on three similarity measures, namely, locational similarity, directional similarity, and geometric similarity functions. A visualization toolkit based on the space-time cube concept exploits these functionalities to create a user-interactive environment for exploring mobile objects data. Furthermore, the characteristics of visualized trajectories are exported to be utilized for data mining, which leads to the integration of GVis and KDD. Case studies using three movement datasets (personal travel data survey in Lexington, Kentucky, wild chicken movement data in Thailand, and self-tracking data in Utah) demonstrate the potential of the system to extract meaningful patterns from the otherwise difficult to comprehend collections of space-time trajectories.

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

Data Stream Mining

NASA Astrophysics Data System (ADS)

Gaber, Mohamed Medhat; Zaslavsky, Arkady; Krishnaswamy, Shonali

Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).

Water Underground

NASA Astrophysics Data System (ADS)

de Graaf, I. E. M.

2014-12-01

The world's largest accessible source of freshwater is hidden underground. However it remains difficult to estimate its volume, and we still cannot answer the question; will there be enough for everybody? In many places of the world groundwater abstraction is unsustainable: more water is used than refilled, leading to decreasing river discharges and declining groundwater levels. It is predicted that for many regions in the world unsustainable water use will increase in the coming decades, due to rising human water use under a changing climate. It would not take long before water shortage causes widespread droughts and the first water war begins. Improving our knowledge about our hidden water is the first step to prevent such large water conflicts. The world's largest aquifers are mapped, but these maps do not mention how much water these aquifers contain or how fast water levels decline. If we can add thickness and geohydrological information to these aquifer maps, we can estimate how much water is stored and its flow direction. Also, data on groundwater age and how fast the aquifer is refilled is needed to predict the impact of human water use and climate change on the groundwater resource. Ultimately, if we can provide this knowledge water conflicts will focus more on a fair distribution instead of absolute amounts of water.

Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

PubMed Central

2016-01-01

Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower–visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based systems for knowledge discovery in biodiversity and ecosystem informatics. PMID:27851814

Environmental Visualization and Horizontal Fusion

DTIC Science & Technology

2005-10-01

the section on EVIS Rules. Federated Search – Discovering Content Another method of discovering services and their content has been implemented...in HF through a next-generation knowledge discovery framework called Federated Search . A virtual information space, called Collateral Space was...environmental mission effects products, is presented later in the paper. Federated Search allows users to search through Collateral Space data that is

The English Monolingual Dictionary: Its Use among Second Year Students of University Technology of Malaysia, International Campus, Kuala Lumpur

ERIC Educational Resources Information Center

Manan, Amerrudin Abd.; Al-Zubaidi, Khairi Obaid

2011-01-01

This research was conducted to seek information on English Monolingual Dictionary (EMD) use among 2nd year students of Universiti Teknologi Malaysia, International Campus, Kuala Lumpur (UTMKL). Specifically, the researchers wish to discover, firstly, the students' habit and attitude in EMD use; secondly, to discover their knowledge with regard to…

A framework for interval-valued information system

NASA Astrophysics Data System (ADS)

Yin, Yunfei; Gong, Guanghong; Han, Liang

2012-09-01

Interval-valued information system is used to transform the conventional dataset into the interval-valued form. To conduct the interval-valued data mining, we conduct two investigations: (1) construct the interval-valued information system, and (2) conduct the interval-valued knowledge discovery. In constructing the interval-valued information system, we first make the paired attributes in the database discovered, and then, make them stored in the neighbour locations in a common database and regard them as 'one' new field. In conducting the interval-valued knowledge discovery, we utilise some related priori knowledge and regard the priori knowledge as the control objectives; and design an approximate closed-loop control mining system. On the implemented experimental platform (prototype), we conduct the corresponding experiments and compare the proposed algorithms with several typical algorithms, such as the Apriori algorithm, the FP-growth algorithm and the CLOSE+ algorithm. The experimental results show that the interval-valued information system method is more effective than the conventional algorithms in discovering interval-valued patterns.

Discovering Collaboration and Knowledge Management Practices for the Future Digital Factory

NASA Astrophysics Data System (ADS)

Flores, Myrna; Vera, Tomas; Tucci, Christopher

Recently there has been an explosion of new technologies and tools such as wikis, blogs, tags, Facebook, among many others, that are commonly identified under Web 2.0 and which promise a new digital business ecosystem fed by formal/informal and internal/external relationships and interactions. Although Web 2.0 is very promising to enable such collective knowledge creation, technology by itself is not the only ingredient. It is also required to define the right strategy, governance, culture, processes, training, incentives among others, before implementing such innovative open spaces for collaboration and knowledge sharing. Therefore, the objective of this paper is to present a Knowledge Management (KM) Framework and a Maturity Model developed by a CEMEX and EPFL collaborative research project to discover the AS-IS collaboration practices in CEMEX before the implementation of the SMARTBRICKS Web 2.0 prototype for Business Process Management (BPM), currently under development by the Intelligent Manufacturing Systems (IMS) Swiss Digital Factory (DiFac) project.

Discovering and Articulating What Is Not yet Known: Using Action Learning and Grounded Theory as a Knowledge Management Strategy

ERIC Educational Resources Information Center

Pauleen, David J.; Corbitt, Brian; Yoong, Pak

2007-01-01

Purpose: To provide a conceptual model for the discovery and articulation of emergent organizational knowledge, particularly knowledge that develops when people work with new technologies. Design/methodology/approach: The model is based on two widely accepted research methods--action learning and grounded theory--and is illustrated using a case…

Using web-based technology to deliver scientific knowledge: the Southern Forest Encyclopedia Network.

Treesearch

John M. Pye; H. Michael Rauscher; Deborah K. Kennard; Patricia A. Flebbe; J. Bryan Jordin; William G. Hubbard; Cynthia Fowler; James Ward

2007-01-01

Forest science, like any science, is a continuous process of discovering new knowledge, reevaluating existing knowledge, and revising our theories and management practices in light of these changes. The forest science community has not yet found the solution to the problem of getting continuously changing science efficiently and effectively into the hands of those who...

Automated generation of massive image knowledge collections using Microsoft Live Labs Pivot to promote neuroimaging and translational research.

PubMed

Viangteeravat, Teeradache; Anyanwu, Matthew N; Ra Nagisetty, Venkateswara; Kuscu, Emin

2011-07-15

Massive datasets comprising high-resolution images, generated in neuro-imaging studies and in clinical imaging research, are increasingly challenging our ability to analyze, share, and filter such images in clinical and basic translational research. Pivot collection exploratory analysis provides each user the ability to fully interact with the massive amounts of visual data to fully facilitate sufficient sorting, flexibility and speed to fluidly access, explore or analyze the massive image data sets of high-resolution images and their associated meta information, such as neuro-imaging databases from the Allen Brain Atlas. It is used in clustering, filtering, data sharing and classifying of the visual data into various deep zoom levels and meta information categories to detect the underlying hidden pattern within the data set that has been used. We deployed prototype Pivot collections using the Linux CentOS running on the Apache web server. We also tested the prototype Pivot collections on other operating systems like Windows (the most common variants) and UNIX, etc. It is demonstrated that the approach yields very good results when compared with other approaches used by some researchers for generation, creation, and clustering of massive image collections such as the coronal and horizontal sections of the mouse brain from the Allen Brain Atlas. Pivot visual analytics was used to analyze a prototype of dataset Dab2 co-expressed genes from the Allen Brain Atlas. The metadata along with high-resolution images were automatically extracted using the Allen Brain Atlas API. It is then used to identify the hidden information based on the various categories and conditions applied by using options generated from automated collection. A metadata category like chromosome, as well as data for individual cases like sex, age, and plan attributes of a particular gene, is used to filter, sort and to determine if there exist other genes with a similar characteristics to Dab2. And online access to the mouse brain pivot collection can be viewed using the link http://edtech-dev.uthsc.edu/CTSI/teeDev1/unittest/PaPa/collection.html (user name: tviangte and password: demome) Our proposed algorithm has automated the creation of large image Pivot collections; this will enable investigators of clinical research projects to easily and quickly analyse the image collections through a perspective that is useful for making critical decisions about the image patterns discovered.

A new look at the Y tetraquarks and Ω _c baryons in the diquark model

NASA Astrophysics Data System (ADS)

Ali, Ahmed; Maiani, Luciano; Borisov, Anatoly V.; Ahmed, Ishtiaq; Aslam, M. Jamil; Parkhomenko, Alexander Ya.; Polosa, Antonio D.; Rehman, Abdur

2018-01-01

We analyze the hidden charm P-wave tetraquarks in the diquark model, using an effective Hamiltonian incorporating the dominant spin-spin, spin-orbit and tensor interactions. We compare with other P-wave systems such as P-wave charmonia and the newly discovered Ω _c baryons, analysed recently in this framework. Given the uncertain experimental situation on the Y states, we allow for different spectra and discuss the related parameters in the diquark model. In addition to the presently observed ones, we expect many more states in the supermultiplet of L=1 diquarkonia, whose J^{PC} quantum numbers and masses are worked out, using the parameters from the currently preferred Y-states pattern. The existence of these new resonances would be a decisive footprint of the underlying diquark dynamics.

[Results of a structurized discussion within the framework of abortion with particular reference to problems of pregnancy, conflict and related topics (author's transl)].

PubMed

Woynar, W; Schuster, E; Oberheuser, F

1980-02-01

Structured discussions within the framework of social counseling were held with 112 patients in connection with abortion. They were structured according to sociopsychologoical criteria in order to discover any hidden conflicts prevailing in those patients seeking abortion. It became clear that there was a discrepancy between the individual expectation and its translation into reality. Also there was a situation in which too much was demanded of the patient, resulting in an inability to cope with the factors governing her life with subsequent fear of mental and social isolation. Sociologically speaking, the group was divided between elderly socially secured patients who already had children and young patients still undergoing educational or vocational training. (Authors' modified)

Earthquake-induced burial of archaeological sites along the southern Washington coast about A.D. 1700

USGS Publications Warehouse

Cole, S.C.; Atwater, B.F.; McCutcheon, P.T.; Stein, J.K.; Hemphill-Haley, E.

1996-01-01

Although inhabited by thousands of people when first reached by Europeans, the Pacific coast of southern Washington has little recognized evidence of prehistoric human occupation. This apparent contradiction may be explained partly by geologic evidence for coastal submergence during prehistoric earthquakes on the Cascadia subduction zone. Recently discovered archaeological sites, exposed in the banks of two tidal streams, show evidence for earthquake-induced submergence and consequent burial by intertidal mud about A.D. 1700. We surmise that, because of prehistoric earthquakes, other archaeological sites may now lie hidden beneath the surfaces of modern tidelands. Such burial of archaeological sites raises questions about the estimation of prehistoric human population densities along coasts subject to earthquake-induced submergence. ?? 1996 John Wiley & Sons, Inc.

An analysis of pilot error-related aircraft accidents

NASA Technical Reports Server (NTRS)

Kowalsky, N. B.; Masters, R. L.; Stone, R. B.; Babcock, G. L.; Rypka, E. W.

1974-01-01

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis.

The hidden life of integrative and conjugative elements

PubMed Central

Delavat, François; Miyazaki, Ryo; Carraro, Nicolas; Pradervand, Nicolas

2017-01-01

Abstract Integrative and conjugative elements (ICEs) are widespread mobile DNA that transmit both vertically, in a host-integrated state, and horizontally, through excision and transfer to new recipients. Different families of ICEs have been discovered with more or less restricted host ranges, which operate by similar mechanisms but differ in regulatory networks, evolutionary origin and the types of variable genes they contribute to the host. Based on reviewing recent experimental data, we propose a general model of ICE life style that explains the transition between vertical and horizontal transmission as a result of a bistable decision in the ICE–host partnership. In the large majority of cells, the ICE remains silent and integrated, but hidden at low to very low frequencies in the population specialized host cells appear in which the ICE starts its process of horizontal transmission. This bistable process leads to host cell differentiation, ICE excision and transfer, when suitable recipients are present. The ratio of ICE bistability (i.e. ratio of horizontal to vertical transmission) is the outcome of a balance between fitness costs imposed by the ICE horizontal transmission process on the host cell, and selection for ICE distribution (i.e. ICE ‘fitness’). From this emerges a picture of ICEs as elements that have adapted to a mostly confined life style within their host, but with a very effective and dynamic transfer from a subpopulation of dedicated cells. PMID:28369623

A Neighboring Dwarf Irregular Galaxy Hidden by the Milky Way

NASA Astrophysics Data System (ADS)

Massey, Philip; Henning, P. A.; Kraan-Korteweg, R. C.

2003-11-01

We have obtained VLA and optical follow-up observations of the low-velocity H I source HIZSS 3 discovered by Henning et al. and Rivers in a survey for nearby galaxies hidden by the disk of the Milky Way. Its radio characteristics are consistent with this being a nearby (~1.8 Mpc) low-mass dwarf irregular galaxy (dIm). Our optical imaging failed to reveal a resolved stellar population but did detect an extended Hα emission region. The location of the Hα source is coincident with a partially resolved H I cloud in the 21 cm map. Spectroscopy confirms that the Hα source has a similar radial velocity to that of the H I emission at this location, and thus we have identified an optical counterpart. The Hα emission (100 pc in diameter and with a luminosity of 1.4×1038 ergs s-1) is characteristic of a single H II region containing a modest population of OB stars. The galaxy's radial velocity and distance from the solar apex suggests that it is not a Local Group member, although a more accurate distance is needed to be certain. The properties of HIZSS 3 are comparable to those of GR 8, a nearby dIm with a modest amount of current star formation. Further observations are needed to characterize its stellar population, determine the chemical abundances, and obtain a more reliable distance estimate.

Workplace ageism: discovering hidden bias.

PubMed

Malinen, Sanna; Johnston, Lucy

2013-01-01

BACKGROUND/STUDY CONTEXT: Research largely shows no performance differences between older and younger employees, or that older workers even outperform younger employees, yet negative attitudes towards older workers can underpin discrimination. Unfortunately, traditional "explicit" techniques for assessing attitudes (i.e., self-report measures) have serious drawbacks. Therefore, using an approach that is novel to organizational contexts, the authors supplemented explicit with implicit (indirect) measures of attitudes towards older workers, and examined the malleability of both. This research consists of two studies. The authors measured self-report (explicit) attitudes towards older and younger workers with a survey, and implicit attitudes with a reaction-time-based measure of implicit associations. In addition, to test whether attitudes were malleable, the authors measured attitudes before and after a mental imagery intervention, where the authors asked participants in the experimental group to imagine respected and valued older workers from their surroundings. Negative, stable implicit attitudes towards older workers emerged in two studies. Conversely, explicit attitudes showed no age bias and were more susceptible to change intervention, such that attitudes became more positive towards older workers following the experimental manipulation. This research demonstrates the unconscious nature of bias against older workers, and highlights the utility of implicit attitude measures in the context of the workplace. In the current era of aging workforce and skill shortages, implicit measures may be necessary to illuminate hidden workplace ageism.

Knowledge of the risks associated with skin bleaching among Togolese users.

PubMed

Kpanake, L; Sastre, M T Munoz; Sorum, P C; Mullet, E

2008-01-01

We examined the extent of Togolese users' knowledge of the health risks associated with the regular use of bleaching agents. A massive underestimation of some of the main risks was discovered. The more frequent the use of bleaching agents, the higher the underestimation.

Cost-Benefit Analysis of Confidentiality Policies for Advanced Knowledge Management Systems

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

May, D

Knowledge Discovery (KD) processes can create new information within a Knowledge Management (KM) system. In many domains, including government, this new information must be secured against unauthorized disclosure. Applying an appropriate confidentiality policy achieves this. However, it is not evident which confidentiality policy to apply, especially when the goals of sharing and disseminating knowledge have to be balanced with the requirements to secure knowledge. This work proposes to solve this problem by developing a cost-benefit analysis technique for examining the tradeoffs between securing and sharing discovered knowledge.

A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

NASA Astrophysics Data System (ADS)

Xu, Jin; Li, Zheng; Li, Shuliang; Zhang, Yanyan

2015-07-01

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

Privacy Is Become with, Data Perturbation

NASA Astrophysics Data System (ADS)

Singh, Er. Niranjan; Singhai, Niky

2011-06-01

Privacy is becoming an increasingly important issue in many data mining applications that deal with health care, security, finance, behavior and other types of sensitive data. Is particularly becoming important in counterterrorism and homeland security-related applications. We touch upon several techniques of masking the data, namely random distortion, including the uniform and Gaussian noise, applied to the data in order to protect it. These perturbation schemes are equivalent to additive perturbation after the logarithmic Transformation. Due to the large volume of research in deriving private information from the additive noise perturbed data, the security of these perturbation schemes is questionable Many artificial intelligence and statistical methods exist for data analysis interpretation, Identifying and measuring the interestingness of patterns and rules discovered, or to be discovered is essential for the evaluation of the mined knowledge and the KDD process as a whole. While some concrete measurements exist, assessing the interestingness of discovered knowledge is still an important research issue. As the tool for the algorithm implementations we chose the language of choice in industrial world MATLAB.

Inspiring Generations through Knowledge and Discovery. Strategic Plan. Fiscal Years 2010-2015

ERIC Educational Resources Information Center

Smithsonian Institution, 2015

2015-01-01

Imagine being able to access all known information about an insect species--whether it was discovered 100 years or 100 days ago--with one touch of the screen. Picture a world in which you can not only see Smithsonian objects online but also hear them and watch them in motion. Or imagine learning that Smithsonian astrophysicists discovered a new,…

The Hidden Dimension of Strategic Planning: Explorations in the Formation of Perspectives

DTIC Science & Technology

1991-09-01

13 2. Laws--Or Points Of Reference?.........18 B. THE HORIZONTAL LEVEL OF DECISION - MAKING . . . . 23 1. KNOWLEDGE, RATIONALITY , AND... decision - making is a horizontal level ranging from logic and rationalism to subjective emotionalism. This is the dimension of decision - making with which...the process of decision - making . The basis of game theory is the dual premises of rationality and maximization of utility.6 "It [game theory] is

Dogmatism and the "Knowledge Gap" among Users of the Mass Media of Communication: A Study in Brasilia, Brasil.

ERIC Educational Resources Information Center

Simmons, Robert E.; Garda, Eduardo Carlos

A study was conducted to discover whether (1) use of each of the print and broadcast media could be correlated with subjects' knowledge level, and (2) whether controlling for dogmatism would increase the proportion of media users, with higher levels of knowledge among those less dogmatic, and decrease the proportion among the more dogmatic.…

Discovering Knowledge from Noisy Databases Using Genetic Programming.

ERIC Educational Resources Information Center

Wong, Man Leung; Leung, Kwong Sak; Cheng, Jack C. Y.

2000-01-01

Presents a framework that combines Genetic Programming and Inductive Logic Programming, two approaches in data mining, to induce knowledge from noisy databases. The framework is based on a formalism of logic grammars and is implemented as a data mining system called LOGENPRO (Logic Grammar-based Genetic Programming System). (Contains 34…

Hum-mPLoc 3.0: prediction enhancement of human protein subcellular localization through modeling the hidden correlations of gene ontology and functional domain features.

PubMed

Zhou, Hang; Yang, Yang; Shen, Hong-Bin

2017-03-15

Protein subcellular localization prediction has been an important research topic in computational biology over the last decade. Various automatic methods have been proposed to predict locations for large scale protein datasets, where statistical machine learning algorithms are widely used for model construction. A key step in these predictors is encoding the amino acid sequences into feature vectors. Many studies have shown that features extracted from biological domains, such as gene ontology and functional domains, can be very useful for improving the prediction accuracy. However, domain knowledge usually results in redundant features and high-dimensional feature spaces, which may degenerate the performance of machine learning models. In this paper, we propose a new amino acid sequence-based human protein subcellular location prediction approach Hum-mPLoc 3.0, which covers 12 human subcellular localizations. The sequences are represented by multi-view complementary features, i.e. context vocabulary annotation-based gene ontology (GO) terms, peptide-based functional domains, and residue-based statistical features. To systematically reflect the structural hierarchy of the domain knowledge bases, we propose a novel feature representation protocol denoted as HCM (Hidden Correlation Modeling), which will create more compact and discriminative feature vectors by modeling the hidden correlations between annotation terms. Experimental results on four benchmark datasets show that HCM improves prediction accuracy by 5-11% and F 1 by 8-19% compared with conventional GO-based methods. A large-scale application of Hum-mPLoc 3.0 on the whole human proteome reveals proteins co-localization preferences in the cell. www.csbio.sjtu.edu.cn/bioinf/Hum-mPLoc3/. hbshen@sjtu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

[Dawning of inhalational anesthesia: a historical perspective.].

