WorldWideScience

Sample records for cumulus ensemble gce

  1. Fluctuations in a quasi-stationary shallow cumulus cloud ensemble

    Directory of Open Access Journals (Sweden)

    M. Sakradzija

    2015-01-01

    Full Text Available We propose an approach to stochastic parameterisation of shallow cumulus clouds to represent the convective variability and its dependence on the model resolution. To collect information about the individual cloud lifecycles and the cloud ensemble as a whole, we employ a large eddy simulation (LES model and a cloud tracking algorithm, followed by conditional sampling of clouds at the cloud-base level. In the case of a shallow cumulus ensemble, the cloud-base mass flux distribution is bimodal, due to the different shallow cloud subtypes, active and passive clouds. Each distribution mode can be approximated using a Weibull distribution, which is a generalisation of exponential distribution by accounting for the change in distribution shape due to the diversity of cloud lifecycles. The exponential distribution of cloud mass flux previously suggested for deep convection parameterisation is a special case of the Weibull distribution, which opens a way towards unification of the statistical convective ensemble formalism of shallow and deep cumulus clouds. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate a shallow convective cloud ensemble. It is formulated as a compound random process, with the number of convective elements drawn from a Poisson distribution, and the cloud mass flux sampled from a mixed Weibull distribution. Convective memory is accounted for through the explicit cloud lifecycles, making the model formulation consistent with the choice of the Weibull cloud mass flux distribution function. The memory of individual shallow clouds is required to capture the correct convective variability. The resulting distribution of the subgrid convective states in the considered shallow cumulus case is scale-adaptive – the smaller the grid size, the broader the distribution.

  2. Integrated cumulus ensemble and turbulence (ICET): An integrated parameterization system for general circulation models (GCMs)

    Energy Technology Data Exchange (ETDEWEB)

    Evans, J.L.; Frank, W.M.; Young, G.S. [Pennsylvania State Univ., University Park, PA (United States)

    1996-04-01

    Successful simulations of the global circulation and climate require accurate representation of the properties of shallow and deep convective clouds, stable-layer clouds, and the interactions between various cloud types, the boundary layer, and the radiative fluxes. Each of these phenomena play an important role in the global energy balance, and each must be parameterized in a global climate model. These processes are highly interactive. One major problem limiting the accuracy of parameterizations of clouds and other processes in general circulation models (GCMs) is that most of the parameterization packages are not linked with a common physical basis. Further, these schemes have not, in general, been rigorously verified against observations adequate to the task of resolving subgrid-scale effects. To address these problems, we are designing a new Integrated Cumulus Ensemble and Turbulence (ICET) parameterization scheme, installing it in a climate model (CCM2), and evaluating the performance of the new scheme using data from Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Testbed (CART) sites.

  3. The tropical water and energy cycles in a cumulus ensemble model. Part 1: Equilibrium climate

    Science.gov (United States)

    Sui, C. H.; Lau, K. M.; Tao, W. K.; Simpson, J.

    1994-01-01

    A cumulus ensemble model is used to study the tropical water and energy cycles and their role in the climate system. The model includes cloud dynamics, radiative processes, and microphysics that incorporate all important production and conversion processes among water vapor and five species of hydrometeors. Radiative transfer in clouds is parameterized based on cloud contents and size distributions of each bulk hydrometeor. Several model integrations have been carried out under a variety of imposed boundary and large-scale conditions. In Part 1 of this paper, the primary focus is on the water and heat budgets of the control experiment, which is designed to simulate the convective - radiative equilibrium response of the model to an imposed vertical velocity and a fixed sea surface temperature at 28 C. The simulated atmosphere is conditionally unstable below the freezing level and close to neutral above the freezing level. The equilibrium water budget shows that the total moisture source, M(sub s), which is contributed by surface evaporation (0.24 M(sub s)) and the large-scale advection (0.76 M(sub s)), all converts to mean surface precipitation bar-P(sub s). Most of M(sub s) is transported verticaly in convective regions where much of the condensate is generated and falls to surface (0.68 bar-P(sub s)). The remaining condensate detrains at a rate of 0.48 bar-P(sub s) and constitutes 65% of the source for stratiform clouds above the melting level. The upper-level stratiform cloud dissipates into clear environment at a rate of 0.14 bar-P(sub s), which is a significant moisture source comparable to the detrained water vapor (0.15 bar-P(sub s)) to the upper troposphere from convective clouds. In the lower troposphere, stratiform clouds evaporate at a rate of 0.41 bar-P(sub s), which is a more dominant moisture source than surface evaporation (0.22 bar-P(sub s)). The precipitation falling to the surface in the stratiform region is about 0.32 bar-P(sub s). The associated

