Folk Media in Development.

ERIC Educational Resources Information Center

Instructional Technology Report, 1975

1975-01-01

This issue is dedicated to folk media. Using Indonesia for his case study, Dr. Nat Colletta analyzes traditional culture as a medium for development. Juan Diaz Bordenave expresses doubts about adapting folk media to development objectives; Susan Hostetler and Arthur Gillette report on uses of the theater to promote development objectives; and…

Introducing Creativity in the Ensemble Setting: National Standards Meet Comprehensive Musicianship

ERIC Educational Resources Information Center

Norris, Charles E.

2010-01-01

This article explores realistic ways with which ensemble conductors can facilitate the conceptual acquisition of their students via creative activities. Creativity, as included in the National Standards, is presented through the "eyes" of comprehensive musicianship. (Contains 2 figures, 2 tables, and 9 notes.)

Folk healing: a description and synthesis.

PubMed

Ness, R C; Wintrob, R M

1981-11-01

All societies have developed ways of dealing with physical and mental illness, defined as folk healing systems. The authors review the systems of folk healing that have evolved in different cultural groups in the United States. They describe the faith healing practices of fundamentalist Christian groups, the belief in rootwork among white and black people in the southeastern United States, curanderismo among Mexican-Americans, and espiritismo among Americans from Puerto Rico. Most believers in folk healing also go to physicians for medical care. The authors argue that physicians should familiarize themselves with patients' folk healing beliefs in order to serve them more effectively.

Use of Folk Therapy in Taiwan: A Nationwide Cross-Sectional Survey of Prevalence and Associated Factors

PubMed Central

Shih, Chun-Chuan; Huang, Lu-Hsiang; Lane, Hsin-Long; Tsai, Chin-Chuan; Lin, Jaung-Geng; Chen, Ta-Liang; Yeh, Chun-Chieh; Liao, Chien-Chang

2015-01-01

Background. This study investigates the prevalence of and factors associated with users of folk therapy in Taiwan. Methods. Using data from the 2005 National Health Interview Survey and the National Health Insurance Research Database, we identified 16,750 adults aged 20 years and older. Sociodemographic factors, lifestyle, medical utilization, and health behaviors were compared between people using and not using folk therapy. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of factors associated with folk therapy were analyzed. Results. The one-month prevalence of folk therapy use was 6.8%, which was significantly associated with ages of 30–59 years (OR = 1.98, 95% CI = 1.49–2.63), women (OR = 1.63, 95% CI = 1.40–1.90), nonindigenous population (OR = 1.90, 95% CI = 1.14–3.17), having two or more unhealthy lifestyle habits (OR = 1.51, 95% CI = 1.26–1.81), high density of traditional Chinese medicine (TCM) physicians (OR = 1.40, 95% CI = 1.20–1.62), and being ill without receiving medical care in past six months (OR = 2.11, 95% CI = 1.76–2.53). Medical care utilization of TCM and Western medicine were also associated factors for folk therapy. Conclusions. The use of folk therapy is correlated with sociodemographics, lifestyle and health behaviors. PMID:26170878

Folk knowledge of invertebrates in Central Europe - folk taxonomy, nomenclature, medicinal and other uses, folklore, and nature conservation.

PubMed

Ulicsni, Viktor; Svanberg, Ingvar; Molnár, Zsolt

2016-10-11

There is scarce information about European folk knowledge of wild invertebrate fauna. We have documented such folk knowledge in three regions, in Romania, Slovakia and Croatia. We provide a list of folk taxa, and discuss folk biological classification and nomenclature, salient features, uses, related proverbs and sayings, and conservation. We collected data among Hungarian-speaking people practising small-scale, traditional agriculture. We studied "all" invertebrate species (species groups) potentially occurring in the vicinity of the settlements. We used photos, held semi-structured interviews, and conducted picture sorting. We documented 208 invertebrate folk taxa. Many species were known which have, to our knowledge, no economic significance. 36 % of the species were known to at least half of the informants. Knowledge reliability was high, although informants were sometimes prone to exaggeration. 93 % of folk taxa had their own individual names, and 90 % of the taxa were embedded in the folk taxonomy. Twenty four species were of direct use to humans (4 medicinal, 5 consumed, 11 as bait, 2 as playthings). Completely new was the discovery that the honey stomachs of black-coloured carpenter bees (Xylocopa violacea, X. valga) were consumed. 30 taxa were associated with a proverb or used for weather forecasting, or predicting harvests. Conscious ideas about conserving invertebrates only occurred with a few taxa, but informants would generally refrain from harming firebugs (Pyrrhocoris apterus), field crickets (Gryllus campestris) and most butterflies. We did not find any mythical creatures among invertebrate folk taxa. Almost every invertebrate species was regarded as basically harmful. Where possible, they were destroyed or at least regarded as worth eradicating. However, we could find no evidence to suggest any invertebrate species had suffered population loss as a result of conscious destruction. Sometimes knowledge pertaining to the taxa could have more

Discovering the United States through Children's Folk Literature

ERIC Educational Resources Information Center

Perez-Stable, Maria

2005-01-01

A nation's folk literature offers a window into its people and their beliefs across time and geographic locations. Whether the stories are tall tales, creation stories, or fairy tales, they reveal insights into the make-up of the populace--what they believe, what motivates them, what their attitudes are, how they behave, and how time and place…

Towards the Operational Ensemble-based Data Assimilation System for the Wave Field at the National Weather Service

NASA Astrophysics Data System (ADS)

Flampouris, Stylianos; Penny, Steve; Alves, Henrique

2017-04-01

The National Centers for Environmental Prediction (NCEP) of the National Oceanic and Atmospheric Administration (NOAA) provides the operational wave forecast for the US National Weather Service (NWS). Given the continuous efforts to improve forecast, NCEP is developing an ensemble-based data assimilation system, based on the local ensemble transform Kalman filter (LETKF), the existing operational global wave ensemble system (GWES) and on satellite and in-situ observations. While the LETKF was designed for atmospheric applications (Hunt et al 2007), and has been adapted for several ocean models (e.g. Penny 2016), this is the first time applied for oceanic waves assimilation. This new wave assimilation system provides a global estimation of the surface sea state and its approximate uncertainty. It achieves this by analyzing the 21-member ensemble of the significant wave height provided by GWES every 6h. Observations from four altimeters and all the available in-situ measurements are used in this analysis. The analysis of the significant wave height is used for initializing the next forecasting cycle; the data assimilation system is currently being tested for operational use.

Concepts of Chinese Folk Happiness

ERIC Educational Resources Information Center

Ip, Po Keung

2011-01-01

Discourses on Chinese folk happiness are often based on anecdotal narratives or qualitative analysis. Two traditional concepts of happiness popular in Chinese culture are introduced. The paper constructs a concept of Chinese folk happiness on basis of the findings of a scientific survey on the Taiwanese people regarding their concepts of…

Folk Literature of South Asia.

ERIC Educational Resources Information Center

Wadley, Susan S., Ed.

1975-01-01

The collection of articles in this volume focuses on different kinds of folk literature from Bengal, Tamilnad, Bihar, Hindi-speaking North India, and Nepal. An introductory article by S.S. Wadley discusses types of folk literature in Karimpur. The remaining articles are organized according to cultural themes: "The Lustful Stepmother in the…

A comparison of breeding and ensemble transform vectors for global ensemble generation

NASA Astrophysics Data System (ADS)

Deng, Guo; Tian, Hua; Li, Xiaoli; Chen, Jing; Gong, Jiandong; Jiao, Meiyan

2012-02-01

To compare the initial perturbation techniques using breeding vectors and ensemble transform vectors, three ensemble prediction systems using both initial perturbation methods but with different ensemble member sizes based on the spectral model T213/L31 are constructed at the National Meteorological Center, China Meteorological Administration (NMC/CMA). A series of ensemble verification scores such as forecast skill of the ensemble mean, ensemble resolution, and ensemble reliability are introduced to identify the most important attributes of ensemble forecast systems. The results indicate that the ensemble transform technique is superior to the breeding vector method in light of the evaluation of anomaly correlation coefficient (ACC), which is a deterministic character of the ensemble mean, the root-mean-square error (RMSE) and spread, which are of probabilistic attributes, and the continuous ranked probability score (CRPS) and its decomposition. The advantage of the ensemble transform approach is attributed to its orthogonality among ensemble perturbations as well as its consistence with the data assimilation system. Therefore, this study may serve as a reference for configuration of the best ensemble prediction system to be used in operation.

Misrepresenting Chinese Folk Happiness: A Critique of a Study

ERIC Educational Resources Information Center

Ip, Po-Keung

2013-01-01

Discourses on Chinese folk happiness are often based on anecdotal narratives or qualitative analysis. A recent study on Chinese folk happiness using qualitative method seems to provide some empirical findings beyond anecdotal evidence on Chinese folk happiness. This paper critically examines the study's constructed image of Chinese folk happiness,…

Establishment of a New National Reference Ensemble of Water Triple Point Cells

NASA Astrophysics Data System (ADS)

Senn, Remo

2017-10-01

The results of the Bilateral Comparison EURAMET.T-K3.5 (w/VSL, The Netherlands) with the goal to link Switzerland's ITS-90 realization (Ar to Al) to the latest key comparisons gave strong indications for a discrepancy in the realization of the triple point of water. Due to the age of the cells of about twenty years, it was decided to replace the complete reference ensemble with new "state-of-the-art" cells. Three new water triple point cells from three different suppliers were purchased, as well as a new maintenance bath for an additional improvement of the realization. In several loops measurements were taken, each cell of both ensembles intercompared, and the deviations and characteristics determined. The measurements show a significant lower average value of the old ensemble of 0.59 ± 0.25 mK (k=2) in comparison with the new one. Likewise, the behavior of the old cells is very unstable with a drift downward during the realization of the triple point. Based on these results the impact of the new ensemble on the ITS-90 realization from Ar to Al was calculated and set in the context to performed calibrations and their related uncertainties in the past. This paper presents the instrumentation, cells, measurement procedure, results, uncertainties and impact of the new national reference ensemble of water triple point cells on the current ITS-90 realization in Switzerland.

Folk Stories and Social Identification in Multilingual Classrooms

ERIC Educational Resources Information Center

Creese, Angela; Wu, Chao-Jung; Blackledge, Adrian

2009-01-01

This paper considers the processes of using folk stories for the teaching of community languages in a UK complementary school. We look at the appropriation of folk stories by teachers to teach young people Mandarin while also considering their possibilities as heritage texts. We consider how the teacher and students use the folk story as…

A Different Approach to Teaching Social Studies: Folk Songs History

ERIC Educational Resources Information Center

Tangülü, Zafer

2014-01-01

The purpose of this study is to determine the effect of teaching and learning the subjects of Social Studies with folk songs in secondary school students. This study is made in 2012-2013 Academic Year Spring Term with seventh grade students studying in secondary school bounded Mugla Provincial Directorate for National Education. 67 students have…

The Role and Characteristics of Collections of Folk Recepies in the Folk and Traditional Medicine of Bosnia and Herzegovina

PubMed Central

Skrbo, Armin; Masic, Izet

2017-01-01

Introduction: Folk medicine represents part of the folk culture, when we first think about the rural culture with characteristic of the rural population in the pre-industrial period. The difference between official and folk medicine is manifested in the education, knowledge and social status of those practicing folk medicine as well as their patients. The most common ways of treating were the treatment by use of herbs, magic and treatments based on religious beliefs. So, it is of no surprise that folk medicine was the main form of treatment for the inhabitants of Bosnia and Herzegovina (B&H) in the past. In addition to many herbalists, quacks and religious officials who treated the patients with records, there were also spells, i.e. women who, by pronouncing various magic formulas, treated the patients. Each village had at least one person who practiced this type of treatment. Discussion: Numerous, original documents and records have been stored in the archives of the monastery throughout B&H, including very valuable literature in the field of medicine and pharmacy, which testifies of the very important role of Franciscans in the treatment of the population in Bosnia and Herzegovina. The most extensive health service of the Franciscans since their arrival in Bosnia in 1291 was the decadent era of Turkish rule, mostly from the 17th century until the Austro-Hungarian occupation of Bosnia and Herzegovina in 1978. In the sources of national thought, and on the basis of professional medical books, the Franciscans created recipes for the treatment of certain diseases, which they then collected in so-called „Ljekaruse” (Collections of folk recipes), and over time there was a lot of them. Most of the ljekarusa are hand-printed booklets, for some it is known the time and place of creation, and less often the author of the text. Ljekarusa is a very important source of information about our medical past. Some of them were processed and recorded, while a significant part

A Movement Approach to Teaching Folk Dance.

ERIC Educational Resources Information Center

Figley, Grace

1981-01-01

The importance of learning new movement skills is shown in relation to learning folk dances. Folk dancing not only improves physical skills, but also results in an understanding and appreciation of the richness of other cultures. (JN)

Folk beliefs of cultural changes in China

PubMed Central

Xu, Yi; Hamamura, Takeshi

2014-01-01

For the last several decades, Chinese society has experienced transformative changes. How are these changes understood among Chinese people? To examine this question, Part 1 in this research solicited folk beliefs of cultural change from a group of Chinese participants in an open-ended format, and the generated folk beliefs were rated by another group of participants in Part 2 to gage each belief's level of agreement. Part 3 plotted the folk beliefs retained in Part 2 using the Google Ngram Viewer in order to infer the amount of intellectual interests that each belief has received cross-temporarily. These analyses suggested a few themes in Chinese folk beliefs of cultural change (1) rising perceived importance of materialism and individualism in understanding contemporary Chinese culture and Chinese psychology relative to those of the past (2) rising perceived importance of freedom, democracy and human rights and (3) enduring perceived importance of family relations and friendship as well as patriotism. Interestingly, findings from Parts 2 and 3 diverged somewhat, illuminating possible divergence between folk beliefs and intellectual interests especially for issues related to heritage of Confucianism. PMID:25309491

The Challenge and Benefit of Evaluating Folk Dancing Quality

ERIC Educational Resources Information Center

Rhone, Jeffrey

2017-01-01

The physical, social, and music attributes inherent to folk dancing make it an ideal component of music education curricula. The communal experience of folk dancing is unprecedented for many adults and children. These experiences are unique because folk dancing can foster individual and group learning through music, and noncompetitive play. There…

Modulated neural processing of Western harmony in folk musicians.

PubMed

Brattico, Elvira; Tupala, Tiina; Glerean, Enrico; Tervaniemi, Mari

2013-07-01

A chord deviating from the conventions of Western tonal music elicits an early right anterior negativity (ERAN) in inferofrontal brain regions. Here, we tested whether the ERAN is modulated by expertise in more than one music culture, as typical of folk musicians. Finnish folk musicians and nonmusicians participated in electroencephalography recordings. The cadences consisted of seven chords. In incongruous cadences, the third, fifth, or seventh chord was a Neapolitan. The ERAN to the Neapolitans was enhanced in folk musicians compared to nonmusicians. Folk musicians showed an enhanced P3a for the ending Neapolitan. The Neapolitan at the fifth position was perceived differently and elicited a late enhanced ERAN in folk musicians. Hence, expertise in more than one music culture seems to modify chord processing by enhancing the ERAN to ambivalent chords and the P3a to incongruous chords, and by altering their perceptual attributes. Copyright © 2013 Society for Psychophysiological Research.

Introducing Children to Folk Tales. Bill Harp Professional Teachers Library.

ERIC Educational Resources Information Center

Weir, Beth

This book provides K-8 teachers with an introductory resource on folk tales. The book acknowledges that teachers are often very interested in folk tales but lack the time to research them. Each chapter contains some background information on a story type or a character. The book's six chapters are as follows: (1) "The Folk Tale Tradition"; (2)…

Multi-Model Ensemble Wake Vortex Prediction

NASA Technical Reports Server (NTRS)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Humanizing folk devils using ethnography.

PubMed

Myers, Peter L

2018-01-01

The sociological concepts of the "moral panic" and the deviant "folk devil" apply to the drug panics in the United States over methamphetamine, heroin, and crack cocaine. Mothers or pregnant women who smoke crack cocaine, and their babies, are assigned exaggerated "demonic" attributes that result in stigma and societal rejection. Otherwise, ethnographic studies of drug users demonstrate realities that are other than what might be considered were one to merely look at their use and the consequences. These considerations are examined with respect to the image of folk devils, methadone program attendees, smokers of "blunts," opium den habitués, and others grouped together as negative influences as a result of their drug habits.

Folk Art Tells a Story: An Activity Guide.

ERIC Educational Resources Information Center

Thompson, Susan Conklin

Folk art tells the story of many generations and reflects cultures everywhere. It is a wonderful tool for introducing students to world cultures and traditions. This book brings the world of folk art into the classroom with extension activities that integrate art, social studies, science, language arts, and music. Organized into three sections,…

An analysis of contemporary East African folk psychotherapy.

PubMed

Rappaport, H; Dent, P L

1979-03-01

In an effort to identify the characteristics of folk psychotherapy that could account for its tenacity in East Africa, a total of 31 Tanzanian shamans were studied. It was found that patients with emotional problems make use of both the folk and Western therapists and that a clear conceptual distinction is made between the services offered. The range of techniques used, style of service delivered, and the fundamental (or underlying) model of causation were all analysed. It was concluded that folk therapy is an effective approach to psychosocial disorders which, in the future, should be considered a dynamic supplement to Western practices. Additionally, based on the appeal of the medicine man, new directions for Western psychotherapy were suggested.

Development of an adverse events reporting form for Korean folk medicine.

PubMed

Park, Jeong Hwan; Choi, Sun-Mi; Moon, Sujeong; Kim, Sungha; Kim, Boyoung; Kim, Min-Kyeoung; Lee, Sanghun

2017-05-01

We developed an adverse events (AEs) reporting form for Korean folk medicine. The first version of the form was developed and tested in the clinical setting for spontaneous reporting of AEs. Additional revisions to the reporting form were made based on collected data and expert input. We developed an AEs reporting form for Korean folk medicine. The items of this form were based on patient information, folk medicine properties, and AEs. For causality assessment, folk medicine properties such as classification, common and vernacular names, scientific name, part used, harvesting time, storage conditions, purchasing route, product licensing, prescription, persons with similar exposure, any remnant of raw natural products collected from the patient, and cautions or contraindications were added. This is the first reporting form for AEs that incorporates important characteristics of Korean folk medicine. This form would have an important role in reporting adverse events for Korean folk medicine. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

Development of an adverse events reporting form for Korean folk medicine

PubMed Central

Park, Jeong Hwan; Choi, Sun‐Mi; Moon, Sujeong; Kim, Sungha; Kim, Boyoung; Kim, Min‐Kyeoung

2016-01-01

Abstract Purpose We developed an adverse events (AEs) reporting form for Korean folk medicine. Methods The first version of the form was developed and tested in the clinical setting for spontaneous reporting of AEs. Additional revisions to the reporting form were made based on collected data and expert input. Results We developed an AEs reporting form for Korean folk medicine. The items of this form were based on patient information, folk medicine properties, and AEs. For causality assessment, folk medicine properties such as classification, common and vernacular names, scientific name, part used, harvesting time, storage conditions, purchasing route, product licensing, prescription, persons with similar exposure, any remnant of raw natural products collected from the patient, and cautions or contraindications were added. Conclusions This is the first reporting form for AEs that incorporates important characteristics of Korean folk medicine. This form would have an important role in reporting adverse events for Korean folk medicine. © 2016 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd. PMID:27501410

Regional Classification of Traditional Japanese Folk Songs

NASA Astrophysics Data System (ADS)

Kawase, Akihiro; Tokosumi, Akifumi

In this study, we focus on the melodies of Japanese folk songs, and examine the basic structures of Japanese folk songs that represent the characteristics of different regions. We sample the five largest song genres within the music corpora of the Nihon Min-yo Taikan (Anthology of Japanese Folk Songs), consisting of 202,246 tones from 1,794 song pieces from 45 prefectures in Japan. Then, we calculate the probabilities of 24 transition patterns that fill the interval of the perfect fourth pitch, which is the interval that maintains most of the frequency for one-step and two-step pitch transitions within 11 regions, in order to determine the parameters for cluster analysis. As a result, we successively classify the regions into two basic groups, eastern Japan and western Japan, which corresponds to geographical factors and cultural backgrounds, and also match accent distributions in the Japanese language.

Is Psychoanalysis a Folk Psychology?

PubMed Central

Arminjon, Mathieu

2013-01-01

Even as the neuro-psychoanalytic field has matured, from a naturalist point of view, the epistemological status of Freudian interpretations still remains problematic at a naturalist point of view. As a result of the resurgence of hermeneutics, the claim has been made that psychoanalysis is an extension of folk psychology. For these “extensionists,” asking psychoanalysis to prove its interpretations would be as absurd as demanding the proofs of the scientific accuracy of folk psychology. I propose to show how Dennett’s theory of the intentional stance allows us to defend an extensionist position while sparing us certain hermeneutic difficulties. In conclusion, I will consider how Shevrin et al. (1996) experiments could turn extensionist conceptual considerations into experimentally testable issues. PMID:23525879

Hungarian Folk Arts and Crafts. Educational Curriculum Kit 6.

ERIC Educational Resources Information Center

Boros-Kazai, Andrew

This booklet provides a brief introduction to Hungarian arts and crafts. A discussion of the historical development and characteristics of Hungarian folk art supplies the background for a section in which regional styles of Hungarian folk art are described (Transdanubia, the Highlands of northern Hungary, Transylvania, and the Great Hungarian…

Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

NASA Astrophysics Data System (ADS)

Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim

2017-07-01

We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

Ensemble habitat mapping of invasive plant species

USGS Publications Warehouse

Stohlgren, T.J.; Ma, P.; Kumar, S.; Rocca, M.; Morisette, J.T.; Jarnevich, C.S.; Benson, N.

2010-01-01

Ensemble species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. Ensemble models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species-environment relationships difficult to determine. We tested five individual models (logistic regression, boosted regression trees, random forest, multivariate adaptive regression splines (MARS), and maximum entropy model or Maxent) and ensemble modeling for selected nonnative plant species in Yellowstone and Grand Teton National Parks, Wyoming; Sequoia and Kings Canyon National Parks, California, and areas of interior Alaska. The models are based on field data provided by the park staffs, combined with topographic, climatic, and vegetation predictors derived from satellite data. For the four invasive plant species tested, ensemble models were the only models that ranked in the top three models for both field validation and test data. Ensemble models may be more robust than individual species-environment matching models for risk analysis. ?? 2010 Society for Risk Analysis.

Happily Ever After: Sharing Folk Literature with Elementary and Middle School Students

ERIC Educational Resources Information Center

Young, Terrell A., Ed.

2004-01-01

As an instructional tool, folk literature can foster literacy, promote cultural awareness, and create connections with the content areas. Yet few resources provide background about folk literature and how to use it your classroom. "Happily Ever After" fills this gap with a reader-friendly collection of articles that define folk literature and its…

Assessing a local ensemble Kalman filter: perfect model experiments with the National Centers for Environmental Prediction global model

NASA Astrophysics Data System (ADS)

Szunyogh, Istvan; Kostelich, Eric J.; Gyarmati, G.; Patil, D. J.; Hunt, Brian R.; Kalnay, Eugenia; Ott, Edward; Yorke, James A.

2005-08-01

The accuracy and computational efficiency of the recently proposed local ensemble Kalman filter (LEKF) data assimilation scheme is investigated on a state-of-the-art operational numerical weather prediction model using simulated observations. The model selected for this purpose is the T62 horizontal- and 28-level vertical-resolution version of the Global Forecast System (GFS) of the National Center for Environmental Prediction. The performance of the data assimilation system is assessed for different configurations of the LEKF scheme. It is shown that a modest size (40-member) ensemble is sufficient to track the evolution of the atmospheric state with high accuracy. For this ensemble size, the computational time per analysis is less than 9 min on a cluster of PCs. The analyses are extremely accurate in the mid-latitude storm track regions. The largest analysis errors, which are typically much smaller than the observational errors, occur where parametrized physical processes play important roles. Because these are also the regions where model errors are expected to be the largest, limitations of a real-data implementation of the ensemble-based Kalman filter may be easily mistaken for model errors. In light of these results, the importance of testing the ensemble-based Kalman filter data assimilation systems on simulated observations is stressed.

The Usability of Erzurum Folk Songs in Viola Education

ERIC Educational Resources Information Center

Parasiz, Gökalp; Kervancioglu, M. Hanifi

2017-01-01

Present study is a descriptive and applied study from different sides. It was aimed to make the applications prepared for the usability of Erzurum's folk songs available in music and instrument education. First literature review was conducted and totally 240 folk songs were determined to belong to Erzurum province. Among the songs determined,…

The Meaning and Use of Folk Speech in Art Criticism.

ERIC Educational Resources Information Center

Congdon, Kristin G.

1986-01-01

This article investigates the use of folk speech in the art criticism of people who are not art professionals. Maintains that if folk speech is recognized and evaluated in the art classroom, art educators may help expand both the visual and verbal perceptions and expressions of students. (JDH)

Folk-Economic Beliefs: An Evolutionary Cognitive Model.

PubMed

Boyer, Pascal; Petersen, Michael Bang

2017-10-12

The domain of "folk-economics" consists in explicit beliefs about the economy held by laypeople, untrained in economics, about such topics as e.g., the causes of the wealth of nations, the benefits or drawbacks of markets and international trade, the effects of regulation, the origins of inequality, the connection between work and wages, the economic consequences of immigration, or the possible causes of unemployment. These beliefs are crucial in forming people's political beliefs, and in shaping their reception of different policies. Yet, they often conflict with elementary principles of economic theory and are often described as the consequences of ignorance, irrationality or specific biases. As we will argue, these past perspectives fail to predict the particular contents of popular folk-economic beliefs and, as a result, there is no systematic study of the cognitive factors involved in their emergence and cultural success. Here we propose that the cultural success of particular beliefs about the economy is predictable if we consider the influence of specialized, largely automatic inference systems that evolved as adaptations to ancestral human small-scale sociality. These systems, for which there is independent evidence, include free-rider detection, fairness-based partner-choice, ownership intuitions, coalitional psychology, and more. Information about modern mass-market conditions activates these specific inference-systems, resulting in particular intuitions, e.g., that impersonal transactions are dangerous or that international trade is a zero-sum game. These intuitions in turn make specific policy proposals more likely than others to become intuitively compelling, and as a consequence exert a crucial influence on political choices.

Generalized canonical ensembles and ensemble equivalence

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

Costeniuc, M.; Ellis, R.S.; Turkington, B.

2006-02-15

This paper is a companion piece to our previous work [J. Stat. Phys. 119, 1283 (2005)], which introduced a generalized canonical ensemble obtained by multiplying the usual Boltzmann weight factor e{sup -{beta}}{sup H} of the canonical ensemble with an exponential factor involving a continuous function g of the Hamiltonian H. We provide here a simplified introduction to our previous work, focusing now on a number of physical rather than mathematical aspects of the generalized canonical ensemble. The main result discussed is that, for suitable choices of g, the generalized canonical ensemble reproduces, in the thermodynamic limit, all the microcanonical equilibriummore » properties of the many-body system represented by H even if this system has a nonconcave microcanonical entropy function. This is something that in general the standard (g=0) canonical ensemble cannot achieve. Thus a virtue of the generalized canonical ensemble is that it can often be made equivalent to the microcanonical ensemble in cases in which the canonical ensemble cannot. The case of quadratic g functions is discussed in detail; it leads to the so-called Gaussian ensemble.« less

Toward a Theoretical Approach to Teaching Folk Art: A Definition.

ERIC Educational Resources Information Center

Congdon, Kristin G.

1987-01-01

Proposes a definition for folk art based on analyzing and sorting the descriptors and identifiers used in the disciplines of art history, folklore, anthropology, and antique and folk art collection. The proposed definition is not meant to specify an undeniable category of art, but rather to suggest specific aspects which should be identified in…

Teaching Hispanic Culture through Folk Music

ERIC Educational Resources Information Center

Griffin, Robert J.

1977-01-01

Folk music is musical expression of deep culture, and is therefore a useful tool in teaching culture in the language class. The use of Spanish music to teach Hispanic culture is described. Useful books and music are suggested. (CHK)

Other Dreams, Other Schools: Folk Colleges in Social and Ethnic Movements.

ERIC Educational Resources Information Center

Paulston, Rolland G.

The book presents 13 articles which examine objectives, practices, sociocultural influences, and limitations of folk high schools in Northern Europe and North America from 1800 to the 1970s. Folk high schools are residential education institutions for young adults which are based upon heightening individual consciousness and commitment to a…

The Gothic Folk Devils Strike Back! Theorizing Folk Devil Reaction in the Post-Columbine Era

ERIC Educational Resources Information Center

Griffiths, Richard

2010-01-01

Folk devils have to date been significantly overlooked in previous studies of moral panics. While several studies have called attention to this problematic (Thornton and McRobbie 1995, De Young 2004, Lumsden 2009), no specific theoretical framework has been proposed for reading this dimension of a moral panic. This paper argues that a moral panic…

Curanderismo: consequences of folk medicine.