PubMed

Maia, R Icardo Jakson de Freitas; Fernandes, Cláudia Regina

2002-11-01

History, unlike one may imagine, is not something unchangeable and limited to the past. It is adapted according to conveniences of one or other ruling social class. Deliberately or accidentally hidden information, when unveiled may change current concepts, so far taken for granted. So, history, as any other science, is not totally impartial; it suffers influences and interferences of political, religious, economic and cultural thinking. The same is true for anesthesia. Some questions remain unanswered: Why did it take so long for the civilization to control pain? Who did in fact discover Anesthesia? How was the world when Anesthesia was officially discovered? To discuss such questions it is necessary to go back to the History of Anesthesia. This paper addresses the surgical act, pain and anesthesia from the Hellenic culture to the first officially recognized anesthesia, often emphasizing forgotten names and historical peculiarities which have benefited or harmed one or other discoverer. It also focuses on values, culture and scientific developments of the 19th century, correlating them to events that marked the dawning of anesthesia. It would be unfair to attribute the merit of discovering anesthesia to a single person. Historical peculiarities that benefited or harmed one or other researcher cannot be forgotten. Morton was undoubtedly the most favored by the circumstances. He lived in a privileged time and place and has met the most adequate people to his intent. However there is still a question. After all, who is the most important: the father of the idea or who disclosed it? The answer will certainly remain in the field of subjectivity.

A tripartite clustering analysis on microRNA, gene and disease model.

PubMed

Shen, Chengcheng; Liu, Ying

2012-02-01

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

Food Safety and Sustainable Nutrition Workshops: Educational Experiences for Primary School Children in Turin, Italy.

PubMed

Traversa, Amaranta; Adriano, Daniela; Bellio, Alberto; Bianchi, Daniela Manila; Gallina, Silvia; Ippolito, Clara; Romano, Angelo; Durelli, Paola; Pezzana, Andrea; Decastelli, Lucia

2017-01-24

European control and prevention policies are focused to guarantee a high level of protection of consumers' health. Food-borne diseases as obesity, diabetes, food allergy, and food-borne outbreaks are increasing. To prevent food-borne diseases, it is fundamental to involve consumers, in particular children, in educational experiences aimed to learn the proper behaviours to be applied. In this context, we designed and performed 5 educational workshops about food safety, hidden allergens in food and nutrition aimed to involve children attending primary and summer school. These experiences let us collect observations about children knowledge and behaviours. From May to October 2015, a total of 1708 children aged 6 to 11 years joined our workshops. Children were involved in listening activities, laboratory experiments, handling games and sensory experiences. All participants were familiar with food allergy and were interested to know how to behave with allergic people. Children showed great curiosity in discovering that many foods normally contain live bacteria. Less than 25% of children reported to skip breakfast, to have it watching TV or to spend few minutes for it. Many of them (>75%) thought that fruits and vegetables are all year-round available and are not related to a specific period. Very few participants (<25%) knew that freezing is the treatment to be applied to make fresh fish safe from parasites. Children involved in food safety and nutrition educational experiences have the opportunity to increase their awareness about the correct behaviours to prevent food-borne diseases and to improve their own critical thinking about food consumption.

The effect of families on the process of outpatient visits in family practice.

PubMed

Main, D S; Holcomb, S; Dickinson, P; Crabtree, B F

2001-10-01

Our goal was to describe how physician knowledge of patients' families affects the processes of patient care in family practices. Using a multimethod comparative case study design, detailed dictated field notes were recorded after direct observation of patient encounters and the office environment as part of the Prevention and Competing Demands in Primary Care Study. We identified domains of outpatient visits in which patients were accompanied by a family member or in which family-oriented content was discussed. Outpatient encounters with 1637 patients presenting in 18 family practices in the Midwest were analyzed using an editing style. We developed a typology for ways in which family context affects outpatient visits. Patients were accompanied during 35% of all outpatient visits, the vast majority of these visits involving children. Family history or a family member's problems were discussed during 35% of visits during which no family member was present. An analysis of these "family-oriented" visits resulted in a typology of 6 ways that family context informs and affects the outpatient visit: (1) using family social context to illuminate patient disease, illness, and health; (2) using family to discover the source of an illness; (3) discussing and managing the health and illness of family members; (4) family concern for patient's health; (5) using the family as a care resource and care collaborator; and, (6) giving family members unscheduled care. Family context is an important feature of family practice that influences the processes of patient care. Since family-oriented care is an essential feature of family practice, outcomes of this largely hidden part of care deserve further study.

Computational Evolutionary Methodology for Knowledge Discovery and Forecasting in Epidemiology and Medicine

NASA Astrophysics Data System (ADS)

Rao, Dhananjai M.; Chernyakhovsky, Alexander; Rao, Victoria

2008-05-01

Humanity is facing an increasing number of highly virulent and communicable diseases such as avian influenza. Researchers believe that avian influenza has potential to evolve into one of the deadliest pandemics. Combating these diseases requires in-depth knowledge of their epidemiology. An effective methodology for discovering epidemiological knowledge is to utilize a descriptive, evolutionary, ecological model and use bio-simulations to study and analyze it. These types of bio-simulations fall under the category of computational evolutionary methods because the individual entities participating in the simulation are permitted to evolve in a natural manner by reacting to changes in the simulated ecosystem. This work describes the application of the aforementioned methodology to discover epidemiological knowledge about avian influenza using a novel eco-modeling and bio-simulation environment called SEARUMS. The mathematical principles underlying SEARUMS, its design, and the procedure for using SEARUMS are discussed. The bio-simulations and multi-faceted case studies conducted using SEARUMS elucidate its ability to pinpoint timelines, epicenters, and socio-economic impacts of avian influenza. This knowledge is invaluable for proactive deployment of countermeasures in order to minimize negative socioeconomic impacts, combat the disease, and avert a pandemic.

Computational Evolutionary Methodology for Knowledge Discovery and Forecasting in Epidemiology and Medicine

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

Rao, Dhananjai M.; Chernyakhovsky, Alexander; Rao, Victoria

2008-05-08

Humanity is facing an increasing number of highly virulent and communicable diseases such as avian influenza. Researchers believe that avian influenza has potential to evolve into one of the deadliest pandemics. Combating these diseases requires in-depth knowledge of their epidemiology. An effective methodology for discovering epidemiological knowledge is to utilize a descriptive, evolutionary, ecological model and use bio-simulations to study and analyze it. These types of bio-simulations fall under the category of computational evolutionary methods because the individual entities participating in the simulation are permitted to evolve in a natural manner by reacting to changes in the simulated ecosystem. Thismore » work describes the application of the aforementioned methodology to discover epidemiological knowledge about avian influenza using a novel eco-modeling and bio-simulation environment called SEARUMS. The mathematical principles underlying SEARUMS, its design, and the procedure for using SEARUMS are discussed. The bio-simulations and multi-faceted case studies conducted using SEARUMS elucidate its ability to pinpoint timelines, epicenters, and socio-economic impacts of avian influenza. This knowledge is invaluable for proactive deployment of countermeasures in order to minimize negative socioeconomic impacts, combat the disease, and avert a pandemic.« less

Knowledge discovery of drug data on the example of adverse reaction prediction

PubMed Central

2014-01-01

Background Antibiotics are the widely prescribed drugs for children and most likely to be related with adverse reactions. Record on adverse reactions and allergies from antibiotics considerably affect the prescription choices. We consider this a biomedical decision-making problem and explore hidden knowledge in survey results on data extracted from a big data pool of health records of children, from the Health Center of Osijek, Eastern Croatia. Results We applied and evaluated a k-means algorithm to the dataset to generate some clusters which have similar features. Our results highlight that some type of antibiotics form different clusters, which insight is most helpful for the clinician to support better decision-making. Conclusions Medical professionals can investigate the clusters which our study revealed, thus gaining useful knowledge and insight into this data for their clinical studies. PMID:25079450

'You must know what you mean when you say that': the morality of knowledge claims about ADHD in radio phone-ins.

PubMed

Versteeg, Wytske; Te Molder, Hedwig

2018-05-01

Drawing on a corpus of radio phone-ins, we present a discursive psychological analysis of how mothers carefully tailor their knowledge claims regarding their children with Attention Deficit Hyperactivity Disorder (ADHD). Mothers typically claim knowledge about their children's good intentions, but not about the 'ADHD-ness' of their conduct. Whereas the former is seen as appropriate knowledge for a concerned parent, the latter is treated as a matter of expert knowledge. We show that as soon as problematic behaviour is treated as observable from the outside and describable by mothers and other lay persons, it becomes vulnerable to being formulated as 'normal disobedience', rather than symptomatic of a professionally administered, doctorable condition. We argue that it is important to be aware of the moralities hidden in knowledge claims, as they help sustain an unproductive perspective in which either the child's brain or his mother is blamed for behaviour perceived as problematic. © 2018 The Authors. Sociology of Health & Illness published by John Wiley & Sons Ltd on behalf of Foundation for SHIL.

The sunstone and polarised skylight: ancient Viking navigational tools?

NASA Astrophysics Data System (ADS)

Ropars, Guy; Lakshminarayanan, Vasudevan; Le Floch, Albert

2014-10-01

Although the polarisation of the light was discovered at the beginning of the nineteenth century, the Vikings could have used the polarised light around the tenth century in their navigation to America, using a 'sunstone' evoked in the Icelandic Sagas. Indeed, the birefringence of the Iceland spar (calcite), a common crystal in Scandinavia, permits a simple observation of the axis of polarisation of the skylight at the zenith. From this, it is possible to guess the azimuth of a hidden Sun below the horizon, for instance. The high sensitivity of the differential method provided by the ordinary and extraordinary beams of calcite at its so-called isotropy point is about two orders higher than that of the best dichroic polariser and permits to reach an accuracy of ±1° for the Sun azimuth (at sunrise and sunset). Unfortunately, due to the relative fragility of calcite, only the so-called Alderney crystal was discovered on board a 16th ancient ship. Curiously, beyond its use as a sunstone by the Vikings, during these last millennia calcite has led to the discovery of the polarisation of the light itself by Malus and is currently being used to detect the atmospheres of exoplanets. Moreover, the differential method for the light polarisation detection is widely used in the animal world.

Operationalizing Place: Discovering, Reasoning about, and Exploring Place Knowledge from Descriptions

ERIC Educational Resources Information Center

Adams, Benjamin Thomas

2012-01-01

Places and place types, such as "small town", play a fundamental role in how people organize knowledge about the world. Although places are commonly referenced in human communication, often they are not canonically defined and many of the properties people associate with them have proved difficult to operationalize. In information…

Games for Learning: Which Template Generates Social Construction of Knowledge?

ERIC Educational Resources Information Center

Garcia, Francisco A.

2015-01-01

The purpose of this study was to discover how three person teams use game templates (trivia, role-play, or scavenger hunt) to socially construct knowledge. The researcher designed an experimental Internet-based database to facilitate teams creating each game. Teams consisted of teachers, students, hobbyist, and business owners who shared similar…

Temporal competition between differentiation programs determines cell fate choice

NASA Astrophysics Data System (ADS)

Kuchina, Anna; Espinar, Lorena; Cagatay, Tolga; Balbin, Alejandro; Alvarado, Alma; Garcia-Ojalvo, Jordi; Suel, Gurol

2011-03-01

During pluripotent differentiation, cells adopt one of several distinct fates. The dynamics of this decision-making process are poorly understood, since cell fate choice may be governed by interactions between differentiation programs that are active at the same time. We studied the dynamics of decision-making in the model organism Bacillus subtilis by simultaneously measuring the activities of competing differentiation programs (sporulation and competence) in single cells. We discovered a precise switch-like point of cell fate choice previously hidden by cell-cell variability. Engineered artificial crosslinks between competence and sporulation circuits revealed that the precision of this choice is generated by temporal competition between the key players of two differentiation programs. Modeling suggests that variable progression towards a switch-like decision might represent a general strategy to maximize adaptability and robustness of cellular decision-making.

Lorentzian symmetry predicts universality beyond scaling laws

NASA Astrophysics Data System (ADS)

Watson, Stephen J.

2017-06-01

We present a covariant theory for the ageing characteristics of phase-ordering systems that possess dynamical symmetries beyond mere scalings. A chiral spin dynamics which conserves the spin-up (+) and spin-down (-) fractions, μ+ and μ- , serves as the emblematic paradigm of our theory. Beyond a parabolic spatio-temporal scaling, we discover a hidden Lorentzian dynamical symmetry therein, and thereby prove that the characteristic length L of spin domains grows in time t according to L = \\fracβ{\\sqrt{1 - σ^2}}t\\frac{1{2}} , where σ:= μ+ - μ- (the invariant spin-excess) and β is a universal constant. Furthermore, the normalised length distributions of the spin-up and the spin-down domains each provably adopt a coincident universal (σ-independent) time-invariant form, and this supra-universal probability distribution is empirically verified to assume a form reminiscent of the Wigner surmise.

Leveraging health social networking communities in translational research.

PubMed

Webster, Yue W; Dow, Ernst R; Koehler, Jacob; Gudivada, Ranga C; Palakal, Mathew J

2011-08-01

Health social networking communities are emerging resources for translational research. We have designed and implemented a framework called HyGen, which combines Semantic Web technologies, graph algorithms and user profiling to discover and prioritize novel associations across disciplines. This manuscript focuses on the key strategies developed to overcome the challenges in handling patient-generated content in Health social networking communities. Heuristic and quantitative evaluations were carried out in colorectal cancer. The results demonstrate the potential of our approach to bridge silos and to identify hidden links among clinical observations, drugs, genes and diseases. In Amyotrophic Lateral Sclerosis case studies, HyGen has identified 15 of the 20 published disease genes. Additionally, HyGen has highlighted new candidates for future investigations, as well as a scientifically meaningful connection between riluzole and alcohol abuse. Copyright © 2011 Elsevier Inc. All rights reserved.

Multiband full-bandwidth anisotropic Eliashberg theory of interfacial electron-phonon coupling and high - Tc superconductivity in FeSe /SrTiO3

NASA Astrophysics Data System (ADS)

Aperis, Alex; Oppeneer, Peter M.

2018-02-01

We examine the impact of interfacial phonons on the superconducting state of FeSe /SrTiO3 developing a material's specific multiband, full bandwidth, and anisotropic Eliashberg theory for this system. Our self-consistent calculations highlight the importance of the interfacial electron-phonon interaction, which is hidden behind the seemingly weak-coupling constant λm=0.4 , in mediating the high Tc, and explain other puzzling experimental observations, such as the s -wave symmetry and replica bands. We discover that the formation of replica bands has a Tc decreasing effect that is nevertheless compensated by deep Fermi-sea Cooper pairing which has a Tc enhancing effect. We predict a strong-coupling dip-hump signature in the tunneling spectra due to the interfacial coupling.

Primary sacral hydatid cyst. A case report.

PubMed

Joshi, Nayana; Hernandez-Martinez, Alejandro; Seijas-Vazquez, Roberto

2007-10-01

This case report highlights an unusual osseous spinal presentation of a well described disease, hydatidosis. A 59-year-old woman presented with increasing back pain and bilateral radiculopathy. Examination disclosed symptoms of spinal stenosis and urinary incontinence. Radiographs showed an expansive lytic lesion affecting the pelvic bones with destruction of the bone cortex. Laboratory analyses were performed and the patient underwent CT and MRI studies. Serology for Echinococcus was positive. When assessing sciatica, low back pain or lower limb weakness the pelvic cavity should be examined for hidden disease that might explain the neurological symptoms. Hydatid disease of bone should be considered in the differential diagnosis of any bone mass discovered in the human body. Diagnosis was delayed in this case because the pelvic cavity was not studied when radiculopathy symptoms started and there was no coexisting visceral involvement.

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

Thi, Ngoc Anh Nguyen; Yang, Hyung-Jeong; Kim, SunHee; Do, Luu Ngoc

2014-01-01

Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden dynamics and correlations in ECG time series. The discovery of the comprehensible and interpretable features of the proposed feature extraction methodology effectively represents the accuracy and the reliability of clustering results. Particularly, the empirical evaluation results of the proposed method demonstrate the improved performance of clustering compared to the previous main stream feature extraction approaches for ECG time series clustering tasks. Furthermore, the experimental results on real-world datasets show scalability with linear computation time to the duration of the time series.

EMG-based speech recognition using hidden markov models with global control variables.

PubMed

Lee, Ki-Seung

2008-03-01

It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.

Functional Neuronal Processing of Human Body Odors

PubMed Central

Lundström, Johan N.; Olsson, Mats J.

2013-01-01

Body odors carry informational cues of great importance for individuals across a wide range of species, and signals hidden within the body odor cocktail are known to regulate several key behaviors in animals. For a long time, the notion that humans may be among these species has been dismissed. We now know, however, that each human has a unique odor signature that carries information related to his or her genetic makeup, as well as information about personal environmental variables, such as diet and hygiene. Although a substantial number of studies have investigated the behavioral effects of body odors, only a handful have studied central processing. Recent studies have, however, demonstrated that the human brain responds to fear signals hidden within the body odor cocktail, is able to extract kin specific signals, and processes body odors differently than other perceptually similar odors. In this chapter, we provide an overview of the current knowledge of how the human brain processes body odors and the potential importance these signals have for us in everyday life. PMID:20831940

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.

Water underground

NASA Astrophysics Data System (ADS)

de Graaf, Inge

2015-04-01

The world's largest assessable source of freshwater is hidden underground, but we do not know what is happening to it yet. In many places of the world groundwater is abstracted at unsustainable rates: more water is used than being recharged, leading to decreasing river discharges and declining groundwater levels. It is predicted that for many regions of the world unsustainable water use will increase, due to increasing human water use under changing climate. It would not be long before shortage causes widespread droughts and the first water war begins. Improving our knowledge about our hidden water is the first step to stop this. The world largest aquifers are mapped, but these maps do not mention how much water they contain or how fast water levels decline. If we can add a third dimension to the aquifer maps, so a thickness, and add geohydrological information we can estimate how much water is stored. Also data on groundwater age and how fast it is refilled is needed to predict the impact of human water use and climate change on the groundwater resource.

Passive acoustic leak detection for sodium cooled fast reactors using hidden Markov models

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

Riber Marklund, A.; Kishore, S.; Prakash, V.

2015-07-01

Acoustic leak detection for steam generators of sodium fast reactors have been an active research topic since the early 1970's and several methods have been tested over the years. Inspired by its success in the field of automatic speech recognition, we here apply hidden Markov models (HMM) in combination with Gaussian mixture models (GMM) to the problem. To achieve this, we propose a new feature calculation scheme, based on the temporal evolution of the power spectral density (PSD) of the signal. Using acoustic signals recorded during steam/water injection experiments done at the Indira Gandhi Centre for Atomic Research (IGCAR), themore » proposed method is tested. We perform parametric studies on the HMM+GMM model size and demonstrate that the proposed method a) performs well without a priori knowledge of injection noise, b) can incorporate several noise models and c) has an output distribution that simplifies false alarm rate control. (authors)« less

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.

Teaching Glycoproteins with a Classical Paper: Knowledge and Methods in the Course of an Exciting Discovery--The story of Discovering HK-ATPase [Beta]-Subunit

ERIC Educational Resources Information Center

Zhu, Lixin

2008-01-01

To integrate research into the teaching of glycoproteins, the story of discovering hydrogen-potassium ATPase (HK-ATPase) [beta] subunit is presented in a way covering all the important teaching points. The interaction between the HK-ATPase [alpha] subunit and a glycoprotein of 60-80 kDa was demonstrated to support the existence of the [beta]…

Improving on hidden Markov models: An articulatorily constrained, maximum likelihood approach to speech recognition and speech coding

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

Hogden, J.