  4. Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

    Science.gov (United States)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

  5. A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

    Science.gov (United States)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data

  6. Enhancing GCE A-Level Programmes.

    Science.gov (United States)

    Holding, Gordon

    This document, which is based on the findings of a study of 10 further education (FE) colleges throughout the United Kingdom, is intended to help FE colleges review and enhance their curriculum for 16- to 19-year-old students in General Certificate of Education (GCE) A-level (Advanced Level) courses. Discussed first are the following reasons for…

  7. Comparability of [0-Level] GCE Grades in 1968 and 1973.

    Science.gov (United States)

    Backhouse, John K.

    1978-01-01

    Willmott's comparison of General Certificate of Education (GCE) scores in 1968 and 1973 is reexamined. The trend toward an increasing percentage of students who pass is confirmed, but estimates of standard errors indicate that subtest differences may be attributed to the sampling plan. (CP)

  8. Comparing Content in Selected GCE A Levels and Advanced GNVQs.

    Science.gov (United States)

    Holding, Gordon; And Others

    1996-01-01

    In an action research project, four British further education colleges compared mandatory units of three Advanced General National Vocational Qualifications (GNVQs)--business, art and design, and health and social care--with related General Certificate of Education Advanced Level (GCE A-level) syllabuses. Activities included a detailed comparison…

  9. Test Writing and Speaking at GCE Ordinary Level

    Science.gov (United States)

    Harding, Ann

    1974-01-01

    Discusses diversity which has arisen in testing of productive skills at GCE O level. Criteria to apply in assessment of foreign language acquisition, and writing and speaking tests in particular, are discussed, as well as the weighting of writing and speaking at O level. (RM)

  10. Bovine cumulus-oocyte disconnection in vitro

    DEFF Research Database (Denmark)

    Maddox-Hyttel, Poul

    1987-01-01

    Cumulus-oocyte complexes were obtained from cows by aspiration of small (1-6 mm in diameter) antral follicles after slaughter. Complexes with a compact multilayered cumulus investment were cultured and processed for transmission electron microscopy after different periods of culture including a 0...

  11. Visualizing Cumulus Clouds in Virtual Reality

    NARCIS (Netherlands)

    Griffith, E.J.

    2010-01-01

    This thesis focuses on interactively visualizing, and ultimately simulating, cumulus clouds both in virtual reality (VR) and with a standard desktop computer. The cumulus clouds in question are found in data sets generated by Large-Eddy Simulations (LES), which are used to simulate a small section

  12. Cumulus Microphysics and Climate Sensitivity.

    Science.gov (United States)