PubMed

DeBellonia, Renato Rocco; Marcus, Steven; Shih, Richard; Kashani, John; Rella, Joseph G; Ruck, Bruce

2008-04-01

Curanderismo, folk medicine, is an important and common aspect of Hispanic culture. Its use is not well understood by US medical physicians and is often overlooked when Hispanic patients present to US hospitals. We present a case of isopropyl alcohol toxicity in a 4-year-old child due to the use of a curanderismo treatment of "espanto" (evil spirits).

The Celebration of Death: Two Folk Tales about DEath. Mini-Module.

ERIC Educational Resources Information Center

African-American Inst., New York, NY. School Services Div.

This module contains two African folk tales about death, two descriptions of African funerals, a lesson plan with 11 questions exploring the finality of and customs surrounding death, and a bibliography of five books which deal with African religious beliefs. The folk tales present concepts of death and immortality of the soul. The descriptions of…

Seasonal Drought Prediction in East Africa: Can National Multi-Model Ensemble Forecasts Help?

NASA Technical Reports Server (NTRS)

Shukla, Shraddhanand; Roberts, J. B.; Funk, Christopher; Robertson, F. R.; Hoell, Andrew

2015-01-01

The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as in 2011 part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However seasonal drought prediction in this region faces several challenges. Lack of skillful seasonal rainfall forecasts; the focus of this presentation, is one of those major challenges. In the past few decades, major strides have been taken towards improvement of seasonal scale dynamical climate forecasts. The National Centers for Environmental Prediction's (NCEP) National Multi-model Ensemble (NMME) is one such state-of-the-art dynamical climate forecast system. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ ensemble member forecasts. Recent studies have indicated that in general NMME offers improvement over forecasts from any single model. However thus far the skill of NMME for forecasting rainfall in a vulnerable region like the East Africa has been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons for the region. (i.e. March-April-May, July-August-September and October-November- December). Simultaneously we also describe hybrid approaches; that combine statistical approaches with NMME forecasts; to improve rainfall forecast skill in the region when raw NMME forecasts lack in skill.

Seasonal Drought Prediction in East Africa: Can National Multi-Model Ensemble Forecasts Help?

NASA Technical Reports Server (NTRS)

Shukla, Shraddhanand; Roberts, J. B.; Funk, Christopher; Robertson, F. R.; Hoell, Andrew

2014-01-01

The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as in 2011 part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However seasonal drought prediction in this region faces several challenges. Lack of skillful seasonal rainfall forecasts; the focus of this presentation, is one of those major challenges. In the past few decades, major strides have been taken towards improvement of seasonal scale dynamical climate forecasts. The National Centers for Environmental Prediction's (NCEP) National Multi-model Ensemble (NMME) is one such state-of-the-art dynamical climate forecast system. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ ensemble member forecasts. Recent studies have indicated that in general NMME offers improvement over forecasts from any single model. However thus far the skill of NMME for forecasting rainfall in a vulnerable region like the East Africa has been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons for the region. (i.e. March-April-May, July-August-September and October-November- December). Simultaneously we also describe hybrid approaches; that combine statistical approaches with NMME forecasts; to improve rainfall forecast skill in the region when raw NMME forecasts lack in skill.

The Ensembl REST API: Ensembl Data for Any Language.

PubMed

Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

2015-01-01

We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.

Imitation, Awareness, and Folk Linguistic Artifacts

ERIC Educational Resources Information Center

Brunner, Elizabeth Gentry

2010-01-01

Imitations are sophisticated performances displaying regular patterns. The study of imitation allows linguists to understand speakers' perceptions of sociolinguistic variation. In this dissertation, I analyze imitations of non-native accents in order to answer two questions: what can imitation reveal about perception, and how are "folk linguistic…

The Ensembl REST API: Ensembl Data for Any Language

PubMed Central

Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R. S.; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

2015-01-01

Motivation: We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. Availability and implementation: The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. Contact: ayates@ebi.ac.uk or flicek@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25236461

Computational Drafting of Plot Structures for Russian Folk Tales.

PubMed

Gervás, Pablo

The plots of stories are known to follow general patterns in terms of their overall structure. This was the basic tenet of structuralist approaches to narratology. Vladimir Propp proposed a procedure for the generation of new tales based on his semi-formal description of the structure of Russian folk tales. This is one of the first existing instances of a creative process described procedurally. The present paper revisits Propp's morphology to build a system that generates instances of Russian folk tales. Propp's view of the folk tale as a rigid sequence of character functions is employed as a plot driver, and some issues that Propp declared relevant but did not explore in detail-such as long-range dependencies between functions or the importance of endings-are given computational shape in the context of a broader architecture that captures all the aspects discussed by Propp. A set of simple evaluation metrics for the resulting outputs is defined inspired on Propp's formalism. The potential of the resulting system for providing a creative story generation system is discussed, and possible lines of future work are discussed.

Cultural Democracy, Folk Schools and Community Development: Some Ethical and Philosophical Issues.

ERIC Educational Resources Information Center

Brose, David A.

1991-01-01

Folk and settlement schools have served predominantly Anglo-American constituents and have focused upon Anglo-American and western European traditions. The John C. Campbell Folk School (JCCFS) was founded in southwestern North Carolina in 1925. The school's founder, Olive Dame Campbell, was considered progressive in her time in desiring to serve…

Passing It On--Folk Artists and Education in Cumberland County, New Jersey.

ERIC Educational Resources Information Center

Moonsammy, Rita Zorn

This New Jersey Folk Artists in Education program brings community educators together with professional educators to enrich students' appreciation of their own and others' traditional cultures at the same time as they develop basic skills. The life stories of nine folk artists and their communities, as well as the stories of how they work together…

[Research and analysis to Shui nationality medicine treatment orthopedics & traumatology].

PubMed

Hu, Jian-Shan; Li, Pu; Yang, Yong; Chen, Xin-Chun; Lin, Li

2013-05-01

To investigated Shui nationality folk medicine's awareness to orthopedics & traumatology, the history of orthopedics & traumatology treatment, Shui nationality folk doctors' practicing medicine, heritage, diagnosis and treatment methods and tools, etc, through investigated drug resources category and distribution characteristics of Shui nationality medicine to orthopedics & traumatology treatment, explored and finished Shui nationality medicine orthopedics & traumatology treatment theoretical system. After more than 5 years' exploration and finishing, preliminarily formed the theoretical system framework and medicine application characteristics of Shui nationality medicine treating orthopedics & traumatology. Shui nationality medicine treatment orthopedics & traumatology has distinctive national style, and worthy to further exploration and research.

The Polish Folk High Schools. Occasional Papers in Continuing Education. Number 17.

ERIC Educational Resources Information Center

Kulich, Jindra; Bron-Wojciechowska, Agnieszka

Polish folk high schools are modeled after schools developed in the mid-1850s in Denmark to provide general, non-credit education for young adults in rural areas. The main objectives of the folk high schools are to provide a climate for individual student development and to serve as centers where young adults can learn about their cultural…

Multi-dimensionality and variability in folk classification of stingless bees (Apidae: Meliponini).

PubMed

Zamudio, Fernando; Hilgert, Norma I

2015-05-23

Not long ago Eugene Hunn suggested using a combination of cognitive, linguistic, ecological and evolutionary theories in order to account for the dynamic character of ethnoecology in the study of folk classification systems. In this way he intended to question certain homogeneity in folk classifications models and deepen in the analysis and interpretation of variability in folk classifications. This paper studies how a rural culturally mixed population of the Atlantic Forest of Misiones (Argentina) classified honey-producing stingless bees according to the linguistic, cognitive and ecological dimensions of folk classification. We also analyze the socio-ecological meaning of binomialization in naming and the meaning of general local variability in the appointment of stingless bees. We used three different approaches: the classical approach developed by Brent Berlin which relies heavily on linguistic criteria, the approach developed by Eleonor Rosch which relies on psychological (cognitive) principles of categorization and finally we have captured the ecological dimension of folk classification in local narratives. For the second approximation, we developed ways of measuring the degree of prototypicality based on a total of 107 comparisons of the type "X is similar to Y" identified in personal narratives. Various logical and grouping strategies coexist and were identified as: graded of lateral linkage, hierarchical and functional. Similarity judgments among folk taxa resulted in an implicit logic of classification graded according to taxa's prototypicality. While there is a high agreement on naming stingless bees with monomial names, a considerable number of underrepresented binomial names and lack of names were observed. Two possible explanations about reported local naming variability are presented. We support the multidimensionality of folk classification systems. This confirms the specificity of local classification systems but also reflects the use of grouping

Simulation's Ensemble is Better Than Ensemble Simulation

NASA Astrophysics Data System (ADS)

Yan, X.

2017-12-01

Simulation's ensemble is better than ensemble simulation Yan Xiaodong State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE) Beijing Normal University,19 Xinjiekouwai Street, Haidian District, Beijing 100875, China Email: yxd@bnu.edu.cnDynamical system is simulated from initial state. However initial state data is of great uncertainty, which leads to uncertainty of simulation. Therefore, multiple possible initial states based simulation has been used widely in atmospheric science, which has indeed been proved to be able to lower the uncertainty, that was named simulation's ensemble because multiple simulation results would be fused . In ecological field, individual based model simulation (forest gap models for example) can be regarded as simulation's ensemble compared with community based simulation (most ecosystem models). In this talk, we will address the advantage of individual based simulation and even their ensembles.

Ensemble Methods

NASA Astrophysics Data System (ADS)

Re, Matteo; Valentini, Giorgio

2012-03-01

Ensemble methods are statistical and computational learning procedures reminiscent of the human social learning behavior of seeking several opinions before making any crucial decision. The idea of combining the opinions of different "experts" to obtain an overall “ensemble” decision is rooted in our culture at least from the classical age of ancient Greece, and it has been formalized during the Enlightenment with the Condorcet Jury Theorem[45]), which proved that the judgment of a committee is superior to those of individuals, provided the individuals have reasonable competence. Ensembles are sets of learning machines that combine in some way their decisions, or their learning algorithms, or different views of data, or other specific characteristics to obtain more reliable and more accurate predictions in supervised and unsupervised learning problems [48,116]. A simple example is represented by the majority vote ensemble, by which the decisions of different learning machines are combined, and the class that receives the majority of “votes” (i.e., the class predicted by the majority of the learning machines) is the class predicted by the overall ensemble [158]. In the literature, a plethora of terms other than ensembles has been used, such as fusion, combination, aggregation, and committee, to indicate sets of learning machines that work together to solve a machine learning problem [19,40,56,66,99,108,123], but in this chapter we maintain the term ensemble in its widest meaning, in order to include the whole range of combination methods. Nowadays, ensemble methods represent one of the main current research lines in machine learning [48,116], and the interest of the research community on ensemble methods is witnessed by conferences and workshops specifically devoted to ensembles, first of all the multiple classifier systems (MCS) conference organized by Roli, Kittler, Windeatt, and other researchers of this area [14,62,85,149,173]. Several theories have been

Folk Etymology (In English and Elsewhere).

ERIC Educational Resources Information Center

Poruciuc, Adrian

Folk etymology is defined as a change in word or phrase form resulting from an incorrect popular idea of its origin or meaning. Irregular phonetic-semantic shifts are produced by inter-language borrowing or by intra-language passage from one period to another. These shifts are more common in periods when there are no, or few, normative factors…

Retention of College Students and Freshman-Year Music Ensemble Participation

ERIC Educational Resources Information Center

Crowe, Don R.

2015-01-01

This study investigates the effects of music ensemble participation during the freshman fall semester on the ongoing retention of college students. Retention of college students is a concern across the nation. The research question for the study was, "Is there a correlation between participation in music ensembles during college students'…

Folk Medicine of Nasik District (Maharashtra), India

PubMed Central

Patil, M.V.; Patil, D.A.

2001-01-01

The study concerns the first -hand information on 50 ethnomedicinal plants traditional used by aborigines and rural folks of Nasik district, Maharashtra, for the treatment of various human ailments and disorders. The paper gives botanical identity, local name, family and mode of administration. PMID:22557009

Residue-level global and local ensemble-ensemble comparisons of protein domains.

PubMed

Clark, Sarah A; Tronrud, Dale E; Karplus, P Andrew

2015-09-01

Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a "consistency check" of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. © 2015 The Protein Society.

Residue-level global and local ensemble-ensemble comparisons of protein domains

PubMed Central

Clark, Sarah A; Tronrud, Dale E; Andrew Karplus, P

2015-01-01

Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a “consistency check” of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. PMID:26032515

Prevalence and factors associated with the use of alternative (folk) medicine practitioners in 8 countries of the former Soviet Union.

PubMed

Stickley, Andrew; Koyanagi, Ai; Richardson, Erica; Roberts, Bayard; Balabanova, Dina; McKee, Martin

2013-04-11

Research suggests that since the collapse of the Soviet Union there has been a sharp growth in the use of complementary and alternative medicine (CAM) in some former Soviet countries. However, as yet, comparatively little is known about the use of CAM in the countries throughout this region. Against this background, the aim of the current study was to determine the prevalence of using alternative (folk) medicine practitioners in eight countries of the former Soviet Union (fSU) and to examine factors associated with their use. Data were obtained from the Living Conditions, Lifestyles and Health (LLH) survey undertaken in eight former Soviet countries (Armenia, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Russia and Ukraine) in 2001. In this nationally representative cross-sectional survey, 18428 respondents were asked about how they treated 10 symptoms, with options including the use of alternative (folk) medicine practitioners. Multivariate logistic regression analysis was used to determine the factors associated with the treatment of differing symptoms by such practitioners in these countries. The prevalence of using an alternative (folk) medicine practitioner for symptom treatment varied widely between countries, ranging from 3.5% in Armenia to 25.0% in Kyrgyzstan. For nearly every symptom, respondents living in rural locations were more likely to use an alternative (folk) medicine practitioner than urban residents. Greater wealth was also associated with using these practitioners, while distrust of doctors played a role in the treatment of some symptoms. The widespread use of alternative (folk) medicine practitioners in some fSU countries and the growth of this form of health care provision in the post-Soviet period in conditions of variable licensing and regulation, highlights the urgent need for more research on this phenomenon and its potential effects on population health in the countries in this region.

Teaching Strategies for Specialized Ensembles.

ERIC Educational Resources Information Center

Teaching Music, 1999

1999-01-01

Provides a strategy, from the book "Strategies for Teaching Specialized Ensembles," that addresses Standard 9A of the National Standards for Music Education. Explains that students will identify and describe the musical and historical characteristics of the classical era in music they perform and in audio examples. (CMK)

[Resources and application of She's nationality wild medicinal plants].

PubMed

Lei, Hou-Xing; Li, Jian-Liang; Zheng, Song-Ming; Fan, Li-Hua; Li, Shui-Fu; Cheng, Wen-Liang; Hua, Jin-Wei; Yu, Hua-Li; Dai, De-Xiong; Xie, Yuan-Wei

2014-08-01

To make a thorough investigation of the common She's nationality wild medicinal plants resources in our country, including the species, the distribution, the folk application and the endemic medicinal plant species, Field surveyed was conducted with 25 She people mainly lived area (county, district or city) throughout the country, the folk prescription and treatment cases provided by She's medical personnel, the drug usage and dosage, the commonly used traditional She's medicine and drug samples were collected. And the distribution, growing environment of these plants were investigated, their characteristics, photographs, GPS data and track were record , and the fresh wax leaf or plants specimens were collected. In total 1 600 varieties of folk medicine of She's nationality, 450 disease names and 1 016 prescriptions were collected. 520 kinds of these medicinal plants were commonly used, growing mainly distributed in the southeastern China, about 200 meters above sea level to 1 500 meters. There are 5 First-Grade State protection wild plants (medicinal), 15 second-Grade State protection wild plants (medicinal), and 11 She characteristic medicinal plants in our study, they belong to 144 families, 312 genera 494 species, 2 subspecies, 17 varieties, 3 forms and 1 cultivated varieties of She's nationality. Folk medicine usage is different from the traditional Chinese medicine and ethnic medicine. This survey finds out the common She's nationality wild medicinal plants resources in China, including the species, the distribution, the folk application and commonly used drugs, and found the rare and endangered medicinal plants and the She's nationality endemic medicinal plants, which provides a basis for further development and use the traditional She's medicine resources.

Demographics, training, and practice patterns of practitioners of folk medicine in Taiwan: a survey of the Taipei metropolitan area.

PubMed

Tsai, Pei-Shan; Lee, Pi-Hsia; Wang, Mei-Yeh

2008-12-01

The purpose of this study was to investigate the demographics, training, and practice patterns of folk medicine practitioners, their opinions toward statutory regulation of folk medicine, and the formal education and credentialing for folk medicine providers in the metropolitan Taipei area. A cross-sectional survey design was used. Included in the survey were 200 folk medicine practitioners in Taipei city and 200 folk medicine practitioners in Taipei county. The survey questionnaire consisted of 3 domains including demographics and training; practice patterns; and opinions toward statutory regulation of folk medicine and formal education and credentialing for Tuina, Ba Guan, Gua Sha, and reflexology providers. The response rates ranged from 86.3% to 99.5%. A typical folk medicine provider in the Taipei metropolitan area was a middle-aged man with a high school degree who worked about 50 hours a week. The majority of the providers in the Taipei metropolitan area received their training through apprenticeship. Years of training and experience varied widely among these practitioners. About 80% had received more than one year of training prior to starting their practice. Adult men and women were their major clientele. The major treatment modalities they offered were Tuina, Gua Sha, Ba Guan, reflexology, and meridian massage. The majority of the respondents agreed that practitioners should receive formal education and training and agreed that certifying the qualifications of folk medicine practitioners is necessary. Findings from the present survey provide an understanding of the training and practice patterns of Taiwanese folk medicine practitioners, highlight folk medicine practitioners' needs for formal education and training, and stress the importance of statutory regulation of folk medicine in Taiwan.

Pediatric lead poisoning from folk prescription for treating epilepsy.

PubMed

Ying, Xiao-Lan; Xu, Jian; Markowitz, Morri; Yan, Chong-Huai

2016-10-01

A case of lead poisoning resulting from the ingestion of a folk remedy for treating epilepsy is reported. The initial blood lead concentration of this 6-y-old boy was 63.6μg/dl upon admission. He presented with abdominal pain, constipation, and irritability. The patient's liver function tests were significantly increased. Through chelation therapy, the blood lead concentration dropped markedly and clinical symptoms greatly improved. His blood and urine samples were collected for the kinetic analysis of lead elimination. Folk prescriptions for epilepsy should be considered as potential sources of lead intoxication. Lead poisoning should be taken into consideration for unknown causes of abdominal pain. Copyright © 2016. Published by Elsevier B.V.

Folk Linguistics and Language Teaching Education. A Case Study in an Italian Secondary School

ERIC Educational Resources Information Center

Santipolo, Matteo

2016-01-01

This paper, after shortly introducing "Folk Linguistics" by defining its domain of competence [cf. Preston, Dennis R., ed. 1999. "Handbook of Perceptual Dialectology." Amsterdam: John Benjamins; Niedzielski, Nancy A., and Dennis R. Preston. 2003. "Folk Linguistics." Berlin: Mouton de Gruyter], attempts to draw an…

Verification of folk medicinal potentiality for some common plants in Jordan.

PubMed

Al-Qura'n, S

2006-10-01

87 Species belonging to 59 genera and 33 plant families were identified and presented in the area of study. The largest 3 families are: Lamiaceae (9 aquatic species), Asteraceae (7 species), and Salicaceae (7 species). The largest genera are Mentha (6 species), Polygonum (5 species), and Salix (5 species). 63 folk medicinal aquatic species (73.3%) have therapeutic similarities with neighbouring countries, while the 24 remaining species (26.7%) haven't such therapeutic similarity. Emerged species (living with close contact with water body) were the most recorded, while amphibious, submerged or floating species were the least. The folk medicinal importance value of aquatic species recorded was identified according to Friedman parameters. 21 species (24%) have ROP values higher than 50, and therefore; have the highest popularity in folk medicinal potentiality. 26 species (29.9%) have therapeutic effects informed by less than three informants, and therefore, excluded from further consideration. 40 species (46.1%) have ROP values less than 50, and therefore; considered nonpopular medicinal plants.

Florida Folk Festival: Asian and Pacific Island Traditions in Florida. Resource Materials for Teachers.

ERIC Educational Resources Information Center

Smith. KC, Ed.

This information and activity booklet discusses the Florida Folk Festival, a celebration that offers students and teachers an opportunity to hear music, taste foods, see folk art demonstrations, observe dance, and listen to stories that celebrate Florida's cultural and ethnic legacies. The booklet offers resources for learning about Florida…

Tuning Features of Chinese Folk Song Singing: A Case Study of Hua'er Music.

PubMed

Yang, Yang; Welch, Graham; Sundberg, Johan; Himonides, Evangelos

2015-07-01

The learning and teaching of different singing styles, such as operatic and Chinese folk singing, was often found to be very challenging in professional music education because of the complexity of varied musical properties and vocalizations. By studying the acoustical and musical parameters of the singing voice, this study identified distinctive tuning characteristics of a particular folk music in China-Hua'er music-to inform the ineffective folk singing practices, which were hampered by the neglect of inherent tuning issues in music. Thirteen unaccompanied folk song examples from four folk singers were digitally audio recorded in a sound studio. Using an analyzing toolkit consisting of Praat, PeakFit, and MS Excel, the fundamental frequencies (F0) of these song examples were extracted into sets of "anchor pitches" mostly used, which were further divided into 253 F0 clusters. The interval structures of anchor pitches within each song were analyzed and then compared across 13 examples providing parameters that indicate the tuning preference of this particular singing style. The data analyses demonstrated that all singers used a tuning pattern consisting of five major anchor pitches suggesting a nonequal-tempered bias in singing. This partly verified the pentatonic scale proposed in previous empirical research but also argued a potential misunderstanding of the studied folk music scale that failed to take intrinsic tuning issues into consideration. This study suggests that, in professional music training, any tuning strategy should be considered in terms of the reference pitch and likely tuning systems. Any accompanying instruments would need to be tuned to match the underlying tuning bias. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

National originality of the architecture of Khreshchatyk as a unique ensemble of the period of totalitarianism

NASA Astrophysics Data System (ADS)

Oliynyk, Olena

2018-03-01

Khreschatyk is a page apart in the history of world architecture. While it has a number of distinct characteristics of totalitarian architecture, Khreschatyk is the only architectural ensemble of the period to combine na-tional tradition with the exalted sentiment of Soviet architecture of the Stalin era. Also, it uniquely matched architecture and landscape. The façades has elements of Ukrainian baroque, which sets Khreschatyk apart from similar ensembles of the 1940s-1950s in other countries that mainly drew upon Ne-oclassicism or Modernism. While period architecture in other countries is typically marked by its grand scale and heavily accentuated civic spirit - complete with a denigration of the individual at the expense of the manifest greatness of Authority, Khreschatyk stand out for its pronounced harmony as an environment based on the careful preservation of old heritage, the skill-ful use of the landscape, and the introduction of traditional motifs, alongside an almost total lack of Soviet symbols. Unlike the grim grandness of totali-tarian architecture in other countries, the facades of the residential buildings that line Khreschatyk emanate joie de vivre and admiration for the fertility of Ukrainian soil.

Folk Phenomenology and the Offering of Teaching

ERIC Educational Resources Information Center

Rocha, Samuel D.

2016-01-01

This article will move in five parts. It begins with some priming notes on the relationship between philosophy of education and curriculum theory. Then it rehearses a collage of selected passages from a recent book, "Folk Phenomenology: Education, Study, and the Human Person" (Rocha, 2015a). Then the author works in a more speculative…

The Hydrologic Ensemble Prediction Experiment (HEPEX)

NASA Astrophysics Data System (ADS)

Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.

2012-12-01

The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological ensemble prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

Using Folk Literature. Learning Package No. 3.

ERIC Educational Resources Information Center

Smith, Carl, Comp.

Originally developed for the Department of Defense Schools (DoDDS) system, this learning package on using folk literature is designed for teachers who wish to upgrade or expand their teaching skills on their own. The package includes a comprehensive search of the ERIC database; a lecture giving an overview on the topic; the full text of several…

Comparison of Movement Notation (Laban) and Traditional Methodological Learning Success in Teaching Folk Dances

ERIC Educational Resources Information Center

Elyagutu, Dilek Cantekin; Hazar, Muhsin

2017-01-01

In this research, Movement Notation (Laban) and Traditional Method in Folk dance Teaching were compared in terms of learning success. Movement notation group (n = 14) and Traditional group (n = 14) consisting of students from the S.U. State Conservatory Turkish Folk Dance Department were formed. During the 14-week-long study, the symbols of the…

Research on the Boost of Development on Young Children's Fine Motor by Folk Games

ERIC Educational Resources Information Center

Wei, Xia

2016-01-01

As Chinese traditional folk culture, folk games have unique educational value which can boost the development of young children's fine motor. Based on previous investigation of fine motor skill of children in Nanchong, Sichuan Province, the researcher chose a middle class in public city kindergarten A with lower survey score as the study object.…

Three-model ensemble wind prediction in southern Italy

NASA Astrophysics Data System (ADS)

Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo

2016-03-01

Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

Ensemble Downscaling of Winter Seasonal Forecasts: The MRED Project

NASA Astrophysics Data System (ADS)

Arritt, R. W.; Mred Team

2010-12-01

The Multi-Regional climate model Ensemble Downscaling (MRED) project is a multi-institutional project that is producing large ensembles of downscaled winter seasonal forecasts from coupled atmosphere-ocean seasonal prediction models. Eight regional climate models each are downscaling 15-member ensembles from the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) and the new NASA seasonal forecast system based on the GEOS5 atmospheric model coupled with the MOM4 ocean model. This produces 240-member ensembles, i.e., 8 regional models x 15 global ensemble members x 2 global models, for each winter season (December-April) of 1982-2003. Results to date show that combined global-regional downscaled forecasts have greatest skill for seasonal precipitation anomalies during strong El Niño events such as 1982-83 and 1997-98. Ensemble means of area-averaged seasonal precipitation for the regional models generally track the corresponding results for the global model, though there is considerable inter-model variability amongst the regional models. For seasons and regions where area mean precipitation is accurately simulated the regional models bring added value by extracting greater spatial detail from the global forecasts, mainly due to better resolution of terrain in the regional models. Our results also emphasize that an ensemble approach is essential to realizing the added value from the combined global-regional modeling system.

HLPI-Ensemble: Prediction of human lncRNA-protein interactions based on ensemble strategy.

PubMed

Hu, Huan; Zhang, Li; Ai, Haixin; Zhang, Hui; Fan, Yetian; Zhao, Qi; Liu, Hongsheng

2018-03-27

LncRNA plays an important role in many biological and disease progression by binding to related proteins. However, the experimental methods for studying lncRNA-protein interactions are time-consuming and expensive. Although there are a few models designed to predict the interactions of ncRNA-protein, they all have some common drawbacks that limit their predictive performance. In this study, we present a model called HLPI-Ensemble designed specifically for human lncRNA-protein interactions. HLPI-Ensemble adopts the ensemble strategy based on three mainstream machine learning algorithms of Support Vector Machines (SVM), Random Forests (RF) and Extreme Gradient Boosting (XGB) to generate HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble, respectively. The results of 10-fold cross-validation show that HLPI-SVM Ensemble, HLPI-RF Ensemble and HLPI-XGB Ensemble achieved AUCs of 0.95, 0.96 and 0.96, respectively, in the test dataset. Furthermore, we compared the performance of the HLPI-Ensemble models with the previous models through external validation dataset. The results show that the false positives (FPs) of HLPI-Ensemble models are much lower than that of the previous models, and other evaluation indicators of HLPI-Ensemble models are also higher than those of the previous models. It is further showed that HLPI-Ensemble models are superior in predicting human lncRNA-protein interaction compared with previous models. The HLPI-Ensemble is publicly available at: http://ccsipb.lnu.edu.cn/hlpiensemble/ .

Folk Hero Modeling Therapy for Puerto Rican Adolescents.

ERIC Educational Resources Information Center

Costantino, Guiseppe; And Others

1988-01-01

Describes development of a new modality for Puerto Rican adolescents which presents Puerto Rican folk heros and heroines in modeling therapy targeted towards enhancing adolescents' pride in their ethnic heritage. Evaluation of therapy using 21 adolescents indicated subjects increased in self-disclosure and self-confidence, gained pride, learned…

Individual differences in ensemble perception reveal multiple, independent levels of ensemble representation.