The goal of the proposed research is to test a statistical model of speech recognition that incorporates the knowledge that speech is produced by relatively slow motions of the tongue, lips, and other speech articulators. This model is called Maximum Likelihood Continuity Mapping (Malcom). Many speech researchers believe that by using constraints imposed by articulator motions, we can improve or replace the current hidden Markov model based speech recognition algorithms. Unfortunately, previous efforts to incorporate information about articulation into speech recognition algorithms have suffered because (1) slight inaccuracies in our knowledge or the formulation of our knowledge about articulation maymore » decrease recognition performance, (2) small changes in the assumptions underlying models of speech production can lead to large changes in the speech derived from the models, and (3) collecting measurements of human articulator positions in sufficient quantity for training a speech recognition algorithm is still impractical. The most interesting (and in fact, unique) quality of Malcom is that, even though Malcom makes use of a mapping between acoustics and articulation, Malcom can be trained to recognize speech using only acoustic data. By learning the mapping between acoustics and articulation using only acoustic data, Malcom avoids the difficulties involved in collecting articulator position measurements and does not require an articulatory synthesizer model to estimate the mapping between vocal tract shapes and speech acoustics. Preliminary experiments that demonstrate that Malcom can learn the mapping between acoustics and articulation are discussed. Potential applications of Malcom aside from speech recognition are also discussed. Finally, specific deliverables resulting from the proposed research are described.« less

The Fast Follower: Coming Up Behind Development Leaders

DTIC Science & Technology

2015-06-01

DoD faces a shrinking defense industrial base and a more global tech marketplace and competes with the rise of consumer electronics that have short...to others and positions itself to rapidly exploit the newly discovered technical knowledge by quickly applying that knowledge to the unique needs of...technical aware- ness, organized for speed in innovation and has an intimate knowledge of its customer. From its vantage point on the first mover’s

Perceptions as Hypotheses

NASA Astrophysics Data System (ADS)

Gregory, R. L.

1980-07-01

Perceptions may be compared with hypotheses in science. The methods of acquiring scientific knowledge provide a working paradigm for investigating processes of perception. Much as the information channels of instruments, such as radio telescopes, transmit signals which are processed according to various assumptions to give useful data, so neural signals are processed to give data for perception. To understand perception, the signal codes and the stored knowledge or assumptions used for deriving perceptual hypotheses must be discovered. Systematic perceptual errors are important clues for appreciating signal channel limitations, and for discovering hypothesis-generating procedures. Although this distinction between `physiological' and `cognitive' aspects of perception may be logically clear, it is in practice surprisingly difficult to establish which are responsible even for clearly established phenomena such as the classical distortion illusions. Experimental results are presented, aimed at distinguishing between and discovering what happens when there is mismatch with the neural signal channel, and when neural signals are processed inappropriately for the current situation. This leads us to make some distinctions between perceptual and scientific hypotheses, which raise in a new form the problem: What are `objects'?

A framework of knowledge creation processes in participatory simulation of hospital work systems.

PubMed

Andersen, Simone Nyholm; Broberg, Ole

2017-04-01

Participatory simulation (PS) is a method to involve workers in simulating and designing their own future work system. Existing PS studies have focused on analysing the outcome, and minimal attention has been devoted to the process of creating this outcome. In order to study this process, we suggest applying a knowledge creation perspective. The aim of this study was to develop a framework describing the process of how ergonomics knowledge is created in PS. Video recordings from three projects applying PS of hospital work systems constituted the foundation of process mining analysis. The analysis resulted in a framework revealing the sources of ergonomics knowledge creation as sequential relationships between the activities of simulation participants sharing work experiences; experimenting with scenarios; and reflecting on ergonomics consequences. We argue that this framework reveals the hidden steps of PS that are essential when planning and facilitating PS that aims at designing work systems. Practitioner Summary: When facilitating participatory simulation (PS) in work system design, achieving an understanding of the PS process is essential. By applying a knowledge creation perspective and process mining, we investigated the knowledge-creating activities constituting the PS process. The analysis resulted in a framework of the knowledge-creating process in PS.

A simulation study of gene-by-environment interactions in GWAS implies ample hidden effects

PubMed Central

Marigorta, Urko M.; Gibson, Greg

2014-01-01

The switch to a modern lifestyle in recent decades has coincided with a rapid increase in prevalence of obesity and other diseases. These shifts in prevalence could be explained by the release of genetic susceptibility for disease in the form of gene-by-environment (GxE) interactions. Yet, the detection of interaction effects requires large sample sizes, little replication has been reported, and a few studies have demonstrated environmental effects only after summing the risk of GWAS alleles into genetic risk scores (GRSxE). We performed extensive simulations of a quantitative trait controlled by 2500 causal variants to inspect the feasibility to detect gene-by-environment interactions in the context of GWAS. The simulated individuals were assigned either to an ancestral or a modern setting that alters the phenotype by increasing the effect size by 1.05–2-fold at a varying fraction of perturbed SNPs (from 1 to 20%). We report two main results. First, for a wide range of realistic scenarios, highly significant GRSxE is detected despite the absence of individual genotype GxE evidence at the contributing loci. Second, an increase in phenotypic variance after environmental perturbation reduces the power to discover susceptibility variants by GWAS in mixed cohorts with individuals from both ancestral and modern environments. We conclude that a pervasive presence of gene-by-environment effects can remain hidden even though it contributes to the genetic architecture of complex traits. PMID:25101110

Application of a hybrid association rules/decision tree model for drought monitoring

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Molajou, Amir

2017-12-01

The previous researches have shown that the incorporation of the oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST) into hydro-climatic models could provide important predictive information about hydro-climatic variability. In this paper, the hybrid application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between drought of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. Two major steps of the proposed model were the classification of de-trend SST data and selecting the most effective groups and extracting hidden information involved in the data. The techniques of decision tree which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and Heidke Skill Score (HSS) measures were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast drought and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and drought of Tabriz and Kermanshah synoptic stations so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 70 and 80% respectively for Tabriz and Kermanshah synoptic stations.

Critical object recognition in millimeter-wave images with robustness to rotation and scale.

PubMed

Mohammadzade, Hoda; Ghojogh, Benyamin; Faezi, Sina; Shabany, Mahdi

2017-06-01

Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing features. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difficult. Thus, regular image processing and classification methods cannot be used for these images and additional pre-processings and classification methods should be introduced. This paper proposes a novel pre-processing method for canceling rotation and scale using principal component analysis. In addition, a two-layer classification method is introduced and utilized for recognition. Moreover, a large dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as support vector machines can recognize 45.5% of a type of critical objects at 34.2% false alarm rate (FAR), which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR, which indicates a highly significant improvement. The significant contribution of this work is to introduce a new method for analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noted in the field of millimeter-wave image analysis.

A Parallel Processing and Diversified-Hidden-Gene-Based Genetic Algorithm Framework for Fuel-Optimal Trajectory Design for Interplanetary Spacecraft Missions

NASA Astrophysics Data System (ADS)

Somavarapu, Dhathri H.

This thesis proposes a new parallel computing genetic algorithm framework for designing fuel-optimal trajectories for interplanetary spacecraft missions. The framework can capture the deep search space of the problem with the use of a fixed chromosome structure and hidden-genes concept, can explore the diverse set of candidate solutions with the use of the adaptive and twin-space crowding techniques and, can execute on any high-performance computing (HPC) platform with the adoption of the portable message passing interface (MPI) standard. The algorithm is implemented in C++ with the use of the MPICH implementation of the MPI standard. The algorithm uses a patched-conic approach with two-body dynamics assumptions. New procedures are developed for determining trajectories in the Vinfinity-leveraging legs of the flight from the launch and non-launch planets and, deep-space maneuver legs of the flight from the launch and non-launch planets. The chromosome structure maintains the time of flight as a free parameter within certain boundaries. The fitness or the cost function of the algorithm uses only the mission Delta V, and does not include time of flight. The optimization is conducted with two variations for the minimum mission gravity-assist sequence, the 4-gravity-assist, and the 3-gravity-assist, with a maximum of 5 gravity-assists allowed in both the cases. The optimal trajectories discovered using the framework in both of the cases demonstrate the success of this framework.

Sneaking a peek: pigeons use peripheral vision (not mirrors) to find hidden food.

PubMed

Ünver, Emre; Garland, Alexis; Tabrik, Sepideh; Güntürkün, Onur

2017-07-01

A small number of species are capable of recognizing themselves in the mirror when tested with the mark-and-mirror test. This ability is often seen as evidence of self-recognition and possibly even self-awareness. Strangely, a number of species, for example monkeys, pigs and dogs, are unable to pass the mark test but can locate rewarding objects by using the reflective properties of a mirror. Thus, these species seem to understand how a visual reflection functions but cannot apply it to their own image. We tested this discrepancy in pigeons-a species that does not spontaneously pass the mark test. Indeed, we discovered that pigeons can successfully find a hidden food reward using only the reflection, suggesting that pigeons can also use and potentially understand the reflective properties of mirrors, even in the absence of self-recognition. However, tested under monocular conditions, the pigeons approached and attempted to walk through the mirror rather than approach the physical food, displaying similar behavior to patients with mirror agnosia. These findings clearly show that pigeons do not use the reflection of mirrors to locate reward, but actually see the food peripherally with their near-panoramic vision. A re-evaluation of our current understanding of mirror-mediated behavior might be necessary-especially taking more fully into account species differences in visual field. This study suggests that use of reflections in a mirrored surface as a tool may be less widespread than currently thought.

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

Out of the white hole: a holographic origin for the Big Bang

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

Pourhasan, Razieh; Afshordi, Niayesh; Mann, Robert B., E-mail: rpourhasan@perimeterinstitute.ca, E-mail: nafshordi@pitp.ca, E-mail: rbmann@uwaterloo.ca

While most of the singularities of General Relativity are expected to be safely hidden behind event horizons by the cosmic censorship conjecture, we happen to live in the causal future of the classical Big Bang singularity, whose resolution constitutes the active field of early universe cosmology. Could the Big Bang be also hidden behind a causal horizon, making us immune to the decadent impacts of a naked singularity? We describe a braneworld description of cosmology with both 4d induced and 5D bulk gravity (otherwise known as Dvali-Gabadadze-Porati, or DGP model), which exhibits this feature: the universe emerges as a sphericalmore » 3-brane out of the formation of a 5D Schwarzschild black hole. In particular, we show that a pressure singularity of the holographic fluid, discovered earlier, happens inside the white hole horizon, and thus need not be real or imply any pathology. Furthermore, we outline a novel mechanism through which any thermal atmosphere for the brane, with comoving temperature of ∼20% of the 5D Planck mass can induce scale-invariant primordial curvature perturbations on the brane, circumventing the need for a separate process (such as cosmic inflation) to explain current cosmological observations. Finally, we note that 5D space-time is asymptotically flat, and thus potentially allows an S-matrix or (after minor modifications) an AdS/CFT description of the cosmological Big Bang.« less

Correlation Effects and Hidden Spin-Orbit Entangled Electronic Order in Parent and Electron-Doped Iridates Sr2 IrO4

NASA Astrophysics Data System (ADS)

Zhou, Sen; Jiang, Kun; Chen, Hua; Wang, Ziqiang

2017-10-01

Analogs of the high-Tc cuprates have been long sought after in transition metal oxides. Because of the strong spin-orbit coupling, the 5 d perovskite iridates Sr2 IrO4 exhibit a low-energy electronic structure remarkably similar to the cuprates. Whether a superconducting state exists as in the cuprates requires understanding the correlated spin-orbit entangled electronic states. Recent experiments discovered hidden order in the parent and electron-doped iridates, some with striking analogies to the cuprates, including Fermi surface pockets, Fermi arcs, and pseudogap. Here, we study the correlation and disorder effects in a five-orbital model derived from the band theory. We find that the experimental observations are consistent with a d -wave spin-orbit density wave order that breaks the symmetry of a joint twofold spin-orbital rotation followed by a lattice translation. There is a Berry phase and a plaquette spin flux due to spin procession as electrons hop between Ir atoms, akin to the intersite spin-orbit coupling in quantum spin Hall insulators. The associated staggered circulating Jeff=1 /2 spin current can be probed by advanced techniques of spin-current detection in spintronics. This electronic order can emerge spontaneously from the intersite Coulomb interactions between the spatially extended iridium 5 d orbitals, turning the metallic state into an electron-doped quasi-2D Dirac semimetal with important implications on the possible superconducting state suggested by recent experiments.

ESO's Hidden Treasures Brought to Light

NASA Astrophysics Data System (ADS)

2011-01-01

ESO's Hidden Treasures 2010 astrophotography competition attracted nearly 100 entries, and ESO is delighted to announce the winners. Hidden Treasures gave amateur astronomers the opportunity to search ESO's vast archives of astronomical data for a well-hidden cosmic gem. Astronomy enthusiast Igor Chekalin from Russia won the first prize in this difficult but rewarding challenge - the trip of a lifetime to ESO's Very Large Telescope at Paranal, Chile. The pictures of the Universe that can be seen in ESO's releases are impressive. However, many hours of skilful work are required to assemble the raw greyscale data captured by the telescopes into these colourful images, correcting them for distortions and unwanted signatures of the instrument, and enhancing them so as to bring out the details contained in the astronomical data. ESO has a team of professional image processors, but for the ESO's Hidden Treasures 2010 competition, the experts decided to give astronomy and photography enthusiasts the opportunity to show the world what they could do with the mammoth amount of data contained in ESO's archives. The enthusiasts who responded to the call submitted nearly 100 entries in total - far exceeding initial expectations, given the difficult nature of the challenge. "We were completely taken aback both by the quantity and the quality of the images that were submitted. This was not a challenge for the faint-hearted, requiring both an advanced knowledge of data processing and an artistic eye. We are thrilled to have discovered so many talented people," said Lars Lindberg Christensen, Head of ESO's education and Public Outreach Department. Digging through many terabytes of professional astronomical data, the entrants had to identify a series of greyscale images of a celestial object that would reveal the hidden beauty of our Universe. The chance of a great reward for the lucky winner was enough to spur on the competitors; the first prize being a trip to ESO's Very Large Telescope in Paranal, Chile, with guided tours and the opportunity to participate in a night's observations. Runner-up prizes included an iPod, books and DVDs. Furthermore, the highest ranked images will be released for the world to see on www.eso.org as Photo Releases or Pictures of the Week, co-crediting the winners. The jury evaluated the entries based on the quality of the data processing, the originality of the image and the overall aesthetic feel. As several of the highest ranked images were submitted by the same people, the jury decided to make awards to the ten most talented participants, so as to give more people the opportunity to win a prize and reward their hard work and talent. The ten winners of the competition are: * First prize, a trip to Paranal + goodies: Igor Chekalin (Russia). * Second prize, an iPod Touch + goodies: Sergey Stepanenko (Ukraine). * Third Prize, VLT laser cube model + goodies: Andy Strappazzon (Belgium). * Fourth to tenth prizes, Eyes on the Skies Book + DVD + goodies: Joseph (Joe) DePasquale (USA), Manuel (Manu) Mejias (Argentina), Alberto Milani (Italy), Joshua (Josh) Barrington (USA), Oleg Maliy (Ukraine), Adam Kiil (United Kingdom), Javier Fuentes (Chile). The ten winners submitted the twenty highest ranked images: 1. M78 by Igor Chekalin. 2. NGC3169 & NGC3166 and SN 2003cg by Igor Chekalin. 3. NGC6729 by Sergey Stepanenko. 4. The Moon by Andy Strappazzon. 5. NGC 3621 by Joseph (Joe) DePasquale. 6. NGC 371 by Manuel (Manu) Mejias. 7. Dust of Orion Nebula (ESO 2.2m telescope) by Igor Chekalin. 8. NGC1850 EMMI by Sergey Stepanenko. 9. Abell 1060 by Manuel (Manu) Mejias. 10. Celestial Prominences NGC3582 by Joseph DePasquale. 11. Globular Cluster NGC288 by Alberto Milani. 12. Antennae Galaxies by Alberto Milani. 13. Sakurai's Object by Joshua (Josh) Barrington. 14. NGC 1929, N44 Superbubble by Manuel (Manu) Mejias. 15. NGC 3521 by Oleg Maliy. 16. NGC 6744 by Andy Strappazzon. 17. NGC 2217 by Oleg Maliy. 18. VIMOS.2008-01-31T07_16_47j by Adam Kiil. 19. NGC 2467 - number 2 by Josh Barrington. 20. Haffner 18 and 19 by Javier Fuentes. Igor Chekalin, winner of the trip to Paranal, says: "It was a great experience and pleasure to work with such amazing data. As an amateur astrophotographer, this was the most difficult processing and post-processing job I have ever done. My participation in the Hidden Treasures competition gave me a range of challenges, from installing new software to studying techniques and even operating systems that I did not know before." The success of the ESO's Hidden Treasures 2010 competition and the enthusiasm of the skilled participants made it easy to decide to run a follow-up to the competition. Stay tuned and check www.eso.org for news about ESO's Hidden Treasures 2011. More information ESO, the European Southern Observatory, is the foremost intergovernmental astronomy organisation in Europe and the world's most productive astronomical observatory. It is supported by 15 countries: Austria, Belgium, Brazil, the Czech Republic, Denmark, France, Finland, Germany, Italy, the Netherlands, Portugal, Spain, Sweden, Switzerland and the United Kingdom. ESO carries out an ambitious programme focused on the design, construction and operation of powerful ground-based observing facilities enabling astronomers to make important scientific discoveries. ESO also plays a leading role in promoting and organising cooperation in astronomical research. ESO operates three unique world-class observing sites in Chile: La Silla, Paranal and Chajnantor. At Paranal, ESO operates the Very Large Telescope, the world's most advanced visible-light astronomical observatory and VISTA, the world's largest survey telescope. ESO is the European partner of a revolutionary astronomical telescope ALMA, the largest astronomical project in existence. ESO is currently planning a 42-metre European Extremely Large optical/near-infrared Telescope, the E-ELT, which will become "the world's biggest eye on the sky".

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

NASA Astrophysics Data System (ADS)

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A. A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-12-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool.

Production of individualized V gene databases reveals high levels of immunoglobulin genetic diversity

PubMed Central

Corcoran, Martin M.; Phad, Ganesh E.; Bernat, Néstor Vázquez; Stahl-Hennig, Christiane; Sumida, Noriyuki; Persson, Mats A.A.; Martin, Marcel; Hedestam, Gunilla B. Karlsson

2016-01-01

Comprehensive knowledge of immunoglobulin genetics is required to advance our understanding of B cell biology. Validated immunoglobulin variable (V) gene databases are close to completion only for human and mouse. We present a novel computational approach, IgDiscover, that identifies germline V genes from expressed repertoires to a specificity of 100%. IgDiscover uses a cluster identification process to produce candidate sequences that, once filtered, results in individualized germline V gene databases. IgDiscover was tested in multiple species, validated by genomic cloning and cross library comparisons and produces comprehensive gene databases even where limited genomic sequence is available. IgDiscover analysis of the allelic content of the Indian and Chinese-origin rhesus macaques reveals high levels of immunoglobulin gene diversity in this species. Further, we describe a novel human IGHV3-21 allele and confirm significant gene differences between Balb/c and C57BL6 mouse strains, demonstrating the power of IgDiscover as a germline V gene discovery tool. PMID:27995928

Knowledge Management in Consultancies and High-Tech Companies: A Social Systems Perspective

ERIC Educational Resources Information Center

Kasper, Helmut; Muhlbacher, Jurgen; Muller, Barbara

2008-01-01

In dealing with Knowledge Management (KM) literature, we have to diagnose three essential points: first, we have detected a lack of comprehensive theoretical models based on "grand theories", secondly, we have discovered an overemphasis of "good" values, like openness and trust, that help organisations to learn. And thirdly, we have to recognise…

What Can Be Learned from a Comparison of Two Agricultural Knowledge Systems? The Case of the Netherlands and Israel.

ERIC Educational Resources Information Center

Blum, Abraham

1991-01-01

Compared the agricultural knowledge systems (AKS) of the Netherlands and Israel; analyzed the features that made the systems effective and applicable to other countries. The analysis discovered eight elements that explain the success of these AKSs and demonstrated the value of comparative case studies. (JOW)

The Alchemy of Art: Transforming Student Art into Science Knowledge in the Chemistry Classroom

ERIC Educational Resources Information Center

Flores, Mickie

2005-01-01

Art provides students a way to visually represent their scientific knowledge and at the same time helps teachers assess student understanding. Examining a drawing allows teachers to scrutinize students' mental model of a science concept. Science can be described as a continuing process of discovering the order and recurring patterns in nature;…

Are They Living What They Learn?: Assessing Knowledge and Attitude Change in Introductory Politics Courses

ERIC Educational Resources Information Center

Martin, Pamela; Tankersley, Holley; Ye, Min

2012-01-01

Many assessment studies are devoted to discovering whether student knowledge increases after successful completion of a specific course; fewer studies attempt to examine whether students undergo a change in their values and attitudes as a result of that coursework. Given the continuing emphasis on assessment and the fulfillment of core curriculum…

Technological Innovation: Higher Education, Small Manufacturing Enterprises Growth and the Five (I) Technological Development Model in Kenya

ERIC Educational Resources Information Center

Ng'ang'a, S. I.; Kabethi, J. M.; Kiumbe, P. M.; Otii, Leonard

2014-01-01

In Less Developed Countries (LDCs), most graduates from higher institutions of learning are absorbed in the informal sector and/or micro and small enterprises. Knowledge development through training, research and experiential learning may lead to creating or discovering new knowledge/technology or creating new value, by applying…

Child Maltreatment: Optimizing Recognition and Reporting by School Nurses.