    del Genio, Anthony D.; Kovari, William; Yao, Mao-Sung; Jonas, Jeffrey

    2005-07-01

    Precipitation processes in convective storms are potentially a major regulator of cloud feedback. An unresolved issue is how the partitioning of convective condensate between precipitation-size particles that fall out of updrafts and smaller particles that are detrained to form anvil clouds will change as the climate warms. Tropical Rainfall Measuring Mission (TRMM) observations of tropical oceanic convective storms indicate higher precipitation efficiency at warmer sea surface temperature (SST) but also suggest that cumulus anvil sizes, albedos, and ice water paths become insensitive to warming at high temperatures. International Satellite Cloud Climatology Project (ISCCP) data show that instantaneous cirrus and deep convective cloud fractions are positively correlated and increase with SST except at the highest temperatures, but are sensitive to variations in large-scale vertical velocity. A simple conceptual model based on a Marshall-Palmer drop size distribution, empirical terminal velocity-particle size relationships, and assumed cumulus updraft speeds reproduces the observed tendency for detrained condensate to approach a limiting value at high SST. These results suggest that the climatic behavior of observed tropical convective clouds is intermediate between the extremes required to support the thermostat and adaptive iris hypotheses.

  13. Cumulus convection and the terrestrial water-vapor distribution

    Science.gov (United States)

    Donner, Leo J.

    1988-01-01

    Cumulus convection plays a significant role in determining the structure of the terrestrial water vapor field. Cumulus convection acts directly on the moisture field by condensing and precipitating water vapor and by redistributing water vapor through cumulus induced eddy circulations. The mechanisms by which cumulus convection influences the terrestrial water vapor distribution is outlined. Calculations using a theory due to Kuo is used to illustrate the mechanisms by which cumulus convection works. Understanding of these processes greatly aids the ability of researchers to interpret the seasonal and spatial distribution of atmospheric water vapor by providing information on the nature of sources and sinks and the global circulation.

  14. Stratocumulus to Cumulus Transition by Drizzle

    Science.gov (United States)

    Yamaguchi, Takanobu; Feingold, Graham; Kazil, Jan

    2017-10-01

    The stratocumulus to cumulus transition (SCT) is typically considered to be a slow, multiday process, caused primarily by dry air entrainment associated with overshooting cumulus, with minor influence of drizzle. This study revisits the role of drizzle in the SCT with large eddy simulations coupled with a two-moment bulk microphysics scheme that includes a budget on aerosol (Na) and cloud droplet number concentrations (Nc). We show a strong precipitation-induced modulation of the SCT by drizzle initiated in penetrative cumulus under stratocumulus. Lagrangian SCT simulations are initiated with various, moderate Na (100-250 cm-3), which produce little to no drizzle from the stratocumulus. As expected, drizzle formation in cumuli is regulated by cloud depth and Nc, with stronger dependence on cloud depth, so that, for the current case, drizzle is generated in all simulations once cumulus clouds become sufficiently deep. The drizzle generated in the cumuli washes out stratocumulus cloud water and much of the aerosol, and a cumulus state appears for approximately 10 h. With additional simulations with a fixed Nc (100 cm-3), we show that prediction of Nc is necessary for this fast SCT since it is a result of a positive feedback of collision-coalescence-induced aerosol depletion that enhances drizzle formation. A fixed Nc does not permit this feedback, and thus results in weak influence of drizzle on the SCT. Simulations with fixed droplet concentrations that bracket the time varying aerosol/drop concentrations are therefore not representative of the role of drizzle in the SCT.

  15. Data, Meet Compute: NASA's Cumulus Ingest Architecture

    Science.gov (United States)

    Quinn, Patrick

    2018-01-01

    NASA's Earth Observing System Data and Information System (EOSDIS) houses nearly 30PBs of critical Earth Science data and with upcoming missions is expected to balloon to between 200PBs-300PBs over the next seven years. In addition to the massive increase in data collected, researchers and application developers want more and faster access - enabling complex visualizations, long time-series analysis, and cross dataset research without needing to copy and manage massive amounts of data locally. NASA has looked to the cloud to address these needs, building its Cumulus system to manage the ingest of diverse data in a wide variety of formats into the cloud. In this talk, we look at what Cumulus is from a high level and then take a deep dive into how it manages complexity and versioning associated with multiple AWS Lambda and ECS microservices communicating through AWS Step Functions across several disparate installations

  16. Role of cumulus cells during vitrification and fertilization of mature bovine oocytes

    NARCIS (Netherlands)

    Ortiz-Escribano, N.; Smits, K.; Piepers, S.; Abbeel, Van den E.; Woelders, H.; Soom, Van A.