PubMed

Haberman, Jason; Brady, Timothy F; Alvarez, George A

2015-04-01

Ensemble perception, including the ability to "see the average" from a group of items, operates in numerous feature domains (size, orientation, speed, facial expression, etc.). Although the ubiquity of ensemble representations is well established, the large-scale cognitive architecture of this process remains poorly defined. We address this using an individual differences approach. In a series of experiments, observers saw groups of objects and reported either a single item from the group or the average of the entire group. High-level ensemble representations (e.g., average facial expression) showed complete independence from low-level ensemble representations (e.g., average orientation). In contrast, low-level ensemble representations (e.g., orientation and color) were correlated with each other, but not with high-level ensemble representations (e.g., facial expression and person identity). These results suggest that there is not a single domain-general ensemble mechanism, and that the relationship among various ensemble representations depends on how proximal they are in representational space. (c) 2015 APA, all rights reserved).

"Some Things in My House Have a Pulse and a Downbeat": The Role of Folk and Traditional Arts Instruction in Supporting Student Learning

ERIC Educational Resources Information Center

Palmer Wolf, Dennie; Holochwost, Steven J.; Bar-Zemer, Tal; Dargan, Amanda; Selhorst, Anika

2014-01-01

The authors investigated the association between participation in Nations in Neighborhoods (NiN), a program of folk and traditional arts instruction, and achievement in English language arts in a sample of low-income elementary school students, many of whom were recent immigrants and English language learners. The program drew on the core…

Ensembl regulation resources

PubMed Central

Zerbino, Daniel R.; Johnson, Nathan; Juetteman, Thomas; Sheppard, Dan; Wilder, Steven P.; Lavidas, Ilias; Nuhn, Michael; Perry, Emily; Raffaillac-Desfosses, Quentin; Sobral, Daniel; Keefe, Damian; Gräf, Stefan; Ahmed, Ikhlak; Kinsella, Rhoda; Pritchard, Bethan; Brent, Simon; Amode, Ridwan; Parker, Anne; Trevanion, Steven; Birney, Ewan; Dunham, Ian; Flicek, Paul

2016-01-01

New experimental techniques in epigenomics allow researchers to assay a diversity of highly dynamic features such as histone marks, DNA modifications or chromatin structure. The study of their fluctuations should provide insights into gene expression regulation, cell differentiation and disease. The Ensembl project collects and maintains the Ensembl regulation data resources on epigenetic marks, transcription factor binding and DNA methylation for human and mouse, as well as microarray probe mappings and annotations for a variety of chordate genomes. From this data, we produce a functional annotation of the regulatory elements along the human and mouse genomes with plans to expand to other species as data becomes available. Starting from well-studied cell lines, we will progressively expand our library of measurements to a greater variety of samples. Ensembl’s regulation resources provide a central and easy-to-query repository for reference epigenomes. As with all Ensembl data, it is freely available at http://www.ensembl.org, from the Perl and REST APIs and from the public Ensembl MySQL database server at ensembldb.ensembl.org. Database URL: http://www.ensembl.org PMID:26888907

An Analysis of the Folk Artist in Education Program.

ERIC Educational Resources Information Center

Congdon, Kristin G.

1986-01-01

Discussed are (1) the goals and practices of the Folk Artist in Education (FAIE) program, (2) the FAIE in relationship to the Artist in Education program criticisms, (3) improving FAIE programs, and (4) reasons for its support. (RM)

Pop, Rock, and Folk Music: An Overlooked Resource

ERIC Educational Resources Information Center

Dubin, Fraida

1975-01-01

Proposes the use of pop, rock, and folk music as material far removed from the traditional and attuned to the learners' interests. Typical examples are analyzed with respect to phonology, grammar and semantics. A final category, "overall idea songs," linguistically unclassifiable, is found to be attractive and highly motivating. (IFS/WGA)

The Hydrologic Ensemble Prediction Experiment (HEPEX)

NASA Astrophysics Data System (ADS)

Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena

2015-04-01

The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (www.hepex.org), HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

NASA Astrophysics Data System (ADS)

Chen, Lei; Kamel, Mohamed S.

2016-01-01

In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

Ensembl 2004.

PubMed

Birney, E; Andrews, D; Bevan, P; Caccamo, M; Cameron, G; Chen, Y; Clarke, L; Coates, G; Cox, T; Cuff, J; Curwen, V; Cutts, T; Down, T; Durbin, R; Eyras, E; Fernandez-Suarez, X M; Gane, P; Gibbins, B; Gilbert, J; Hammond, M; Hotz, H; Iyer, V; Kahari, A; Jekosch, K; Kasprzyk, A; Keefe, D; Keenan, S; Lehvaslaiho, H; McVicker, G; Melsopp, C; Meidl, P; Mongin, E; Pettett, R; Potter, S; Proctor, G; Rae, M; Searle, S; Slater, G; Smedley, D; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Storey, R; Ureta-Vidal, A; Woodwark, C; Clamp, M; Hubbard, T

2004-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organize biology around the sequences of large genomes. It is a comprehensive and integrated source of annotation of large genome sequences, available via interactive website, web services or flat files. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. The facilities of the system range from sequence analysis to data storage and visualization and installations exist around the world both in companies and at academic sites. With a total of nine genome sequences available from Ensembl and more genomes to follow, recent developments have focused mainly on closer integration between genomes and external data.

Using automatic generation of Labanotation to protect folk dance

NASA Astrophysics Data System (ADS)

Wang, Jiaji; Miao, Zhenjiang; Guo, Hao; Zhou, Ziming; Wu, Hao

2017-01-01

Labanotation uses symbols to describe human motion and is an effective means of protecting folk dance. We use motion capture data to automatically generate Labanotation. First, we convert the motion capture data of the biovision hierarchy file into three-dimensional coordinate data. Second, we divide human motion into element movements. Finally, we analyze each movement and find the corresponding notation. Our work has been supervised by an expert in Labanotation to ensure the correctness of the results. At present, the work deals with a subset of symbols in Labanotation that correspond to several basic movements. Labanotation contains many symbols and several new symbols may be introduced for improvement in the future. We will refine our work to handle more symbols. The automatic generation of Labanotation can greatly improve the work efficiency of documenting movements. Thus, our work will significantly contribute to the protection of folk dance and other action arts.

Folk Remedies and Child Abuse: A Review with Emphasis on Caida de Mollera and Its Relationship to Shaken Baby Syndrome.

ERIC Educational Resources Information Center

Hansen, Karen Kirhofer

1998-01-01

Reviews a variety of folk remedies such as coining (Southeast Asia), cupping (primarily Russia), and moxibustion (Asia), which may be confused with child abuse. It especially considers the Hispanic folk illness "caida de mollera" (fallen fontanelle) but rejects the idea in the literature that folk treatment can cause the injuries seen in…

Bringing the "Folk" into Applied Linguistics: An Introduction

ERIC Educational Resources Information Center

Wilton, Antje; Stegu, Martin

2011-01-01

As applied linguistics is mainly concerned with solving the language-related problems of laypeople, the examination of folk views constitutes an important research field and its relevance is illustrated in this issue of the AILA review. In this introductory article, we address some of the more general aspects that need to be considered in the…

Folk Tales, Fairy Tales, and History: Uses and Classification.

ERIC Educational Resources Information Center

Claremont, Francesca

1993-01-01

Compiles excerpts from two 1964 lectures that examine the use of folk and fairy tales for the teaching of prehistory, geography, and grammar. Provides a starting point for thinking about the power of literature as an integrating medium in the Montessori elementary classroom. (HTH)

Folk Calendars in the Balkan Region

NASA Astrophysics Data System (ADS)

Kolev, Dimiter

Folk calendars are a good source for studying the knowledge and rituals of peoples from distant epochs. The turbulent history of the cultures in the Balkan Peninsula leads to a mixture of calendar traditions - different calendar types and naming systems of the calendar units (months and weekdays). Despite the differences, they share a common astronomical basis and the seasonal structure is of fundamental importance (i.e., dividing the year into two economic seasons - warm and cold). The Old Bulgarian 12-year calendar is also mentioned briefly.

Folk Arts in the Home: New Mexican Tinwork.

ERIC Educational Resources Information Center

Gomez, Aurelia; Sullivan, Laura Temple

New Mexican tinwork is a folk art tradition that developed out of Mexican and European silver work. Due to a lack of silver in New Mexico, tin became the material of choice. Rooted in European Hispanic traditions, this contemporary craft is yet another example of the resourceful ingenuity and adaptation that characterizes many New Mexican folk…

Elders' use of folk medicine and complementary and alternative therapies: an integrative review with implications for case managers.

PubMed

Sackett, Kay; Carter, Melondie; Stanton, Marietta

2014-01-01

The purpose of this study was to determine the prevalence of complementary and alternative medicine (CAM), folk medicine, and other nontraditional therapy use by the elderly population. For all case managers who coordinate health care for the elderly as they transition from one setting to another and participate in health promotion and prevention activities. A computerized database search of MEDLINE, CINAHL, ProQuest, and PsycINFO was completed before writing the integrative review. Six hundred ninety-seven abstracts were identified. Forty-five articles were further screened. Twenty-five articles met the criteria for inclusion. The integrative review is composed of 25 articles. Support for folk medicine and CAM use by older adults is located at Levels 5 and 6 of Melynk and Fine-Overholt's Hierarchy of Evidence. Folk medicine and CAM are used by the elderly for self-care purposes. A combination of both nontraditional and traditional medical interventions is used by the elderly. Although the choice to use folk medicine and CAM seems to transcend culture, the specific therapies chosen often emerge from the individual's cultural or ethnic heritage. Traditional health care providers may be unaware of elders' use of CAM or folk medicine alternatives. Case managers as coordinators of care across the health continuum are in a unique position to encourage, support, and enhance the use of folk medicine and CAM that complements traditional medical interventions for the elderly.

The Ensemble Canon

NASA Technical Reports Server (NTRS)

MIittman, David S

2011-01-01

Ensemble is an open architecture for the development, integration, and deployment of mission operations software. Fundamentally, it is an adaptation of the Eclipse Rich Client Platform (RCP), a widespread, stable, and supported framework for component-based application development. By capitalizing on the maturity and availability of the Eclipse RCP, Ensemble offers a low-risk, politically neutral path towards a tighter integration of operations tools. The Ensemble project is a highly successful, ongoing collaboration among NASA Centers. Since 2004, the Ensemble project has supported the development of mission operations software for NASA's Exploration Systems, Science, and Space Operations Directorates.

DART: Tools and Support for Ensemble Data Assimilation Research, Operations, and Education

NASA Astrophysics Data System (ADS)

Hoar, T. J.; Anderson, J. L.; Collins, N.; Raeder, K.; Kershaw, H.; Romine, G. S.; Mizzi, A. P.; Chatterjee, A.; Karspeck, A. R.; Zarzycki, C. M.; Ha, S. Y.; Barre, J.; Gaubert, B.

2014-12-01

The Data Assimilation Research Testbed (DART) is a community facility for ensemble data assimilation developed and supported by the National Center for Atmospheric Research. DART provides a comprehensive suite of software, documentation, examples and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers from the Data Assimilation Research Section at NCAR are available to actively support DART users who want to use existing DART products or develop their own new applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories doing operational prediction with large state-of-the-art models. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers. This poster focuses on several recent research activities using DART with geophysical models. First, DART is being used with the Community Atmosphere Model Spectral Element (CAM-SE) and Model for Prediction Across Scales (MPAS) global atmospheric models that support locally enhanced grid resolution. Initial results from ensemble assimilation with both models are presented. DART is also being used to produce ensemble analyses of atmospheric tracers, in particular CO, in both the global CAM-Chem model and the regional Weather Research and Forecast with chemistry (WRF-Chem) model by assimilating observations from the Measurements of Pollution in the Troposphere (MOPITT) and Infrared Atmospheric Sounding Interferometer (IASI) instruments. Results from ensemble analyses in both models are presented. An interface between DART and the Community Atmosphere Biosphere Land Exchange (CABLE) model has been completed and ensemble land surface analyses with DART/CABLE will be discussed. Finally, an update on ensemble analyses in the fully-coupled Community Earth System (CESM

A New Multivariate Approach in Generating Ensemble Meteorological Forcings for Hydrological Forecasting

NASA Astrophysics Data System (ADS)

Khajehei, Sepideh; Moradkhani, Hamid

2015-04-01

Producing reliable and accurate hydrologic ensemble forecasts are subject to various sources of uncertainty, including meteorological forcing, initial conditions, model structure, and model parameters. Producing reliable and skillful precipitation ensemble forecasts is one approach to reduce the total uncertainty in hydrological applications. Currently, National Weather Prediction (NWP) models are developing ensemble forecasts for various temporal ranges. It is proven that raw products from NWP models are biased in mean and spread. Given the above state, there is a need for methods that are able to generate reliable ensemble forecasts for hydrological applications. One of the common techniques is to apply statistical procedures in order to generate ensemble forecast from NWP-generated single-value forecasts. The procedure is based on the bivariate probability distribution between the observation and single-value precipitation forecast. However, one of the assumptions of the current method is fitting Gaussian distribution to the marginal distributions of observed and modeled climate variable. Here, we have described and evaluated a Bayesian approach based on Copula functions to develop an ensemble precipitation forecast from the conditional distribution of single-value precipitation forecasts. Copula functions are known as the multivariate joint distribution of univariate marginal distributions, which are presented as an alternative procedure in capturing the uncertainties related to meteorological forcing. Copulas are capable of modeling the joint distribution of two variables with any level of correlation and dependency. This study is conducted over a sub-basin in the Columbia River Basin in USA using the monthly precipitation forecasts from Climate Forecast System (CFS) with 0.5x0.5 Deg. spatial resolution to reproduce the observations. The verification is conducted on a different period and the superiority of the procedure is compared with Ensemble Pre

Lost Skies of Italian Folk Astronomy

NASA Astrophysics Data System (ADS)

Barale, Piero

The limited archival material and the scarcity of evidence from the oldest living representatives of various communities effectively restrict research on archaic astronomical knowledge within Italy to the Alpine area and the most northerly part of the Appenines. These are territories where, fortunately, the folk culture is historically recognized as being very conservative. The sky provided a series of "astral instruments" used for planning religious festivals, fairs, and work in the fields through an empirical-symbolic approach and ancient sidereal calendars with which the valley dwellers were able to arrange daily life.

Ensemble Models

EPA Science Inventory

Ensemble forecasting has been used for operational numerical weather prediction in the United States and Europe since the early 1990s. An ensemble of weather or climate forecasts is used to characterize the two main sources of uncertainty in computer models of physical systems: ...

Folk and biological perceptions of dementia among Asian ethnic minorities in Hawaii.

PubMed

Suzuki, Rika; Goebert, Deborah; Ahmed, Iqbal; Lu, Brett

2015-06-01

To study if Asian ethnic groups in Hawaii today maintain folk-based beliefs about dementia, have inadequate biomedical understanding of dementia, and differ among each other regarding perceptions of dementia. The study adapts and expands a 2004 survey of ethnic groups on perceptions of Alzheimer disease demonstrating that ethnic minority groups hold more folk perceptions and less biomedical perceptions of dementia than Caucasians. This study surveys particular ethnic minority family members of elders admitted to four long-term care and inpatient facilities in Hawaii. Seventy-one family members completed surveys, including 23 Chinese, 18 Filipino, and 30 Japanese participants. Elders may or may not have had the diagnosis of dementia, though an estimated half of elders in all four facilities already held the diagnosis of dementia. Findings indicated that Japanese and Chinese respondents in this study held perceptions about dementia that were more consistent with current biomedical understanding compared with their Filipino counterparts (mean differences/percent correct for Japanese: 57%, Chinese: 56% versus Filipino: 38%; F = 6.39, df = 2,55, p = 0.003). Filipino respondents were less likely than Japanese and Chinese respondents to report that persons with dementia can develop physical and mental problems-97% of Japanese participants and 82% of Chinese participants responded correctly compared with 63% of Filipino participants (Fisher's Exact test p = 0.009). With regard to folk beliefs about dementia, variation occurred with no consistent trend among the groups. Low levels of biomedical understanding of dementia were reflected by all three subgroups of Asians living in Hawaii with less prominence of folk beliefs compared with prior studies of ethnic minority perceptions. Education did not predict variability in dementia perceptions among the groups. Lower levels of acculturation, suggested by primary home language other than English, may correlate with a perception

Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Mittman, David S.; Shams, Khawaja, S.; Bachmann, Andrew G.; Ludowise, Melissa

2013-01-01

This software simplifies the process of having to set up an Eclipse IDE programming environment for the members of the cross-NASA center project, Ensemble. It achieves this by assembling all the necessary add-ons and custom tools/preferences. This software is unique in that it allows developers in the Ensemble Project (approximately 20 to 40 at any time) across multiple NASA centers to set up a development environment almost instantly and work on Ensemble software. The software automatically has the source code repositories and other vital information and settings included. The Eclipse IDE is an open-source development framework. The NASA (Ensemble-specific) version of the software includes Ensemble-specific plug-ins as well as settings for the Ensemble project. This software saves developers the time and hassle of setting up a programming environment, making sure that everything is set up in the correct manner for Ensemble development. Existing software (i.e., standard Eclipse) requires an intensive setup process that is both time-consuming and error prone. This software is built once by a single user and tested, allowing other developers to simply download and use the software

The role of ensemble post-processing for modeling the ensemble tail

NASA Astrophysics Data System (ADS)

Van De Vyver, Hans; Van Schaeybroeck, Bert; Vannitsem, Stéphane

2016-04-01

The past decades the numerical weather prediction community has witnessed a paradigm shift from deterministic to probabilistic forecast and state estimation (Buizza and Leutbecher, 2015; Buizza et al., 2008), in an attempt to quantify the uncertainties associated with initial-condition and model errors. An important benefit of a probabilistic framework is the improved prediction of extreme events. However, one may ask to what extent such model estimates contain information on the occurrence probability of extreme events and how this information can be optimally extracted. Different approaches have been proposed and applied on real-world systems which, based on extreme value theory, allow the estimation of extreme-event probabilities conditional on forecasts and state estimates (Ferro, 2007; Friederichs, 2010). Using ensemble predictions generated with a model of low dimensionality, a thorough investigation is presented quantifying the change of predictability of extreme events associated with ensemble post-processing and other influencing factors including the finite ensemble size, lead time and model assumption and the use of different covariates (ensemble mean, maximum, spread...) for modeling the tail distribution. Tail modeling is performed by deriving extreme-quantile estimates using peak-over-threshold representation (generalized Pareto distribution) or quantile regression. Common ensemble post-processing methods aim to improve mostly the ensemble mean and spread of a raw forecast (Van Schaeybroeck and Vannitsem, 2015). Conditional tail modeling, on the other hand, is a post-processing in itself, focusing on the tails only. Therefore, it is unclear how applying ensemble post-processing prior to conditional tail modeling impacts the skill of extreme-event predictions. This work is investigating this question in details. Buizza, Leutbecher, and Isaksen, 2008: Potential use of an ensemble of analyses in the ECMWF Ensemble Prediction System, Q. J. R. Meteorol

"Folk" Understandings of Quality in UK Higher Hospitality Education

ERIC Educational Resources Information Center

Wood, Roy

2015-01-01

Purpose: The purpose of this paper is to provide an overview of the evolution of "folk" understandings of quality in higher hospitality education and the consequent implications of these understandings for current quality concerns in the field. Design/methodology/approach: The paper combines a historical survey of the stated topic…

Entropy of network ensembles

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

2009-03-01

In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

Ensembl variation resources

PubMed Central

2010-01-01

Background The maturing field of genomics is rapidly increasing the number of sequenced genomes and producing more information from those previously sequenced. Much of this additional information is variation data derived from sampling multiple individuals of a given species with the goal of discovering new variants and characterising the population frequencies of the variants that are already known. These data have immense value for many studies, including those designed to understand evolution and connect genotype to phenotype. Maximising the utility of the data requires that it be stored in an accessible manner that facilitates the integration of variation data with other genome resources such as gene annotation and comparative genomics. Description The Ensembl project provides comprehensive and integrated variation resources for a wide variety of chordate genomes. This paper provides a detailed description of the sources of data and the methods for creating the Ensembl variation databases. It also explores the utility of the information by explaining the range of query options available, from using interactive web displays, to online data mining tools and connecting directly to the data servers programmatically. It gives a good overview of the variation resources and future plans for expanding the variation data within Ensembl. Conclusions Variation data is an important key to understanding the functional and phenotypic differences between individuals. The development of new sequencing and genotyping technologies is greatly increasing the amount of variation data known for almost all genomes. The Ensembl variation resources are integrated into the Ensembl genome browser and provide a comprehensive way to access this data in the context of a widely used genome bioinformatics system. All Ensembl data is freely available at http://www.ensembl.org and from the public MySQL database server at ensembldb.ensembl.org. PMID:20459805

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2013-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography. These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S. P.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2012-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography (METOC). These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as

Folk Dances of the Southern Mountains: A Beginner's Collection.

ERIC Educational Resources Information Center

Quint, Laurie

Step-by-step instructions and diagrams for 11 traditional folk dances of the southern Appalachian mountain region appropriate for beginners are provided. The dances are grouped into five broad categories: (1) openers, which use a leader to pick up participants as the dance progresses; (2) mixers (Oh, Susannah, Texas Schottische, Gary Gordon's…

For White Folks Who Teach (Music) in the Hood

ERIC Educational Resources Information Center

Karvelis, Noah J.

2017-01-01

In this article, I aim to critically analyze theories contained within Dr. Christopher Emdin's newest book "For White Folks Who Teach in the Hood (and the Rest of Ya'll Too!)" in the context of the music classroom. To begin, I summarize Christopher Emdin's theories of both "reality" and "pentecostal" pedagogy and then…

Locally Weighted Ensemble Clustering.

PubMed

Huang, Dong; Wang, Chang-Dong; Lai, Jian-Huang

2018-05-01

Due to its ability to combine multiple base clusterings into a probably better and more robust clustering, the ensemble clustering technique has been attracting increasing attention in recent years. Despite the significant success, one limitation to most of the existing ensemble clustering methods is that they generally treat all base clusterings equally regardless of their reliability, which makes them vulnerable to low-quality base clusterings. Although some efforts have been made to (globally) evaluate and weight the base clusterings, yet these methods tend to view each base clustering as an individual and neglect the local diversity of clusters inside the same base clustering. It remains an open problem how to evaluate the reliability of clusters and exploit the local diversity in the ensemble to enhance the consensus performance, especially, in the case when there is no access to data features or specific assumptions on data distribution. To address this, in this paper, we propose a novel ensemble clustering approach based on ensemble-driven cluster uncertainty estimation and local weighting strategy. In particular, the uncertainty of each cluster is estimated by considering the cluster labels in the entire ensemble via an entropic criterion. A novel ensemble-driven cluster validity measure is introduced, and a locally weighted co-association matrix is presented to serve as a summary for the ensemble of diverse clusters. With the local diversity in ensembles exploited, two novel consensus functions are further proposed. Extensive experiments on a variety of real-world datasets demonstrate the superiority of the proposed approach over the state-of-the-art.

Chinese Folk Art: The Small Skills of Carving Insects. Activities for Children of All Ages. Activity Sheets.

ERIC Educational Resources Information Center

White, Caryn

Chinese folk art, known as "the small skills of carving insects," differs from artworks produced by skilled or highly educated Chinese artisans. Folk art is defined as works that are created by ordinary citizens and that often are items designed for personal use. The designation, "the small skills of carving insects," occurred…

Some Chinese folk prescriptions for wind-cold type common cold.

PubMed

Hai-Long, Zhai; Shimin, Chen; Yalan, Lu

2015-07-01

Although self-limiting, the common cold (gǎn mào) is highly prevalent. There are no effective antivirals to cure the common cold and few effective measures to prevent it, However, for thousands years, Chinese people have treated the common cold with natural herbs, According to the traditional Chinese medicine (TCM) theory ( zhōng yī lǐ lùn), the common cold is considered as an exterior syndrome, which can be further divided into the wind-cold type ( fēng hán xíng), the wind-heat type ( fēng rè xíng), and the summer heat dampness type ( shǔ rè xíng). Since the most common type of common cold caught in winter and spring is the wind-cold type, the article introduced some Chinese folk prescriptions for the wind-cold type common cold with normal and weak physique, respectively. For thousands of years, Chinese folk prescriptions for the common cold, as complementary and alternative medicine (CAM; bǔ chōng yǔ tì dài yī xué), have been proven to be effective, convenient, cheap, and most importantly, safe. The Chinese folk prescriptions ( zhōng guó mín jiān chǔ fāng) for the wind-cold type common cold are quite suitable for general practitioners or patients with the wind-cold type common cold, to treat the disease. Of course, their pharmacological features and mechanisms of action need to be further studied.

Prayer: folk home remedy vs. spiritual practice.

PubMed

Easom, Leisa R; Easom, Linda R

2006-01-01

A multidisciplinary review of the literature reveals that prayer, in a multicultural context, may be viewed as both a folk home remedy and a practice of spirituality. Understanding cultural differences and similarities of the use of prayer as a variable for health promotion may have implications for tailoring treatment approaches to eliminate disparities in providing care to clients of diverse cultural backgrounds. This paper presents these similarities and differences within the cultural beliefs of the White, African-American, and Hispanic populations.

A Content Analysis of Asian-Pacific Folk Songs in American Elementary Music Textbooks from 1967 to 2008

ERIC Educational Resources Information Center

Culig, Edna Aurora C.

2012-01-01

In this quanto-historical study, the author conducted a content analysis of Asian-Pacific (AP) folk songs in 18 American elementary music textbooks published from 1967 to 2008. The researcher addressed the questions: (1) To what degree are AP folk songs included in the printed and recorded repertoire of elementary music textbook series published…

Folk Art Traditions and Beyond: Travel with "SchoolArts" to Santa Fe, New Mexico in July 2008

ERIC Educational Resources Information Center

Walkup, Nancy

2007-01-01

This article briefly discusses a seminar that will focus on the fifth annual Folk Art Festival at the Museum of International Folk Art in Santa Fe, with additional emphasis on Georgia O'Keeffe's life and art in New Mexico, and Hispanic and Native American cultural traditions. Activities include museum visits, field trips, invited speakers,…

Pedagogical Challenges in Folk Music Teaching in Higher Education: A Case Study of Hua'er Music in China

ERIC Educational Resources Information Center

Yang, Yang; Welch, Graham

2016-01-01

Recent literature suggests that traditional approaches in folk music education are not necessarily compatible with the pedagogical conventions of formal music education. Whilst several recent studies have tended to define these non-classical-music learning contexts as "informal", the practice of folk music that was recently introduced…

Imprinting and recalling cortical ensembles.

PubMed

Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S; Yuste, Rafael

2016-08-12

Neuronal ensembles are coactive groups of neurons that may represent building blocks of cortical circuits. These ensembles could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations from ensembles in the visual cortex of awake mice builds neuronal ensembles that recur spontaneously after being imprinted and do not disrupt preexisting ones. Moreover, imprinted ensembles can be recalled by single- cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. Copyright © 2016, American Association for the Advancement of Science.

World Music Ensemble: Kulintang

ERIC Educational Resources Information Center

Beegle, Amy C.

2012-01-01

As instrumental world music ensembles such as steel pan, mariachi, gamelan and West African drums are becoming more the norm than the exception in North American school music programs, there are other world music ensembles just starting to gain popularity in particular parts of the United States. The kulintang ensemble, a drum and gong ensemble…

NCAR's Experimental Real-time Convection-allowing Ensemble Prediction System

NASA Astrophysics Data System (ADS)

Schwartz, C. S.; Romine, G. S.; Sobash, R.; Fossell, K.

2016-12-01

Since April 2015, the National Center for Atmospheric Research's (NCAR's) Mesoscale and Microscale Meteorology (MMM) Laboratory, in collaboration with NCAR's Computational Information Systems Laboratory (CISL), has been producing daily, real-time, 10-member, 48-hr ensemble forecasts with 3-km horizontal grid spacing over the conterminous United States (http://ensemble.ucar.edu). These computationally-intensive, next-generation forecasts are produced on the Yellowstone supercomputer, have been embraced by both amateur and professional weather forecasters, are widely used by NCAR and university researchers, and receive considerable attention on social media. Initial conditions are supplied by NCAR's Data Assimilation Research Testbed (DART) software and the forecast model is NCAR's Weather Research and Forecasting (WRF) model; both WRF and DART are community tools. This presentation will focus on cutting-edge research results leveraging the ensemble dataset, including winter weather predictability, severe weather forecasting, and power outage modeling. Additionally, the unique design of the real-time analysis and forecast system and computational challenges and solutions will be described.