PubMed

Jordan, Kathleen S; MacKay, Peggy; Woods, Stephanie J

2017-05-01

School nurses perform a crucial role in the prevention, identification, intervention, and reporting of child maltreatment. The purpose of this article is to share the highlights of a research project conducted to (a) examine the effectiveness of an educational intervention program in increasing the knowledge, confidence, and self-efficacy in school nurses regarding children at risk of maltreatment; and (b) discover issues surrounding the comfort level engaging with children, communicating with teachers and other personnel, and ethical issues. The study consisted of two phases. Phase 1 was a face-to-face evidenced-based educational intervention. Focus groups implemented in Phase 2 discovered specific concerns of school nurses. Results indicate a significant increase in school nurse knowledge, confidence, and self-efficacy related to children at risk. Five themes were identified from the focus groups: the importance of interprofessional collaboration, identifiers of children at risk of maltreatment, the role of the school nurse as a mentor and leader, the importance of advancing one's knowledge and skill set, and constraints faced by school nurses.

A New Paradigm Hidden in Steganography

DTIC Science & Technology

2000-01-01

In steganography , we do not make the \\strong" assumption that Eve has knowledge of the steganographic algorithm . This is why there may, or may not be...the n least signi cant bits ( LSB ) of each pixel in the cov- erimage, with the n most signi cant bits (MSB) from the corresponding pixel of the image to...e.g., 2 LSB are (0,0) ) to 3 (e.g., 2 LSB are (1,1) ), it is visually impossible for Eve to detect the steganography . Of course, if Eve has knowl

Understanding inference as a source of knowledge: children's ability to evaluate the certainty of deduction, perception, and guessing.

PubMed

Pillow, B H; Hill, V; Boyce, A; Stein, C

2000-03-01

Three experiments investigated children's understanding of inference as a source of knowledge. Children observed a puppet make a statement about the color of one of two hidden toys after the puppet (a) looked directly at the toy (looking), (b) looked at the other toy (inference), or (c) looked at neither toy (guessing). Most 4-, 5-, and 6-year-olds did not rate the puppet as being more certain of the toy's color after the puppet looked directly at it or inferred its color than they did after the puppet guessed its color. Most 8 and 9-year-olds distinguished inference and looking from guessing. The tendency to explain the puppet's knowledge by referring to inference increased with age. Children who referred to inference in their explanations were more likely to judge deductive inference as more certain than guessing.

The public understanding of nanotechnology in the food domain: the hidden role of views on science, technology, and nature.

PubMed

Vandermoere, Frederic; Blanchemanche, Sandrine; Bieberstein, Andrea; Marette, Stephan; Roosen, Jutta

2011-03-01

In spite of great expectations about the potential of nanotechnology, this study shows that people are rather ambiguous and pessimistic about nanotechnology applications in the food domain. Our findings are drawn from a survey of public perceptions about nanotechnology food and nanotechnology food packaging (N = 752). Multinomial logistic regression analyses further reveal that knowledge about food risks and nanotechnology significantly influences people's views about nanotechnology food packaging. However, knowledge variables were unrelated to support for nanofood, suggesting that an increase in people's knowledge might not be sufficient to bridge the gap between the excitement some business leaders in the food sector have and the restraint of the public. Additionally, opposition to nanofood was not related to the use of heuristics but to trust in governmental agencies. Furthermore, the results indicate that public perceptions of nanoscience in the food domain significantly relate to views on science, technology, and nature.

Escape from metaignorance: how children develop an understanding of their own lack of knowledge.

PubMed

Rohwer, Michael; Kloo, Daniela; Perner, Josef

2012-11-01

Previous research yielded conflicting results about when children can accurately assess their epistemic states in different hiding tasks. In Experiment 1, ninety-two 3- to 7-year-olds were either shown which object was hidden inside a box, were totally ignorant about what it could be, or were presented with two objects one of which was being put inside (partial exposure). Even 3-year-olds could assess their epistemic states in the total ignorance and the complete knowledge task. However, only children older than 5 could assess their ignorance in the partial exposure task. In Experiment 2 with one hundred and one 3- to 7-year-olds, similar results were found for children under 5 years even when more objects were shown in partial exposure tasks. Implications for children's developing theory of knowledge are discussed. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Application of Weka environment to determine factors that stand behind non-alcoholic fatty liver disease (NAFLD)

NASA Astrophysics Data System (ADS)

Plutecki, Michal M.; Wierzbicka, Aldona; Socha, Piotr; Mulawka, Jan J.

2009-06-01

The paper describes an innovative approach to discover new knowledge in non-alcoholic fatty liver disease (NAFLD). In order to determine the factors that may cause the disease a number of classification and attribute selection algorithms have been applied. Only those with the best classification results were chosen. Several interesting facts associated with this unclear disease have been discovered. All data mining computations were made in Weka environment.

Exciting discoveries of strong gravitational lenses from the HSC Survey

NASA Astrophysics Data System (ADS)

More, Anupreeta; Team 1: Masayuki Tanaka, Kenneth Wong, et al.; Team 2: Chien-Hsiu Lee, Masamune Oguri, et al.

2017-01-01

Strong gravitational lenses have numerous applications in astrophysics and cosmology. We expect to discover thousands of strong gravitational lenses from the Hyper Suprime-Cam (HSC) Survey, thanks to its unique combination of deep and wide imaging. I will give highlights on a few interesting gravitational lenses that were discovered recently from early HSC data, for example, the first spectroscopically confirmed double source plane (DSP) lens system dubbed ''Eye of Horus'' and the highest-redshift quadruply-lensed low-luminosity Active Galactic Nucleus (LLAGN).DSP lenses such as ''Eye of Horus'' are even more rare than ordinary lenses but provide tighter constraints on the lens mass distribution and can also be useful to measure cosmological parameters such as Dark Energy and Matter density parameter. The lensed LLAGN discovered recently from HSC is only the second such lens system in our knowledge. LLAGNs are thought to have differentmechanisms driving their nuclear activity compared to their brighter counterparts i.e. quasars. Our knowledge about this abundant but faint population of AGNs is limited to the local universe so far. But lensing magnification will allow studies of distant LLAGNs which should be discovered in large numbers from a deep survey like HSC for the first time. Also, owing to the variable nature of LLAGNs, they could potentially be used as a cosmological probe similar to the lensed quasars.

Multiagent data warehousing and multiagent data mining for cerebrum/cerebellum modeling

NASA Astrophysics Data System (ADS)

Zhang, Wen-Ran

2002-03-01

An algorithm named Neighbor-Miner is outlined for multiagent data warehousing and multiagent data mining. The algorithm is defined in an evolving dynamic environment with autonomous or semiautonomous agents. Instead of mining frequent itemsets from customer transactions, the new algorithm discovers new agents and mining agent associations in first-order logic from agent attributes and actions. While the Apriori algorithm uses frequency as a priory threshold, the new algorithm uses agent similarity as priory knowledge. The concept of agent similarity leads to the notions of agent cuboid, orthogonal multiagent data warehousing (MADWH), and multiagent data mining (MADM). Based on agent similarities and action similarities, Neighbor-Miner is proposed and illustrated in a MADWH/MADM approach to cerebrum/cerebellum modeling. It is shown that (1) semiautonomous neurofuzzy agents can be identified for uniped locomotion and gymnastic training based on attribute relevance analysis; (2) new agents can be discovered and agent cuboids can be dynamically constructed in an orthogonal MADWH, which resembles an evolving cerebrum/cerebellum system; and (3) dynamic motion laws can be discovered as association rules in first order logic. Although examples in legged robot gymnastics are used to illustrate the basic ideas, the new approach is generally suitable for a broad category of data mining tasks where knowledge can be discovered collectively by a set of agents from a geographically or geometrically distributed but relevant environment, especially in scientific and engineering data environments.

Visualising nursing data using correspondence analysis.

PubMed

Kokol, Peter; Blažun Vošner, Helena; Železnik, Danica

2016-09-01

Digitally stored, large healthcare datasets enable nurses to use 'big data' techniques and tools in nursing research. Big data is complex and multi-dimensional, so visualisation may be a preferable approach to analyse and understand it. To demonstrate the use of visualisation of big data in a technique called correspondence analysis. In the authors' study, relations among data in a nursing dataset were shown visually in graphs using correspondence analysis. The case presented demonstrates that correspondence analysis is easy to use, shows relations between data visually in a form that is simple to interpret, and can reveal hidden associations between data. Correspondence analysis supports the discovery of new knowledge. Implications for practice Knowledge obtained using correspondence analysis can be transferred immediately into practice or used to foster further research.

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.

NIDA for Teens

MedlinePlus

... Test Your Knowledge Tech-wise: Discovering Medications by Computer Sleep Is Your Brain’s Best Friend See All Blog Items Activities, Games, and More Addiction Science Award Videos About Us Accessibility FOIA NIH Home ...

A meta-cognitive learning algorithm for a Fully Complex-valued Relaxation Network.

PubMed

Savitha, R; Suresh, S; Sundararajan, N

2012-08-01

This paper presents a meta-cognitive learning algorithm for a single hidden layer complex-valued neural network called "Meta-cognitive Fully Complex-valued Relaxation Network (McFCRN)". McFCRN has two components: a cognitive component and a meta-cognitive component. A Fully Complex-valued Relaxation Network (FCRN) with a fully complex-valued Gaussian like activation function (sech) in the hidden layer and an exponential activation function in the output layer forms the cognitive component. The meta-cognitive component contains a self-regulatory learning mechanism which controls the learning ability of FCRN by deciding what-to-learn, when-to-learn and how-to-learn from a sequence of training data. The input parameters of cognitive components are chosen randomly and the output parameters are estimated by minimizing a logarithmic error function. The problem of explicit minimization of magnitude and phase errors in the logarithmic error function is converted to system of linear equations and output parameters of FCRN are computed analytically. McFCRN starts with zero hidden neuron and builds the number of neurons required to approximate the target function. The meta-cognitive component selects the best learning strategy for FCRN to acquire the knowledge from training data and also adapts the learning strategies to implement best human learning components. Performance studies on a function approximation and real-valued classification problems show that proposed McFCRN performs better than the existing results reported in the literature. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Determination of Children's Knowledge of Global Lunar Patterns from Online Essays Using Text Mining Analysis

ERIC Educational Resources Information Center

Cheon, Jongpil; Lee, Sangno; Smith, Walter; Song, Jaeki; Kim, Yongjin

2013-01-01

The purpose of this study was to use text mining analysis of early adolescents' online essays to determine their knowledge of global lunar patterns. Australian and American students in grades five to seven wrote about global lunar patterns they had discovered by sharing observations with each other via the Internet. These essays were analyzed for…

The Effects of University Mergers in China since 1990s: From the Perspective of Knowledge Production

ERIC Educational Resources Information Center

Mao, Ya-qing; Du, Yuan; Liu, Jing-juan

2009-01-01

Purpose: The purpose of this paper is to discover and better understand the efficiency of university mergers from the perspective of knowledge production, with the research capability as the point of contact. Design/methodology/approach: In total, 20 colleges and universities directly under the central ministries that merged in 2000 were taken as…

Virtual Chemistry Laboratory: Effect of Constructivist Learning Environment

ERIC Educational Resources Information Center

Tatli, Zeynep; Ayas, Alipasa

2012-01-01

The lab applications, which were started to be applied through mid 19th century, not only provide a new point of view but also bring about a new dimension to the lessons. At early times they were used to prove theoretical knowledge but lately they turned into environments where students freely discover knowledge as an individual or in groups. The…

Analysis of mesenchymal stem cell differentiation in vitro using classification association rule mining.

PubMed

Wang, Weiqi; Wang, Yanbo Justin; Bañares-Alcántara, René; Coenen, Frans; Cui, Zhanfeng

2009-12-01

In this paper, data mining is used to analyze the data on the differentiation of mammalian Mesenchymal Stem Cells (MSCs), aiming at discovering known and hidden rules governing MSC differentiation, following the establishment of a web-based public database containing experimental data on the MSC proliferation and differentiation. To this effect, a web-based public interactive database comprising the key parameters which influence the fate and destiny of mammalian MSCs has been constructed and analyzed using Classification Association Rule Mining (CARM) as a data-mining technique. The results show that the proposed approach is technically feasible and performs well with respect to the accuracy of (classification) prediction. Key rules mined from the constructed MSC database are consistent with experimental observations, indicating the validity of the method developed and the first step in the application of data mining to the study of MSCs.

Modeling-Enabled Systems Nutritional Immunology

PubMed Central

Verma, Meghna; Hontecillas, Raquel; Abedi, Vida; Leber, Andrew; Tubau-Juni, Nuria; Philipson, Casandra; Carbo, Adria; Bassaganya-Riera, Josep

2016-01-01

This review highlights the fundamental role of nutrition in the maintenance of health, the immune response, and disease prevention. Emerging global mechanistic insights in the field of nutritional immunology cannot be gained through reductionist methods alone or by analyzing a single nutrient at a time. We propose to investigate nutritional immunology as a massively interacting system of interconnected multistage and multiscale networks that encompass hidden mechanisms by which nutrition, microbiome, metabolism, genetic predisposition, and the immune system interact to delineate health and disease. The review sets an unconventional path to apply complex science methodologies to nutritional immunology research, discovery, and development through “use cases” centered around the impact of nutrition on the gut microbiome and immune responses. Our systems nutritional immunology analyses, which include modeling and informatics methodologies in combination with pre-clinical and clinical studies, have the potential to discover emerging systems-wide properties at the interface of the immune system, nutrition, microbiome, and metabolism. PMID:26909350

Hidden patterns of reciprocity.

PubMed

Syi

2014-03-21

Reciprocity can help the evolution of cooperation. To model both types of reciprocity, we need the concept of strategy. In the case of direct reciprocity there are four second-order action rules (Simple Tit-for-tat, Contrite Tit-for-tat, Pavlov, and Grim Trigger), which are able to promote cooperation. In the case of indirect reciprocity the key component of cooperation is the assessment rule. There are, again, four elementary second-order assessment rules (Image Scoring, Simple Standing, Stern Judging, and Shunning). The eight concepts can be formalized in an ontologically thin way we need only an action predicate and a value function, two agent concepts, and the constant of goodness. The formalism helps us to discover that the action and assessment rules can be paired, and that they show the same patterns. The logic of these patterns can be interpreted with the concept of punishment that has an inherent paradoxical nature. Copyright © 2013 Elsevier Ltd. All rights reserved.

Life and Death on Mars and Earth

NASA Technical Reports Server (NTRS)

Zahnle, K. J.; Sleep, N. H.

1999-01-01

Failure to discover life on Mars has led a great many experts to conclude that it must be hiding. Where? The likeliest hiding places are deep beneath the surface, where geothermal heat could permit liquid water. In this the search for life on Mars parallels the search for water on Mars. Liquid water has been, at least on occasion, a geologically significant presence on the surface. Channels were cut and plains dissected. This water is now hidden, in all likelihood having drained to the base of the porous regolith, where it fills possibly frozen aquifers. Presumably any surviving biota has followed the water from the surface to its hiding places in the deep. Accordingly, we have extended our environmental impact assessment of the environmental hazards posed by large asteroid and comet impacts to Mars, and compare its case to Earth's. In particular, we address the continuous habitability of surface and subsurface environments.

Cardiac data mining (CDM); organization and predictive analytics on biomedical (cardiac) data

NASA Astrophysics Data System (ADS)

Bilal, M. Musa; Hussain, Masood; Basharat, Iqra; Fatima, Mamuna

2013-10-01

Data mining and data analytics has been of immense importance to many different fields as we witness the evolution of data sciences over recent years. Biostatistics and Medical Informatics has proved to be the foundation of many modern biological theories and analysis techniques. These are the fields which applies data mining practices along with statistical models to discover hidden trends from data that comprises of biological experiments or procedures on different entities. The objective of this research study is to develop a system for the efficient extraction, transformation and loading of such data from cardiologic procedure reports given by Armed Forces Institute of Cardiology. It also aims to devise a model for the predictive analysis and classification of this data to some important classes as required by cardiologists all around the world. This includes predicting patient impressions and other important features.

Geophysical, geochemical, and geological investigations of the Dunes geothermal system, Imperial Valley, California

NASA Technical Reports Server (NTRS)

Elders, W. A.; Combs, J.; Coplen, T. B.; Kolesar, P.; Bird, D. K.

1974-01-01

The Dunes anomaly is a water-dominated geothermal system in the alluvium of the Salton Trough, lacking any surface expression. It was discovered by shallow-temperature gradient measurements. A 612-meter-deep test well encountered several temperature-gradient reversals, with a maximum of 105 C at 114 meters. The program involves surface geophysics, including electrical, gravity, and seismic methods, down-hole geophysics and petrophysics of core samples, isotopic and chemical studies of water samples, and petrological and geochemical studies of the cores and cuttings. The aim is (1) to determine the source and temperature history of the brines, (2) to understand the interaction between the brines and rocks, and (3) to determine the areal extent, nature, origin, and history of the geothermal system. These studies are designed to provide better definition of exploration targets for hidden geothermal anomalies and to contribute to improved techniques of exploration and resource assessment.

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.

Rapid experimental SAD phasing and hot-spot identification with halogenated fragments

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

Bauman, Joseph D.; Harrison, Jerry Joe E. K.; Arnold, Eddy

2016-01-01

Through X-ray crystallographic fragment screening, 4-bromopyrazole was discovered to be a `magic bullet' that is capable of binding at many of the ligand `hot spots' found in HIV-1 reverse transcriptase (RT). The binding locations can be in pockets that are `hidden' in the unliganded crystal form, allowing rapid identification of these sites forin silicoscreening. In addition to hot-spot identification, this ubiquitous yet specific binding provides an avenue for X-ray crystallographic phase determination, which can be a significant bottleneck in the determination of the structures of novel proteins. The anomalous signal from 4-bromopyrazole or 4-iodopyrazole was sufficient to determine the structuresmore » of three proteins (HIV-1 RT, influenza A endonuclease and proteinase K) by single-wavelength anomalous dispersion (SAD) from single crystals. Both compounds are inexpensive, readily available, safe and very soluble in DMSO or water, allowing efficient soaking into crystals.« less

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

Integrated Taxonomy Reveals Hidden Diversity in Northern Australian Fishes: A New Species of Seamoth (Genus Pegasus)

PubMed Central

Osterhage, Deborah; Pogonoski, John J.; Appleyard, Sharon A.; White, William T.

2016-01-01

Fishes are one of the most intensively studied marine taxonomic groups yet cryptic species are still being discovered. An integrated taxonomic approach is used herein to delineate and describe a new cryptic seamoth (genus Pegasus) from what was previously a wide-ranging species. Preliminary mitochondrial DNA barcoding indicated possible speciation in Pegasus volitans specimens collected in surveys of the Torres Strait and Great Barrier Reef off Queensland in Australia. Morphological and meristic investigations found key differences in a number of characters between P. volitans and the new species, P. tetrabelos. Further mt DNA barcoding of both the COI and the slower mutating 16S genes of additional specimens provided strong support for two separate species. Pegasus tetrabelos and P. volitans are sympatric in northern Australia and were frequently caught together in trawls at the same depths. PMID:26934529

Pulsar-irradiated stars in dense globular clusters

NASA Technical Reports Server (NTRS)

Tavani, Marco

1992-01-01

We discuss the properties of stars irradiated by millisecond pulsars in 'hard' binaries of dense globular clusters. Irradiation by a relativistic pulsar wind as in the case of the eclipsing millisecond pulsar PSR 1957+20 alter both the magnitude and color of the companion star. Some of the blue stragglers (BSs) recently discovered in dense globular clusters can be irradiated stars in binaries containing powerful millisecond pulsars. The discovery of pulsar-driven orbital modulations of BS brightness and color with periods of a few hours together with evidence for radio and/or gamma-ray emission from BS binaries would valuably contribute to the understanding of the evolution of collapsed stars in globular clusters. Pulsar-driven optical modulation of cluster stars might be the only observable effect of a new class of binary pulsars, i.e., hidden millisecond pulsars enshrouded in the evaporated material lifted off from the irradiated companion star.

A dedicated network for social interaction processing in the primate brain.