Cultural Transfer in Adult Education: The Case of The Folk Development Colleges in Tanzania

NASA Astrophysics Data System (ADS)

Rogers, Alan

2000-05-01

This paper examines the issues surrounding the cultural transfer of educational practices and institutions between industrialised countries and developing societies. It pays particular attention to adult education, and - using the case study of the Folk High Schools of Sweden and the Folk Development Colleges of Tanzania between 1975 and 1996 - it tries to develop an argument about the conditions under which such transfers may be successful. It suggests that there needs to be something of a match between the ideologies, discourse and functions of the educational institution within both societies; that the transfer of more than one element of any educational system would assist take-up; that the issue of whether the transfer is a top-down or a bottom-up one is also important; and that such transfers are most successful when the receiving society takes control of the transfer and comes to own it and to adapt it to their own usages. The case study is based on a two year evaluation of the Tanzanian Folk Development Colleges under the aid programme of the Swedish International Development Agency (Sida).

On Nash Equilibrium and Evolutionarily Stable States That Are Not Characterised by the Folk Theorem

PubMed Central

Li, Jiawei; Kendall, Graham

2015-01-01

In evolutionary game theory, evolutionarily stable states are characterised by the folk theorem because exact solutions to the replicator equation are difficult to obtain. It is generally assumed that the folk theorem, which is the fundamental theory for non-cooperative games, defines all Nash equilibria in infinitely repeated games. Here, we prove that Nash equilibria that are not characterised by the folk theorem do exist. By adopting specific reactive strategies, a group of players can be better off by coordinating their actions in repeated games. We call it a type-k equilibrium when a group of k players coordinate their actions and they have no incentive to deviate from their strategies simultaneously. The existence and stability of the type-k equilibrium in general games is discussed. This study shows that the sets of Nash equilibria and evolutionarily stable states have greater cardinality than classic game theory has predicted in many repeated games. PMID:26288088

Multi-RCM ensemble downscaling of global seasonal forecasts (MRED)

NASA Astrophysics Data System (ADS)

Arritt, R. W.

2008-12-01

The Multi-RCM Ensemble Downscaling (MRED) project was recently initiated to address the question, Can regional climate models provide additional useful information from global seasonal forecasts? MRED will use a suite of regional climate models to downscale seasonal forecasts produced by the new National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) seasonal forecast system and the NASA GEOS5 system. The initial focus will be on wintertime forecasts in order to evaluate topographic forcing, snowmelt, and the potential usefulness of higher resolution, especially for near-surface fields influenced by high resolution orography. Each regional model will cover the conterminous US (CONUS) at approximately 32 km resolution, and will perform an ensemble of 15 runs for each year 1982-2003 for the forecast period 1 December - 30 April. MRED will compare individual regional and global forecasts as well as ensemble mean precipitation and temperature forecasts, which are currently being used to drive macroscale land surface models (LSMs), as well as wind, humidity, radiation, turbulent heat fluxes, which are important for more advanced coupled macro-scale hydrologic models. Metrics of ensemble spread will also be evaluated. Extensive analysis will be performed to link improvements in downscaled forecast skill to regional forcings and physical mechanisms. Our overarching goal is to determine what additional skill can be provided by a community ensemble of high resolution regional models, which we believe will eventually define a strategy for more skillful and useful regional seasonal climate forecasts.

Verification of Ensemble Forecasts for the New York City Operations Support Tool

NASA Astrophysics Data System (ADS)

Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

2012-12-01

The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble

NWS Operational Requirements for Ensemble-Based Hydrologic Forecasts

NASA Astrophysics Data System (ADS)

Hartman, R. K.

2008-12-01

Ensemble-based hydrologic forecasts have been developed and issued by National Weather Service (NWS) staff at River Forecast Centers (RFCs) for many years. Used principally for long-range water supply forecasts, only the uncertainty associated with weather and climate have been traditionally considered. As technology and societal expectations of resource managers increase, the use and desire for risk-based decision support tools has also increased. These tools require forecast information that includes reliable uncertainty estimates across all time and space domains. The development of reliable uncertainty estimates associated with hydrologic forecasts is being actively pursued within the United States and internationally. This presentation will describe the challenges, components, and requirements for operational hydrologic ensemble-based forecasts from the perspective of a NOAA/NWS River Forecast Center.

Ladrillo and Tales of Juan Bobo: Puerto Rican Folk Tales.

ERIC Educational Resources Information Center

Matos, Reinaldo; Matos, Ana

These two illustrated elementary readers contain the Spanish and English versions of the Puerto Rican folk tales, "Ladrillo" and "Cuentos de Juan Bobo." They are part of a series of reading materials for elementary-level migrant children. These materials are intended to help the child relate to his culture, develop interest in…

The Danish Folk High School: An Experiment in Humanistic Education.

ERIC Educational Resources Information Center

Davis, David Charles

This historical and comparative study examines the folk high school movement in Denmark from the standpoint of the New Humanism as expressed in the writings of Carl Rogers, Abraham Maslow, Sidney Jourard, and others. These schools are unique among the many educational forms and institutions western man has developed. Private, nonprofit residential…

American Folk Music and Folklore Recordings 1984: A Selected List.

ERIC Educational Resources Information Center

Library of Congress, Washington, DC. American Folklife Center.

In an effort to encourage appreciation of the rich folk heritage of the United States, the American Folklife Center of the Library of Congress presents this annual list of 30 recordings selected by a panel of distinguished experts from nearly two hundred titles submitted by producers, suggested by folklorists and ethnomusicologists, and proposed…

The Fairy-Folk Tale in Media Art: Reflections of Disney and Duvall.

ERIC Educational Resources Information Center

Molloy, Toni

1988-01-01

Focuses on Walt Disney and Shelley Duvall, mass media producers who furnish children with fairy-folklore. Compares and contrasts what Disney and Duvall do and do not convey through their fairy-folk tales. (MS)

Effects of a Westernized Korean Folk Music Selection on Students' Music Familiarity and Preference for Its Traditional Version

ERIC Educational Resources Information Center

Kang, Sangmi; Yoo, Hyesoo

2016-01-01

The purpose of this study was to reveal the effects of Westernized arrangements of traditional Korean folk music on music familiarity and preference. Two separate labs in one intact class were assigned to one of two treatment groups of either listening to traditional Korean folk songs (n?=?18) or listening to Western arrangements of the same…

Brief communication: bioarcheological and biocultural evidence for the New England vampire folk belief.

PubMed

Sledzik, P S; Bellantoni, N

1994-06-01

Folk beliefs associated with death and disease can impact on the bioarcheological record. Unusual postmortem actions by humans and distinctive paleopathological evidence may be clues to these beliefs. This report presents bioarcheological and paleopathological evidence in support of a 19th century New England folk belief in vampires with a particular reference to a colonial period burial. The New England folk belief in vampires revolves around the ability of a deceased tuberculosis victim to return from the dead as a vampire and cause the "wasting away" of the surviving relatives. To stop the actions of the vampire, the body of the consumptive was exhumed and disrupted in various ways. Twelve historic accounts of this activity indicate that the belief was not uncommon in 19th century New England. This creative interpretation of contagion is consistent with the etiology of tuberculosis. Three pieces of evidence are important in this case. The skeletal of a 50- to 55-year-old male from a mid-19th century Connecticut cemetery exhibiting pulmonary tuberculosis rib lesions are discussed. In addition, certain bones in the skeleton were rearranged after decomposition was complete. A historic vampire account from the same time period and geographical location place the belief within the parameters of the cemetery.

Multi-RCM ensemble downscaling of global seasonal forecasts (MRED)

NASA Astrophysics Data System (ADS)

Arritt, R.

2009-04-01

Regional climate models (RCMs) have long been used to downscale global climate simulations. In contrast the ability of RCMs to downscale seasonal climate forecasts has received little attention. The Multi-RCM Ensemble Downscaling (MRED) project was recently initiated to address the question, Does dynamical downscaling using RCMs provide additional useful information for seasonal forecasts made by global models? MRED is using a suite of RCMs to downscale seasonal forecasts produced by the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) seasonal forecast system and the NASA GEOS5 system. The initial focus is on wintertime forecasts in order to evaluate topographic forcing, snowmelt, and the usefulness of higher resolution for near-surface fields influenced by high resolution orography. Each RCM covers the conterminous U.S. at approximately 32 km resolution, comparable to the scale of the North American Regional Reanalysis (NARR) which will be used to evaluate the models. The forecast ensemble for each RCM is comprised of 15 members over a period of 22+ years (from 1982 to 2003+) for the forecast period 1 December - 30 April. Each RCM will create a 15-member lagged ensemble by starting on different dates in the preceding November. This results in a 120-member ensemble for each projection (8 RCMs by 15 members per RCM). The RCMs will be continually updated at their lateral boundaries using 6-hourly output from CFS or GEOS5. Hydrometeorological output will be produced in a standard netCDF-based format for a common analysis grid, which simplifies both model intercomparison and the generation of ensembles. MRED will compare individual RCM and global forecasts as well as ensemble mean precipitation and temperature forecasts, which are currently being used to drive macroscale land surface models (LSMs). Metrics of ensemble spread will also be evaluated. Extensive process-oriented analysis will be performed to link improvements in

Development and Use of the Hydrologic Ensemble Forecast System by the National Weather Service to Support the New York City Water Supply

NASA Astrophysics Data System (ADS)

Shedd, R.; Reed, S. M.; Porter, J. H.

2015-12-01

The National Weather Service (NWS) has been working for several years on the development of the Hydrologic Ensemble Forecast System (HEFS). The objective of HEFS is to provide ensemble river forecasts incorporating the best precipitation and temperature forcings at any specific time horizon. For the current implementation, this includes the Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFSv2). One of the core partners that has been working with the NWS since the beginning of the development phase of HEFS is the New York City Department of Environmental Protection (NYCDEP) which is responsible for the complex water supply system for New York City. The water supply system involves a network of reservoirs in both the Delaware and Hudson River basins. At the same time that the NWS was developing HEFS, NYCDEP was working on enhancing the operations of their water supply reservoirs through the development of a new Operations Support Tool (OST). OST is designed to guide reservoir system operations to ensure an adequate supply of high-quality drinking water for the city, as well as to meet secondary objectives for reaches downstream of the reservoirs assuming the primary water supply goals can be met. These secondary objectives include fisheries and ecosystem support, enhanced peak flow attenuation beyond that provided natively by the reservoirs, salt front management, and water supply for other cities. Since January 2014, the NWS Northeast and Middle Atlantic River Forecast Centers have provided daily one year forecasts from HEFS to NYCDEP. OST ingests these forecasts, couples them with near-real-time environmental and reservoir system data, and drives models of the water supply system. The input of ensemble forecasts results in an ensemble of model output, from which information on the range and likelihood of possible future system states can be extracted. This type of probabilistic information provides system managers with additional

Ensembl comparative genomics resources

PubMed Central

Muffato, Matthieu; Beal, Kathryn; Fitzgerald, Stephen; Gordon, Leo; Pignatelli, Miguel; Vilella, Albert J.; Searle, Stephen M. J.; Amode, Ridwan; Brent, Simon; Spooner, William; Kulesha, Eugene; Yates, Andrew; Flicek, Paul

2016-01-01

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org. PMID:26896847

A Survey on Weifang Teachers' Attitudes toward Teaching Chinese Folk Music

ERIC Educational Resources Information Center

Han, Ruochen; Leung, Bo Wah

2017-01-01

In mainland China, the implementation of the junior secondary school's music curriculum is highly dependent on music teachers' attitudes towards music and music education. This study investigated the possible relationship between teachers' attitudes towards teaching Chinese folk music and their music teaching practice in junior secondary schools…

American Folk Music and Folklore Recordings 1983: A Selected List.

ERIC Educational Resources Information Center

Library of Congress, Washington, DC. American Folklife Center.

Recognizing the need to inform the public about newly issued folk recordings and audio tapes, the American Folklife Center of the Library of Congress initiates this annual list of selected titles, chosen by a panel of distinguished experts from a compilation of 1983 releases prepared by the Center staff. Although not a comprehensive list, it is…

Dikir Farmasi: folk songs for health education

PubMed Central

Bahri, Salmah; Lee, Kah Seng; Adenan, Mohammad Aswady; Murugiah, Muthu Kumar; Khan, Tahir Mehmood; Neoh, Chin Fen; Long, Chiau Ming

2016-01-01

Abstract In an effort to enhance public awareness, we develop Dikir Farmasi as an innovative approach to deliver health information. Dikir Farmasi combines the elements of dikir barat (a type of traditional folk song rhythm) and traditional sketches which are popular in the state of Kelantan, Malaysia. These sketches and dikir barat rhythmic songs, with lyrics touch on issues such as drug abuse and regulation are presented in an entertaining and humorous way. Health promotion messages are disseminated using Dikir Farmasi in the form of compact disks, video compact disks, stage performance, exhibition, social media, printed media (signboard, brochure and flyer). PMID:27695527

Impacts of calibration strategies and ensemble methods on ensemble flood forecasting over Lanjiang basin, Southeast China

NASA Astrophysics Data System (ADS)

Liu, Li; Xu, Yue-Ping

2017-04-01

Ensemble flood forecasting driven by numerical weather prediction products is becoming more commonly used in operational flood forecasting applications.In this study, a hydrological ensemble flood forecasting system based on Variable Infiltration Capacity (VIC) model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated.The hydrological model is optimized by parallel programmed ɛ-NSGAII multi-objective algorithm and two respectively parameterized models are determined to simulate daily flows and peak flows coupled with a modular approach.The results indicatethat the ɛ-NSGAII algorithm permits more efficient optimization and rational determination on parameter setting.It is demonstrated that the multimodel ensemble streamflow mean have better skills than the best singlemodel ensemble mean (ECMWF) and the multimodel ensembles weighted on members and skill scores outperform other multimodel ensembles. For typical flood event, it is proved that the flood can be predicted 3-4 days in advance, but the flows in rising limb can be captured with only 1-2 days ahead due to the flash feature. With respect to peak flows selected by Peaks Over Threshold approach, the ensemble means from either singlemodel or multimodels are generally underestimated as the extreme values are smoothed out by ensemble process.

Developing the Good Life by Living It: The Influence of Attending a Norwegian Folk High School on Well-Being

ERIC Educational Resources Information Center

Erickson, Erik Kristian

2017-01-01

This study explored the influence attending a Norwegian folk high school had on the long-term well-being of former students. The Norwegian folk high schools represent a unique form of publicly funded education with an emphasis on learning through shared experience and that by law, the schools cannot issue grades, give formal examinations, or…

Teaching the Korean Folk Song ("Arirang") through Performing, Creating, and Responding

ERIC Educational Resources Information Center

Yoo, Hyesoo; Kang, Sangmi

2017-01-01

This article introduces a pedagogical approach to teaching one of the renowned Korean folk songs ("Arirang") based on the comprehensive musicianship approach and the 2014 Music Standards (competencies in performing, creating, and responding to music). The authors provide in-depth information for music educators to help their students…

Ensembl comparative genomics resources.

PubMed

Herrero, Javier; Muffato, Matthieu; Beal, Kathryn; Fitzgerald, Stephen; Gordon, Leo; Pignatelli, Miguel; Vilella, Albert J; Searle, Stephen M J; Amode, Ridwan; Brent, Simon; Spooner, William; Kulesha, Eugene; Yates, Andrew; Flicek, Paul

2016-01-01

Evolution provides the unifying framework with which to understand biology. The coherent investigation of genic and genomic data often requires comparative genomics analyses based on whole-genome alignments, sets of homologous genes and other relevant datasets in order to evaluate and answer evolutionary-related questions. However, the complexity and computational requirements of producing such data are substantial: this has led to only a small number of reference resources that are used for most comparative analyses. The Ensembl comparative genomics resources are one such reference set that facilitates comprehensive and reproducible analysis of chordate genome data. Ensembl computes pairwise and multiple whole-genome alignments from which large-scale synteny, per-base conservation scores and constrained elements are obtained. Gene alignments are used to define Ensembl Protein Families, GeneTrees and homologies for both protein-coding and non-coding RNA genes. These resources are updated frequently and have a consistent informatics infrastructure and data presentation across all supported species. Specialized web-based visualizations are also available including synteny displays, collapsible gene tree plots, a gene family locator and different alignment views. The Ensembl comparative genomics infrastructure is extensively reused for the analysis of non-vertebrate species by other projects including Ensembl Genomes and Gramene and much of the information here is relevant to these projects. The consistency of the annotation across species and the focus on vertebrates makes Ensembl an ideal system to perform and support vertebrate comparative genomic analyses. We use robust software and pipelines to produce reference comparative data and make it freely available. Database URL: http://www.ensembl.org. © The Author(s) 2016. Published by Oxford University Press.

Contemporary Challenges in Learning and Teaching Folk Music in a Higher Education Context: A Case Study of Hua'er Music

ERIC Educational Resources Information Center

Yang, Yang; Welch, Graham

2014-01-01

Literature reviews suggest that traditional approaches in folk music education are not necessarily compatible with the conventions of formal music education. Whilst many recent studies have tended to define these non-classical music learning contexts as "informal", the practice of folk transmission music appears to be much more complex…

EnsembleGraph: Interactive Visual Analysis of Spatial-Temporal Behavior for Ensemble Simulation Data

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

Shu, Qingya; Guo, Hanqi; Che, Limei

We present a novel visualization framework—EnsembleGraph— for analyzing ensemble simulation data, in order to help scientists understand behavior similarities between ensemble members over space and time. A graph-based representation is used to visualize individual spatiotemporal regions with similar behaviors, which are extracted by hierarchical clustering algorithms. A user interface with multiple-linked views is provided, which enables users to explore, locate, and compare regions that have similar behaviors between and then users can investigate and analyze the selected regions in detail. The driving application of this paper is the studies on regional emission influences over tropospheric ozone, which is based onmore » ensemble simulations conducted with different anthropogenic emission absences using the MOZART-4 (model of ozone and related tracers, version 4) model. We demonstrate the effectiveness of our method by visualizing the MOZART-4 ensemble simulation data and evaluating the relative regional emission influences on tropospheric ozone concentrations. Positive feedbacks from domain experts and two case studies prove efficiency of our method.« less

Measuring social interaction in music ensembles

PubMed Central

D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano

2016-01-01

Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances. PMID:27069054

Measuring social interaction in music ensembles.

PubMed

Volpe, Gualtiero; D'Ausilio, Alessandro; Badino, Leonardo; Camurri, Antonio; Fadiga, Luciano

2016-05-05

Music ensembles are an ideal test-bed for quantitative analysis of social interaction. Music is an inherently social activity, and music ensembles offer a broad variety of scenarios which are particularly suitable for investigation. Small ensembles, such as string quartets, are deemed a significant example of self-managed teams, where all musicians contribute equally to a task. In bigger ensembles, such as orchestras, the relationship between a leader (the conductor) and a group of followers (the musicians) clearly emerges. This paper presents an overview of recent research on social interaction in music ensembles with a particular focus on (i) studies from cognitive neuroscience; and (ii) studies adopting a computational approach for carrying out automatic quantitative analysis of ensemble music performances. © 2016 The Author(s).

Statistical Ensemble of Large Eddy Simulations

NASA Technical Reports Server (NTRS)

Carati, Daniele; Rogers, Michael M.; Wray, Alan A.; Mansour, Nagi N. (Technical Monitor)

2001-01-01

A statistical ensemble of large eddy simulations (LES) is run simultaneously for the same flow. The information provided by the different large scale velocity fields is used to propose an ensemble averaged version of the dynamic model. This produces local model parameters that only depend on the statistical properties of the flow. An important property of the ensemble averaged dynamic procedure is that it does not require any spatial averaging and can thus be used in fully inhomogeneous flows. Also, the ensemble of LES's provides statistics of the large scale velocity that can be used for building new models for the subgrid-scale stress tensor. The ensemble averaged dynamic procedure has been implemented with various models for three flows: decaying isotropic turbulence, forced isotropic turbulence, and the time developing plane wake. It is found that the results are almost independent of the number of LES's in the statistical ensemble provided that the ensemble contains at least 16 realizations.

Improving medium-range ensemble streamflow forecasts through statistical post-processing

NASA Astrophysics Data System (ADS)

Mendoza, Pablo; Wood, Andy; Clark, Elizabeth; Nijssen, Bart; Clark, Martyn; Ramos, Maria-Helena; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Probabilistic hydrologic forecasts are a powerful source of information for decision-making in water resources operations. A common approach is the hydrologic model-based generation of streamflow forecast ensembles, which can be implemented to account for different sources of uncertainties - e.g., from initial hydrologic conditions (IHCs), weather forecasts, and hydrologic model structure and parameters. In practice, hydrologic ensemble forecasts typically have biases and spread errors stemming from errors in the aforementioned elements, resulting in a degradation of probabilistic properties. In this work, we compare several statistical post-processing techniques applied to medium-range ensemble streamflow forecasts obtained with the System for Hydromet Applications, Research and Prediction (SHARP). SHARP is a fully automated prediction system for the assessment and demonstration of short-term to seasonal streamflow forecasting applications, developed by the National Center for Atmospheric Research, University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. The suite of post-processing techniques includes linear blending, quantile mapping, extended logistic regression, quantile regression, ensemble analogs, and the generalized linear model post-processor (GLMPP). We assess and compare these techniques using multi-year hindcasts in several river basins in the western US. This presentation discusses preliminary findings about the effectiveness of the techniques for improving probabilistic skill, reliability, discrimination, sharpness and resolution.

Tales of the Supernatural: A Selected List of Recordings Made in the United States and Placed in the Archive of Folk Culture. Folk Archive Finding Aid.

ERIC Educational Resources Information Center

Delcambre, Angie C., Comp.; And Others

This finding aid is a selected list of supernatural-related narratives recorded in the United States and held in the Archive of Folk Culture of the Library of Congress. Brief descriptions of the recordings are accompanied by identification numbers. Information about listening to or ordering any of the listed recordings is available from the…

Joys of Community Ensemble Playing: The Case of the Happy Roll Elastic Ensemble in Taiwan

ERIC Educational Resources Information Center

Hsieh, Yuan-Mei; Kao, Kai-Chi

2012-01-01

The Happy Roll Elastic Ensemble (HREE) is a community music ensemble supported by Tainan Culture Centre in Taiwan. With enjoyment and friendship as its primary goals, it aims to facilitate the joys of ensemble playing and the spirit of social networking. This article highlights the key aspects of HREE's development in its first two years…

SRNL PARTICIPATION IN THE MULTI-SCALE ENSEMBLE EXERCISES

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

Buckley, R

2007-10-29

Consequence assessment during emergency response often requires atmospheric transport and dispersion modeling to guide decision making. A statistical analysis of the ensemble of results from several models is a useful way of estimating the uncertainty for a given forecast. ENSEMBLE is a European Union program that utilizes an internet-based system to ingest transport results from numerous modeling agencies. A recent set of exercises required output on three distinct spatial and temporal scales. The Savannah River National Laboratory (SRNL) uses a regional prognostic model nested within a larger-scale synoptic model to generate the meteorological conditions which are in turn used inmore » a Lagrangian particle dispersion model. A discussion of SRNL participation in these exercises is given, with particular emphasis on requirements for provision of results in a timely manner with regard to the various spatial scales.« less

Ensemble Data Mining Methods

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.

2004-01-01

Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be as competent as possible, but the members should be complementary to one another. If the members are not complementary, Le., if they always agree, then the committee is unnecessary---any one member is sufficient. If the members are complementary, then when one or a few members make an error, the probability is high that the remaining members can correct this error. Research in ensemble methods has largely revolved around designing ensembles consisting of competent yet complementary models.

Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions

USGS Publications Warehouse

Viney, N.R.; Bormann, H.; Breuer, L.; Bronstert, A.; Croke, B.F.W.; Frede, H.; Graff, T.; Hubrechts, L.; Huisman, J.A.; Jakeman, A.J.; Kite, G.W.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Willems, P.

2009-01-01

This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in

The Weighted-Average Lagged Ensemble.

PubMed

DelSole, T; Trenary, L; Tippett, M K

2017-11-01

A lagged ensemble is an ensemble of forecasts from the same model initialized at different times but verifying at the same time. The skill of a lagged ensemble mean can be improved by assigning weights to different forecasts in such a way as to maximize skill. If the forecasts are bias corrected, then an unbiased weighted lagged ensemble requires the weights to sum to one. Such a scheme is called a weighted-average lagged ensemble. In the limit of uncorrelated errors, the optimal weights are positive and decay monotonically with lead time, so that the least skillful forecasts have the least weight. In more realistic applications, the optimal weights do not always behave this way. This paper presents a series of analytic examples designed to illuminate conditions under which the weights of an optimal weighted-average lagged ensemble become negative or depend nonmonotonically on lead time. It is shown that negative weights are most likely to occur when the errors grow rapidly and are highly correlated across lead time. The weights are most likely to behave nonmonotonically when the mean square error is approximately constant over the range forecasts included in the lagged ensemble. An extreme example of the latter behavior is presented in which the optimal weights vanish everywhere except at the shortest and longest lead times.

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

NASA Astrophysics Data System (ADS)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

75 FR 26284 - National Endowment for the Arts; Arts Advisory Panel

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-11

... NATIONAL FOUNDATION ON THE ARTS AND THE HUMANITIES National Endowment for the Arts; Arts Advisory..., notice is hereby given that nine meetings of the Arts Advisory Panel to the National Council on the Arts... meeting, from 3 p.m. to 3:30 p.m. EDT, will be closed. Folk and Traditional Arts (application review...

Parenthood and Happiness: A Review of Folk Theories versus Empirical Evidence

ERIC Educational Resources Information Center

Hansen, Thomas

2012-01-01

This paper reviews and compares folk theories and empirical evidence about the influence of parenthood on happiness and life satisfaction. The review of attitudes toward parenthood and childlessness reveals that people tend to believe that parenthood is central to a meaningful and fulfilling life, and that the lives of childless people are…

Adaptive correction of ensemble forecasts

NASA Astrophysics Data System (ADS)

Pelosi, Anna; Battista Chirico, Giovanni; Van den Bergh, Joris; Vannitsem, Stephane

2017-04-01

Forecasts from numerical weather prediction (NWP) models often suffer from both systematic and non-systematic errors. These are present in both deterministic and ensemble forecasts, and originate from various sources such as model error and subgrid variability. Statistical post-processing techniques can partly remove such errors, which is particularly important when NWP outputs concerning surface weather variables are employed for site specific applications. Many different post-processing techniques have been developed. For deterministic forecasts, adaptive methods such as the Kalman filter are often used, which sequentially post-process the forecasts by continuously updating the correction parameters as new ground observations become available. These methods are especially valuable when long training data sets do not exist. For ensemble forecasts, well-known techniques are ensemble model output statistics (EMOS), and so-called "member-by-member" approaches (MBM). Here, we introduce a new adaptive post-processing technique for ensemble predictions. The proposed method is a sequential Kalman filtering technique that fully exploits the information content of the ensemble. One correction equation is retrieved and applied to all members, however the parameters of the regression equations are retrieved by exploiting the second order statistics of the forecast ensemble. We compare our new method with two other techniques: a simple method that makes use of a running bias correction of the ensemble mean, and an MBM post-processing approach that rescales the ensemble mean and spread, based on minimization of the Continuous Ranked Probability Score (CRPS). We perform a verification study for the region of Campania in southern Italy. We use two years (2014-2015) of daily meteorological observations of 2-meter temperature and 10-meter wind speed from 18 ground-based automatic weather stations distributed across the region, comparing them with the corresponding COSMO

On the generation of climate model ensembles

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy; Phipps, Steven J.

2014-10-01

Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.

Ensembl 2002: accommodating comparative genomics.

PubMed

Clamp, M; Andrews, D; Barker, D; Bevan, P; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Hubbard, T; Kasprzyk, A; Keefe, D; Lehvaslaiho, H; Iyer, V; Melsopp, C; Mongin, E; Pettett, R; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Birney, E

2003-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.

A Diagnostics Tool to detect ensemble forecast system anomaly and guide operational decisions

NASA Astrophysics Data System (ADS)

Park, G. H.; Srivastava, A.; Shrestha, E.; Thiemann, M.; Day, G. N.; Draijer, S.