PubMed

Sliwa, J; Freiwald, W A

2017-05-19

Primate cognition requires interaction processing. Interactions can reveal otherwise hidden properties of intentional agents, such as thoughts and feelings, and of inanimate objects, such as mass and material. Where and how interaction analyses are implemented in the brain is unknown. Using whole-brain functional magnetic resonance imaging in macaque monkeys, we discovered a network centered in the medial and ventrolateral prefrontal cortex that is exclusively engaged in social interaction analysis. Exclusivity of specialization was found for no other function anywhere in the brain. Two additional networks, a parieto-premotor and a temporal one, exhibited both social and physical interaction preference, which, in the temporal lobe, mapped onto a fine-grain pattern of object, body, and face selectivity. Extent and location of a dedicated system for social interaction analysis suggest that this function is an evolutionary forerunner of human mind-reading capabilities. Copyright © 2017, American Association for the Advancement of Science.

A synopsis of centipedes in Brazilian caves: hidden species diversity that needs conservation (Myriapoda, Chilopoda)

PubMed Central

Chagas-Jr, Amazonas; Bichuette, Maria Elina

2018-01-01

Abstract This study revises centipede fauna found in Brazilian caves, focusing on troglomorphic taxa and emphasizing conservation status. We present 563 centipede specimens from 274 caves across eleven Brazilian states. Of these, 22 records were derived from existing literature and 252 are newly collected. Specimens represent four orders, ten families, 18 genera, and 47 morphospecies. Together, the cave records represent 21 % of Brazil’s centipede fauna. Scolopendromorpha was the most representative order (41 %), followed by Geophilomorpha (26 %), Scutigeromorpha (23 %), and Lithobiomorpha (10 %). Six species were found only in caves, with four considered troglobitic. The distribution of Cryptops iporangensis, the first Brazilian troglobitic centipede species to be discovered, was expanded to other three caves. Cryptops spelaeoraptor and Cryptops iporangensis are two troglobitic species considered Vulnerable and Endangered, respectively, according to the IUCN Red List. Main threats to Brazilian caves are mining, hydroelectric projects, water pollution, and unregulated tourism. PMID:29674871

Taare Zameen Par and dyslexic savants

PubMed Central

Chakravarty, Ambar

2009-01-01

The film Taare Zameen Par (Stars upon the Ground) portrays the tormented life at school and at home of a child with dyslexia and his eventual success after his artistic talents are discovered by his art teacher at the boarding school. The film hints at a curious neurocognitive phenomenon of creativity in the midst of language disability, as exemplified in the lives of people like Leonardo da Vinci and Albert Einstein, both of whom demonstrated extraordinary creativity even though they were probably affected with developmental learning disorders. It has been hypothesized that a developmental delay in the dominant hemisphere most likely ‘disinhibits’ the nondominant parietal lobe, unmasking talents—artistic or otherwise—in some such individuals. It has been suggested that, in remedial training, children with learning disorders be encouraged to develop such hidden talents to full capacity, rather than be subjected to the usual overemphasis on the correction of the disturbed coded symbol operations. PMID:20142854

Taare Zameen Par and dyslexic savants.

PubMed

Chakravarty, Ambar

2009-04-01

The film Taare Zameen Par (Stars upon the Ground) portrays the tormented life at school and at home of a child with dyslexia and his eventual success after his artistic talents are discovered by his art teacher at the boarding school. The film hints at a curious neurocognitive phenomenon of creativity in the midst of language disability, as exemplified in the lives of people like Leonardo da Vinci and Albert Einstein, both of whom demonstrated extraordinary creativity even though they were probably affected with developmental learning disorders. It has been hypothesized that a developmental delay in the dominant hemisphere most likely 'disinhibits' the nondominant parietal lobe, unmasking talents-artistic or otherwise-in some such individuals. It has been suggested that, in remedial training, children with learning disorders be encouraged to develop such hidden talents to full capacity, rather than be subjected to the usual overemphasis on the correction of the disturbed coded symbol operations.

Impact of an Advanced Cardiac Life Support Simulation Laboratory Experience on Pharmacy Student Confidence and Knowledge.

PubMed

Maxwell, Whitney D; Mohorn, Phillip L; Haney, Jason S; Phillips, Cynthia M; Lu, Z Kevin; Clark, Kimberly; Corboy, Alex; Ragucci, Kelly R

2016-10-25

Objective. To assess the impact of an advanced cardiac life support (ACLS) simulation on pharmacy student confidence and knowledge. Design. Third-year pharmacy students participated in a simulation experience that consisted of team roles training, high-fidelity ACLS simulations, and debriefing. Students completed a pre/postsimulation confidence and knowledge assessment. Assessment. Overall, student knowledge assessment scores and student confidence scores improved significantly. Student confidence and knowledge changes from baseline were not significantly correlated. Conversely, a significant, weak positive correlation between presimulation studying and both presimulation confidence and presimulation knowledge was discovered. Conclusions. Overall, student confidence and knowledge assessment scores in ACLS significantly improved from baseline; however, student confidence and knowledge were not significantly correlated.

Base changes in tumour DNA have the power to reveal the causes and evolution of cancer

DOE PAGES

Hollstein, M.; Alexandrov, L. B.; Wild, C. P.; ...

2016-06-06

Next-generation sequencing (NGS) technology has demonstrated that the cancer genomes are peppered with mutations. Although most somatic tumour mutations are unlikely to have any role in the cancer process per se, the spectra of DNA sequence changes in tumour mutation catalogues have the potential to identify the mutagens, and to reveal the mutagenic processes responsible for human cancer. Very recently, a novel approach for data mining of the vast compilations of tumour NGS data succeeded in separating and precisely defining at least 30 distinct patterns of sequence change hidden in mutation databases. At least half of these mutational signatures canmore » be readily assigned to known human carcinogenic exposures or endogenous mechanisms of mutagenesis. A quantum leap in our knowledge of mutagenesis in human cancers has resulted, stimulating a flurry of research activity. We trace here the major findings leading first to the hypothesis that carcinogenic insults leave characteristic imprints on the DNA sequence of tumours, and culminating in empirical evidence from NGS data that well-defined carcinogen mutational signatures are indeed present in tumour genomic DNA from a variety of cancer types. The notion that tumour DNAs can divulge environmental sources of mutation is now a well-accepted fact. This approach to cancer aetiology has also incriminated various endogenous, enzyme-driven processes that increase the somatic mutation load in sporadic cancers. The tasks now confronting the field of molecular epidemiology are to assign mutagenic processes to orphan and newly discovered tumour mutation patterns, and to determine whether avoidable cancer risk factors influence signatures produced by endogenous enzymatic mechanisms. As a result, innovative research with experimental models and exploitation of the geographical heterogeneity in cancer incidence can address these challenges.« less

Hubble Explores the Hidden Dark Side of a Spiral Galaxy

NASA Image and Video Library

2017-12-08

This shining disk of a spiral galaxy sits approximately 25 million light-years away from Earth in the constellation of Sculptor. Named NGC 24, the galaxy was discovered by British astronomer William Herschel in 1785, and measures some 40,000 light-years across. This picture was taken using the NASA/ESA Hubble Space Telescope’s Advanced Camera for Surveys, known as ACS for short. It shows NGC 24 in detail, highlighting the blue bursts (young stars), dark lanes (cosmic dust), and red bubbles (hydrogen gas) of material peppered throughout the galaxy’s spiral arms. Numerous distant galaxies can also been seen hovering around NGC 24’s perimeter. However, there may be more to this picture than first meets the eye. Astronomers suspect that spiral galaxies like NGC 24 and the Milky Way are surrounded by, and contained within, extended haloes of dark matter. Dark matter is a mysterious substance that cannot be seen; instead, it reveals itself via its gravitational interactions with surrounding material. Its existence was originally proposed to explain why the outer parts of galaxies, including our own, rotate unexpectedly fast, but it is thought to also play an essential role in a galaxy’s formation and evolution. Most of NGC 24’s mass — a whopping 80 percent — is thought to be held within such a dark halo. Image Credit: NASA/ESA NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Base changes in tumour DNA have the power to reveal the causes and evolution of cancer

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

Hollstein, M.; Alexandrov, L. B.; Wild, C. P.

Next-generation sequencing (NGS) technology has demonstrated that the cancer genomes are peppered with mutations. Although most somatic tumour mutations are unlikely to have any role in the cancer process per se, the spectra of DNA sequence changes in tumour mutation catalogues have the potential to identify the mutagens, and to reveal the mutagenic processes responsible for human cancer. Very recently, a novel approach for data mining of the vast compilations of tumour NGS data succeeded in separating and precisely defining at least 30 distinct patterns of sequence change hidden in mutation databases. At least half of these mutational signatures canmore » be readily assigned to known human carcinogenic exposures or endogenous mechanisms of mutagenesis. A quantum leap in our knowledge of mutagenesis in human cancers has resulted, stimulating a flurry of research activity. We trace here the major findings leading first to the hypothesis that carcinogenic insults leave characteristic imprints on the DNA sequence of tumours, and culminating in empirical evidence from NGS data that well-defined carcinogen mutational signatures are indeed present in tumour genomic DNA from a variety of cancer types. The notion that tumour DNAs can divulge environmental sources of mutation is now a well-accepted fact. This approach to cancer aetiology has also incriminated various endogenous, enzyme-driven processes that increase the somatic mutation load in sporadic cancers. The tasks now confronting the field of molecular epidemiology are to assign mutagenic processes to orphan and newly discovered tumour mutation patterns, and to determine whether avoidable cancer risk factors influence signatures produced by endogenous enzymatic mechanisms. As a result, innovative research with experimental models and exploitation of the geographical heterogeneity in cancer incidence can address these challenges.« less

Discovering the Solar System

NASA Astrophysics Data System (ADS)

Jones, Barrie W.

1999-04-01

Discovering the Solar System Barrie W. Jones The Open University, Milton Keynes, UK Discovering the Solar System is a comprehensive, up-to-date account of the Solar System and of the ways in which the various bodies have been investigated and modelled. The approach is thematic, with sequences of chapters on the interiors of planetary bodies, on their surfaces, and on their atmospheres. Within each sequence there is a chapter on general principles and processes followed by one or two chapters on specific bodies. There is also an introductory chapter, a chapter on the origin of the Solar System, and a chapter on asteroids, comets and meteorites. Liberally illustrated with diagrams, black and white photographs and colour plates, Discovering the Solar System also features: * tables of essential data * question and answers within the text * end of section review questions with answers and comments Discovering the Solar System is essential reading for all undergraduate students for whom astronomy or planetary science are components of their degrees, and for those at a more advanced level approaching the subject for the first time. It will also be of great interest to non-specialists with a keen interest in astronomy. A small amount of scientific knowledge is assumed plus familiarity with basic algebra and graphs. There is no calculus. Praise for this book includes: ".certainly qualifies as an authoritative text. The author clearly has an encyclopedic knowledge of the subject." Meteorics and Planetary Science ".liberally doused with relevant graphs, tables, and black and white figures of good quality." EOS, Transactions of the American Geophysical Union ".one of the best books on the Solar System I have seen. The general accuracy and quality of the content is excellent." Journal of the British Astronomical Association

Automated generation of massive image knowledge collections using Microsoft Live Labs Pivot to promote neuroimaging and translational research

PubMed Central

2011-01-01

Background Massive datasets comprising high-resolution images, generated in neuro-imaging studies and in clinical imaging research, are increasingly challenging our ability to analyze, share, and filter such images in clinical and basic translational research. Pivot collection exploratory analysis provides each user the ability to fully interact with the massive amounts of visual data to fully facilitate sufficient sorting, flexibility and speed to fluidly access, explore or analyze the massive image data sets of high-resolution images and their associated meta information, such as neuro-imaging databases from the Allen Brain Atlas. It is used in clustering, filtering, data sharing and classifying of the visual data into various deep zoom levels and meta information categories to detect the underlying hidden pattern within the data set that has been used. Method We deployed prototype Pivot collections using the Linux CentOS running on the Apache web server. We also tested the prototype Pivot collections on other operating systems like Windows (the most common variants) and UNIX, etc. It is demonstrated that the approach yields very good results when compared with other approaches used by some researchers for generation, creation, and clustering of massive image collections such as the coronal and horizontal sections of the mouse brain from the Allen Brain Atlas. Results Pivot visual analytics was used to analyze a prototype of dataset Dab2 co-expressed genes from the Allen Brain Atlas. The metadata along with high-resolution images were automatically extracted using the Allen Brain Atlas API. It is then used to identify the hidden information based on the various categories and conditions applied by using options generated from automated collection. A metadata category like chromosome, as well as data for individual cases like sex, age, and plan attributes of a particular gene, is used to filter, sort and to determine if there exist other genes with a similar characteristics to Dab2. And online access to the mouse brain pivot collection can be viewed using the link http://edtech-dev.uthsc.edu/CTSI/teeDev1/unittest/PaPa/collection.html (user name: tviangte and password: demome) Conclusions Our proposed algorithm has automated the creation of large image Pivot collections; this will enable investigators of clinical research projects to easily and quickly analyse the image collections through a perspective that is useful for making critical decisions about the image patterns discovered. PMID:21884637

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.

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method.

PubMed

Guo, Xinyu; Dominick, Kelli C; Minai, Ali A; Li, Hailong; Erickson, Craig A; Lu, Long J

2017-01-01

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t -test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t -test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided.

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.

Discovering the knowledge creation process of an expert group in women-friendly policy: The policy case of Seoul City.

PubMed

Oh, Young Sam; Nam, SungHee; Kim, Yuna

2016-01-01

This research explores how expert knowledge is created in the process of women-friendly policy making, based on actor network theory (ANT). To address this purpose, this study uses the "Women's Happiness in the City of Seoul" policy initiated by the local government of Seoul as one example of policy development. Research findings demonstrate that knowledge creation in expert groups followed the four stages suggested by ANT. In addition, this study found that various types of knowledge emerged from individual experts. This research elucidates the process of knowledge creation and its meanings for women-friendly policy.

Waving goodbye

NASA Image and Video Library

2015-10-05

This planetary nebula is called PK 329-02.2 and is located in the constellation of Norma in the southern sky. It is also sometimes referred to as Menzel 2, or Mz 2, named after the astronomer Donald Menzel who discovered the nebula in 1922. When stars that are around the mass of the Sun reach their final stages of life, they shed their outer layers into space, which appear as glowing clouds of gas called planetary nebulae. The ejection of mass in stellar burnout is irregular and not symmetrical, so that planetary nebulae can have very complex shapes. In the case of Menzel 2 the nebula forms a winding blue cloud that perfectly aligns with two stars at its centre. In 1999 astronomers discovered that the star at the upper right is in fact the central star of the nebula, and the star to the lower left is probably a true physical companion of the central star. For tens of thousands of years the stellar core will be cocooned in spectacular clouds of gas and then, over a period of a few thousand years, the gas will fade away into the depths of the Universe. The curving structure of Menzel 2 resembles a last goodbye before the star reaches its final stage of retirement as a white dwarf. A version of this image was entered into the Hubble's Hidden Treasures image processing competition by contestant Serge Meunier.

Quantum Nash Equilibria and Quantum Computing

NASA Astrophysics Data System (ADS)

Fellman, Philip Vos; Post, Jonathan Vos

In 2004, At the Fifth International Conference on Complex Systems, we drew attention to some remarkable findings by researchers at the Santa Fe Institute (Sato, Farmer and Akiyama, 2001) about hitherto unsuspected complexity in the Nash Equilibrium. As we progressed from these findings about heteroclinic Hamiltonians and chaotic transients hidden within the learning patterns of the simple rock-paper-scissors game to some related findings on the theory of quantum computing, one of the arguments we put forward was just as in the late 1990's a number of new Nash equilibria were discovered in simple bi-matrix games (Shubik and Quint, 1996; Von Stengel, 1997, 2000; and McLennan and Park, 1999) we would begin to see new Nash equilibria discovered as the result of quantum computation. While actual quantum computers remain rather primitive (Toibman, 2004), and the theory of quantum computation seems to be advancing perhaps a bit more slowly than originally expected, there have, nonetheless, been a number of advances in computation and some more radical advances in an allied field, quantum game theory (Huberman and Hogg, 2004) which are quite significant. In the course of this paper we will review a few of these discoveries and illustrate some of the characteristics of these new "Quantum Nash Equilibria". The full text of this research can be found at http://necsi.org/events/iccs6/viewpaper.php?id-234

Using ADOPT Algorithm and Operational Data to Discover Precursors to Aviation Adverse Events

NASA Technical Reports Server (NTRS)

Janakiraman, Vijay; Matthews, Bryan; Oza, Nikunj

2018-01-01

The US National Airspace System (NAS) is making its transition to the NextGen system and assuring safety is one of the top priorities in NextGen. At present, safety is managed reactively (correct after occurrence of an unsafe event). While this strategy works for current operations, it may soon become ineffective for future airspace designs and high density operations. There is a need for proactive management of safety risks by identifying hidden and "unknown" risks and evaluating the impacts on future operations. To this end, NASA Ames has developed data mining algorithms that finds anomalies and precursors (high-risk states) to safety issues in the NAS. In this paper, we describe a recently developed algorithm called ADOPT that analyzes large volumes of data and automatically identifies precursors from real world data. Precursors help in detecting safety risks early so that the operator can mitigate the risk in time. In addition, precursors also help identify causal factors and help predict the safety incident. The ADOPT algorithm scales well to large data sets and to multidimensional time series, reduce analyst time significantly, quantify multiple safety risks giving a holistic view of safety among other benefits. This paper details the algorithm and includes several case studies to demonstrate its application to discover the "known" and "unknown" safety precursors in aviation operation.

Hello to Arms

NASA Technical Reports Server (NTRS)

2005-01-01

This image highlights the hidden spiral arms (blue) that were discovered around the nearby galaxy NGC 4625 by the ultraviolet eyes of NASA's Galaxy Evolution Explorer.

The image is composed of ultraviolet and visible-light data, from the Galaxy Evolution Explorer and the California Institute of Technology's Digitized Sky Survey, respectively. Near-ultraviolet light is colored green; far-ultraviolet light is colored blue; and optical light is colored red.

As the image demonstrates, the lengthy spiral arms are nearly invisible when viewed in optical light while bright in ultraviolet. This is because they are bustling with hot, newborn stars that radiate primarily ultraviolet light.

The youthful arms are also very long, stretching out to a distance four times the size of the galaxy's core. They are part of the largest ultraviolet galactic disk discovered so far.

Located 31 million light-years away in the constellation Canes Venatici, NGC 4625 is the closest galaxy ever seen with such a young halo of arms. It is slightly smaller than our Milky Way, both in size and mass. However, the fact that this galaxy's disk is forming stars very actively suggests that it might evolve into a more massive and mature galaxy resembling our own.

The armless companion galaxy seen below NGC 4625 is called NGC 4618. Astronomers do not know why it lacks arms but speculate that it may have triggered the development of arms in NGC 4625.

3XMM J185246.6+003317: Another Low Magnetic Field Magnetar

NASA Astrophysics Data System (ADS)

Rea, N.; Viganò, D.; Israel, G. L.; Pons, J. A.; Torres, D. F.

2014-01-01

We study the outburst of the newly discovered X-ray transient 3XMM J185246.6+003317, re-analyzing all available XMM-Newton observations of the source to perform a phase-coherent timing analysis, and derive updated values of the period and period derivative. We find the source rotating at P = 11.55871346(6) s (90% confidence level; at epoch MJD 54728.7) but no evidence for a period derivative in the seven months of outburst decay spanned by the observations. This translates to a 3σ upper limit for the period derivative of \\dot{P}< 1.4\\times 10^{-13} s s-1, which, assuming the classical magneto-dipolar braking model, gives a limit on the dipolar magnetic field of B dip < 4.1 × 1013 G. The X-ray outburst and spectral characteristics of 3XMM J185246.6+003317 confirm its identification as a magnetar, but the magnetic field upper limit we derive defines it as the third "low-B" magnetar discovered in the past 3 yr, after SGR 0418+5729 and Swift J1822.3-1606. We have also obtained an upper limit to the quiescent luminosity (<4 × 1033 erg s-1), in line with the expectations for an old magnetar. The discovery of this new low field magnetar reaffirms the prediction of about one outburst per year from the hidden population of aged magnetars.

a Probabilistic Embedding Clustering Method for Urban Structure Detection

NASA Astrophysics Data System (ADS)

Lin, X.; Li, H.; Zhang, Y.; Gao, L.; Zhao, L.; Deng, M.