2017-12-01

The hydrologic community is moving toward using ensemble forecasts to take uncertainty into account during the decision-making process. The New York City Department of Environmental Protection (DEP) implements several types of ensemble forecasts in their decision-making process: ensemble products for a statistical model (Hirsch and enhanced Hirsch); the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) forecasts based on the classical Ensemble Streamflow Prediction (ESP) technique; and the new NWS Hydrologic Ensemble Forecasting Service (HEFS) forecasts. To remove structural error and apply the forecasts to additional forecast points, the DEP post processes both the AHPS and the HEFS forecasts. These ensemble forecasts provide mass quantities of complex data, and drawing conclusions from these forecasts is time-consuming and difficult. The complexity of these forecasts also makes it difficult to identify system failures resulting from poor data, missing forecasts, and server breakdowns. To address these issues, we developed a diagnostic tool that summarizes ensemble forecasts and provides additional information such as historical forecast statistics, forecast skill, and model forcing statistics. This additional information highlights the key information that enables operators to evaluate the forecast in real-time, dynamically interact with the data, and review additional statistics, if needed, to make better decisions. We used Bokeh, a Python interactive visualization library, and a multi-database management system to create this interactive tool. This tool compiles and stores data into HTML pages that allows operators to readily analyze the data with built-in user interaction features. This paper will present a brief description of the ensemble forecasts, forecast verification results, and the intended applications for the diagnostic tool.

Imprinting and Recalling Cortical Ensembles

PubMed Central

Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki; Peterka, Darcy S.; Yuste, Rafael

2017-01-01

Neuronal ensembles are coactive groups of neurons that may represent emergent building blocks of neural circuits. They could be formed by Hebbian plasticity, whereby synapses between coactive neurons are strengthened. Here we report that repetitive activation with two-photon optogenetics of neuronal populations in visual cortex of awake mice generates artificially induced ensembles which recur spontaneously after being imprinted and do not disrupt preexistent ones. Moreover, imprinted ensembles can be recalled by single cell stimulation and remain coactive on consecutive days. Our results demonstrate the persistent reconfiguration of cortical circuits by two-photon optogenetics into neuronal ensembles that can perform pattern completion. PMID:27516599

Economic impact of the 2008 American Folk Festival in Bangor, Maine

Treesearch

Bernardita Silva; Marilynne Mann; Harold Daniel

2010-01-01

Festivals and events are becoming increasingly important drivers of tourism activity in Maine. Based on a survey of festival visitors, this study used an IMPLANTM input-output model to estimate the economic impact of the 2008 American Folk Festival in Bangor, ME. The Center for Tourism Research and Outreach estimated that 95,626 local and...

Ensemble Pulsar Time Scale

NASA Astrophysics Data System (ADS)

Yin, Dong-shan; Gao, Yu-ping; Zhao, Shu-hong

2017-07-01

Millisecond pulsars can generate another type of time scale that is totally independent of the atomic time scale, because the physical mechanisms of the pulsar time scale and the atomic time scale are quite different from each other. Usually the pulsar timing observations are not evenly sampled, and the internals between two data points range from several hours to more than half a month. Further more, these data sets are sparse. All this makes it difficult to generate an ensemble pulsar time scale. Hence, a new algorithm to calculate the ensemble pulsar time scale is proposed. Firstly, a cubic spline interpolation is used to densify the data set, and make the intervals between data points uniform. Then, the Vondrak filter is employed to smooth the data set, and get rid of the high-frequency noises, and finally the weighted average method is adopted to generate the ensemble pulsar time scale. The newly released NANOGRAV (North American Nanohertz Observatory for Gravitational Waves) 9-year data set is used to generate the ensemble pulsar time scale. This data set includes the 9-year observational data of 37 millisecond pulsars observed by the 100-meter Green Bank telescope and the 305-meter Arecibo telescope. It is found that the algorithm used in this paper can reduce effectively the influence caused by the noises in pulsar timing residuals, and improve the long-term stability of the ensemble pulsar time scale. Results indicate that the long-term (> 1 yr) stability of the ensemble pulsar time scale is better than 3.4 × 10-15.

Quantum ensembles of quantum classifiers.

PubMed

Schuld, Maria; Petruccione, Francesco

2018-02-09

Quantum machine learning witnesses an increasing amount of quantum algorithms for data-driven decision making, a problem with potential applications ranging from automated image recognition to medical diagnosis. Many of those algorithms are implementations of quantum classifiers, or models for the classification of data inputs with a quantum computer. Following the success of collective decision making with ensembles in classical machine learning, this paper introduces the concept of quantum ensembles of quantum classifiers. Creating the ensemble corresponds to a state preparation routine, after which the quantum classifiers are evaluated in parallel and their combined decision is accessed by a single-qubit measurement. This framework naturally allows for exponentially large ensembles in which - similar to Bayesian learning - the individual classifiers do not have to be trained. As an example, we analyse an exponentially large quantum ensemble in which each classifier is weighed according to its performance in classifying the training data, leading to new results for quantum as well as classical machine learning.

Screening of anti-Helicobacter pylori herbs deriving from Taiwanese folk medicinal plants.

PubMed

Wang, Yuan-Chuen; Huang, Tung-Liang

2005-02-01

In this study, extracts from 50 Taiwanese folk medicinal plants were examined and screened for anti-Helicobacter pylori activity. Ninety-five percent ethanol was used for herbal extraction. Paederia scandens (Lour.) Merr. (PSM), Plumbago zeylanica L. (PZL), Anisomeles indica (L.) O. Kuntze (AIOK), Bombax malabaricum DC. (BMDC) and Alpinia speciosa (J. C. Wendl.) K. Schum. (ASKS) and Bombax malabaricum DC. (BMDC) all demonstrated strong anti-H. pylori activities. The minimum inhibitory concentration values of the anti-H. pylori activity given by the five ethanol herb extracts ranged from 0.64 to 10.24 mg ml(-1). Twenty-six herbs, including Artemisia argvi Levl. et Vant (AALEV), Phyla nodiflora (Linn.) Greene (PNG) and others, showed moderate anti-H. pylori activity. The additional 19 herbs, including Areca catechu Linn. (ACL), Euphorbia hirta Linn. (EHL) and Gnaphalium adnatum Wall. ex DC. (GAWEDC), possessed lower anti-H. pylori effects. About half of the Taiwanese folk medicinal plants tested, demonstrated to possess higher anti-H. pylori activity.

Ensemble Statistical Post-Processing of the National Air Quality Forecast Capability: Enhancing Ozone Forecasts in Baltimore, Maryland

NASA Technical Reports Server (NTRS)

Garner, Gregory G.; Thompson, Anne M.

2013-01-01

An ensemble statistical post-processor (ESP) is developed for the National Air Quality Forecast Capability (NAQFC) to address the unique challenges of forecasting surface ozone in Baltimore, MD. Air quality and meteorological data were collected from the eight monitors that constitute the Baltimore forecast region. These data were used to build the ESP using a moving-block bootstrap, regression tree models, and extreme-value theory. The ESP was evaluated using a 10-fold cross-validation to avoid evaluation with the same data used in the development process. Results indicate that the ESP is conditionally biased, likely due to slight overfitting while training the regression tree models. When viewed from the perspective of a decision-maker, the ESP provides a wealth of additional information previously not available through the NAQFC alone. The user is provided the freedom to tailor the forecast to the decision at hand by using decision-specific probability thresholds that define a forecast for an ozone exceedance. Taking advantage of the ESP, the user not only receives an increase in value over the NAQFC, but also receives value for An ensemble statistical post-processor (ESP) is developed for the National Air Quality Forecast Capability (NAQFC) to address the unique challenges of forecasting surface ozone in Baltimore, MD. Air quality and meteorological data were collected from the eight monitors that constitute the Baltimore forecast region. These data were used to build the ESP using a moving-block bootstrap, regression tree models, and extreme-value theory. The ESP was evaluated using a 10-fold cross-validation to avoid evaluation with the same data used in the development process. Results indicate that the ESP is conditionally biased, likely due to slight overfitting while training the regression tree models. When viewed from the perspective of a decision-maker, the ESP provides a wealth of additional information previously not available through the NAQFC alone

Dance for Students with Orthopedic Conditions--Popular, Square, Folk, Modern, [and] Ballet.

ERIC Educational Resources Information Center

Harris, Cordelia Graves

1979-01-01

Preparation for teaching dance to orthopedically handicapped students is discussed in addition to specific suggestions for teaching popular dance, square dance, folk dance, modern dance, and ballet. Dancing is seen as a way to give orthopedically handicapped students physical education success without competition. Recommended music for each type…

Bringing the Magic of Folk Literature and Nursery Rhymes to Communication Classes

ERIC Educational Resources Information Center

Gan, Ivan

2015-01-01

Orators of folk literature and nursery rhymes entertain, inform, and persuade their audiences through the straightforward plots in those genres. Because nursery rhymes recitations usually happen in groups, they help children acquire the mechanics of oral communication and promote communal bonding. Although nursery rhymes have a simpler form than…

Revisiting Folk Moral Realism.

PubMed

Pölzler, Thomas

2017-01-01

Moral realists believe that there are objective moral truths. According to one of the most prominent arguments in favour of this view, ordinary people experience morality as realist-seeming, and we have therefore prima facie reason to believe that realism is true. Some proponents of this argument have claimed that the hypothesis that ordinary people experience morality as realist-seeming is supported by psychological research on folk metaethics. While most recent research has been thought to contradict this claim, four prominent earlier studies (by Goodwin and Darley, Wainryb et al., Nichols, and Nichols and Folds-Bennett) indeed seem to suggest a tendency towards realism. My aim in this paper is to provide a detailed internal critique of these four studies. I argue that, once interpreted properly, all of them turn out in line with recent research. They suggest that most ordinary people experience morality as "pluralist-" rather than realist-seeming, i.e., that ordinary people have the intuition that realism is true with regard to some moral issues, but variants of anti-realism are true with regard to others. This result means that moral realism may be less well justified than commonly assumed.

A Statistical Description of Neural Ensemble Dynamics

PubMed Central

Long, John D.; Carmena, Jose M.

2011-01-01

The growing use of multi-channel neural recording techniques in behaving animals has produced rich datasets that hold immense potential for advancing our understanding of how the brain mediates behavior. One limitation of these techniques is they do not provide important information about the underlying anatomical connections among the recorded neurons within an ensemble. Inferring these connections is often intractable because the set of possible interactions grows exponentially with ensemble size. This is a fundamental challenge one confronts when interpreting these data. Unfortunately, the combination of expert knowledge and ensemble data is often insufficient for selecting a unique model of these interactions. Our approach shifts away from modeling the network diagram of the ensemble toward analyzing changes in the dynamics of the ensemble as they relate to behavior. Our contribution consists of adapting techniques from signal processing and Bayesian statistics to track the dynamics of ensemble data on time-scales comparable with behavior. We employ a Bayesian estimator to weigh prior information against the available ensemble data, and use an adaptive quantization technique to aggregate poorly estimated regions of the ensemble data space. Importantly, our method is capable of detecting changes in both the magnitude and structure of correlations among neurons missed by firing rate metrics. We show that this method is scalable across a wide range of time-scales and ensemble sizes. Lastly, the performance of this method on both simulated and real ensemble data is used to demonstrate its utility. PMID:22319486

Monthly ENSO Forecast Skill and Lagged Ensemble Size

PubMed Central

DelSole, T.; Tippett, M.K.; Pegion, K.

2018-01-01

Abstract The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real‐time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real‐time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8–10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities. PMID:29937973

Monthly ENSO Forecast Skill and Lagged Ensemble Size

NASA Astrophysics Data System (ADS)

Trenary, L.; DelSole, T.; Tippett, M. K.; Pegion, K.

2018-04-01

The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real-time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real-time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8-10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities.

Agricultural, domestic and handicraft folk uses of plants in the Tyrrhenian sector of Basilicata (Italy)

PubMed Central

Salerno, Giovanni; Guarrera, Paolo Maria; Caneva, Giulia

2005-01-01

Background Research was carried out into agricultural and domestic-handicraft uses in folk traditions in the Tyrrhenian sector of the Basilicata region (southern Italy), as it is typically representative of ethnobotanical applications in the Mediterranean area. From the point of view of furnishing a botanical support for the study of local "material culture" data was collected through field interviews of 49 informants, most of whom were farmers. Results The taxa cited are 60, belonging to 32 botanical families, of which 18 are employed for agricultural uses and 51 for domestic-handicraft folk uses. Data show a diffuse use of plants for many purposes, both in agricultural (present uses 14%; past uses 1%) and for domestic-handicraft use (present uses 40%; past uses 45%); most of the latter are now in decline. Conclusion 60 data look uncommon or typical of the places studied. Some domestic-handicraft folk uses are typical of southern Italy (e.g. the use of Ampelodesmos mauritanicus for making ties, ropes, torches, baskets or that of Acer neapolitanum for several uses). Other uses (e.g. that of Inula viscosa and Calamintha nepeta for peculiar brooms, and of Origanum heracleoticum for dyeing wool red) are previously unpublished. PMID:16270919

Similarity Measures for Protein Ensembles

PubMed Central

Lindorff-Larsen, Kresten; Ferkinghoff-Borg, Jesper

2009-01-01

Analyses of similarities and changes in protein conformation can provide important information regarding protein function and evolution. Many scores, including the commonly used root mean square deviation, have therefore been developed to quantify the similarities of different protein conformations. However, instead of examining individual conformations it is in many cases more relevant to analyse ensembles of conformations that have been obtained either through experiments or from methods such as molecular dynamics simulations. We here present three approaches that can be used to compare conformational ensembles in the same way as the root mean square deviation is used to compare individual pairs of structures. The methods are based on the estimation of the probability distributions underlying the ensembles and subsequent comparison of these distributions. We first validate the methods using a synthetic example from molecular dynamics simulations. We then apply the algorithms to revisit the problem of ensemble averaging during structure determination of proteins, and find that an ensemble refinement method is able to recover the correct distribution of conformations better than standard single-molecule refinement. PMID:19145244

Neurological implications and neuropsychological considerations on folk music and dance.

PubMed

Sironi, Vittorio A; Riva, Michele A

2015-01-01

Neurological and neuropsychological aspects of folk music and traditional dance have been poorly investigated by historical and scientific literature. Some of these performances could be indeed the manifestation of latent pathological conditions or the expression of liberation rituals. This chapter aimed at analyzing the relationships between traditional dance, folk music, and neurological and psychiatric disorders. Since ancient times, dance has been used in the individual or collective as treatment of some diseases, including epilepsy and movement disorders (dyskinesia, chorea, etc.). Dionysia in Ancient Greece, St. Vitus dance in the Middle Age, tarantism and other traditional dances of southern Italy and of non-Western countries might be credited as curative rituals of these neurological and psychiatric conditions. During the nineteenth century, dance was also used for the treatment of psychiatric patients; the relationship between dance and insanity could also be reflected in classical ballets and music of that period. Nowadays, neuropsychiatric manifestations could also be evidenced in modern dances (mass fainting at rock concerts, flash mobs); some ballroom dances are commonly used for the rehabilitation of patients suffering from neurodegenerative and psychiatric conditions. Interdisciplinary research on these subjects (ethnomusicology and cultural anthropology, clinical neurology and dynamic psychology, neuroradiology and neurophysiology, and socioneurology and neuromusicology) should be increased. © 2015 Elsevier B.V. All rights reserved.

Improving database enrichment through ensemble docking

NASA Astrophysics Data System (ADS)

Rao, Shashidhar; Sanschagrin, Paul C.; Greenwood, Jeremy R.; Repasky, Matthew P.; Sherman, Woody; Farid, Ramy

2008-09-01

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.

Multi-criterion model ensemble of CMIP5 surface air temperature over China

NASA Astrophysics Data System (ADS)

Yang, Tiantian; Tao, Yumeng; Li, Jingjing; Zhu, Qian; Su, Lu; He, Xiaojia; Zhang, Xiaoming

2018-05-01

The global circulation models (GCMs) are useful tools for simulating climate change, projecting future temperature changes, and therefore, supporting the preparation of national climate adaptation plans. However, different GCMs are not always in agreement with each other over various regions. The reason is that GCMs' configurations, module characteristics, and dynamic forcings vary from one to another. Model ensemble techniques are extensively used to post-process the outputs from GCMs and improve the variability of model outputs. Root-mean-square error (RMSE), correlation coefficient (CC, or R) and uncertainty are commonly used statistics for evaluating the performances of GCMs. However, the simultaneous achievements of all satisfactory statistics cannot be guaranteed in using many model ensemble techniques. In this paper, we propose a multi-model ensemble framework, using a state-of-art evolutionary multi-objective optimization algorithm (termed MOSPD), to evaluate different characteristics of ensemble candidates and to provide comprehensive trade-off information for different model ensemble solutions. A case study of optimizing the surface air temperature (SAT) ensemble solutions over different geographical regions of China is carried out. The data covers from the period of 1900 to 2100, and the projections of SAT are analyzed with regard to three different statistical indices (i.e., RMSE, CC, and uncertainty). Among the derived ensemble solutions, the trade-off information is further analyzed with a robust Pareto front with respect to different statistics. The comparison results over historical period (1900-2005) show that the optimized solutions are superior over that obtained simple model average, as well as any single GCM output. The improvements of statistics are varying for different climatic regions over China. Future projection (2006-2100) with the proposed ensemble method identifies that the largest (smallest) temperature changes will happen in the

New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

NASA Astrophysics Data System (ADS)

Cane, D.; Milelli, M.

2009-09-01

The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

Verifying and Postprocesing the Ensemble Spread-Error Relationship

NASA Astrophysics Data System (ADS)

Hopson, Tom; Knievel, Jason; Liu, Yubao; Roux, Gregory; Wu, Wanli

2013-04-01

With the increased utilization of ensemble forecasts in weather and hydrologic applications, there is a need to verify their benefit over less expensive deterministic forecasts. One such potential benefit of ensemble systems is their capacity to forecast their own forecast error through the ensemble spread-error relationship. The paper begins by revisiting the limitations of the Pearson correlation alone in assessing this relationship. Next, we introduce two new metrics to consider in assessing the utility an ensemble's varying dispersion. We argue there are two aspects of an ensemble's dispersion that should be assessed. First, and perhaps more fundamentally: is there enough variability in the ensembles dispersion to justify the maintenance of an expensive ensemble prediction system (EPS), irrespective of whether the EPS is well-calibrated or not? To diagnose this, the factor that controls the theoretical upper limit of the spread-error correlation can be useful. Secondly, does the variable dispersion of an ensemble relate to variable expectation of forecast error? Representing the spread-error correlation in relation to its theoretical limit can provide a simple diagnostic of this attribute. A context for these concepts is provided by assessing two operational ensembles: 30-member Western US temperature forecasts for the U.S. Army Test and Evaluation Command and 51-member Brahmaputra River flow forecasts of the Climate Forecast and Applications Project for Bangladesh. Both of these systems utilize a postprocessing technique based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. In addition, the methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. We will describe both ensemble systems briefly, review the steps used to calibrate the ensemble forecast, and present

Learners' Descriptions of German Pronunciation, Vocabulary, and Grammar: A Folk Linguistic Account

ERIC Educational Resources Information Center

Chavez, Monika

2009-01-01

Following a folk linguistic approach, this investigation of first-, second- and fourth-year learners' accounts of German found that (1) few had held pre-conceived notions about German prior to language study; (2) most pre-conceived notions concerned German pronunciation; (3) pre-conceived notions about vocabulary were most likely to influence the…

South Texas Mexican American Use of Traditional Folk and Mainstream Alternative Therapies

ERIC Educational Resources Information Center

Martinez, Leslie N.

2009-01-01

A telephone survey was conducted with a large sample of Mexican Americans from border (n = 1,001) and nonborder (n = 1,030) regions in Texas. Patterns of traditional folk and mainstream complementary and alternative medicine (CAM) use were analyzed with two binary logistic regressions, using gender, self-rated health, confidence in medical…

Mixture models for protein structure ensembles.

PubMed

Hirsch, Michael; Habeck, Michael

2008-10-01

Protein structure ensembles provide important insight into the dynamics and function of a protein and contain information that is not captured with a single static structure. However, it is not clear a priori to what extent the variability within an ensemble is caused by internal structural changes. Additional variability results from overall translations and rotations of the molecule. And most experimental data do not provide information to relate the structures to a common reference frame. To report meaningful values of intrinsic dynamics, structural precision, conformational entropy, etc., it is therefore important to disentangle local from global conformational heterogeneity. We consider the task of disentangling local from global heterogeneity as an inference problem. We use probabilistic methods to infer from the protein ensemble missing information on reference frames and stable conformational sub-states. To this end, we model a protein ensemble as a mixture of Gaussian probability distributions of either entire conformations or structural segments. We learn these models from a protein ensemble using the expectation-maximization algorithm. Our first model can be used to find multiple conformers in a structure ensemble. The second model partitions the protein chain into locally stable structural segments or core elements and less structured regions typically found in loops. Both models are simple to implement and contain only a single free parameter: the number of conformers or structural segments. Our models can be used to analyse experimental ensembles, molecular dynamics trajectories and conformational change in proteins. The Python source code for protein ensemble analysis is available from the authors upon request.

Image Change Detection via Ensemble Learning

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

Martin, Benjamin W; Vatsavai, Raju

2013-01-01

The concept of geographic change detection is relevant in many areas. Changes in geography can reveal much information about a particular location. For example, analysis of changes in geography can identify regions of population growth, change in land use, and potential environmental disturbance. A common way to perform change detection is to use a simple method such as differencing to detect regions of change. Though these techniques are simple, often the application of these techniques is very limited. Recently, use of machine learning methods such as neural networks for change detection has been explored with great success. In this work,more » we explore the use of ensemble learning methodologies for detecting changes in bitemporal synthetic aperture radar (SAR) images. Ensemble learning uses a collection of weak machine learning classifiers to create a stronger classifier which has higher accuracy than the individual classifiers in the ensemble. The strength of the ensemble lies in the fact that the individual classifiers in the ensemble create a mixture of experts in which the final classification made by the ensemble classifier is calculated from the outputs of the individual classifiers. Our methodology leverages this aspect of ensemble learning by training collections of weak decision tree based classifiers to identify regions of change in SAR images collected of a region in the Staten Island, New York area during Hurricane Sandy. Preliminary studies show that the ensemble method has approximately 11.5% higher change detection accuracy than an individual classifier.« less

A Theoretical Analysis of Why Hybrid Ensembles Work.

PubMed

Hsu, Kuo-Wei

2017-01-01

Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

Input Decimated Ensembles

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)

2001-01-01

Using an ensemble of classifiers instead of a single classifier has been shown to improve generalization performance in many pattern recognition problems. However, the extent of such improvement depends greatly on the amount of correlation among the errors of the base classifiers. Therefore, reducing those correlations while keeping the classifiers' performance levels high is an important area of research. In this article, we explore input decimation (ID), a method which selects feature subsets for their ability to discriminate among the classes and uses them to decouple the base classifiers. We provide a summary of the theoretical benefits of correlation reduction, along with results of our method on two underwater sonar data sets, three benchmarks from the Probenl/UCI repositories, and two synthetic data sets. The results indicate that input decimated ensembles (IDEs) outperform ensembles whose base classifiers use all the input features; randomly selected subsets of features; and features created using principal components analysis, on a wide range of domains.

A Theoretical Analysis of Why Hybrid Ensembles Work

PubMed Central

2017-01-01

Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles. PMID:28255296

Victims, Heroes, and Just Plain Folks (Teaching and Learning about Cultural Diversity).

ERIC Educational Resources Information Center

Miller, Howard M., Ed.

1998-01-01

Argues that multicultural education, if it is to be effective and meaningful, needs to be woven throughout the curriculum. Discusses 11 children's books that take into account the age and maturity level of students as they tell forthright stories of the victims, heroes, and just plain folks of the Holocaust, slavery, and the involuntary of…

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

NASA Astrophysics Data System (ADS)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

What Do Grandmothers Think about Self-Esteem? American and Taiwanese Folk Theories Revisited

ERIC Educational Resources Information Center

Cho, Grace E.; Sandel, Todd L.; Miller, Peggy J.; Wang, Su-hua

2005-01-01

The study investigates European American and Taiwanese grandmothers' folk theories of childrearing and self-esteem, building on an earlier comparison of mothers from the same families. Adopting methods that privilege local meanings, we bring grandmothers' voices into the conversation about childrearing, thereby contributing to a deeper…

Evaluation of an Ensemble Dispersion Calculation.

NASA Astrophysics Data System (ADS)

Draxler, Roland R.

2003-02-01

A Lagrangian transport and dispersion model was modified to generate multiple simulations from a single meteorological dataset. Each member of the simulation was computed by assuming a ±1-gridpoint shift in the horizontal direction and a ±250-m shift in the vertical direction of the particle position, with respect to the meteorological data. The configuration resulted in 27 ensemble members. Each member was assumed to have an equal probability. The model was tested by creating an ensemble of daily average air concentrations for 3 months at 75 measurement locations over the eastern half of the United States during the Across North America Tracer Experiment (ANATEX). Two generic graphical displays were developed to summarize the ensemble prediction and the resulting concentration probabilities for a specific event: a probability-exceed plot and a concentration-probability plot. Although a cumulative distribution of the ensemble probabilities compared favorably with the measurement data, the resulting distribution was not uniform. This result was attributed to release height sensitivity. The trajectory ensemble approach accounts for about 41%-47% of the variance in the measurement data. This residual uncertainty is caused by other model and data errors that are not included in the ensemble design.

The Relationship between English Language Learner Status and Music Ensemble Participation

ERIC Educational Resources Information Center

Lorah, Julie A.; Sanders, Elizabeth A.; Morrison, Steven J.

2014-01-01

Authors of previous research have reported that U.S. English language learner (ELL) students participate in school-sponsored music ensembles (band, orchestra, and choir) at a lower rate than their native-English-speaking peers (non-ELLs). The current study examined this phenomenon using a nationally representative sample of U.S. 10th graders (14-…

SIMULATION OF THE ICELAND VOLCANIC ERUPTION OF APRIL 2010 USING THE ENSEMBLE SYSTEM

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

Buckley, R.

2011-05-10

The Eyjafjallajokull volcanic eruption in Iceland in April 2010 disrupted transportation in Europe which ultimately affected travel plans for many on a global basis. The Volcanic Ash Advisory Centre (VAAC) is responsible for providing guidance to the aviation industry of the transport of volcanic ash clouds. There are nine such centers located globally, and the London branch (headed by the United Kingdom Meteorological Office, or UKMet) was responsible for modeling the Iceland volcano. The guidance provided by the VAAC created some controversy due to the burdensome travel restrictions and uncertainty involved in the prediction of ash transport. The Iceland volcanicmore » eruption provides a useful exercise of the European ENSEMBLE program, coordinated by the Joint Research Centre (JRC) in Ispra, Italy. ENSEMBLE, a decision support system for emergency response, uses transport model results from a variety of countries in an effort to better understand the uncertainty involved with a given accident scenario. Model results in the form of airborne concentration and surface deposition are required from each member of the ensemble in a prescribed format that may then be uploaded to a website for manipulation. The Savannah River National Laboratory (SRNL) is the lone regular United States participant throughout the 10-year existence of ENSEMBLE. For the Iceland volcano, four separate source term estimates have been provided to ENSEMBLE participants. This paper focuses only on one of those source terms. The SRNL results in relation to other modeling agency results along with useful information obtained using an ensemble of transport results will be discussed.« less

On the predictability of outliers in ensemble forecasts

NASA Astrophysics Data System (ADS)

Siegert, S.; Bröcker, J.; Kantz, H.

2012-03-01

In numerical weather prediction, ensembles are used to retrieve probabilistic forecasts of future weather conditions. We consider events where the verification is smaller than the smallest, or larger than the largest ensemble member of a scalar ensemble forecast. These events are called outliers. In a statistically consistent K-member ensemble, outliers should occur with a base rate of 2/(K+1). In operational ensembles this base rate tends to be higher. We study the predictability of outlier events in terms of the Brier Skill Score and find that forecast probabilities can be calculated which are more skillful than the unconditional base rate. This is shown analytically for statistically consistent ensembles. Using logistic regression, forecast probabilities for outlier events in an operational ensemble are calculated. These probabilities exhibit positive skill which is quantitatively similar to the analytical results. Possible causes of these results as well as their consequences for ensemble interpretation are discussed.

Rethinking the Default Construction of Multimodel Climate Ensembles

DOE PAGES

Rauser, Florian; Gleckler, Peter; Marotzke, Jochem

2015-07-21

Here, we discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process.more » If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. Finally, with an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.« less

Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume

2013-01-01

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.

The Turtle Went To War. Northern Cheyenne Folk Tales. Indian Culture Series.

ERIC Educational Resources Information Center

Tall Bull, Henry; Weist, Tom

The book takes its title from the first of nine Northern Cheyenne folk tales, illustrated by Indian children in grades 2-8. The stories are: "The Turtle Went to War" about a turtle who makes war on the Indians and takes two scalps; "The Cat", explaining why cats eat first and wash later; "The Frog and the Watersnake",…

The Danish Folk High Schools. Bulletin, 1914, No. 22. Whole Number 595

ERIC Educational Resources Information Center

Foght, H. W.