2017-09-01

Urban structure detection is a basic task in urban geography. Clustering is a core technology to detect the patterns of urban spatial structure, urban functional region, and so on. In big data era, diverse urban sensing datasets recording information like human behaviour and human social activity, suffer from complexity in high dimension and high noise. And unfortunately, the state-of-the-art clustering methods does not handle the problem with high dimension and high noise issues concurrently. In this paper, a probabilistic embedding clustering method is proposed. Firstly, we come up with a Probabilistic Embedding Model (PEM) to find latent features from high dimensional urban sensing data by "learning" via probabilistic model. By latent features, we could catch essential features hidden in high dimensional data known as patterns; with the probabilistic model, we can also reduce uncertainty caused by high noise. Secondly, through tuning the parameters, our model could discover two kinds of urban structure, the homophily and structural equivalence, which means communities with intensive interaction or in the same roles in urban structure. We evaluated the performance of our model by conducting experiments on real-world data and experiments with real data in Shanghai (China) proved that our method could discover two kinds of urban structure, the homophily and structural equivalence, which means clustering community with intensive interaction or under the same roles in urban space.

The Discovery of a Second Luminous Low Mass X-Ray Binary System in the Globular Cluster M15

NASA Technical Reports Server (NTRS)

White, Nicholas E.; Angelini, Lorella

2001-01-01

Using the Chandra X-ray Observatory we have discovered a second bright X-ray source in the globular cluster M15 that is 2.7" to the west of AC211, the previously known low mass X-ray binary (LMXB) in this system. Prior to the 0.5" imaging capability of Chandra this second source could not have been resolved from AC211. The luminosity and spectrum of this new source, which we call M15-X2, are consistent with it also being a LMXB system. This is the first time that two LMXBs have been seen to be simultaneously active in a globular cluster. The new source, M15-X2, is coincident with a 18th U magnitude very blue star. The discovery of a second LMXB in M15 clears up a long standing puzzle where the X-ray and optical properties of AC211 appear consistent with the central source being hidden behind an accretion disk corona, and yet also showed a luminous X-ray burst suggesting the neutron star is directly visible. This discovery suggests instead that the X-ray burst did not come from AC211, but rather from the newly discovered X-ray source. We discuss the implications of this discovery for X-ray observations of globular clusters in nearby galaxies.

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…

The Circle of Apollonius: A Discovery Activity.

ERIC Educational Resources Information Center

Cain, Ralph W.

1994-01-01

Presents an activity using simple constructions and a knowledge of proportions to discover that the sets of points generated by the described procedures are circles. Presents a proof of the result. (Author/MKR)

Key Relation Extraction from Biomedical Publications.

PubMed

Huang, Lan; Wang, Ye; Gong, Leiguang; Kulikowski, Casimir; Bai, Tian

2017-01-01

Within the large body of biomedical knowledge, recent findings and discoveries are most often presented as research articles. Their number has been increasing sharply since the turn of the century, presenting ever-growing challenges for search and discovery of knowledge and information related to specific topics of interest, even with the help of advanced online search tools. This is especially true when the goal of a search is to find or discover key relations between important concepts or topic words. We have developed an innovative method for extracting key relations between concepts from abstracts of articles. The method focuses on relations between keywords or topic words in the articles. Early experiments with the method on PubMed publications have shown promising results in searching and discovering keywords and their relationships that are strongly related to the main topic of an article.

Functional neuronal processing of human body odors.

PubMed

Lundström, Johan N; Olsson, Mats J

2010-01-01

Body odors carry informational cues of great importance for individuals across a wide range of species, and signals hidden within the body odor cocktail are known to regulate several key behaviors in animals. For a long time, the notion that humans may be among these species has been dismissed. We now know, however, that each human has a unique odor signature that carries information related to his or her genetic makeup, as well as information about personal environmental variables, such as diet and hygiene. Although a substantial number of studies have investigated the behavioral effects of body odors, only a handful have studied central processing. Recent studies have, however, demonstrated that the human brain responds to fear signals hidden within the body odor cocktail, is able to extract kin specific signals, and processes body odors differently than other perceptually similar odors. In this chapter, we provide an overview of the current knowledge of how the human brain processes body odors and the potential importance these signals have for us in everyday life. Copyright © 2010 Elsevier Inc. All rights reserved.

Hidden complexity of free energy surfaces for peptide (protein) folding.

PubMed

Krivov, Sergei V; Karplus, Martin

2004-10-12

An understanding of the thermodynamics and kinetics of protein folding requires a knowledge of the free energy surface governing the motion of the polypeptide chain. Because of the many degrees of freedom involved, surfaces projected on only one or two progress variables are generally used in descriptions of the folding reaction. Such projections result in relatively smooth surfaces, but they could mask the complexity of the unprojected surface. Here we introduce an approach to determine the actual (unprojected) free energy surface and apply it to the second beta-hairpin of protein G, which has been used as a model system for protein folding. The surface is represented by a disconnectivity graph calculated from a long equilibrium folding-unfolding trajectory. The denatured state is found to have multiple low free energy basins. Nevertheless, the peptide shows exponential kinetics in folding to the native basin. Projected surfaces obtained from the present analysis have a simple form in agreement with other studies of the beta-hairpin. The hidden complexity found for the beta-hairpin surface suggests that the standard funnel picture of protein folding should be revisited.

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

Characterization of hidden rules linking symptoms and selection of acupoint using an artificial neural network model.

PubMed

Jung, Won-Mo; Park, In-Soo; Lee, Ye-Seul; Kim, Chang-Eop; Lee, Hyangsook; Hahm, Dae-Hyun; Park, Hi-Joon; Jang, Bo-Hyoung; Chae, Younbyoung

2018-04-12

Comprehension of the medical diagnoses of doctors and treatment of diseases is important to understand the underlying principle in selecting appropriate acupoints. The pattern recognition process that pertains to symptoms and diseases and informs acupuncture treatment in a clinical setting was explored. A total of 232 clinical records were collected using a Charting Language program. The relationship between symptom information and selected acupoints was trained using an artificial neural network (ANN). A total of 11 hidden nodes with the highest average precision score were selected through a tenfold cross-validation. Our ANN model could predict the selected acupoints based on symptom and disease information with an average precision score of 0.865 (precision, 0.911; recall, 0.811). This model is a useful tool for diagnostic classification or pattern recognition and for the prediction and modeling of acupuncture treatment based on clinical data obtained in a real-world setting. The relationship between symptoms and selected acupoints could be systematically characterized through knowledge discovery processes, such as pattern identification.

A University-Industry Collaborative Response to the Growing Global Demand for Student Talent: Using Interpretive Phenomenology to Discover Life-World Knowledge

ERIC Educational Resources Information Center

Vauterin, Johanna Julia; Linnanen, Lassi; Michelsen, Karl-Erik

2013-01-01

The supply of student talent is now taking on an increasingly global dimension and this has extended the breadth of university-industry interaction. Set in the context of a rapidly growing international student market, knowledge transfer between academia and business through global student talent supply is an emerging practice. This paper…

Dynamic Battlefield Visualization: Knowledge Management in a Complex, Emergent PMESII-PT Battlefield

DTIC Science & Technology

2009-06-01

organizations was articulated over two decades ago by Jerome Bruner (1986). Specifically, he argued that humans employ two distinctive modes of...narrative knowledge underscored by the writings of Jerome Bruner , Karl Weick, Laurence Prusak, and John Seely Brown. Finally, it consistently supports...a known battle calculus) and ambiguity (pattern/trend analysis to reveal operational variances or to discover influence mechanisms that can be

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.

Crafting the microworld: how Robert Hooke constructed knowledge about small things

PubMed Central

Lawson, Ian

2016-01-01

This paper investigates the way in which Robert Hooke constructed his microscopical observations. His Micrographia is justifiably famous for its detailed engravings, which communicated Hooke's observations of tiny nature to his readers, but less attention has been paid to how he went about making the observations themselves. In this paper I explore the relationship between the materiality of his instrument and the epistemic images he produced. Behind the pictures lies an array of hidden materials, and the craft knowledge it took to manipulate them. By investigating the often counter-theoretical and conflicting practices of his ingenious microscope use, I demonstrate the way in which Hooke crafted the microworld for his readers, giving insight into how early modern microscopy was understood by its practitioners and audience. PMID:27017680

CRAFTING THE MICROWORLD: HOW ROBERT HOOKE CONSTRUCTED KNOWLEDGE ABOUT SMALL THINGS.

PubMed

Lawson, Ian

2016-03-20

This paper investigates the way in which Robert Hooke constructed his microscopical observations. His Micrographia is justifiably famous for its detailed engravings, which communicated Hooke's observations of tiny nature to his readers, but less attention has been paid to how he went about making the observations themselves. In this paper I explore the relationship between the materiality of his instrument and the epistemic images he produced. Behind the pictures lies an array of hidden materials, and the craft knowledge it took to manipulate them. By investigating the often counter-theoretical and conflicting practices of his ingenious microscope use, I demonstrate the way in which Hooke crafted the microworld for his readers, giving insight into how early modern microscopy was understood by its practitioners and audience.

--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

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.

Science in General Education

ERIC Educational Resources Information Center

Read, Andrew F.

2013-01-01

General education must develop in students an appreciation of the power of science, how it works, why it is an effective knowledge generation tool, and what it can deliver. Knowing what science has discovered is desirable but less important.

A hidden oncogenic positive feedback loop caused by crosstalk between Wnt and ERK pathways.

PubMed

Kim, D; Rath, O; Kolch, W; Cho, K-H

2007-07-05

The Wnt and the extracellular signal regulated-kinase (ERK) pathways are both involved in the pathogenesis of various kinds of cancers. Recently, the existence of crosstalk between Wnt and ERK pathways was reported. Gathering all reported results, we have discovered a positive feedback loop embedded in the crosstalk between the Wnt and ERK pathways. We have developed a plausible model that represents the role of this hidden positive feedback loop in the Wnt/ERK pathway crosstalk based on the integration of experimental reports and employing established basic mathematical models of each pathway. Our analysis shows that the positive feedback loop can generate bistability in both the Wnt and ERK signaling pathways, and this prediction was further validated by experiments. In particular, using the commonly accepted assumption that mutations in signaling proteins contribute to cancerogenesis, we have found two conditions through which mutations could evoke an irreversible response leading to a sustained activation of both pathways. One condition is enhanced production of beta-catenin, the other is a reduction of the velocity of MAP kinase phosphatase(s). This enables that high activities of Wnt and ERK pathways are maintained even without a persistent extracellular signal. Thus, our study adds a novel aspect to the molecular mechanisms of carcinogenesis by showing that mutational changes in individual proteins can cause fundamental functional changes well beyond the pathway they function in by a positive feedback loop embedded in crosstalk. Thus, crosstalk between signaling pathways provides a vehicle through which mutations of individual components can affect properties of the system at a larger scale.

Hierarchically Structured Non-Intrusive Sign Language Recognition. Chapter 2

NASA Technical Reports Server (NTRS)

Zieren, Jorg; Zieren, Jorg; Kraiss, Karl-Friedrich

2007-01-01

This work presents a hierarchically structured approach at the nonintrusive recognition of sign language from a monocular frontal view. Robustness is achieved through sophisticated localization and tracking methods, including a combined EM/CAMSHIFT overlap resolution procedure and the parallel pursuit of multiple hypotheses about hands position and movement. This allows handling of ambiguities and automatically corrects tracking errors. A biomechanical skeleton model and dynamic motion prediction using Kalman filters represents high level knowledge. Classification is performed by Hidden Markov Models. 152 signs from German sign language were recognized with an accuracy of 97.6%.

Empirical Analysis and Refinement of Expert System Knowledge Bases

DTIC Science & Technology

1990-03-31

the number of hidden units and the error rates is listed in Figure 6. 3.3. Cancer Data A data qet for eva!ukting th.- Frognosis of breast cancer ...Alternative Rule Induction Methods A data set for evaluating the prognosis of breast cancer recurrence was analyzed by Michalski’s AQI5 rule induction program...AQ15 7 2 32% PVM 2 1 23% Figure 6-3: Comparative Summa-y for AQI5 and PVM on Breast Cancer Data 6.2.2. Alternative Decision Tree Induction Methods

Altered States of Consciousness

PubMed Central

Butts, June Dobbs

1978-01-01

Medicine, sex, and religion are presented as related areas of human thought and behavior in which people traditionally have sought temporary release from daily living. In essence, these areas represent a search for altered states of consciousness. The harmful way is through drug addiction. Five common characteristics are cited for the three areas. Examples of their universality are traceable by their omnipresence and their appearance in most childhood games—especially those taking on sexual nuances—which are usually hidden from adults. If Eastern knowledge and control of bodily processes were geared to Western technology, mankind would benefit. PMID:712866

[The journey of Legionella pneumophila from amoebae to macrophage. Reflections on the largest outbreak of legionnaire's disease].

PubMed

Segovia Hernández, Manuel

2005-01-01

Legionella, the causative agent of legionnaire's disease (LD), can survive and grow in amoebic cells. Free-living amoebae may play a role in the selection of virulence traits and in adaptation to survival in macrophages, and represent an important reservoir of Legionella. These amoebae may act as a Trojan horse bringing hidden bacteria within the human environments. The community outbreak of LD that occurred in Murcia in July 2001, the largest such outbreak ever reported, afforded an unusual opportunity to improve the knowledge of this disease.

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

Empirical study using network of semantically related associations in bridging the knowledge gap.

PubMed

Abedi, Vida; Yeasin, Mohammed; Zand, Ramin

2014-11-27

The data overload has created a new set of challenges in finding meaningful and relevant information with minimal cognitive effort. However designing robust and scalable knowledge discovery systems remains a challenge. Recent innovations in the (biological) literature mining tools have opened new avenues to understand the confluence of various diseases, genes, risk factors as well as biological processes in bridging the gaps between the massive amounts of scientific data and harvesting useful knowledge. In this paper, we highlight some of the findings using a text analytics tool, called ARIANA--Adaptive Robust and Integrative Analysis for finding Novel Associations. Empirical study using ARIANA reveals knowledge discovery instances that illustrate the efficacy of such tool. For example, ARIANA can capture the connection between the drug hexamethonium and pulmonary inflammation and fibrosis that caused the tragic death of a healthy volunteer in a 2001 John Hopkins asthma study, even though the abstract of the study was not part of the semantic model. An integrated system, such as ARIANA, could assist the human expert in exploratory literature search by bringing forward hidden associations, promoting data reuse and knowledge discovery as well as stimulating interdisciplinary projects by connecting information across the disciplines.

Deep-Subwavelength Resolving and Manipulating of Hidden Chirality in Achiral Nanostructures.

PubMed

Zu, Shuai; Han, Tianyang; Jiang, Meiling; Lin, Feng; Zhu, Xing; Fang, Zheyu

2018-04-24

The chiral state of light plays a vital role in light-matter interactions and the consequent revolution of nanophotonic devices and advanced modern chiroptics. As the light-matter interaction goes into the nano- and quantum world, numerous chiroptical technologies and quantum devices require precise knowledge of chiral electromagnetic modes and chiral radiative local density of states (LDOS) distributions in detail, which directly determine the chiral light-matter interaction for applications such as chiral light detection and emission. With classical optical techniques failing to directly measure the chiral radiative LDOS, deep-subwavelength imaging and control of circular polarization (CP) light associated phenomena are introduced into the agenda. Here, we simultaneously reveal the hidden chiral electromagnetic mode and acquire its chiral radiative LDOS distribution of a single symmetric nanostructure at the deep-subwavelength scale by using CP-resolved cathodoluminescence (CL) microscopy. The chirality of the symmetric nanostructure under normally incident light excitation, resulting from the interference between the symmetric and antisymmetric modes of the V-shaped nanoantenna, is hidden in the near field with a giant chiral distribution (∼99%) at the arm-ends, which enables the circularly polarized CL emission from the radiative LDOS hot-spot and the following active helicity control at the deep-subwavelength scale. The proposed V-shaped nanostructure as a functional unit is further applied to the helicity-dependent binary encoding and the two-dimensional display applications. The proposed physical principle and experimental configuration can promote the future chiral characterization and manipulation at the deep-subwavelength scale and provide direct guidelines for the optimization of chiral light-matter interactions for future quantum studies.

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

PubMed

Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Discovering Communicable Scientific Knowledge from Spatio-Temporal Data

NASA Technical Reports Server (NTRS)

Schwabacher, Mark; Langley, Pat; Norvig, Peter (Technical Monitor)

2001-01-01

This paper describes how we used regression rules to improve upon a result previously published in the Earth science literature. In such a scientific application of machine learning, it is crucially important for the learned models to be understandable and communicable. We recount how we selected a learning algorithm to maximize communicability, and then describe two visualization techniques that we developed to aid in understanding the model by exploiting the spatial nature of the data. We also report how evaluating the learned models across time let us discover an error in the data.

FFY 2007 annual report for the Montana Department of Transportation Research Programs

DOT National Transportation Integrated Search

2008-01-01

The Montana Department of Transportation (MDT) conducts research to discover, develop, or extend knowledge needed to operate, maintain, and improve the statewide multimodal transportation system. Specific goals include: evaluation and advancement of ...

UnCommon Knowledge: Projects That Help Middle-School-Age Youth Discover the Science and Mathematics in Everyday Life. Volume One: Hands-On Science Projects.

ERIC Educational Resources Information Center

Carter, Carolyn S.; Keyes, Marian; Kusimo, Patricia S.; Lunsford, Crystal

This guide contains hands-on science activities to connect middle-school students to the traditional knowledge of their grandparents and elders. Because girls often lose interest in science at the middle-school level, and because women in some communities (especially in rural areas) are seldom involved in work with an obvious science basis, the…

UnCommon Knowledge: Projects That Help Middle-School-Age Youth Discover the Science and Mathematics in Everyday Life. Volume Two: Hands-On Math Projects.

ERIC Educational Resources Information Center

Carter, Carolyn S.; Cohen, Sara; Keyes, Marian; Kusimo, Patricia S.; Lunsford, Crystal

This guide contains hands-on mathematics activities to connect middle-school students to the traditional knowledge of their grandparents and elders. Because girls often lose interest in math at the middle-school level, and because women in some communities (especially in rural areas) are seldom involved in work with an obvious math basis, the…

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

"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

Empirical learning of children at kindergartens

NASA Astrophysics Data System (ADS)

Valovičová, Ľubomíra; Sollárová, Eva

2017-01-01

In the report we propose some results of psychology research, associated with development of kindergarten children's creativity, which in the course of one school year in kindergarten completed activities related to physics. Experience shows that the children at this evolution stage are not only capable of but also interested in discovering and getting to know new things. To this end, it is needed to motivate children and enable them to discover the beauty of physics. One possibility is to create educational activities for kindergarten children. In such activities children can investigate, discover, and indirectly learn physics. The goal is to develop physical thinking, natural sciences knowledge, and their personality and intellectual potential. In realization of some of them children practice their motoric and logical thinking as well as some skills.

The fluid mechanics of nutrition: Herman Boerhaave's synthesis of seventeenth-century circulation physiology.

PubMed

Orland, Barbara

2012-06-01

This paper investigates the theory of nutrition of Herman Boerhaave, the famous professor of medicine and chemistry at the university of Leyden. Boerhaave's work, which systematized and synthesized the knowledge of the time, represents a shift from a humoral to a hydraulic model of the body in medicine and culture around 1700. This epistemological reconfiguration of early modern physiological thinking is exemplified with respect to the changing meanings of milk. While over centuries the analogy between blood and milk played an essential role in understanding the hidden workings of the nutritional faculties, following the discovery of the blood circulation the blood-milk analogy was transformed into a chyle-milk analogy. Yet Boerhaave's interpretations show that the use of new knowledge tools did not simply displace the old ways of reasoning. Instead, analogies continued to serve as epistemic instruments. Old theories and new insights overlapped, and contemporary knowledge assimilated past ideas. Copyright © 2011. Published by Elsevier Ltd.

Sports-related concussion

PubMed Central

Torres, Daniel M.; Galetta, Kristin M.; Phillips, H. Westley; Dziemianowicz, E. Mark S.; Wilson, James A.; Dorman, Emily S.; Laudano, Eric; Galetta, Steven L.

2013-01-01

Summary Studies suggest that a lack of standardized knowledge may lead to underreporting and undertreatment of sports-related concussion. However, there has been little work done to establish how this knowledge may affect athletes’ behaviors toward reporting their concussions and removing themselves from play. We conducted an anonymous online survey to assess athletes’ knowledge of signs and symptoms of concussion, and also sought to estimate the potential frequency of underreporting in a collegiate athlete cohort. Among 262 athletes who responded to the survey, 43% of those with a history of concussion reported that they had knowingly hidden symptoms of a concussion to stay in a game, and 22% of athletes overall indicated that they would be unlikely or very unlikely to report concussion symptoms to a coach or athletic trainer in the future. These data suggest that there may be a substantial degree of underreporting of concussion among collegiate athletes, despite most acknowledging that they have been formally educated about the risks of concussion. PMID:24195017

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.

An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages.