1914-01-01

This bulletin contains the third section of Harold W. Foght's report on the rural schools of Denmark. This section of the report pertains almost wholly to the folk high schools, which have by common consent been the most important factor in the transformation in the rural life of Denmark and in the phenomenal economic and social development of…

Ensembl genomes 2016: more genomes, more complexity

USDA-ARS?s Scientific Manuscript database

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent...

Hybrid Data Assimilation without Ensemble Filtering

NASA Technical Reports Server (NTRS)

Todling, Ricardo; Akkraoui, Amal El

2014-01-01

The Global Modeling and Assimilation Office is preparing to upgrade its three-dimensional variational system to a hybrid approach in which the ensemble is generated using a square-root ensemble Kalman filter (EnKF) and the variational problem is solved using the Grid-point Statistical Interpolation system. As in most EnKF applications, we found it necessary to employ a combination of multiplicative and additive inflations, to compensate for sampling and modeling errors, respectively and, to maintain the small-member ensemble solution close to the variational solution; we also found it necessary to re-center the members of the ensemble about the variational analysis. During tuning of the filter we have found re-centering and additive inflation to play a considerably larger role than expected, particularly in a dual-resolution context when the variational analysis is ran at larger resolution than the ensemble. This led us to consider a hybrid strategy in which the members of the ensemble are generated by simply converting the variational analysis to the resolution of the ensemble and applying additive inflation, thus bypassing the EnKF. Comparisons of this, so-called, filter-free hybrid procedure with an EnKF-based hybrid procedure and a control non-hybrid, traditional, scheme show both hybrid strategies to provide equally significant improvement over the control; more interestingly, the filter-free procedure was found to give qualitatively similar results to the EnKF-based procedure.

Motor-motor interactions in ensembles of muscle myosin: using theory to connect single molecule to ensemble measurements

NASA Astrophysics Data System (ADS)

Walcott, Sam

2013-03-01

Interactions between the proteins actin and myosin drive muscle contraction. Properties of a single myosin interacting with an actin filament are largely known, but a trillion myosins work together in muscle. We are interested in how single-molecule properties relate to ensemble function. Myosin's reaction rates depend on force, so ensemble models keep track of both molecular state and force on each molecule. These models make subtle predictions, e.g. that myosin, when part of an ensemble, moves actin faster than when isolated. This acceleration arises because forces between molecules speed reaction kinetics. Experiments support this prediction and allow parameter estimates. A model based on this analysis describes experiments from single molecule to ensemble. In vivo, actin is regulated by proteins that, when present, cause the binding of one myosin to speed the binding of its neighbors; binding becomes cooperative. Although such interactions preclude the mean field approximation, a set of linear ODEs describes these ensembles under simplified experimental conditions. In these experiments cooperativity is strong, with the binding of one molecule affecting ten neighbors on either side. We progress toward a description of myosin ensembles under physiological conditions.

The Ensembl genome database project.

PubMed

Hubbard, T; Barker, D; Birney, E; Cameron, G; Chen, Y; Clark, L; Cox, T; Cuff, J; Curwen, V; Down, T; Durbin, R; Eyras, E; Gilbert, J; Hammond, M; Huminiecki, L; Kasprzyk, A; Lehvaslaiho, H; Lijnzaad, P; Melsopp, C; Mongin, E; Pettett, R; Pocock, M; Potter, S; Rust, A; Schmidt, E; Searle, S; Slater, G; Smith, J; Spooner, W; Stabenau, A; Stalker, J; Stupka, E; Ureta-Vidal, A; Vastrik, I; Clamp, M

2002-01-01

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of the human genome sequence, with confirmed gene predictions that have been integrated with external data sources, and is available as either an interactive web site or as flat files. It is also an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements from sequence analysis to data storage and visualisation. The Ensembl site is one of the leading sources of human genome sequence annotation and provided much of the analysis for publication by the international human genome project of the draft genome. The Ensembl system is being installed around the world in both companies and academic sites on machines ranging from supercomputers to laptops.

Decadal climate prediction in the large ensemble limit

NASA Astrophysics Data System (ADS)

Yeager, S. G.; Rosenbloom, N. A.; Strand, G.; Lindsay, K. T.; Danabasoglu, G.; Karspeck, A. R.; Bates, S. C.; Meehl, G. A.

2017-12-01

In order to quantify the benefits of initialization for climate prediction on decadal timescales, two parallel sets of historical simulations are required: one "initialized" ensemble that incorporates observations of past climate states and one "uninitialized" ensemble whose internal climate variations evolve freely and without synchronicity. In the large ensemble limit, ensemble averaging isolates potentially predictable forced and internal variance components in the "initialized" set, but only the forced variance remains after averaging the "uninitialized" set. The ensemble size needed to achieve this variance decomposition, and to robustly distinguish initialized from uninitialized decadal predictions, remains poorly constrained. We examine a large ensemble (LE) of initialized decadal prediction (DP) experiments carried out using the Community Earth System Model (CESM). This 40-member CESM-DP-LE set of experiments represents the "initialized" complement to the CESM large ensemble of 20th century runs (CESM-LE) documented in Kay et al. (2015). Both simulation sets share the same model configuration, historical radiative forcings, and large ensemble sizes. The twin experiments afford an unprecedented opportunity to explore the sensitivity of DP skill assessment, and in particular the skill enhancement associated with initialization, to ensemble size. This talk will highlight the benefits of a large ensemble size for initialized predictions of seasonal climate over land in the Atlantic sector as well as predictions of shifts in the likelihood of climate extremes that have large societal impact.

Layered Ensemble Architecture for Time Series Forecasting.

PubMed

Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

2016-01-01

Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

Perception of ensemble statistics requires attention.

PubMed

Jackson-Nielsen, Molly; Cohen, Michael A; Pitts, Michael A

2017-02-01

To overcome inherent limitations in perceptual bandwidth, many aspects of the visual world are represented as summary statistics (e.g., average size, orientation, or density of objects). Here, we investigated the relationship between summary (ensemble) statistics and visual attention. Recently, it was claimed that one ensemble statistic in particular, color diversity, can be perceived without focal attention. However, a broader debate exists over the attentional requirements of conscious perception, and it is possible that some form of attention is necessary for ensemble perception. To test this idea, we employed a modified inattentional blindness paradigm and found that multiple types of summary statistics (color and size) often go unnoticed without attention. In addition, we found attentional costs in dual-task situations, further implicating a role for attention in statistical perception. Overall, we conclude that while visual ensembles may be processed efficiently, some amount of attention is necessary for conscious perception of ensemble statistics. Copyright © 2016 Elsevier Inc. All rights reserved.

On the incidence of meteorological and hydrological processors: Effect of resolution, sharpness and reliability of hydrological ensemble forecasts

NASA Astrophysics Data System (ADS)

Abaza, Mabrouk; Anctil, François; Fortin, Vincent; Perreault, Luc

2017-12-01

Meteorological and hydrological ensemble prediction systems are imperfect. Their outputs could often be improved through the use of a statistical processor, opening up the question of the necessity of using both processors (meteorological and hydrological), only one of them, or none. This experiment compares the predictive distributions from four hydrological ensemble prediction systems (H-EPS) utilising the Ensemble Kalman filter (EnKF) probabilistic sequential data assimilation scheme. They differ in the inclusion or not of the Distribution Based Scaling (DBS) method for post-processing meteorological forecasts and the ensemble Bayesian Model Averaging (ensemble BMA) method for hydrological forecast post-processing. The experiment is implemented on three large watersheds and relies on the combination of two meteorological reforecast products: the 4-member Canadian reforecasts from the Canadian Centre for Meteorological and Environmental Prediction (CCMEP) and the 10-member American reforecasts from the National Oceanic and Atmospheric Administration (NOAA), leading to 14 members at each time step. Results show that all four tested H-EPS lead to resolution and sharpness values that are quite similar, with an advantage to DBS + EnKF. The ensemble BMA is unable to compensate for any bias left in the precipitation ensemble forecasts. On the other hand, it succeeds in calibrating ensemble members that are otherwise under-dispersed. If reliability is preferred over resolution and sharpness, DBS + EnKF + ensemble BMA performs best, making use of both processors in the H-EPS system. Conversely, for enhanced resolution and sharpness, DBS is the preferred method.

AUC-Maximizing Ensembles through Metalearning.

PubMed

LeDell, Erin; van der Laan, Mark J; Petersen, Maya

2016-05-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

AUC-Maximizing Ensembles through Metalearning

PubMed Central

LeDell, Erin; van der Laan, Mark J.; Peterson, Maya

2016-01-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree. PMID:27227721

Migrant Mexican Traditions = Tradiciones Migrantes Mexicanas. An Exhibit of Folk Art by Mexican Migrant Farmworkers (Geneseo, New York, September 22-October 4, 1990).

ERIC Educational Resources Information Center

Camacho, Juana; Gomez, Jose Luis

This exhibit guide (in Spanish, with translation in English printed on adjoining columns on each page), describes an exhibition of folk art by Mexican migrant farmworkers presented by thre Folk Arts Program of the BOCES Geneseo Migrant Center. The exhibit is divided into four major themes that farmworkers presented by the BOCES Geneseo Migrant…

Advanced Atmospheric Ensemble Modeling Techniques

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

Buckley, R.; Chiswell, S.; Kurzeja, R.

Ensemble modeling (EM), the creation of multiple atmospheric simulations for a given time period, has become an essential tool for characterizing uncertainties in model predictions. We explore two novel ensemble modeling techniques: (1) perturbation of model parameters (Adaptive Programming, AP), and (2) data assimilation (Ensemble Kalman Filter, EnKF). The current research is an extension to work from last year and examines transport on a small spatial scale (<100 km) in complex terrain, for more rigorous testing of the ensemble technique. Two different release cases were studied, a coastal release (SF6) and an inland release (Freon) which consisted of two releasemore » times. Observations of tracer concentration and meteorology are used to judge the ensemble results. In addition, adaptive grid techniques have been developed to reduce required computing resources for transport calculations. Using a 20- member ensemble, the standard approach generated downwind transport that was quantitatively good for both releases; however, the EnKF method produced additional improvement for the coastal release where the spatial and temporal differences due to interior valley heating lead to the inland movement of the plume. The AP technique showed improvements for both release cases, with more improvement shown in the inland release. This research demonstrated that transport accuracy can be improved when models are adapted to a particular location/time or when important local data is assimilated into the simulation and enhances SRNL’s capability in atmospheric transport modeling in support of its current customer base and local site missions, as well as our ability to attract new customers within the intelligence community.« less

Folk Tales: Getting to Know Southeast Asia. Southeast Asia Curriculum Series, No. 1.

ERIC Educational Resources Information Center

Ridgley, Marlene

A teaching/learning plan designed to provide the elementary classroom teacher with an overview of the geography, environment, culture, and people of Southeast Asia includes five sections on the following subjects: geography, animals, plants, social roles and occupations, and religion. Through the use of folk tales from each of six Southeast Asian…

Exploring Antecedents of Organizational Citizenship Behaviour among Teachers at Norwegian Folk High Schools

ERIC Educational Resources Information Center

Elstad, Eyvind; Christophersen, Knut Andreas; Turmo, Are

2012-01-01

The folk high school (FHS) is a Nordic contribution to global education and is a unique approach to non-university adult education. Because expanded tuition is the true nature of Norwegian FHS, it is important for FHS that its teachers perform discretionary individual extra-role behaviour advantageous to the school organization, a phenomenon…

An Ensemble Approach to Understanding the ENSO Response to Climate Change

NASA Astrophysics Data System (ADS)

Stevenson, S.; Capotondi, A.; Fasullo, J.; Otto-Bliesner, B. L.

2017-12-01

The dynamics of the El Nino/Southern Oscillation (ENSO) are known to be sensitive to changes in background climate conditions, as well as atmosphere/ocean feedbacks. However, the degree to which shifts in ENSO characteristics can be robustly attributed to external climate forcings remains unknown. Efforts to assess these changes in a multi-model framework are subject to uncertainties due to both differing model physics and internal ENSO variability. New community ensembles created at the National Center for Atmospheric Research and the NOAA Geophysical Fluid Dynamics Laboratory are ideally suited to addressing this problem, providing many realizations of the climate of the 850-2100 period with a combination of both natural and anthropogenic climate forcing factors. Here we analyze the impacts of external forcing on El Nino and La Nina evolution using four sets of simulations: the CESM Last Millennium Ensemble (CESM-LME), which covers the 850-2005 period and provides long-term context for forced responses; the Large Ensemble (CESM-LE), which includes 20th century and 21st century (RCP8.5) projections; the Medium Ensemble (CESM-ME), which is composed of 21st century RCP4.5 projections; and a large ensemble with the GFDL ESM2M, which includes 20th century and RCP8.5 projections. In the CESM, ENSO variance increases slightly over the 20th century in all ensembles, with the effects becoming much larger during the 21st. The slower increase in variance over the 20th century is shown to arise from compensating influences from greenhouse gas (GHG) and anthropogenic aerosol emissions, which give way to GHG-dominated effects by 2100. However, the 21st century variance increase is not robust: CESM and the ESM2M differ drastically in their ENSO projections. The mechanisms for these inter-model differences are discussed, as are the implications for the design of future multi-model ENSO projection experiments.

Bayesian ensemble refinement by replica simulations and reweighting.

PubMed

Hummer, Gerhard; Köfinger, Jürgen

2015-12-28

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

Bayesian ensemble refinement by replica simulations and reweighting

NASA Astrophysics Data System (ADS)

Hummer, Gerhard; Köfinger, Jürgen

2015-12-01

We describe different Bayesian ensemble refinement methods, examine their interrelation, and discuss their practical application. With ensemble refinement, the properties of dynamic and partially disordered (bio)molecular structures can be characterized by integrating a wide range of experimental data, including measurements of ensemble-averaged observables. We start from a Bayesian formulation in which the posterior is a functional that ranks different configuration space distributions. By maximizing this posterior, we derive an optimal Bayesian ensemble distribution. For discrete configurations, this optimal distribution is identical to that obtained by the maximum entropy "ensemble refinement of SAXS" (EROS) formulation. Bayesian replica ensemble refinement enhances the sampling of relevant configurations by imposing restraints on averages of observables in coupled replica molecular dynamics simulations. We show that the strength of the restraints should scale linearly with the number of replicas to ensure convergence to the optimal Bayesian result in the limit of infinitely many replicas. In the "Bayesian inference of ensembles" method, we combine the replica and EROS approaches to accelerate the convergence. An adaptive algorithm can be used to sample directly from the optimal ensemble, without replicas. We discuss the incorporation of single-molecule measurements and dynamic observables such as relaxation parameters. The theoretical analysis of different Bayesian ensemble refinement approaches provides a basis for practical applications and a starting point for further investigations.

"It feels more like a parody": Canadian Queer as Folk viewers and the show they love to complain about.

PubMed

Peters, Wendy

2009-01-01

The nighttime television series Queer as Folk (U.S.) was set in Pittsburgh, Pennsylvania, but was filmed in Toronto, Ontario, Canada. Beginning with a brief textual analysis of the representation of lesbians on Queer as Folk, this audience reception study outlines how Canadian viewers who claimed a wide range of sexualities interpreted the representations of lesbians on the series in vastly different ways. While some viewers described the lesbian characters, Melanie and Lindsay, as "an embarrassment" and "more like a parody of lesbians," others enjoyed the "accuracy" and "realism" of these characters.

Ensemble-based data assimilation and optimal sensor placement for scalar source reconstruction

NASA Astrophysics Data System (ADS)

Mons, Vincent; Wang, Qi; Zaki, Tamer

2017-11-01

Reconstructing the characteristics of a scalar source from limited remote measurements in a turbulent flow is a problem of great interest for environmental monitoring, and is challenging due to several aspects. Firstly, the numerical estimation of the scalar dispersion in a turbulent flow requires significant computational resources. Secondly, in actual practice, only a limited number of observations are available, which generally makes the corresponding inverse problem ill-posed. Ensemble-based variational data assimilation techniques are adopted to solve the problem of scalar source localization in a turbulent channel flow at Reτ = 180 . This approach combines the components of variational data assimilation and ensemble Kalman filtering, and inherits the robustness from the former and the ease of implementation from the latter. An ensemble-based methodology for optimal sensor placement is also proposed in order to improve the condition of the inverse problem, which enhances the performances of the data assimilation scheme. This work has been partially funded by the Office of Naval Research (Grant N00014-16-1-2542) and by the National Science Foundation (Grant 1461870).

Ensemble perception of color in autistic adults.

PubMed

Maule, John; Stanworth, Kirstie; Pellicano, Elizabeth; Franklin, Anna

2017-05-01

Dominant accounts of visual processing in autism posit that autistic individuals have an enhanced access to details of scenes [e.g., weak central coherence] which is reflected in a general bias toward local processing. Furthermore, the attenuated priors account of autism predicts that the updating and use of summary representations is reduced in autism. Ensemble perception describes the extraction of global summary statistics of a visual feature from a heterogeneous set (e.g., of faces, sizes, colors), often in the absence of local item representation. The present study investigated ensemble perception in autistic adults using a rapidly presented (500 msec) ensemble of four, eight, or sixteen elements representing four different colors. We predicted that autistic individuals would be less accurate when averaging the ensembles, but more accurate in recognizing individual ensemble colors. The results were consistent with the predictions. Averaging was impaired in autism, but only when ensembles contained four elements. Ensembles of eight or sixteen elements were averaged equally accurately across groups. The autistic group also showed a corresponding advantage in rejecting colors that were not originally seen in the ensemble. The results demonstrate the local processing bias in autism, but also suggest that the global perceptual averaging mechanism may be compromised under some conditions. The theoretical implications of the findings and future avenues for research on summary statistics in autism are discussed. Autism Res 2017, 10: 839-851. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Ensemble perception of color in autistic adults

PubMed Central

Stanworth, Kirstie; Pellicano, Elizabeth; Franklin, Anna

2016-01-01

Dominant accounts of visual processing in autism posit that autistic individuals have an enhanced access to details of scenes [e.g., weak central coherence] which is reflected in a general bias toward local processing. Furthermore, the attenuated priors account of autism predicts that the updating and use of summary representations is reduced in autism. Ensemble perception describes the extraction of global summary statistics of a visual feature from a heterogeneous set (e.g., of faces, sizes, colors), often in the absence of local item representation. The present study investigated ensemble perception in autistic adults using a rapidly presented (500 msec) ensemble of four, eight, or sixteen elements representing four different colors. We predicted that autistic individuals would be less accurate when averaging the ensembles, but more accurate in recognizing individual ensemble colors. The results were consistent with the predictions. Averaging was impaired in autism, but only when ensembles contained four elements. Ensembles of eight or sixteen elements were averaged equally accurately across groups. The autistic group also showed a corresponding advantage in rejecting colors that were not originally seen in the ensemble. The results demonstrate the local processing bias in autism, but also suggest that the global perceptual averaging mechanism may be compromised under some conditions. The theoretical implications of the findings and future avenues for research on summary statistics in autism are discussed. Autism Res 2017, 10: 839–851. © 2016 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research PMID:27874263

A real-time evaluation and demonstration of strategies for 'Over-The-Loop' ensemble streamflow forecasting in US watersheds

NASA Astrophysics Data System (ADS)

Wood, Andy; Clark, Elizabeth; Mendoza, Pablo; Nijssen, Bart; Newman, Andy; Clark, Martyn; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

Many if not most national operational streamflow prediction systems rely on a forecaster-in-the-loop approach that require the hands-on-effort of an experienced human forecaster. This approach evolved from the need to correct for long-standing deficiencies in the models and datasets used in forecasting, and the practice often leads to skillful flow predictions despite the use of relatively simple, conceptual models. Yet the 'in-the-loop' forecast process is not reproducible, which limits opportunities to assess and incorporate new techniques systematically, and the effort required to make forecasts in this way is an obstacle to expanding forecast services - e.g., though adding new forecast locations or more frequent forecast updates, running more complex models, or producing forecast and hindcasts that can support verification. In the last decade, the hydrologic forecasting community has begun develop more centralized, 'over-the-loop' systems. The quality of these new forecast products will depend on their ability to leverage research in areas including earth system modeling, parameter estimation, data assimilation, statistical post-processing, weather and climate prediction, verification, and uncertainty estimation through the use of ensembles. Currently, many national operational streamflow forecasting and water management communities have little experience with the strengths and weaknesses of over-the-loop approaches, even as such systems are beginning to be deployed operationally in centers such as ECMWF. There is thus a need both to evaluate these forecasting advances and to demonstrate their potential in a public arena, raising awareness in forecast user communities and development programs alike. To address this need, the US National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the US Army Corps of Engineers, using the NCAR 'System for Hydromet Analysis Research and Prediction Applications

Evaluation of medium-range ensemble flood forecasting based on calibration strategies and ensemble methods in Lanjiang Basin, Southeast China

NASA Astrophysics Data System (ADS)

Liu, Li; Gao, Chao; Xuan, Weidong; Xu, Yue-Ping

2017-11-01

Ensemble flood forecasts by hydrological models using numerical weather prediction products as forcing data are becoming more commonly used in operational flood forecasting applications. In this study, a hydrological ensemble flood forecasting system comprised of an automatically calibrated Variable Infiltration Capacity model and quantitative precipitation forecasts from TIGGE dataset is constructed for Lanjiang Basin, Southeast China. The impacts of calibration strategies and ensemble methods on the performance of the system are then evaluated. The hydrological model is optimized by the parallel programmed ε-NSGA II multi-objective algorithm. According to the solutions by ε-NSGA II, two differently parameterized models are determined to simulate daily flows and peak flows at each of the three hydrological stations. Then a simple yet effective modular approach is proposed to combine these daily and peak flows at the same station into one composite series. Five ensemble methods and various evaluation metrics are adopted. The results show that ε-NSGA II can provide an objective determination on parameter estimation, and the parallel program permits a more efficient simulation. It is also demonstrated that the forecasts from ECMWF have more favorable skill scores than other Ensemble Prediction Systems. The multimodel ensembles have advantages over all the single model ensembles and the multimodel methods weighted on members and skill scores outperform other methods. Furthermore, the overall performance at three stations can be satisfactory up to ten days, however the hydrological errors can degrade the skill score by approximately 2 days, and the influence persists until a lead time of 10 days with a weakening trend. With respect to peak flows selected by the Peaks Over Threshold approach, the ensemble means from single models or multimodels are generally underestimated, indicating that the ensemble mean can bring overall improvement in forecasting of flows. For

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post / National Weather Service National Centers for Environmental Prediction Environmental Modeling Center NOAA

Ensemble training to improve recognition using 2D ear

NASA Astrophysics Data System (ADS)

Middendorff, Christopher; Bowyer, Kevin W.

2009-05-01

The ear has gained popularity as a biometric feature due to the robustness of the shape over time and across emotional expression. Popular methods of ear biometrics analyze the ear as a whole, leaving these methods vulnerable to error due to occlusion. Many researchers explore ear recognition using an ensemble, but none present a method for designing the individual parts that comprise the ensemble. In this work, we introduce a method of modifying the ensemble shapes to improve performance. We determine how different properties of an ensemble training system can affect overall performance. We show that ensembles built from small parts will outperform ensembles built with larger parts, and that incorporating a large number of parts improves the performance of the ensemble.

Ensemble method for dengue prediction

PubMed Central

Baugher, Benjamin; Moniz, Linda J.; Bagley, Thomas; Babin, Steven M.; Guven, Erhan

2018-01-01

Background In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Methods Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Principal findings Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. Conclusions The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru. PMID:29298320

Ensemble method for dengue prediction.

PubMed

Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

2018-01-01

In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

An information-theoretical perspective on weighted ensemble forecasts

NASA Astrophysics Data System (ADS)

Weijs, Steven V.; van de Giesen, Nick

2013-08-01

This paper presents an information-theoretical method for weighting ensemble forecasts with new information. Weighted ensemble forecasts can be used to adjust the distribution that an existing ensemble of time series represents, without modifying the values in the ensemble itself. The weighting can, for example, add new seasonal forecast information in an existing ensemble of historically measured time series that represents climatic uncertainty. A recent article in this journal compared several methods to determine the weights for the ensemble members and introduced the pdf-ratio method. In this article, a new method, the minimum relative entropy update (MRE-update), is presented. Based on the principle of minimum discrimination information, an extension of the principle of maximum entropy (POME), the method ensures that no more information is added to the ensemble than is present in the forecast. This is achieved by minimizing relative entropy, with the forecast information imposed as constraints. From this same perspective, an information-theoretical view on the various weighting methods is presented. The MRE-update is compared with the existing methods and the parallels with the pdf-ratio method are analysed. The paper provides a new, information-theoretical justification for one version of the pdf-ratio method that turns out to be equivalent to the MRE-update. All other methods result in sets of ensemble weights that, seen from the information-theoretical perspective, add either too little or too much (i.e. fictitious) information to the ensemble.

Contact planarization of ensemble nanowires

NASA Astrophysics Data System (ADS)

Chia, A. C. E.; LaPierre, R. R.

2011-06-01

The viability of four organic polymers (S1808, SC200, SU8 and Cyclotene) as filling materials to achieve planarization of ensemble nanowire arrays is reported. Analysis of the porosity, surface roughness and thermal stability of each filling material was performed. Sonication was used as an effective method to remove the tops of the nanowires (NWs) to achieve complete planarization. Ensemble nanowire devices were fully fabricated and I-V measurements confirmed that Cyclotene effectively planarizes the NWs while still serving the role as an insulating layer between the top and bottom contacts. These processes and analysis can be easily implemented into future characterization and fabrication of ensemble NWs for optoelectronic device applications.

Contact planarization of ensemble nanowires.

PubMed

Chia, A C E; LaPierre, R R

2011-06-17

The viability of four organic polymers (S1808, SC200, SU8 and Cyclotene) as filling materials to achieve planarization of ensemble nanowire arrays is reported. Analysis of the porosity, surface roughness and thermal stability of each filling material was performed. Sonication was used as an effective method to remove the tops of the nanowires (NWs) to achieve complete planarization. Ensemble nanowire devices were fully fabricated and I-V measurements confirmed that Cyclotene effectively planarizes the NWs while still serving the role as an insulating layer between the top and bottom contacts. These processes and analysis can be easily implemented into future characterization and fabrication of ensemble NWs for optoelectronic device applications.

Rare tradition of the folk medicinal use of Aconitum spp. is kept alive in Solčavsko, Slovenia.

PubMed

Povšnar, Marija; Koželj, Gordana; Kreft, Samo; Lumpert, Mateja

2017-08-08

Aconitum species are poisonous plants that have been used in Western medicine for centuries. In the nineteenth century, these plants were part of official and folk medicine in the Slovenian territory. According to current ethnobotanical studies, folk use of Aconitum species is rarely reported in Europe. The purpose of this study was to research the folk medicinal use of Aconitum species in Solčavsko, Slovenia; to collect recipes for the preparation of Aconitum spp., indications for use, and dosing; and to investigate whether the folk use of aconite was connected to poisoning incidents. In Solčavsko, a remote alpine area in northern Slovenia, we performed semi-structured interviews with 19 informants in Solčavsko, 3 informants in Luče, and two retired physicians who worked in that area. Three samples of homemade ethanolic extracts were obtained from informants, and the concentration of aconitine was measured. In addition, four extracts were prepared according to reported recipes. All 22 informants knew of Aconitum spp. and their therapeutic use, and 5 of them provided a detailed description of the preparation and use of "voukuc", an ethanolic extract made from aconite roots. Seven informants were unable to describe the preparation in detail, since they knew of the extract only from the narration of others or they remembered it from childhood. Most likely, the roots of Aconitum tauricum and Aconitum napellus were used for the preparation of the extract, and the solvent was homemade spirits. Four informants kept the extract at home; two extracts were prepared recently (1998 and 2015). Three extracts were analyzed, and 2 contained aconitine. Informants reported many indications for the use of the extract; it was used internally and, in some cases, externally as well. The extract was also used in animals. The extract was measured in drops, but the number of drops differed among the informants. The informants reported nine poisonings with Aconitum spp., but none of

Challenges in Visual Analysis of Ensembles

DOE PAGES

Crossno, Patricia

2018-04-12

Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. In this paper, we explore the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.

Challenges in Visual Analysis of Ensembles

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

Crossno, Patricia

Modeling physical phenomena through computational simulation increasingly relies on generating a collection of related runs, known as an ensemble. In this paper, we explore the challenges we face in developing analysis and visualization systems for large and complex ensemble data sets, which we seek to understand without having to view the results of every simulation run. Implementing approaches and ideas developed in response to this goal, we demonstrate the analysis of a 15K run material fracturing study using Slycat, our ensemble analysis system.