PubMed

Tuarob, Suppawong; Tucker, Conrad S; Salathe, Marcel; Ram, Nilam

2014-06-01

The role of social media as a source of timely and massive information has become more apparent since the era of Web 2.0.Multiple studies illustrated the use of information in social media to discover biomedical and health-related knowledge.Most methods proposed in the literature employ traditional document classification techniques that represent a document as a bag of words.These techniques work well when documents are rich in text and conform to standard English; however, they are not optimal for social media data where sparsity and noise are norms.This paper aims to address the limitations posed by the traditional bag-of-word based methods and propose to use heterogeneous features in combination with ensemble machine learning techniques to discover health-related information, which could prove to be useful to multiple biomedical applications, especially those needing to discover health-related knowledge in large scale social media data.Furthermore, the proposed methodology could be generalized to discover different types of information in various kinds of textual data. Social media data is characterized by an abundance of short social-oriented messages that do not conform to standard languages, both grammatically and syntactically.The problem of discovering health-related knowledge in social media data streams is then transformed into a text classification problem, where a text is identified as positive if it is health-related and negative otherwise.We first identify the limitations of the traditional methods which train machines with N-gram word features, then propose to overcome such limitations by utilizing the collaboration of machine learning based classifiers, each of which is trained to learn a semantically different aspect of the data.The parameter analysis for tuning each classifier is also reported. Three data sets are used in this research.The first data set comprises of approximately 5000 hand-labeled tweets, and is used for cross validation of the classification models in the small scale experiment, and for training the classifiers in the real-world large scale experiment.The second data set is a random sample of real-world Twitter data in the US.The third data set is a random sample of real-world Facebook Timeline posts. Two sets of evaluations are conducted to investigate the proposed model's ability to discover health-related information in the social media domain: small scale and large scale evaluations.The small scale evaluation employs 10-fold cross validation on the labeled data, and aims to tune parameters of the proposed models, and to compare with the stage-of-the-art method.The large scale evaluation tests the trained classification models on the native, real-world data sets, and is needed to verify the ability of the proposed model to handle the massive heterogeneity in real-world social media. The small scale experiment reveals that the proposed method is able to mitigate the limitations in the well established techniques existing in the literature, resulting in performance improvement of 18.61% (F-measure).The large scale experiment further reveals that the baseline fails to perform well on larger data with higher degrees of heterogeneity, while the proposed method is able to yield reasonably good performance and outperform the baseline by 46.62% (F-Measure) on average. Copyright © 2014 Elsevier Inc. All rights reserved.

Use of the Culture Care Theory and ethnonursing method to discover how nursing faculty teach culture care.

PubMed

Mixer, Sandra J

2008-04-01

As the world becomes increasingly multicultural, transcultural nursing education is critical to ensuring a culturally competent workforce. This paper presents a comprehensive review of literature and results of an ethnonursing pilot study using the Culture Care Theory (CCT) to discover how nursing faculty teach culture care. The literature revealed that despite 50 years of transcultural nursing knowledge development through theory, research and practice, there remains a lack of formal, integrated culture education in nursing. The importance of faculty providing generic and professional care to nursing students and using an organising framework to teach culture care was discovered. Additionally, care was essential for faculty health and well-being to enable faculty to teach culture care. This unique use of the theory and method demonstrates its usefulness in discovering and describing the complex nature of teaching culture care. Larger scale studies are predicted to further substantiate the CCT, building the discipline of nursing.

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.

Culture care theory: a major contribution to advance transcultural nursing knowledge and practices.

PubMed

Leininger, Madeleine

2002-07-01

This article is focused on the major features of the Culture Care Diversity and Universality theory as a central contributing theory to advance transcultural nursing knowledge and to use the findings in teaching, research, practice, and consultation. It remains one of the oldest, most holistic, and most comprehensive theories to generate knowledge of diverse and similar cultures worldwide. The theory has been a powerful means to discover largely unknown knowledge in nursing and the health fields. It provides a new mode to assure culturally competent, safe, and congruent transcultural nursing care. The purpose, goal, assumptive premises, ethnonursing research method, criteria, and some findings are highlighted.

Combined mining: discovering informative knowledge in complex data.

PubMed

Cao, Longbing; Zhang, Huaifeng; Zhao, Yanchang; Luo, Dan; Zhang, Chengqi

2011-06-01

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.

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

A Discretization Algorithm for Meteorological Data and its Parallelization Based on Hadoop

NASA Astrophysics Data System (ADS)

Liu, Chao; Jin, Wen; Yu, Yuting; Qiu, Taorong; Bai, Xiaoming; Zou, Shuilong

2017-10-01

In view of the large amount of meteorological observation data, the property is more and the attribute values are continuous values, the correlation between the elements is the need for the application of meteorological data, this paper is devoted to solving the problem of how to better discretize large meteorological data to more effectively dig out the hidden knowledge in meteorological data and research on the improvement of discretization algorithm for large scale data, in order to achieve data in the large meteorological data discretization for the follow-up to better provide knowledge to provide protection, a discretization algorithm based on information entropy and inconsistency of meteorological attributes is proposed and the algorithm is parallelized under Hadoop platform. Finally, the comparison test validates the effectiveness of the proposed algorithm for discretization in the area of meteorological large data.

Giant star seismology

NASA Astrophysics Data System (ADS)

Hekker, S.; Christensen-Dalsgaard, J.

2017-06-01

The internal properties of stars in the red-giant phase undergo significant changes on relatively short timescales. Long near-uninterrupted high-precision photometric timeseries observations from dedicated space missions such as CoRoT and Kepler have provided seismic inferences of the global and internal properties of a large number of evolved stars, including red giants. These inferences are confronted with predictions from theoretical models to improve our understanding of stellar structure and evolution. Our knowledge and understanding of red giants have indeed increased tremendously using these seismic inferences, and we anticipate that more information is still hidden in the data. Unraveling this will further improve our understanding of stellar evolution. This will also have significant impact on our knowledge of the Milky Way Galaxy as well as on exo-planet host stars. The latter is important for our understanding of the formation and structure of planetary systems.

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

Knowledge-Based Topic Model for Unsupervised Object Discovery and Localization.

PubMed

Niu, Zhenxing; Hua, Gang; Wang, Le; Gao, Xinbo

Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.Unsupervised object discovery and localization is to discover some dominant object classes and localize all of object instances from a given image collection without any supervision. Previous work has attempted to tackle this problem with vanilla topic models, such as latent Dirichlet allocation (LDA). However, in those methods no prior knowledge for the given image collection is exploited to facilitate object discovery. On the other hand, the topic models used in those methods suffer from the topic coherence issue-some inferred topics do not have clear meaning, which limits the final performance of object discovery. In this paper, prior knowledge in terms of the so-called must-links are exploited from Web images on the Internet. Furthermore, a novel knowledge-based topic model, called LDA with mixture of Dirichlet trees, is proposed to incorporate the must-links into topic modeling for object discovery. In particular, to better deal with the polysemy phenomenon of visual words, the must-link is re-defined as that one must-link only constrains one or some topic(s) instead of all topics, which leads to significantly improved topic coherence. Moreover, the must-links are built and grouped with respect to specific object classes, thus the must-links in our approach are semantic-specific , which allows to more efficiently exploit discriminative prior knowledge from Web images. Extensive experiments validated the efficiency of our proposed approach on several data sets. It is shown that our method significantly improves topic coherence and outperforms the unsupervised methods for object discovery and localization. In addition, compared with discriminative methods, the naturally existing object classes in the given image collection can be subtly discovered, which makes our approach well suited for realistic applications of unsupervised object discovery.

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.

Applying data mining techniques to medical time series: an empirical case study in electroencephalography and stabilometry.

PubMed

Anguera, A; Barreiro, J M; Lara, J A; Lizcano, D

2016-01-01

One of the major challenges in the medical domain today is how to exploit the huge amount of data that this field generates. To do this, approaches are required that are capable of discovering knowledge that is useful for decision making in the medical field. Time series are data types that are common in the medical domain and require specialized analysis techniques and tools, especially if the information of interest to specialists is concentrated within particular time series regions, known as events. This research followed the steps specified by the so-called knowledge discovery in databases (KDD) process to discover knowledge from medical time series derived from stabilometric (396 series) and electroencephalographic (200) patient electronic health records (EHR). The view offered in the paper is based on the experience gathered as part of the VIIP project. Knowledge discovery in medical time series has a number of difficulties and implications that are highlighted by illustrating the application of several techniques that cover the entire KDD process through two case studies. This paper illustrates the application of different knowledge discovery techniques for the purposes of classification within the above domains. The accuracy of this application for the two classes considered in each case is 99.86% and 98.11% for epilepsy diagnosis in the electroencephalography (EEG) domain and 99.4% and 99.1% for early-age sports talent classification in the stabilometry domain. The KDD techniques achieve better results than other traditional neural network-based classification techniques.

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

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.

Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

PubMed Central

Guo, Xinyu; Dominick, Kelli C.; Minai, Ali A.; Li, Hailong; Erickson, Craig A.; Lu, Long J.

2017-01-01

The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre-defined brain networks including the default-mode, cingulo-opercular, frontal-parietal, and cerebellum. Thirteen of them are statically significant between ASD and TD groups (two sample t-test p < 0.05) while 19 of them are not. The relationship between the statically significant FCs and the corresponding ASD behavior symptoms is discussed based on the literature and clinician's expert knowledge. Meanwhile, the potential reason of obtaining 19 FCs which are not statistically significant is also provided. PMID:28871217

Mathematics in the Early Years.

ERIC Educational Resources Information Center

Copley, Juanita V., Ed.

Noting that young children are capable of surprisingly complex forms of mathematical thinking and learning, this book presents a collection of articles depicting children discovering mathematical ideas, teachers fostering students' informal mathematical knowledge, adults asking questions and listening to answers, and researchers examining…

User Modeling for Contextual Suggestion

DTIC Science & Technology

2014-11-01

information retrieval literature ( Salton et al., 1975). To apply this metric, we converted the user interest model into a vector representation with all...Discovering Virtual Interest Groups across Chat Rooms, International Conference on Knowledge Management and Information Sharing (KMIS 2012). [7] Salton , G., A

A mess of stars

NASA Image and Video Library

2015-08-10

Bursts of pink and red, dark lanes of mottled cosmic dust, and a bright scattering of stars — this NASA/ESA Hubble Space Telescope image shows part of a messy barred spiral galaxy known as NGC 428. It lies approximately 48 million light-years away from Earth in the constellation of Cetus (The Sea Monster). Although a spiral shape is still just about visible in this close-up shot, overall NGC 428’s spiral structure appears to be quite distorted and warped, thought to be a result of a collision between two galaxies. There also appears to be a substantial amount of star formation occurring within NGC 428 — another telltale sign of a merger. When galaxies collide their clouds of gas can merge, creating intense shocks and hot pockets of gas and often triggering new waves of star formation. NGC 428 was discovered by William Herschel in December 1786. More recently a type Ia supernova designated SN2013ct was discovered within the galaxy by Stuart Parker of the BOSS (Backyard Observatory Supernova Search) project in Australia and New Zealand, although it is unfortunately not visible in this image. This image was captured by Hubble’s Advanced Camera for Surveys (ACS) and Wide Field and Planetary Camera 2 (WFPC2). A version of this image was entered into the Hubble’s Hidden Treasures Image Processing competition by contestants Nick Rose and the Flickr user penninecloud. Links: Nick Rose’s image on Flickr Penninecloud’s image on Flickr

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.

Discover Earth

NASA Technical Reports Server (NTRS)

1997-01-01

Discover Earth is a NASA-funded project for teachers of grades 5-12 who want to expand their knowledge of the Earth system, and prepare to become master teachers who promote Earth system science in their own schools, counties, and throughout their state. Participants from the following states are invited to apply: Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Washington, DC. Teachers selected for the project participate in a two-week summer workshop conducted at the University of Maryland, College Park; develop classroom-ready materials during the workshop for broad dissemination; conduct a minimum of two peer training activities during the coming school year; and participate in other enrichment/education opportunities as available and desired. Discover Earth is a team effort that utilizes expertise from a range of contributors, and balances science content with hands-on classroom applications.

Biomarkers intersect with the exposome

PubMed Central

Rappaport, Stephen M.

2016-01-01

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment. PMID:22672124

Can big data transform electronic health records into learning health systems?

PubMed

Harper, Ellen

2014-01-01

In the United States and globally, healthcare delivery is in the midst of an acute transformation with the adoption and use of health information technology (health IT) thus generating increasing amounts of patient care data available in computable form. Secure and trusted use of these data, beyond their original purpose can change the way we think about business, health, education, and innovation in the years to come. "Big Data" is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it.

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.

Prediction of residue-residue contact matrix for protein-protein interaction with Fisher score features and deep learning.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H; Sun, Bilin

2016-11-01

Protein-protein interactions play essential roles in many biological processes. Acquiring knowledge of the residue-residue contact information of two interacting proteins is not only helpful in annotating functions for proteins, but also critical for structure-based drug design. The prediction of the protein residue-residue contact matrix of the interfacial regions is challenging. In this work, we introduced deep learning techniques (specifically, stacked autoencoders) to build deep neural network models to tackled the residue-residue contact prediction problem. In tandem with interaction profile Hidden Markov Models, which was used first to extract Fisher score features from protein sequences, stacked autoencoders were deployed to extract and learn hidden abstract features. The deep learning model showed significant improvement over the traditional machine learning model, Support Vector Machines (SVM), with the overall accuracy increased by 15% from 65.40% to 80.82%. We showed that the stacked autoencoders could extract novel features, which can be utilized by deep neural networks and other classifiers to enhance learning, out of the Fisher score features. It is further shown that deep neural networks have significant advantages over SVM in making use of the newly extracted features. Copyright © 2016. Published by Elsevier Inc.

Clustering Multivariate Time Series Using Hidden Markov Models

PubMed Central

Ghassempour, Shima; Girosi, Federico; Maeder, Anthony

2014-01-01

In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers. PMID:24662996

Capturing the state transitions of seizure-like events using Hidden Markov models.

PubMed

Guirgis, Mirna; Serletis, Demitre; Carlen, Peter L; Bardakjian, Berj L

2011-01-01

The purpose of this study was to investigate the number of states present in the progression of a seizure-like event (SLE). Of particular interest is to determine if there are more than two clearly defined states, as this would suggest that there is a distinct state preceding an SLE. Whole-intact hippocampus from C57/BL mice was used to model epileptiform activity induced by the perfusion of a low Mg(2+)/high K(+) solution while extracellular field potentials were recorded from CA3 pyramidal neurons. Hidden Markov models (HMM) were used to model the state transitions of the recorded SLEs by incorporating various features of the Hilbert transform into the training algorithm; specifically, 2- and 3-state HMMs were explored. Although the 2-state model was able to distinguish between SLE and nonSLE behavior, it provided no improvements compared to visual inspection alone. However, the 3-state model was able to capture two distinct nonSLE states that visual inspection failed to discriminate. Moreover, by developing an HMM based system a priori knowledge of the state transitions was not required making this an ideal platform for seizure prediction algorithms.

Identification of materials hidden inside a sea-going cargo container filled with an organic cargo by using the tagged neutron inspection system

NASA Astrophysics Data System (ADS)

Sudac, Davorin; Matika, Dario; Valkovic, Vladivoj

2008-04-01

A tagged neutron inspection system was used to search for the presence of explosives hidden inside a sea-going cargo container. Several measurements were done with paper, semtex1a and flour samples placed inside a container filled with an organic cargo made of wooden plates. The results of time-of-flight and gamma-ray spectra measurements obtained with a 14 MeV tagged neutron beam have shown that the investigated materials could be well distinguished in a triangle plot with the following coordinates: the number of counts in the carbon peak, the number of counts in the oxygen peak and the number of counts in the transmitted neutron peak. The signature from the semtex1a explosive could be distinguished from the paper and flour signatures in the organic cargo by using the transmission detectors. Some knowledge about the organic matrix type and density is required, otherwise a high rate of false alarm could be expected. According to the present measurements it seems that the system will work in the organic matrix if its density is ⩽0.25 g/cm 3.

Automated recognition of bird song elements from continuous recordings using dynamic time warping and hidden Markov models: a comparative study.

PubMed

Kogan, J A; Margoliash, D

1998-04-01

The performance of two techniques is compared for automated recognition of bird song units from continuous recordings. The advantages and limitations of dynamic time warping (DTW) and hidden Markov models (HMMs) are evaluated on a large database of male songs of zebra finches (Taeniopygia guttata) and indigo buntings (Passerina cyanea), which have different types of vocalizations and have been recorded under different laboratory conditions. Depending on the quality of recordings and complexity of song, the DTW-based technique gives excellent to satisfactory performance. Under challenging conditions such as noisy recordings or presence of confusing short-duration calls, good performance of the DTW-based technique requires careful selection of templates that may demand expert knowledge. Because HMMs are trained, equivalent or even better performance of HMMs can be achieved based only on segmentation and labeling of constituent vocalizations, albeit with many more training examples than DTW templates. One weakness in HMM performance is the misclassification of short-duration vocalizations or song units with more variable structure (e.g., some calls, and syllables of plastic songs). To address these and other limitations, new approaches for analyzing bird vocalizations are discussed.

Discovering protein complexes in protein interaction networks via exploring the weak ties effect

PubMed Central

2012-01-01

Background Studying protein complexes is very important in biological processes since it helps reveal the structure-functionality relationships in biological networks and much attention has been paid to accurately predict protein complexes from the increasing amount of protein-protein interaction (PPI) data. Most of the available algorithms are based on the assumption that dense subgraphs correspond to complexes, failing to take into account the inherence organization within protein complex and the roles of edges. Thus, there is a critical need to investigate the possibility of discovering protein complexes using the topological information hidden in edges. Results To provide an investigation of the roles of edges in PPI networks, we show that the edges connecting less similar vertices in topology are more significant in maintaining the global connectivity, indicating the weak ties phenomenon in PPI networks. We further demonstrate that there is a negative relation between the weak tie strength and the topological similarity. By using the bridges, a reliable virtual network is constructed, in which each maximal clique corresponds to the core of a complex. By this notion, the detection of the protein complexes is transformed into a classic all-clique problem. A novel core-attachment based method is developed, which detects the cores and attachments, respectively. A comprehensive comparison among the existing algorithms and our algorithm has been made by comparing the predicted complexes against benchmark complexes. Conclusions We proved that the weak tie effect exists in the PPI network and demonstrated that the density is insufficient to characterize the topological structure of protein complexes. Furthermore, the experimental results on the yeast PPI network show that the proposed method outperforms the state-of-the-art algorithms. The analysis of detected modules by the present algorithm suggests that most of these modules have well biological significance in context of complexes, suggesting that the roles of edges are critical in discovering protein complexes. PMID:23046740

Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs

PubMed Central

Eloe-Fadrosh, Emiley A.; Paez-Espino, David; Jarett, Jessica; Dunfield, Peter F.; Hedlund, Brian P.; Dekas, Anne E.; Grasby, Stephen E.; Brady, Allyson L.; Dong, Hailiang; Briggs, Brandon R.; Li, Wen-Jun; Goudeau, Danielle; Malmstrom, Rex; Pati, Amrita; Pett-Ridge, Jennifer; Rubin, Edward M.; Woyke, Tanja; Kyrpides, Nikos C.; Ivanova, Natalia N.

2016-01-01

Analysis of the increasing wealth of metagenomic data collected from diverse environments can lead to the discovery of novel branches on the tree of life. Here we analyse 5.2 Tb of metagenomic data collected globally to discover a novel bacterial phylum (‘Candidatus Kryptonia') found exclusively in high-temperature pH-neutral geothermal springs. This lineage had remained hidden as a taxonomic ‘blind spot' because of mismatches in the primers commonly used for ribosomal gene surveys. Genome reconstruction from metagenomic data combined with single-cell genomics results in several high-quality genomes representing four genera from the new phylum. Metabolic reconstruction indicates a heterotrophic lifestyle with conspicuous nutritional deficiencies, suggesting the need for metabolic complementarity with other microbes. Co-occurrence patterns identifies a number of putative partners, including an uncultured Armatimonadetes lineage. The discovery of Kryptonia within previously studied geothermal springs underscores the importance of globally sampled metagenomic data in detection of microbial novelty, and highlights the extraordinary diversity of microbial life still awaiting discovery. PMID:26814032

Perspectives of intellectual processing of large volumes of astronomical data using neural networks

NASA Astrophysics Data System (ADS)

Gorbunov, A. A.; Isaev, E. A.; Samodurov, V. A.