Random matrix ensembles for many-body quantum systems

NASA Astrophysics Data System (ADS)

Vyas, Manan; Seligman, Thomas H.

2018-04-01

Classical random matrix ensembles were originally introduced in physics to approximate quantum many-particle nuclear interactions. However, there exists a plethora of quantum systems whose dynamics is explained in terms of few-particle (predom-inantly two-particle) interactions. The random matrix models incorporating the few-particle nature of interactions are known as embedded random matrix ensembles. In the present paper, we provide a brief overview of these two ensembles and illustrate how the embedded ensembles can be successfully used to study decoherence of a qubit interacting with an environment, both for fermionic and bosonic embedded ensembles. Numerical calculations show the dependence of decoherence on the nature of the environment.

The Vocal Jazz Ensemble: Systemic Interactions in the Creation of Three University Programs

ERIC Educational Resources Information Center

Letson, Stephanie Austin

2010-01-01

This study examined the experiences of three vocal jazz ensemble directors who influenced the field through their successful programs at the university level. These directors, Dr. Gene Aitken, Professor Larry Lapin, and Dr. Stephen Zegree, were chosen because of their national reputations as well as their program's longevity and success. The…

Reproducing multi-model ensemble average with Ensemble-averaged Reconstructed Forcings (ERF) in regional climate modeling

NASA Astrophysics Data System (ADS)

Erfanian, A.; Fomenko, L.; Wang, G.

2016-12-01

Multi-model ensemble (MME) average is considered the most reliable for simulating both present-day and future climates. It has been a primary reference for making conclusions in major coordinated studies i.e. IPCC Assessment Reports and CORDEX. The biases of individual models cancel out each other in MME average, enabling the ensemble mean to outperform individual members in simulating the mean climate. This enhancement however comes with tremendous computational cost, which is especially inhibiting for regional climate modeling as model uncertainties can originate from both RCMs and the driving GCMs. Here we propose the Ensemble-based Reconstructed Forcings (ERF) approach to regional climate modeling that achieves a similar level of bias reduction at a fraction of cost compared with the conventional MME approach. The new method constructs a single set of initial and boundary conditions (IBCs) by averaging the IBCs of multiple GCMs, and drives the RCM with this ensemble average of IBCs to conduct a single run. Using a regional climate model (RegCM4.3.4-CLM4.5), we tested the method over West Africa for multiple combination of (up to six) GCMs. Our results indicate that the performance of the ERF method is comparable to that of the MME average in simulating the mean climate. The bias reduction seen in ERF simulations is achieved by using more realistic IBCs in solving the system of equations underlying the RCM physics and dynamics. This endows the new method with a theoretical advantage in addition to reducing computational cost. The ERF output is an unaltered solution of the RCM as opposed to a climate state that might not be physically plausible due to the averaging of multiple solutions with the conventional MME approach. The ERF approach should be considered for use in major international efforts such as CORDEX. Key words: Multi-model ensemble, ensemble analysis, ERF, regional climate modeling

Real-time demonstration and evaluation of over-the-loop short to medium-range ensemble streamflow forecasting

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Newman, A. J.; Nijssen, B.; Clark, M. P.; Gangopadhyay, S.; Arnold, J. R.

2015-12-01

The US National Weather Service River Forecasting Centers are beginning to operationalize short range to medium range ensemble predictions that have been in development for several years. This practice contrasts with the traditional single-value forecast practice at these lead times not only because the ensemble forecasts offer a basis for quantifying forecast uncertainty, but also because the use of ensembles requires a greater degree of automation in the forecast workflow than is currently used. For instance, individual ensemble member forcings cannot (practically) be manually adjusted, a step not uncommon with the current single-value paradigm, thus the forecaster is required to adopt a more 'over-the-loop' role than before. The relative lack of experience among operational forecasters and forecast users (eg, water managers) in the US with over-the-loop approaches motivates the creation of a real-time demonstration and evaluation platform for exploring the potential of over-the-loop workflows to produce usable ensemble short-to-medium range forecasts, as well as long range predictions. We describe the development and early results of such an effort by a collaboration between NCAR and the two water agencies, the US Army Corps of Engineers and the US Bureau of Reclamation. Focusing on small to medium sized headwater basins around the US, and using multi-decade series of ensemble streamflow hindcasts, we also describe early results, assessing the skill of daily-updating, over-the-loop forecasts driven by a set of ensemble atmospheric outputs from the NCEP GEFS for lead times from 1-15 days.

Minimalist ensemble algorithms for genome-wide protein localization prediction.

PubMed

Lin, Jhih-Rong; Mondal, Ananda Mohan; Liu, Rong; Hu, Jianjun

2012-07-03

Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing ensemble algorithms. We applied the proposed minimalist logistic regression (LR) ensemble algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current ensemble algorithms. Experimental results showed that the minimalist ensemble algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current ensemble algorithms, which greatly reduces computational complexity and running time. It was found that the high performance ensemble algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our ensemble algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based ensemble algorithms, our classifier-based ensemble algorithms achieved much better performance without suffering from inclusion of too many individual predictors. We proposed a method for rational design

Minimalist ensemble algorithms for genome-wide protein localization prediction

PubMed Central

2012-01-01

Background Computational prediction of protein subcellular localization can greatly help to elucidate its functions. Despite the existence of dozens of protein localization prediction algorithms, the prediction accuracy and coverage are still low. Several ensemble algorithms have been proposed to improve the prediction performance, which usually include as many as 10 or more individual localization algorithms. However, their performance is still limited by the running complexity and redundancy among individual prediction algorithms. Results This paper proposed a novel method for rational design of minimalist ensemble algorithms for practical genome-wide protein subcellular localization prediction. The algorithm is based on combining a feature selection based filter and a logistic regression classifier. Using a novel concept of contribution scores, we analyzed issues of algorithm redundancy, consensus mistakes, and algorithm complementarity in designing ensemble algorithms. We applied the proposed minimalist logistic regression (LR) ensemble algorithm to two genome-wide datasets of Yeast and Human and compared its performance with current ensemble algorithms. Experimental results showed that the minimalist ensemble algorithm can achieve high prediction accuracy with only 1/3 to 1/2 of individual predictors of current ensemble algorithms, which greatly reduces computational complexity and running time. It was found that the high performance ensemble algorithms are usually composed of the predictors that together cover most of available features. Compared to the best individual predictor, our ensemble algorithm improved the prediction accuracy from AUC score of 0.558 to 0.707 for the Yeast dataset and from 0.628 to 0.646 for the Human dataset. Compared with popular weighted voting based ensemble algorithms, our classifier-based ensemble algorithms achieved much better performance without suffering from inclusion of too many individual predictors. Conclusions We

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post / National Weather Service National Centers for Environmental Prediction Environmental Modeling Center NOAA

Total probabilities of ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2017-04-01

Ensemble forecasting has a long history from meteorological modelling, as an indication of the uncertainty of the forecasts. However, it is necessary to calibrate and post-process the ensembles as the they often exhibit both bias and dispersion errors. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters varying in space and time, while giving a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, which makes it unsuitable for our purpose. Our post-processing method of the ensembles is developed in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu), where we are making forecasts for whole Europe, and based on observations from around 700 catchments. As the target is flood forecasting, we are also more interested in improving the forecast skill for high-flows rather than in a good prediction of the entire flow regime. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different meteorological forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to estimate the total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but we are adding a spatial penalty in the calibration process to force a spatial correlation of the parameters. The penalty takes

Modality-Driven Classification and Visualization of Ensemble Variance

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

Bensema, Kevin; Gosink, Luke; Obermaier, Harald

Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no informationmore » about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.« less

Hispanic Folk Arts and the Environment: An Interdisciplinary Curriculum Guide. A New Mexican Perspective.

ERIC Educational Resources Information Center

Lopez, Alejandro

This interdisciplinary, bilingual curriculum resource, contains a 29-minute videotape program, 20 colorplate posters, and a curriculum guide. The resource presents an examination of the folklife and folklore expressions of the Hispanic people of New Mexico. The focus of the curriculum is the relationship of survival-based folk activities to the…

Simulation studies of the fidelity of biomolecular structure ensemble recreation

NASA Astrophysics Data System (ADS)

Lätzer, Joachim; Eastwood, Michael P.; Wolynes, Peter G.

2006-12-01

We examine the ability of Bayesian methods to recreate structural ensembles for partially folded molecules from averaged data. Specifically we test the ability of various algorithms to recreate different transition state ensembles for folding proteins using a multiple replica simulation algorithm using input from "gold standard" reference ensembles that were first generated with a Gō-like Hamiltonian having nonpairwise additive terms. A set of low resolution data, which function as the "experimental" ϕ values, were first constructed from this reference ensemble. The resulting ϕ values were then treated as one would treat laboratory experimental data and were used as input in the replica reconstruction algorithm. The resulting ensembles of structures obtained by the replica algorithm were compared to the gold standard reference ensemble, from which those "data" were, in fact, obtained. It is found that for a unimodal transition state ensemble with a low barrier, the multiple replica algorithm does recreate the reference ensemble fairly successfully when no experimental error is assumed. The Kolmogorov-Smirnov test as well as principal component analysis show that the overlap of the recovered and reference ensembles is significantly enhanced when multiple replicas are used. Reduction of the multiple replica ensembles by clustering successfully yields subensembles with close similarity to the reference ensembles. On the other hand, for a high barrier transition state with two distinct transition state ensembles, the single replica algorithm only samples a few structures of one of the reference ensemble basins. This is due to the fact that the ϕ values are intrinsically ensemble averaged quantities. The replica algorithm with multiple copies does sample both reference ensemble basins. In contrast to the single replica case, the multiple replicas are constrained to reproduce the average ϕ values, but allow fluctuations in ϕ for each individual copy. These

Evaluating Alignment of Shapes by Ensemble Visualization

PubMed Central

Raj, Mukund; Mirzargar, Mahsa; Preston, J. Samuel; Kirby, Robert M.; Whitaker, Ross T.

2016-01-01

The visualization of variability in surfaces embedded in 3D, which is a type of ensemble uncertainty visualization, provides a means of understanding the underlying distribution of a collection or ensemble of surfaces. Although ensemble visualization for isosurfaces has been described in the literature, we conduct an expert-based evaluation of various ensemble visualization techniques in a particular medical imaging application: the construction of atlases or templates from a population of images. In this work, we extend contour boxplot to 3D, allowing us to evaluate it against an enumeration-style visualization of the ensemble members and other conventional visualizations used by atlas builders, namely examining the atlas image and the corresponding images/data provided as part of the construction process. We present feedback from domain experts on the efficacy of contour boxplot compared to other modalities when used as part of the atlas construction and analysis stages of their work. PMID:26186768

Bioactive focus in conformational ensembles: a pluralistic approach

NASA Astrophysics Data System (ADS)

Habgood, Matthew

2017-12-01

Computational generation of conformational ensembles is key to contemporary drug design. Selecting the members of the ensemble that will approximate the conformation most likely to bind to a desired target (the bioactive conformation) is difficult, given that the potential energy usually used to generate and rank the ensemble is a notoriously poor discriminator between bioactive and non-bioactive conformations. In this study an approach to generating a focused ensemble is proposed in which each conformation is assigned multiple rankings based not just on potential energy but also on solvation energy, hydrophobic or hydrophilic interaction energy, radius of gyration, and on a statistical potential derived from Cambridge Structural Database data. The best ranked structures derived from each system are then assembled into a new ensemble that is shown to be better focused on bioactive conformations. This pluralistic approach is tested on ensembles generated by the Molecular Operating Environment's Low Mode Molecular Dynamics module, and by the Cambridge Crystallographic Data Centre's conformation generator software.

Entropy of spatial network ensembles

NASA Astrophysics Data System (ADS)

Coon, Justin P.; Dettmann, Carl P.; Georgiou, Orestis

2018-04-01

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly in space and links formed independently between pairs of nodes with probability given by a specified function (the "pair connection function") of their mutual distance. We consider the general case where randomness arises in node positions as well as pairwise connections (i.e., for a given pair distance, the corresponding edge state is a random variable). Classical random geometric graph and exponential graph models can be recovered in certain limits. We derive a simple bound for the entropy of a spatial network ensemble and calculate the conditional entropy of an ensemble given the node location distribution for hard and soft (probabilistic) pair connection functions. Under this formalism, we derive the connection function that yields maximum entropy under general constraints. Finally, we apply our analytical framework to study two practical examples: ad hoc wireless networks and the US flight network. Through the study of these examples, we illustrate that both exhibit properties that are indicative of nearly maximally entropic ensembles.

Ensemble Weight Enumerators for Protograph LDPC Codes

NASA Technical Reports Server (NTRS)

Divsalar, Dariush

2006-01-01

Recently LDPC codes with projected graph, or protograph structures have been proposed. In this paper, finite length ensemble weight enumerators for LDPC codes with protograph structures are obtained. Asymptotic results are derived as the block size goes to infinity. In particular we are interested in obtaining ensemble average weight enumerators for protograph LDPC codes which have minimum distance that grows linearly with block size. As with irregular ensembles, linear minimum distance property is sensitive to the proportion of degree-2 variable nodes. In this paper the derived results on ensemble weight enumerators show that linear minimum distance condition on degree distribution of unstructured irregular LDPC codes is a sufficient but not a necessary condition for protograph LDPC codes.

Total probabilities of ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2016-04-01

Ensemble forecasting has for a long time been used as a method in meteorological modelling to indicate the uncertainty of the forecasts. However, as the ensembles often exhibit both bias and dispersion errors, it is necessary to calibrate and post-process them. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters which are different in space and time, but still can give a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, and cannot directly be regionalized in the way we would like, so we suggest a different path below. The target of our work is to create a mean forecast with uncertainty bounds for a large number of locations in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu) We are therefore more interested in improving the forecast skill for high-flows rather than the forecast skill of lower runoff levels. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to find a total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but assuring that they have some spatial correlation, by adding a spatial penalty in the calibration process. This can in some cases have a slight negative

In the Pause and Listening to the Little People: A Folk Healer's Journey

ERIC Educational Resources Information Center

Robbins, Rockey; Hong, Ji; Jennings, Aaron M.

2012-01-01

This article employs a qualitative case study approach to describe the views and perspectives of a folk healer (White Bear) regarding spiritual healing. White Bear argues for a mobile, in-the-moment form of diagnosis and a "pause," in which the mind ceases to tyrannize and the healer is no longer absorbed in his or her emotions. He contends that a…

An Analysis of Culturalism in Latino Mental Health: Folk Medicine as a Case in Point.

ERIC Educational Resources Information Center

De La Cancela, Victor; Martinez, Iris Zavala

1983-01-01

Identifies limitations of culturalist perspective often advocated by Latino mental health workers outlines folk healing practices they favor. Notes that culturalist perspective suffers from ahistorical/asocial/static conceptualization, and lacks analysis of class/sex/structural dimensions of so-called cultural expressions. Calls for recognition of…

Ensembl BioMarts: a hub for data retrieval across taxonomic space.

PubMed

Kinsella, Rhoda J; Kähäri, Andreas; Haider, Syed; Zamora, Jorge; Proctor, Glenn; Spudich, Giulietta; Almeida-King, Jeff; Staines, Daniel; Derwent, Paul; Kerhornou, Arnaud; Kersey, Paul; Flicek, Paul

2011-01-01

For a number of years the BioMart data warehousing system has proven to be a valuable resource for scientists seeking a fast and versatile means of accessing the growing volume of genomic data provided by the Ensembl project. The launch of the Ensembl Genomes project in 2009 complemented the Ensembl project by utilizing the same visualization, interactive and programming tools to provide users with a means for accessing genome data from a further five domains: protists, bacteria, metazoa, plants and fungi. The Ensembl and Ensembl Genomes BioMarts provide a point of access to the high-quality gene annotation, variation data, functional and regulatory annotation and evolutionary relationships from genomes spanning the taxonomic space. This article aims to give a comprehensive overview of the Ensembl and Ensembl Genomes BioMarts as well as some useful examples and a description of current data content and future objectives. Database URLs: http://www.ensembl.org/biomart/martview/; http://metazoa.ensembl.org/biomart/martview/; http://plants.ensembl.org/biomart/martview/; http://protists.ensembl.org/biomart/martview/; http://fungi.ensembl.org/biomart/martview/; http://bacteria.ensembl.org/biomart/martview/.

Worshipping Satan: Witchcraft and Folk Superstitions in Massachusetts and New France 1692 to 1760.

ERIC Educational Resources Information Center

Bennett, Paul W.

1990-01-01

Discusses the Salem witchcraft trials as a reflection of the social and moral values of colonial Massachusetts and New France. Traces the history of the trials. Describes other instances of witchcraft and folk superstitions during that same historical period. Provides primary sources of a picture, map, and excerpts from letters pertaining to the…

Understanding, Experiencing, and Appreciating the Arts: Folk Pedagogy in Two Elementary Schools in Taiwan

ERIC Educational Resources Information Center

Chen, Yu-Ting; Walsh, Daniel J.

2008-01-01

Drawing on Bruner's notion of folk pedagogy, this research explores how Chinese aesthetic education is perceived and valued at two elementary schools in Taiwan. Using qualitative methods, the research explores how arts teachers guide children to experience arts through the arts curricula in school and the local culture. The study reveals that the…

Drawing from the Well. Oral History and Folk Arts in the Classroom and Community.

ERIC Educational Resources Information Center

Silnutzer, Randi, Ed.; Watrous, Beth Eildin, Ed.

Each chapter of this document describes a different project and approach for introducing students (elementary to high school) to oral history and folk arts. All chapters use a standard format in which a general overview of the project, describing themes, philosophies, and methods are followed by sample lesson plans, teacher guidelines, and student…

Application of an Ensemble Smoother to Precipitation Assimilation

NASA Technical Reports Server (NTRS)

Zhang, Sara; Zupanski, Dusanka; Hou, Arthur; Zupanski, Milija

2008-01-01

Assimilation of precipitation in a global modeling system poses a special challenge in that the observation operators for precipitation processes are highly nonlinear. In the variational approach, substantial development work and model simplifications are required to include precipitation-related physical processes in the tangent linear model and its adjoint. An ensemble based data assimilation algorithm "Maximum Likelihood Ensemble Smoother (MLES)" has been developed to explore the ensemble representation of the precipitation observation operator with nonlinear convection and large-scale moist physics. An ensemble assimilation system based on the NASA GEOS-5 GCM has been constructed to assimilate satellite precipitation data within the MLES framework. The configuration of the smoother takes the time dimension into account for the relationship between state variables and observable rainfall. The full nonlinear forward model ensembles are used to represent components involving the observation operator and its transpose. Several assimilation experiments using satellite precipitation observations have been carried out to investigate the effectiveness of the ensemble representation of the nonlinear observation operator and the data impact of assimilating rain retrievals from the TMI and SSM/I sensors. Preliminary results show that this ensemble assimilation approach is capable of extracting information from nonlinear observations to improve the analysis and forecast if ensemble size is adequate, and a suitable localization scheme is applied. In addition to a dynamically consistent precipitation analysis, the assimilation system produces a statistical estimate of the analysis uncertainty.

Quantifying Uncertainty in Flood Inundation Mapping Using Streamflow Ensembles and Multiple Hydraulic Modeling Techniques

NASA Astrophysics Data System (ADS)

Hosseiny, S. M. H.; Zarzar, C.; Gomez, M.; Siddique, R.; Smith, V.; Mejia, A.; Demir, I.

2016-12-01

The National Water Model (NWM) provides a platform for operationalize nationwide flood inundation forecasting and mapping. The ability to model flood inundation on a national scale will provide invaluable information to decision makers and local emergency officials. Often, forecast products use deterministic model output to provide a visual representation of a single inundation scenario, which is subject to uncertainty from various sources. While this provides a straightforward representation of the potential inundation, the inherent uncertainty associated with the model output should be considered to optimize this tool for decision making support. The goal of this study is to produce ensembles of future flood inundation conditions (i.e. extent, depth, and velocity) to spatially quantify and visually assess uncertainties associated with the predicted flood inundation maps. The setting for this study is located in a highly urbanized watershed along the Darby Creek in Pennsylvania. A forecasting framework coupling the NWM with multiple hydraulic models was developed to produce a suite ensembles of future flood inundation predictions. Time lagged ensembles from the NWM short range forecasts were used to account for uncertainty associated with the hydrologic forecasts. The forecasts from the NWM were input to iRIC and HEC-RAS two-dimensional software packages, from which water extent, depth, and flow velocity were output. Quantifying the agreement between output ensembles for each forecast grid provided the uncertainty metrics for predicted flood water inundation extent, depth, and flow velocity. For visualization, a series of flood maps that display flood extent, water depth, and flow velocity along with the underlying uncertainty associated with each of the forecasted variables were produced. The results from this study demonstrate the potential to incorporate and visualize model uncertainties in flood inundation maps in order to identify the high flood risk zones.

Improving land resource evaluation using fuzzy neural network ensembles

USGS Publications Warehouse

Xue, Yue-Ju; HU, Y.-M.; Liu, S.-G.; YANG, J.-F.; CHEN, Q.-C.; BAO, S.-T.

2007-01-01

Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts' experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require grading the evaluation factors into categorical indexes and could evaluate land resources by using the three kinds of attribute values directly. A fuzzy back propagation neural network (BPNN), a fuzzy radial basis function neural network (RBFNN), a fuzzy BPNN ensemble, and a fuzzy RBFNN ensemble were used to evaluate the land resources in Guangdong Province. The evaluation results by using the fuzzy BPNN ensemble and the fuzzy RBFNN ensemble were much better than those by using the single fuzzy BPNN and the single fuzzy RBFNN, and the error rate of the single fuzzy RBFNN or fuzzy RBFNN ensemble was lower than that of the single fuzzy BPNN or fuzzy BPNN ensemble, respectively. By using the fuzzy neural network ensembles, the validity of land resource evaluation was improved and reliance on land evaluators' experiences was considerably reduced. ?? 2007 Soil Science Society of China.

Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

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

Man, Jun; Zhang, Jiangjiang; Li, Weixuan

2016-10-01

The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees ofmore » freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.« less

Arranged Bursa Folk Songs for Fourhands Piano and Their Practice in Music Education Departments

ERIC Educational Resources Information Center

Demirci, Sirin Akbulut

2016-01-01

The article presents the results of a study carried out within the scope of a project entitled, "Arranged Bursa Folk Songs for Fourhands Piano Extended Piano Techniques and Teaching in Music Education Departments." It is number KUAP (E)-2014/28 of the Uludag University Scientific Research Projects Unit and was supported by the Bursa…

Examining the Relation between Social Values Perception and Moral Maturity Level of Folk Dancers

ERIC Educational Resources Information Center

Dogan, Pinar Karacan

2018-01-01

The purpose of the present study is to examine the relation between social values perceptions and moral maturity levels of folk dancers, and evaluate this relation in terms of some variables. The relational screening model was used in the study. The "Multi-dimensional Social Values Scale," which was developed by Bolat (2013), and the…

Fine-Tuning Your Ensemble's Jazz Style.

ERIC Educational Resources Information Center

Garcia, Antonio J.

1991-01-01

Proposes instructional strategies for directors of jazz groups, including guidelines for developing of skills necessary for good performance. Includes effective methods for positive changes in ensemble style. Addresses jazz group problems such as beat, tempo, staying in tune, wind power, and solo/ensemble lines. Discusses percussionists, bassists,…

Thermodynamic-ensemble independence of solvation free energy.

PubMed

Chong, Song-Ho; Ham, Sihyun

2015-02-10

Solvation free energy is the fundamental thermodynamic quantity in solution chemistry. Recently, it has been suggested that the partial molar volume correction is necessary to convert the solvation free energy determined in different thermodynamic ensembles. Here, we demonstrate ensemble-independence of the solvation free energy on general thermodynamic grounds. Theoretical estimates of the solvation free energy based on the canonical or grand-canonical ensemble are pertinent to experiments carried out under constant pressure without any conversion.

Long-range interacting systems in the unconstrained ensemble.

PubMed

Latella, Ivan; Pérez-Madrid, Agustín; Campa, Alessandro; Casetti, Lapo; Ruffo, Stefano

2017-01-01

Completely open systems can exchange heat, work, and matter with the environment. While energy, volume, and number of particles fluctuate under completely open conditions, the equilibrium states of the system, if they exist, can be specified using the temperature, pressure, and chemical potential as control parameters. The unconstrained ensemble is the statistical ensemble describing completely open systems and the replica energy is the appropriate free energy for these control parameters from which the thermodynamics must be derived. It turns out that macroscopic systems with short-range interactions cannot attain equilibrium configurations in the unconstrained ensemble, since temperature, pressure, and chemical potential cannot be taken as a set of independent variables in this case. In contrast, we show that systems with long-range interactions can reach states of thermodynamic equilibrium in the unconstrained ensemble. To illustrate this fact, we consider a modification of the Thirring model and compare the unconstrained ensemble with the canonical and grand-canonical ones: The more the ensemble is constrained by fixing the volume or number of particles, the larger the space of parameters defining the equilibrium configurations.

Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction.

PubMed

Baker, Christopher M; Gordon, Ascelin; Bode, Michael

2017-04-01

Introducing a new or extirpated species to an ecosystem is risky, and managers need quantitative methods that can predict the consequences for the recipient ecosystem. Proponents of keystone predator reintroductions commonly argue that the presence of the predator will restore ecosystem function, but this has not always been the case, and mathematical modeling has an important role to play in predicting how reintroductions will likely play out. We devised an ensemble modeling method that integrates species interaction networks and dynamic community simulations and used it to describe the range of plausible consequences of 2 keystone-predator reintroductions: wolves (Canis lupus) to Yellowstone National Park and dingoes (Canis dingo) to a national park in Australia. Although previous methods for predicting ecosystem responses to such interventions focused on predicting changes around a given equilibrium, we used Lotka-Volterra equations to predict changing abundances through time. We applied our method to interaction networks for wolves in Yellowstone National Park and for dingoes in Australia. Our model replicated the observed dynamics in Yellowstone National Park and produced a larger range of potential outcomes for the dingo network. However, we also found that changes in small vertebrates or invertebrates gave a good indication about the potential future state of the system. Our method allowed us to predict when the systems were far from equilibrium. Our results showed that the method can also be used to predict which species may increase or decrease following a reintroduction and can identify species that are important to monitor (i.e., species whose changes in abundance give extra insight into broad changes in the system). Ensemble ecosystem modeling can also be applied to assess the ecosystem-wide implications of other types of interventions including assisted migration, biocontrol, and invasive species eradication. © 2016 Society for Conservation Biology.

Beyond food and medicine, but necessary for life, too: other folk plant uses in several territories of Catalonia and the Balearic Islands.

PubMed

Gras, Airy; Garnatje, Teresa; Bonet, M Àngels; Carrió, Esperança; Mayans, Marina; Parada, Montse; Rigat, Montse; Vallès, Joan

2016-06-17

Ethnobotanical academic research, particularly in European industrialised countries, has been, and is, mostly focused on folk uses of food and medicinal plants. Nevertheless, other uses, as may well be supposed, account for a significant portion of these folk uses. In the Catalan linguistic domain, a considerable amount of ethnobotanical work has been produced, but to date almost nothing has been published on these other plant uses. We basically used the method of semistructured interviews to collect data on names, knowledge and use of plants in the above-mentioned fields from 759 informants in three Catalonian (Alt Empordà, Montseny and Ripollès) and two Balearic (Formentera and Mallorca) areas. We identified the plants quoted by the informants and prepared herbarium vouchers. We analysed and compared the results obtained. Information has been collected on 401 genera, 552 species, 81 subspecies and four varieties, belonging to 122 families, totalling 4137 use reports for popular non-food and non-medicinal uses (classified in 14 modalities), and designated with 1303 folk Catalan names. The informant consensus factor is 0.87, accounting for a consistent and robust dataset. Contrarily to what could be thought a priori, and irrespective of the fact that some uses are declining or changing, non-medicinal and non-food folk plant uses strongly persist in the territories considered, are highly considered by their practitioners, and may even imply some economic revenues.

Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system

NASA Astrophysics Data System (ADS)

Sharma, Sanjib; Siddique, Ridwan; Reed, Seann; Ahnert, Peter; Mendoza, Pablo; Mejia, Alfonso

2018-03-01

The relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1-7) are investigated. For this purpose, a regional hydrologic ensemble prediction system (RHEPS) is developed and implemented. The RHEPS is comprised of the following components: (i) hydrometeorological observations (multisensor precipitation estimates, gridded surface temperature, and gauged streamflow); (ii) weather ensemble forecasts (precipitation and near-surface temperature) from the National Centers for Environmental Prediction 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2); (iii) NOAA's Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM); (iv) heteroscedastic censored logistic regression (HCLR) as the statistical preprocessor; (v) two statistical postprocessors, an autoregressive model with a single exogenous variable (ARX(1,1)) and quantile regression (QR); and (vi) a comprehensive verification strategy. To implement the RHEPS, 1 to 7 days weather forecasts from the GEFSRv2 are used to force HL-RDHM and generate raw ensemble streamflow forecasts. Forecasting experiments are conducted in four nested basins in the US Middle Atlantic region, ranging in size from 381 to 12 362 km2. Results show that the HCLR preprocessed ensemble precipitation forecasts have greater skill than the raw forecasts. These improvements are more noticeable in the warm season at the longer lead times (> 3 days). Both postprocessors, ARX(1,1) and QR, show gains in skill relative to the raw ensemble streamflow forecasts, particularly in the cool season, but QR outperforms ARX(1,1). The scenarios that implement preprocessing and postprocessing separately tend to perform similarly, although the postprocessing-alone scenario is often more effective. The scenario involving both preprocessing and postprocessing consistently outperforms the other scenarios. In some cases

Making decisions based on an imperfect ensemble of climate simulators: strategies and future directions

NASA Astrophysics Data System (ADS)

Sanderson, B. M.

2017-12-01

The CMIP ensembles represent the most comprehensive source of information available to decision-makers for climate adaptation, yet it is clear that there are fundamental limitations in our ability to treat the ensemble as an unbiased sample of possible future climate trajectories. There is considerable evidence that models are not independent, and increasing complexity and resolution combined with computational constraints prevent a thorough exploration of parametric uncertainty or internal variability. Although more data than ever is available for calibration, the optimization of each model is influenced by institutional priorities, historical precedent and available resources. The resulting ensemble thus represents a miscellany of climate simulators which defy traditional statistical interpretation. Models are in some cases interdependent, but are sufficiently complex that the degree of interdependency is conditional on the application. Configurations have been updated using available observations to some degree, but not in a consistent or easily identifiable fashion. This means that the ensemble cannot be viewed as a true posterior distribution updated by available data, but nor can observational data alone be used to assess individual model likelihood. We assess recent literature for combining projections from an imperfect ensemble of climate simulators. Beginning with our published methodology for addressing model interdependency and skill in the weighting scheme for the 4th US National Climate Assessment, we consider strategies for incorporating process-based constraints on future response, perturbed parameter experiments and multi-model output into an integrated framework. We focus on a number of guiding questions: Is the traditional framework of confidence in projections inferred from model agreement leading to biased or misleading conclusions? Can the benefits of upweighting skillful models be reconciled with the increased risk of truth lying outside the

Traditional folk beliefs on epilepsy in Norway and Sweden.

PubMed

Tuft, Mia; Nakken, Karl O; Kverndokk, Kyrre

2017-06-01

In Norway and Sweden, epilepsy has for many centuries been considered a strange and mysterious disease. The explanations of its causes have been many and imaginative. One being that epilepsy was caused by the hidden people inhabiting the woods and the mountains. To avoid the disease, these hidden people should not be annoyed. One commonly used treatment principle was to try to place the disease back to the ground, or passing the diseased through a hole or an opening in the nature. Fresh blood from criminals was also considered to have strong antiepileptic properties. In the Scandinavian countries, some of these folk beliefs have been very tenacious. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of the mosquito biting deterrent constituents from the Indian folk remedy plant Jatropha curcas

USDA-ARS?s Scientific Manuscript database

An investigation of the Indian folk remedy plant, Jatropha curcas, was performed to specifically identify the constituents responsible for the mosquito biting deterrent activity of the oil as a whole. Jatropha curcas seed oil is burned in oil lamps in India and part of Africa to repel biting insect...

Indigenous knowledge of folk medicines among tribal minorities in Khyber Pakhtunkhwa, northwestern Pakistan.

PubMed

Sher, Hassan; Aldosari, Ali; Ali, Ahmad; de Boer, Hugo J

2015-05-26

Mapping ethnomedicinal plants and associated indigenous knowledge of folk medicines can provide a comprehensive overview of individual herbs employed in health care. Reliance on medicinal plants in remote parts of northern Pakistan is high, especially among women, but no research has investigated specifically which plants are used. This study investigated indigenous knowledge of folk medicines among tribal minorities in selected sites in upper Swat, Buner and Chitral Districts in Khyber Pakhtunkhwa Province. Interviews were conducted with gender-specific focus groups using questionnaires and standardized data sheets, followed by forest walks in each of the visited areas. General medicinal herb use, preparations, storage, marketing and collection habits for each gender group were ascertained from the questionnaires. In total 168 women and 390 men were interviewed and provided information on 127 different shared medicinal species. Species use consensus among the informants ranged from 2.3% to 83.3%, with Cynodon dactylon, Avena sativa, Celtis australis, Datura stramonium, Solanum nigrum, Skimmia laureola, Spiraea nervosa, Ziziphus jujuba, Rumex hastatus, Plantago lanceolata, Lathyrus aphaca and Ficus palmata having the highest reported consensus. The survey also revealed that a number of medicinal species were exploited by the community for both marketing and personal use, and many of these species were reported as being rare, vulnerable or even endangered. The results revealed that women in all the three districts were important custodians of medicinal plant knowledge, but elder women in general and the women from Buner district in particular had a superior understanding of folk medicine. The forest walks revealed that women׳s traditional medicinal knowledge was based on a more limited diversity of plant species. People in tribal communities have an expressed interest in learning efficient techniques for medicinal plant collection, preparation, storage and

Skill of Ensemble Seasonal Probability Forecasts

NASA Astrophysics Data System (ADS)

Smith, Leonard A.; Binter, Roman; Du, Hailiang; Niehoerster, Falk

2010-05-01

In operational forecasting, the computational complexity of large simulation models is, ideally, justified by enhanced performance over simpler models. We will consider probability forecasts and contrast the skill of ENSEMBLES-based seasonal probability forecasts of interest to the finance sector (specifically temperature forecasts for Nino 3.4 and the Atlantic Main Development Region (MDR)). The ENSEMBLES model simulations will be contrasted against forecasts from statistical models based on the observations (climatological distributions) and empirical dynamics based on the observations but conditioned on the current state (dynamical climatology). For some start dates, individual ENSEMBLES models yield significant skill even at a lead-time of 14 months. The nature of this skill is discussed, and chances of application are noted. Questions surrounding the interpretation of probability forecasts based on these multi-model ensemble simulations are then considered; the distributions considered are formed by kernel dressing the ensemble and blending with the climatology. The sources of apparent (RMS) skill in distributions based on multi-model simulations is discussed, and it is demonstrated that the inclusion of "zero-skill" models in the long range can improve Root-Mean-Square-Error scores, casting some doubt on the common justification for the claim that all models should be included in forming an operational probability forecast. It is argued that the rational response varies with lead time.

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Gui-Long

2001-01-01

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Integrating Professional and Folk Models of HIV Risk: YMSM's Perceptions of High-Risk Sex

ERIC Educational Resources Information Center

Kubicek, Katrina; Carpineto, Julie; McDavitt, Bryce; Weiss, George; Iverson, Ellen F.; Au, Chi-Wai; Kerrone, Dustin; Martinez, Miguel; Kipke, Michele D.

2008-01-01

Risks associated with HIV are well documented in research literature. Although a great deal has been written about high-risk sex, little research has been conducted to examine how young men who have sex with men (YMSM) perceive and define high-risk sexual behavior. In this study, we compare the "professional" and "folk" models of HIV risk based on…

A multiphysical ensemble system of numerical snow modelling

NASA Astrophysics Data System (ADS)

Lafaysse, Matthieu; Cluzet, Bertrand; Dumont, Marie; Lejeune, Yves; Vionnet, Vincent; Morin, Samuel

2017-05-01

Physically based multilayer snowpack models suffer from various modelling errors. To represent these errors, we built the new multiphysical ensemble system ESCROC (Ensemble System Crocus) by implementing new representations of different physical processes in the deterministic coupled multilayer ground/snowpack model SURFEX/ISBA/Crocus. This ensemble was driven and evaluated at Col de Porte (1325 m a.s.l., French alps) over 18 years with a high-quality meteorological and snow data set. A total number of 7776 simulations were evaluated separately, accounting for the uncertainties of evaluation data. The ability of the ensemble to capture the uncertainty associated to modelling errors is assessed for snow depth, snow water equivalent, bulk density, albedo and surface temperature. Different sub-ensembles of the ESCROC system were studied with probabilistic tools to compare their performance. Results show that optimal members of the ESCROC system are able to explain more than half of the total simulation errors. Integrating members with biases exceeding the range corresponding to observational uncertainty is necessary to obtain an optimal dispersion, but this issue can also be a consequence of the fact that meteorological forcing uncertainties were not accounted for. The ESCROC system promises the integration of numerical snow-modelling errors in ensemble forecasting and ensemble assimilation systems in support of avalanche hazard forecasting and other snowpack-modelling applications.

Bidirectional Modulation of Intrinsic Excitability in Rat Prelimbic Cortex Neuronal Ensembles and Non-Ensembles after Operant Learning.

PubMed

Whitaker, Leslie R; Warren, Brandon L; Venniro, Marco; Harte, Tyler C; McPherson, Kylie B; Beidel, Jennifer; Bossert, Jennifer M; Shaham, Yavin; Bonci, Antonello; Hope, Bruce T

2017-09-06

Learned associations between environmental stimuli and rewards drive goal-directed learning and motivated behavior. These memories are thought to be encoded by alterations within specific patterns of sparsely distributed neurons called neuronal ensembles that are activated selectively by reward-predictive stimuli. Here, we use the Fos promoter to identify strongly activated neuronal ensembles in rat prelimbic cortex (PLC) and assess altered intrinsic excitability after 10 d of operant food self-administration training (1 h/d). First, we used the Daun02 inactivation procedure in male FosLacZ-transgenic rats to ablate selectively Fos-expressing PLC neurons that were active during operant food self-administration. Selective ablation of these neurons decreased food seeking. We then used male FosGFP-transgenic rats to assess selective alterations of intrinsic excitability in Fos-expressing neuronal ensembles (FosGFP + ) that were activated during food self-administration and compared these with alterations in less activated non-ensemble neurons (FosGFP - ). Using whole-cell recordings of layer V pyramidal neurons in an ex vivo brain slice preparation, we found that operant self-administration increased excitability of FosGFP + neurons and decreased excitability of FosGFP - neurons. Increased excitability of FosGFP + neurons was driven by increased steady-state input resistance. Decreased excitability of FosGFP - neurons was driven by increased contribution of small-conductance calcium-activated potassium (SK) channels. Injections of the specific SK channel antagonist apamin into PLC increased Fos expression but had no effect on food seeking. Overall, operant learning increased intrinsic excitability of PLC Fos-expressing neuronal ensembles that play a role in food seeking but decreased intrinsic excitability of Fos - non-ensembles. SIGNIFICANCE STATEMENT Prefrontal cortex activity plays a critical role in operant learning, but the underlying cellular mechanisms are

Exploring the calibration of a wind forecast ensemble for energy applications

NASA Astrophysics Data System (ADS)

Heppelmann, Tobias; Ben Bouallegue, Zied; Theis, Susanne

2015-04-01

In the German research project EWeLiNE, Deutscher Wetterdienst (DWD) and Fraunhofer Institute for Wind Energy and Energy System Technology (IWES) are collaborating with three German Transmission System Operators (TSO) in order to provide the TSOs with improved probabilistic power forecasts. Probabilistic power forecasts are derived from probabilistic weather forecasts, themselves derived from ensemble prediction systems (EPS). Since the considered raw ensemble wind forecasts suffer from underdispersiveness and bias, calibration methods are developed for the correction of the model bias and the ensemble spread bias. The overall aim is to improve the ensemble forecasts such that the uncertainty of the possible weather deployment is depicted by the ensemble spread from the first forecast hours. Additionally, the ensemble members after calibration should remain physically consistent scenarios. We focus on probabilistic hourly wind forecasts with horizon of 21 h delivered by the convection permitting high-resolution ensemble system COSMO-DE-EPS which has become operational in 2012 at DWD. The ensemble consists of 20 ensemble members driven by four different global models. The model area includes whole Germany and parts of Central Europe with a horizontal resolution of 2.8 km and a vertical resolution of 50 model levels. For verification we use wind mast measurements around 100 m height that corresponds to the hub height of wind energy plants that belong to wind farms within the model area. Calibration of the ensemble forecasts can be performed by different statistical methods applied to the raw ensemble output. Here, we explore local bivariate Ensemble Model Output Statistics at individual sites and quantile regression with different predictors. Applying different methods, we already show an improvement of ensemble wind forecasts from COSMO-DE-EPS for energy applications. In addition, an ensemble copula coupling approach transfers the time-dependencies of the raw

Ideas for a pattern-oriented approach towards a VERA analysis ensemble

NASA Astrophysics Data System (ADS)

Gorgas, T.; Dorninger, M.

2010-09-01

Ideas for a pattern-oriented approach towards a VERA analysis ensemble For many applications in meteorology and especially for verification purposes it is important to have some information about the uncertainties of observation and analysis data. A high quality of these "reference data" is an absolute necessity as the uncertainties are reflected in verification measures. The VERA (Vienna Enhanced Resolution Analysis) scheme includes a sophisticated quality control tool which accounts for the correction of observational data and provides an estimation of the observation uncertainty. It is crucial for meteorologically and physically reliable analysis fields. VERA is based on a variational principle and does not need any first guess fields. It is therefore NWP model independent and can also be used as an unbiased reference for real time model verification. For downscaling purposes VERA uses an a priori knowledge on small-scale physical processes over complex terrain, the so called "fingerprint technique", which transfers information from rich to data sparse regions. The enhanced Joint D-PHASE and COPS data set forms the data base for the analysis ensemble study. For the WWRP projects D-PHASE and COPS a joint activity has been started to collect GTS and non-GTS data from the national and regional meteorological services in Central Europe for 2007. Data from more than 11.000 stations are available for high resolution analyses. The usage of random numbers as perturbations for ensemble experiments is a common approach in meteorology. In most implementations, like for NWP-model ensemble systems, the focus lies on error growth and propagation on the spatial and temporal scale. When defining errors in analysis fields we have to consider the fact that analyses are not time dependent and that no perturbation method aimed at temporal evolution is possible. Further, the method applied should respect two major sources of analysis errors: Observation errors AND analysis or

Folk Dance Pattern Recognition Over Depth Images Acquired via Kinect Sensor

NASA Astrophysics Data System (ADS)

Protopapadakis, E.; Grammatikopoulou, A.; Doulamis, A.; Grammalidis, N.

2017-02-01

The possibility of accurate recognition of folk dance patterns is investigated in this paper. System inputs are raw skeleton data, provided by a low cost sensor. In particular, data were obtained by monitoring three professional dancers, using a Kinect II sensor. A set of six traditional Greek dances (without their variations) consists the investigated data. A two-step process was adopted. At first, the most descriptive skeleton data were selected using a combination of density based and sparse modelling algorithms. Then, the representative data served as training set for a variety of classifiers.

Argumentation Based Joint Learning: A Novel Ensemble Learning Approach

PubMed Central

Xu, Junyi; Yao, Li; Li, Le

2015-01-01

Recently, ensemble learning methods have been widely used to improve classification performance in machine learning. In this paper, we present a novel ensemble learning method: argumentation based multi-agent joint learning (AMAJL), which integrates ideas from multi-agent argumentation, ensemble learning, and association rule mining. In AMAJL, argumentation technology is introduced as an ensemble strategy to integrate multiple base classifiers and generate a high performance ensemble classifier. We design an argumentation framework named Arena as a communication platform for knowledge integration. Through argumentation based joint learning, high quality individual knowledge can be extracted, and thus a refined global knowledge base can be generated and used independently for classification. We perform numerous experiments on multiple public datasets using AMAJL and other benchmark methods. The results demonstrate that our method can effectively extract high quality knowledge for ensemble classifier and improve the performance of classification. PMID:25966359

Regionalization of post-processed ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2016-05-01

For many years, meteorological models have been run with perturbated initial conditions or parameters to produce ensemble forecasts that are used as a proxy of the uncertainty of the forecasts. However, the ensembles are usually both biased (the mean is systematically too high or too low, compared with the observed weather), and has dispersion errors (the ensemble variance indicates a too low or too high confidence in the forecast, compared with the observed weather). The ensembles are therefore commonly post-processed to correct for these shortcomings. Here we look at one of these techniques, referred to as Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). Originally, the post-processing parameters were identified as a fixed set of parameters for a region. The application of our work is the European Flood Awareness System (http://www.efas.eu), where a distributed model is run with meteorological ensembles as input. We are therefore dealing with a considerably larger data set than previous analyses. We also want to regionalize the parameters themselves for other locations than the calibration gauges. The post-processing parameters are therefore estimated for each calibration station, but with a spatial penalty for deviations from neighbouring stations, depending on the expected semivariance between the calibration catchment and these stations. The estimated post-processed parameters can then be used for regionalization of the postprocessing parameters also for uncalibrated locations using top-kriging in the rtop-package (Skøien et al., 2006, 2014). We will show results from cross-validation of the methodology and although our interest is mainly in identifying exceedance probabilities for certain return levels, we will also show how the rtop package can be used for creating a set of post-processed ensembles through simulations.

Pauci ex tanto numero: reducing redundancy in multi-model ensembles

NASA Astrophysics Data System (ADS)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-02-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date no attempts in this direction are documented within the air quality (AQ) community, although the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared biases among models will determine a biased ensemble, making therefore essential the errors of the ensemble members to be independent so that bias can cancel out. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated) we discourage selecting the members of the ensemble simply on the basis of scores, that is, independence and skills need to be considered disjointly.

EnsembleGASVR: a novel ensemble method for classifying missense single nucleotide polymorphisms.

PubMed

Rapakoulia, Trisevgeni; Theofilatos, Konstantinos; Kleftogiannis, Dimitrios; Likothanasis, Spiros; Tsakalidis, Athanasios; Mavroudi, Seferina

2014-08-15

Single nucleotide polymorphisms (SNPs) are considered the most frequently occurring DNA sequence variations. Several computational methods have been proposed for the classification of missense SNPs to neutral and disease associated. However, existing computational approaches fail to select relevant features by choosing them arbitrarily without sufficient documentation. Moreover, they are limited to the problem of missing values, imbalance between the learning datasets and most of them do not support their predictions with confidence scores. To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a two-step algorithm, which in its first step applies a novel evolutionary embedded algorithm to locate close to optimal Support Vector Regression models. In its second step, these models are combined to extract a universal predictor, which is less prone to overfitting issues, systematizes the rebalancing of the learning sets and uses an internal approach for solving the missing values problem without loss of information. Confidence scores support all the predictions and the model becomes tunable by modifying the classification thresholds. An extensive study was performed for collecting the most relevant features for the problem of classifying SNPs, and a superset of 88 features was constructed. Experimental results show that the proposed framework outperforms well-known algorithms in terms of classification performance in the examined datasets. Finally, the proposed algorithmic framework was able to uncover the significant role of certain features such as the solvent accessibility feature, and the top-scored predictions were further validated by linking them with disease phenotypes. Datasets and codes are freely available on the Web at http://prlab.ceid.upatras.gr/EnsembleGASVR/dataset-codes.zip. All the required information about the article is available through http://prlab.ceid.upatras.gr/Ensemble

20060530 - Global Ensemble Upgrade - NWS ftp

Science.gov Websites

the NWS ftp server and to describe some changes to data locations described in the earlier message on .{YYYYMMDD}/ MAJOR PRODUCT CHANGES TO NCEP GLOBAL ENSEMBLE OUTPUT -- PLEASE READ CAREFULLY Starting with the 12 UTC cycle on 30 May 2006 NCEP Central Operations will implement changes to the global ensemble

Ensemble pharmacophore meets ensemble docking: a novel screening strategy for the identification of RIPK1 inhibitors

NASA Astrophysics Data System (ADS)

Fayaz, S. M.; Rajanikant, G. K.

2014-07-01

Programmed cell death has been a fascinating area of research since it throws new challenges and questions in spite of the tremendous ongoing research in this field. Recently, necroptosis, a programmed form of necrotic cell death, has been implicated in many diseases including neurological disorders. Receptor interacting serine/threonine protein kinase 1 (RIPK1) is an important regulatory protein involved in the necroptosis and inhibition of this protein is essential to stop necroptotic process and eventually cell death. Current structure-based virtual screening methods involve a wide range of strategies and recently, considering the multiple protein structures for pharmacophore extraction has been emphasized as a way to improve the outcome. However, using the pharmacophoric information completely during docking is very important. Further, in such methods, using the appropriate protein structures for docking is desirable. If not, potential compound hits, obtained through pharmacophore-based screening, may not have correct ranks and scores after docking. Therefore, a comprehensive integration of different ensemble methods is essential, which may provide better virtual screening results. In this study, dual ensemble screening, a novel computational strategy was used to identify diverse and potent inhibitors against RIPK1. All the pharmacophore features present in the binding site were captured using both the apo and holo protein structures and an ensemble pharmacophore was built by combining these features. This ensemble pharmacophore was employed in pharmacophore-based screening of ZINC database. The compound hits, thus obtained, were subjected to ensemble docking. The leads acquired through docking were further validated through feature evaluation and molecular dynamics simulation.

Live from Your Neighborhood: A National Study of Outdoor Arts Festivals. Volume Two: Seven Case Studies. Research Report #51

ERIC Educational Resources Information Center

Rosenstein, Carole

2010-01-01

This report complements a national survey of outdoor arts festivals (see "Live from Your Neighborhood: A National Study of Outdoor Arts Festivals, Volume One: Summary Report") by focusing on seven case study festivals: Houston International Festival; Piccolo Spoleto; Lowell Folk Festival; Santa Fe Indian Market; Chicago Jazz Festival;…

Pauci ex tanto numero: reduce redundancy in multi-model ensembles

NASA Astrophysics Data System (ADS)

Solazzo, E.; Riccio, A.; Kioutsioukis, I.; Galmarini, S.

2013-08-01

We explicitly address the fundamental issue of member diversity in multi-model ensembles. To date, no attempts in this direction have been documented within the air quality (AQ) community despite the extensive use of ensembles in this field. Common biases and redundancy are the two issues directly deriving from lack of independence, undermining the significance of a multi-model ensemble, and are the subject of this study. Shared, dependant biases among models do not cancel out but will instead determine a biased ensemble. Redundancy derives from having too large a portion of common variance among the members of the ensemble, producing overconfidence in the predictions and underestimation of the uncertainty. The two issues of common biases and redundancy are analysed in detail using the AQMEII ensemble of AQ model results for four air pollutants in two European regions. We show that models share large portions of bias and variance, extending well beyond those induced by common inputs. We make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble with the advantage of being poorly correlated. Selecting the members for generating skilful, non-redundant ensembles from such subsets proved, however, non-trivial. We propose and discuss various methods of member selection and rate the ensemble performance they produce. In most cases, the full ensemble is outscored by the reduced ones. We conclude that, although independence of outputs may not always guarantee enhancement of scores (but this depends upon the skill being investigated), we discourage selecting the members of the ensemble simply on the basis of scores; that is, independence and skills need to be considered disjointly.

The Road to DLCZ Protocol in Rubidium Ensemble

NASA Astrophysics Data System (ADS)

Li, Chang; Pu, Yunfei; Jiang, Nan; Chang, Wei; Zhang, Sheng; CenterQuantum Information, InstituteInterdisciplinary Information Sciences, Tsinghua Univ Team

2017-04-01

Quantum communication is the powerful approach achieving a fully secure information transferal. The DLCZ protocol ensures that photon linearly decays with transferring distance increasing, which improves the success potential and shortens the time to build up an entangled channel. Apart from that, it provides an advanced idea that building up a quantum internet based on different nodes connected to different sites and themselves. In our laboratory, three sets of laser-cooled Rubidium 87 ensemble have been built. Two of them serve as the single photon emitter, which generate the entanglement between ensemble and photon. What's more, crossed AODs are equipped to multiplex and demultiplex optical circuit so that ensemble is divided into 2 hundred of 2D sub-memory cells. And the third ensemble is used as quantum telecommunication, which converts 780nm photon into telecom-wavelength one. And we have been building double-MOT system, which provides more atoms in ensemble and larger optical density.

DART: New Research Using Ensemble Data Assimilation in Geophysical Models

NASA Astrophysics Data System (ADS)

Hoar, T. J.; Raeder, K.

2015-12-01

The Data Assimilation Research Testbed (DART) is a community facilityfor ensemble data assimilation developed and supported by the NationalCenter for Atmospheric Research. DART provides a comprehensive suite of software, documentation, and tutorials that can be used for ensemble data assimilation research, operations, and education. Scientists and software engineers at NCAR are available to support DART users who want to use existing DART products or develop their own applications. Current DART users range from university professors teaching data assimilation, to individual graduate students working with simple models, through national laboratories doing operational prediction with large state-of-the-art models. DART runs efficiently on many computational platforms ranging from laptops through thousands of cores on the newest supercomputers.This poster focuses on several recent research activities using DART with geophysical models.Using CAM/DART to understand whether OCO-2 Total Precipitable Water observations can be useful in numerical weather prediction.Impacts of the synergistic use of Infra-red CO retrievals (MOPITT, IASI) in CAM-CHEM/DART assimilations.Assimilation and Analysis of Observations of Amazonian Biomass Burning Emissions by MOPITT (aerosol optical depth), MODIS (carbon monoxide) and MISR (plume height).Long term evaluation of the chemical response of MOPITT-CO assimilation in CAM-CHEM/DART OSSEs for satellite planning and emission inversion capabilities.Improved forward observation operators for land models that have multiple land use/land cover segments in a single grid cell,Simulating mesoscale convective systems (MCSs) using a variable resolution, unstructured grid in the Model for Prediction Across Scales (MPAS) and DART.The mesoscale WRF+DART system generated an ensemble of year-long, real-time initializations of a convection allowing model over the United States.Constraining WACCM with observations in the tropical band (30S-30N) using DART

Quantum Gibbs ensemble Monte Carlo

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

Fantoni, Riccardo, E-mail: rfantoni@ts.infn.it; Moroni, Saverio, E-mail: moroni@democritos.it

We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs ensemble Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs ensemble Monte Carlo to include quantum effects, our scheme is viable even for systems with strong quantum delocalization in the degenerate regime of temperature. This is demonstrated by an illustrative application to the gas-superfluid transition of {sup 4}He in two dimensions.

Evaluation of Multi-Model Ensemble System for Seasonal and Monthly Prediction

NASA Astrophysics Data System (ADS)

Zhang, Q.; Van den Dool, H. M.

2013-12-01

Since August 2011, the realtime seasonal forecasts of U.S. National Multi-Model Ensemble (NMME) have been made on 8th of each month by NCEP Climate Prediction Center (CPC). During the first year, the participating models were NCEP/CFSv1&2, GFDL/CM2.2, NCAR/U.Miami/COLA/CCSM3, NASA/GEOS5, IRI/ ECHAM-a & ECHAM-f for the realtime NMME forecast. The Canadian Meteorological Center CanCM3 and CM4 replaced the CFSv1 and IRI's models in the second year. The NMME team at CPC collects three variables, including precipitation, 2-meter temperature and sea surface temperature from each modeling center on a 1x1 global grid, removes systematic errors, makes the grand ensemble mean with equal weight for each model and constructs a probability forecast with equal weight for each member. The team then provides the NMME forecast to the operational CPC forecaster responsible for the seasonal and monthly outlook each month. Verification of the seasonal and monthly prediction from NMME is conducted by calculating the anomaly correlation (AC) from the 30-year hindcasts (1982-2011) of individual model and NMME ensemble. The motivation of this study is to provide skill benchmarks for future improvements of the NMME seasonal and monthly prediction system. The experimental (Phase I) stage of the project already supplies routine guidance to users of the NMME forecasts.

Decadal climate predictions improved by ocean ensemble dispersion filtering

NASA Astrophysics Data System (ADS)

Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

2017-06-01

Decadal predictions by Earth system models aim to capture the state and phase of the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-term weather forecasts represent an initial value problem and long-term climate projections represent a boundary condition problem, the decadal climate prediction falls in-between these two time scales. In recent years, more precise initialization techniques of coupled Earth system models and increased ensemble sizes have improved decadal predictions. However, climate models in general start losing the initialized signal and its predictive skill from one forecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improved by a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. We found that this procedure, called ensemble dispersion filter, results in more accurate results than the standard decadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions show an increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with larger ensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from ocean ensemble dispersion filtering toward the ensemble mean.