2018-01-01

In the process of astronomical observations vast amounts of data are collected. BSA (Big Scanning Antenna) LPI used in the study of impulse phenomena, daily logs 87.5 GB of data (32 TB per year). This data has important implications for both short-and long-term monitoring of various classes of radio sources (including radio transients of different nature), monitoring the Earth’s ionosphere, the interplanetary and the interstellar plasma, the search and monitoring of different classes of radio sources. In the framework of the studies discovered 83096 individual pulse events (in the interval of the study highlighted July 2012 - October 2013), which may correspond to pulsars, twinkling springs, and a rapid radio transients. Detected impulse events are supposed to be used to filter subsequent observations. The study suggests approach, using the creation of the multilayered artificial neural network, which processes the input raw data and after processing, by the hidden layer, the output layer produces a class of impulsive phenomena.

Analysis and prediction of leucine-rich nuclear export signals.

PubMed

la Cour, Tanja; Kiemer, Lars; Mølgaard, Anne; Gupta, Ramneek; Skriver, Karen; Brunak, Søren

2004-06-01

We present a thorough analysis of nuclear export signals and a prediction server, which we have made publicly available. The machine learning prediction method is a significant improvement over the generally used consensus patterns. Nuclear export signals (NESs) are extremely important regulators of the subcellular location of proteins. This regulation has an impact on transcription and other nuclear processes, which are fundamental to the viability of the cell. NESs are studied in relation to cancer, the cell cycle, cell differentiation and other important aspects of molecular biology. Our conclusion from this analysis is that the most important properties of NESs are accessibility and flexibility allowing relevant proteins to interact with the signal. Furthermore, we show that not only the known hydrophobic residues are important in defining a nuclear export signals. We employ both neural networks and hidden Markov models in the prediction algorithm and verify the method on the most recently discovered NESs. The NES predictor (NetNES) is made available for general use at http://www.cbs.dtu.dk/.

Light Higgs channel of the resonant decay of magnon condensate in superfluid (3)He-B.

PubMed

Zavjalov, V V; Autti, S; Eltsov, V B; Heikkinen, P J; Volovik, G E

2016-01-08

In superfluids the order parameter, which describes spontaneous symmetry breaking, is an analogue of the Higgs field in the Standard Model of particle physics. Oscillations of the field amplitude are massive Higgs bosons, while oscillations of the orientation are massless Nambu-Goldstone bosons. The 125 GeV Higgs boson, discovered at Large Hadron Collider, is light compared with electroweak energy scale. Here, we show that such light Higgs exists in superfluid (3)He-B, where one of three Nambu-Goldstone spin-wave modes acquires small mass due to the spin-orbit interaction. Other modes become optical and acoustic magnons. We observe parametric decay of Bose-Einstein condensate of optical magnons to light Higgs modes and decay of optical to acoustic magnons. Formation of a light Higgs from a Nambu-Goldstone mode observed in (3)He-B opens a possibility that such scenario can be realized in other systems, where violation of some hidden symmetry is possible, including the Standard Model.

Discriminative motif discovery via simulated evolution and random under-sampling.

PubMed

Song, Tao; Gu, Hong

2014-01-01

Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs) training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

Theoretical description of the decays Λb→Λ(*)(1/2±,3/2±)+J /ψ

NASA Astrophysics Data System (ADS)

Gutsche, Thomas; Ivanov, Mikhail A.; Körner, Jürgen G.; Lyubovitskij, Valery E.; Lyubushkin, Vladimir V.; Santorelli, Pietro

2017-07-01

We calculate the invariant and helicity amplitudes for the transitions Λb→Λ(*)(JP)+J /ψ , where the Λ(*)(JP) are Λ (s u d )-type ground and excited states with JP quantum numbers JP=1/2± , 3/2± . The calculations are performed in the framework of a covariant confined quark model previously developed by us. We find that the values of the helicity amplitudes for the Λ*(1520 ,3/2-) and the Λ*(1890 ,3/2+) are suppressed compared with those for the ground state Λ (1116 ,1/2+) and the excited state Λ*(1405 ,1/2-). This analysis is important for the identification of the hidden charm pentaquark states Pc+(4380 ) and Pc+(4450 ) which were discovered in the decay chain Λb0→Pc+(→p J /ψ )+K- because the cascade decay chain Λb→Λ*(3/2±)(→p K-)+J /ψ involves the same final state.

Discovery of naked charm particles and lifetime differences among charm species using nuclear emulsion techniques innovated in Japan

PubMed Central

NIU, Kiyoshi

2008-01-01

This is a historical review of the discovery of naked charm particles and lifetime differences among charm species. These discoveries in the field of cosmic-ray physics were made by the innovation of nuclear emulsion techniques in Japan. A pair of naked charm particles was discovered in 1971 in a cosmic-ray interaction, three years prior to the discovery of the hidden charm particle, J/Ψ, in western countries. Lifetime differences between charged and neutral charm particles were pointed out in 1975, which were later re-confirmed by the collaborative Experiment E531 at Fermilab. Japanese physicists led by K.Niu made essential contributions to it with improved emulsion techniques, complemented by electronic detectors. This review also discusses the discovery of artificially produced naked charm particles by us in an accelerator experiment at Fermilab in 1975 and of multiple-pair productions of charm particles in a single interaction in 1987 by the collaborative Experiment WA75 at CERN. PMID:18941283

A CAD Approach to Integrating NDE With Finite Element

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Downey, James; Ghosn, Louis J.; Baaklini, George Y.

2004-01-01

Nondestructive evaluation (NDE) is one of several technologies applied at NASA Glenn Research Center to determine atypical deformities, cracks, and other anomalies experienced by structural components. NDE consists of applying high-quality imaging techniques (such as x-ray imaging and computed tomography (CT)) to discover hidden manufactured flaws in a structure. Efforts are in progress to integrate NDE with the finite element (FE) computational method to perform detailed structural analysis of a given component. This report presents the core outlines for an in-house technical procedure that incorporates this combined NDE-FE interrelation. An example is presented to demonstrate the applicability of this analytical procedure. FE analysis of a test specimen is performed, and the resulting von Mises stresses and the stress concentrations near the anomalies are observed, which indicates the fidelity of the procedure. Additional information elaborating on the steps needed to perform such an analysis is clearly presented in the form of mini step-by-step guidelines.

Profiling Oman education data using data visualization technique

NASA Astrophysics Data System (ADS)

Alalawi, Sultan Juma Sultan; Shaharanee, Izwan Nizal Mohd; Jamil, Jastini Mohd

2016-10-01

This research works presents an innovative data visualization technique to understand and visualize the information of Oman's education data generated from the Ministry of Education Oman "Educational Portal". The Ministry of Education in Sultanate of Oman have huge databases contains massive information. The volume of data in the database increase yearly as many students, teachers and employees enter into the database. The task for discovering and analyzing these vast volumes of data becomes increasingly difficult. Information visualization and data mining offer a better ways in dealing with large volume of information. In this paper, an innovative information visualization technique is developed to visualize the complex multidimensional educational data. Microsoft Excel Dashboard, Visual Basic Application (VBA) and Pivot Table are utilized to visualize the data. Findings from the summarization of the data are presented, and it is argued that information visualization can help related stakeholders to become aware of hidden and interesting information from large amount of data drowning in their educational portal.

Decision-making regarding organ donation in Korean adults: A grounded-theory study.

PubMed

Yeun, Eun Ja; Kwon, Young Mi; Kim, Jung A

2015-06-01

The aim of this study was to identify the hidden patterns of behavior leading toward the decision to donate organs. Thirteen registrants at the Association for Organ Sharing in Korea were recruited. Data were collected using in-depth interview and the interview transcripts were analyzed using Glaserian grounded-theory methodology. The main problem of participants was "body attachment" and the core category (management process) was determined to be "pursuing life." The theme consisted of four phases, which were: "hesitating," "investigating," "releasing," and "re-discovering. " Therefore, to increase organ donations, it is important to find a strategy that will create positive attitudes about organ donation through education and public relations. These results explain and provide a deeper understanding of the main problem that Korean people have about organ donation and their management of decision-making processes. These findings can help care providers to facilitate the decision-making process and respond to public needs while taking into account the sociocultural context within which decisions are made. © 2014 Wiley Publishing Asia Pty Ltd.

Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs.

PubMed

Eloe-Fadrosh, Emiley A; Paez-Espino, David; Jarett, Jessica; Dunfield, Peter F; Hedlund, Brian P; Dekas, Anne E; Grasby, Stephen E; Brady, Allyson L; Dong, Hailiang; Briggs, Brandon R; Li, Wen-Jun; Goudeau, Danielle; Malmstrom, Rex; Pati, Amrita; Pett-Ridge, Jennifer; Rubin, Edward M; Woyke, Tanja; Kyrpides, Nikos C; Ivanova, Natalia N

2016-01-27

Analysis of the increasing wealth of metagenomic data collected from diverse environments can lead to the discovery of novel branches on the tree of life. Here we analyse 5.2 Tb of metagenomic data collected globally to discover a novel bacterial phylum ('Candidatus Kryptonia') found exclusively in high-temperature pH-neutral geothermal springs. This lineage had remained hidden as a taxonomic 'blind spot' because of mismatches in the primers commonly used for ribosomal gene surveys. Genome reconstruction from metagenomic data combined with single-cell genomics results in several high-quality genomes representing four genera from the new phylum. Metabolic reconstruction indicates a heterotrophic lifestyle with conspicuous nutritional deficiencies, suggesting the need for metabolic complementarity with other microbes. Co-occurrence patterns identifies a number of putative partners, including an uncultured Armatimonadetes lineage. The discovery of Kryptonia within previously studied geothermal springs underscores the importance of globally sampled metagenomic data in detection of microbial novelty, and highlights the extraordinary diversity of microbial life still awaiting discovery.

Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs

DOE PAGES

Eloe-Fadrosh, Emiley A.; Paez-Espino, David; Jarett, Jessica; ...

2016-01-27

Analysis of the increasing wealth of metagenomic data collected from diverse environments can lead to the discovery of novel branches on the tree of life. Here we analyse 5.2 Tb of metagenomic data collected globally to discover a novel bacterial phylum (' Candidatus Kryptonia') found exclusively in higherature pH-neutral geothermal springs. This lineage had remained hidden as a taxonomic 'blind spot' because of mismatches in the primers commonly used for ribosomal gene surveys. Genome reconstruction from metagenomic data combined with single-cell genomics results in several high-quality genomes representing four genera from the new phylum. Metabolic reconstruction indicates a heterotrophic lifestylemore » with conspicuous nutritional deficiencies, suggesting the need for metabolic complementarity with other microbes. Co-occurrence patterns identifies a number of putative partners, including an uncultured Armatimonadetes lineage. The discovery of Kryptonia within previously studied geothermal springs underscores the importance of globally sampled metagenomic data in detection of microbial novelty, and highlights the extraordinary diversity of microbial life still awaiting discovery.« less

Number theoretical foundations in cryptography

NASA Astrophysics Data System (ADS)

Atan, Kamel Ariffin Mohd

2017-08-01

In recent times the hazards in relationships among entities in different establishments worldwide have generated exciting developments in cryptography. Central to this is the theory of numbers. This area of mathematics provides very rich source of fundamental materials for constructing secret codes. Some number theoretical concepts that have been very actively used in designing crypto systems will be highlighted in this presentation. This paper will begin with introduction to basic number theoretical concepts which for many years have been thought to have no practical applications. This will include several theoretical assertions that were discovered much earlier in the historical development of number theory. This will be followed by discussion on the "hidden" properties of these assertions that were later exploited by designers of cryptosystems in their quest for developing secret codes. This paper also highlights some earlier and existing cryptosystems and the role played by number theoretical concepts in their constructions. The role played by cryptanalysts in detecting weaknesses in the systems developed by cryptographers concludes this presentation.

Virtual unrolling and deciphering of Herculaneum papyri by X-ray phase-contrast tomography

PubMed Central

Bukreeva, I.; Mittone, A.; Bravin, A.; Festa, G.; Alessandrelli, M.; Coan, P.; Formoso, V.; Agostino, R. G.; Giocondo, M.; Ciuchi, F.; Fratini, M.; Massimi, L.; Lamarra, A.; Andreani, C.; Bartolino, R.; Gigli, G.; Ranocchia, G.; Cedola, A.

2016-01-01

A collection of more than 1800 carbonized papyri, discovered in the Roman ‘Villa dei Papiri’ at Herculaneum is the unique classical library survived from antiquity. These papyri were charred during 79 A.D. Vesuvius eruption, a circumstance which providentially preserved them until now. This magnificent collection contains an impressive amount of treatises by Greek philosophers and, especially, Philodemus of Gadara, an Epicurean thinker of 1st century BC. We read many portions of text hidden inside carbonized Herculaneum papyri using enhanced X-ray phase-contrast tomography non-destructive technique and a new set of numerical algorithms for ‘virtual-unrolling’. Our success lies in revealing the largest portion of Greek text ever detected so far inside unopened scrolls, with unprecedented spatial resolution and contrast, all without damaging these precious historical manuscripts. Parts of text have been decoded and the ‘voice’ of the Epicurean philosopher Philodemus is brought back again after 2000 years from Herculaneum papyri. PMID:27265417

Light Higgs channel of the resonant decay of magnon condensate in superfluid 3He-B

PubMed Central

Zavjalov, V. V.; Autti, S.; Eltsov, V. B.; Heikkinen, P. J.; Volovik, G. E.

2016-01-01

In superfluids the order parameter, which describes spontaneous symmetry breaking, is an analogue of the Higgs field in the Standard Model of particle physics. Oscillations of the field amplitude are massive Higgs bosons, while oscillations of the orientation are massless Nambu-Goldstone bosons. The 125 GeV Higgs boson, discovered at Large Hadron Collider, is light compared with electroweak energy scale. Here, we show that such light Higgs exists in superfluid 3He-B, where one of three Nambu-Goldstone spin-wave modes acquires small mass due to the spin–orbit interaction. Other modes become optical and acoustic magnons. We observe parametric decay of Bose-Einstein condensate of optical magnons to light Higgs modes and decay of optical to acoustic magnons. Formation of a light Higgs from a Nambu-Goldstone mode observed in 3He-B opens a possibility that such scenario can be realized in other systems, where violation of some hidden symmetry is possible, including the Standard Model. PMID:26743951

[Shushu (ancient Chinese numerology) in Lingshu: Gudu (Miraculous Pivot: Bone-Length Measurement)].

PubMed

Zhuo, Lian-Shi

2010-10-01

Lingshu: Gudu (Miraculous Pivot: Bone-Length Measurement) is compared with literatures concerning the Shushu (ancient Chinese numerology) of the Qin Dynasty (221 B. C. - 206 B. C. ) and the Han Dynasty (206 B. C.-220 A. D.) in this article. And it is discovered that "the number of heaven and earth" in Yijing (The Book of Change) was implied in the bone-length measurement. The theory of Shushu is hidden in the sized of head, neck, chest, abdomen, back and 4 extremities according to the measurement. The meaning of establishment of bone-length measurement, which is found to have universality, laid in setting down the measurement of meridians. And it is the origin of the proportional measurement of locating acupoints. Checked with the theory of Shushu, errors in the description of bone-length measurement could also be found in Lingshu: Gudu (Miraculous Pivot: Bone-Length Measurement) of the present edition, which is helpful for the modern study on the measurement.

Discovering Higgs boson decays to lepton jets at hadron colliders.

PubMed

Falkowski, Adam; Ruderman, Joshua T; Volansky, Tomer; Zupan, Jure

2010-12-10

The Higgs boson may decay predominantly into a hidden sector, producing lepton jets instead of the standard Higgs signatures. We propose a search strategy for such a signal at hadron colliders. A promising channel is the associated production of the Higgs boson with a Z or W. The dominant background is Z or W plus QCD jets. The lepton jets can be discriminated from QCD jets by cutting on the electromagnetic fraction and charge ratio. The former is the fraction of jet energy deposited in the electromagnetic calorimeter and the latter is the ratio of energy carried by charged particles to the electromagnetic energy. We use a Monte Carlo description of detector response to estimate QCD rejection efficiencies of O(10⁻³) per jet. The expected 5σ (3σ) discovery reach in Higgs boson mass is ∼115 GeV (150 GeV) at the Tevatron with 10 fb⁻¹ of data and ∼110 GeV (130 GeV) at the 7 TeV LHC with 1 fb⁻¹.

Visual exploration of high-dimensional data through subspace analysis and dynamic projections

DOE PAGES

Liu, S.; Wang, B.; Thiagarajan, J. J.; ...

2015-06-01

Here, we introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that createmore » smooth animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.« less

Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections

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

Liu, S.; Wang, B.; Thiagarajan, Jayaraman J.

2015-06-01

We introduce a novel interactive framework for visualizing and exploring high-dimensional datasets based on subspace analysis and dynamic projections. We assume the high-dimensional dataset can be represented by a mixture of low-dimensional linear subspaces with mixed dimensions, and provide a method to reliably estimate the intrinsic dimension and linear basis of each subspace extracted from the subspace clustering. Subsequently, we use these bases to define unique 2D linear projections as viewpoints from which to visualize the data. To understand the relationships among the different projections and to discover hidden patterns, we connect these projections through dynamic projections that create smoothmore » animated transitions between pairs of projections. We introduce the view transition graph, which provides flexible navigation among these projections to facilitate an intuitive exploration. Finally, we provide detailed comparisons with related systems, and use real-world examples to demonstrate the novelty and usability of our proposed framework.« less

A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream

PubMed Central

Ying Wah, Teh

2014-01-01

Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets. PMID:25110753

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

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.

A fast density-based clustering algorithm for real-time Internet of Things stream.

PubMed

Amini, Amineh; Saboohi, Hadi; Wah, Teh Ying; Herawan, Tutut

2014-01-01

Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.

Stacking order dynamics in the quasi-two-dimensional dichalcogenide 1T-TaS2 probed with MeV ultrafast electron diffraction.

PubMed

Le Guyader, L; Chase, T; Reid, A H; Li, R K; Svetin, D; Shen, X; Vecchione, T; Wang, X J; Mihailovic, D; Dürr, H A

2017-07-01

Transitions between different charge density wave (CDW) states in quasi-two-dimensional materials may be accompanied also by changes in the inter-layer stacking of the CDW. Using MeV ultrafast electron diffraction, the out-of-plane stacking order dynamics in the quasi-two-dimensional dichalcogenide 1 T -TaS 2 is investigated for the first time. From the intensity of the CDW satellites aligned around the commensurate l  = 1/6 characteristic stacking order, it is found out that this phase disappears with a 0.3 ps time constant. Simultaneously, in the same experiment, the emergence of the incommensurate phase, with a slightly slower 2.0 ps time constant, is determined from the intensity of the CDW satellites aligned around the incommensurate l  = 1/3 characteristic stacking order. These results might be of relevance in understanding the metallic character of the laser-induced metastable "hidden" state recently discovered in this compound.

Biggest Radio-Telescope in Northern Europe, the RT-32 in Latvia

NASA Astrophysics Data System (ADS)

Monstein, Christian

2014-08-01

Hidden in the dense coastal forests of Slítere a mysterious ex-Soviet spy center is now used for science. Almost everyone including me who entered the site of the two large radio telescopes called Irbene, are amazed by the surrealistic atmosphere of the abandoned ghost town and two large radio dish antennas in the middle of nowhere. This article will tell more about this site; see also [1]. As the Cold War between the US and USSR entered the space age, the need for Space espionage led to the Soviets designing ways to track and decode signals from US satellites. The project began in 1967 when the remote areas of the Ventspils district were allocated for secret buildup of a site codenamed "Starlet". The location was chosen because of low population and dense forest areas of Slí;tere that also were part of the Soviet border zone - ensuring that no strangers could ever discover it.

A tale of two fractals: The Hofstadter butterfly and the integral Apollonian gaskets

NASA Astrophysics Data System (ADS)

Satija, Indubala I.

2016-11-01

This paper unveils a mapping between a quantum fractal that describes a physical phenomena, and an abstract geometrical fractal. The quantum fractal is the Hofstadter butterfly discovered in 1976 in an iconic condensed matter problem of electrons moving in a two-dimensional lattice in a transverse magnetic field. The geometric fractal is the integer Apollonian gasket characterized in terms of a 300 BC problem of mutually tangent circles. Both of these fractals are made up of integers. In the Hofstadter butterfly, these integers encode the topological quantum numbers of quantum Hall conductivity. In the Apollonian gaskets an infinite number of mutually tangent circles are nested inside each other, where each circle has integer curvature. The mapping between these two fractals reveals a hidden D3 symmetry embedded in the kaleidoscopic images that describe the asymptotic scaling properties of the butterfly. This paper also serves as a mini review of these fractals, emphasizing their hierarchical aspects in terms of Farey fractions.