    2016-01-01

    This study was designed to determine the role of cumulus cells during vitrification of bovine oocytes. Mature cumulus-oocyte complexes (COCs) with many layers of cumulus cells, corona radiata oocytes (CRs), with a few layers of cumulus cells, and denuded oocytes (DOs) without cumulus cells were

  17. Ensemble Methods

    Science.gov (United States)

    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

  18. NYYD Ensemble

    Index Scriptorium Estoniae

    2002-01-01

    NYYD Ensemble'i duost Traksmann - Lukk E.-S. Tüüri teosega "Symbiosis", mis on salvestatud ka hiljuti ilmunud NYYD Ensemble'i CDle. 2. märtsil Rakvere Teatri väikeses saalis ja 3. märtsil Rotermanni Soolalaos, kavas Tüür, Kaumann, Berio, Reich, Yun, Hauta-aho, Buckinx

  19. Effect of intraovarian factors on porcine follicular cells: cumulus expansion, granulosa and cumulus cell progesterone production

    Czech Academy of Sciences Publication Activity Database

    Ježová, M.; Scsuková, S.; Nagyová, Eva; Vranová, J.; Procházka, Radek; Kolena, J.

    2001-01-01

    Roč. 65, - (2001), s. 115-126 ISSN 0378-4320 R&D Projects: GA ČR GA524/98/0231; GA AV ČR KSK5052113 Keywords : pig-ovary * cumulus expansion * luteinization stimulator Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.196, year: 2001

  20. Soil erosion assessment on hillslope of GCE using RUSLE model

    Science.gov (United States)

    Islam, Md. Rabiul; Jaafar, Wan Zurina Wan; Hin, Lai Sai; Osman, Normaniza; Din, Moktar Aziz Mohd; Zuki, Fathiah Mohamed; Srivastava, Prashant; Islam, Tanvir; Adham, Md. Ibrahim

    2018-06-01

    A new method for obtaining the C factor (i.e., vegetation cover and management factor) of the RUSLE model is proposed. The method focuses on the derivation of the C factor based on the vegetation density to obtain a more reliable erosion prediction. Soil erosion that occurs on the hillslope along the highway is one of the major problems in Malaysia, which is exposed to a relatively high amount of annual rainfall due to the two different monsoon seasons. As vegetation cover is one of the important factors in the RUSLE model, a new method that accounts for a vegetation density is proposed in this study. A hillslope near the Guthrie Corridor Expressway (GCE), Malaysia, is chosen as an experimental site whereby eight square plots with the size of 8× 8 and 5× 5 m are set up. A vegetation density available on these plots is measured by analyzing the taken image followed by linking the C factor with the measured vegetation density using several established formulas. Finally, erosion prediction is computed based on the RUSLE model in the Geographical Information System (GIS) platform. The C factor obtained by the proposed method is compared with that of the soil erosion guideline Malaysia, thereby predicted erosion is determined by both the C values. Result shows that the C value from the proposed method varies from 0.0162 to 0.125, which is lower compared to the C value from the soil erosion guideline, i.e., 0.8. Meanwhile predicted erosion computed from the proposed C value is between 0.410 and 3.925 t ha^{-1 } yr^{-1} compared to 9.367 to 34.496 t ha^{-1} yr^{-1 } range based on the C value of 0.8. It can be concluded that the proposed method of obtaining a reasonable C value is acceptable as the computed predicted erosion is found to be classified as a very low zone, i.e. less than 10 t ha^{-1 } yr^{-1} whereas the predicted erosion based on the guideline has classified the study area as a low zone of erosion, i.e., between 10 and 50 t ha^{-1 } yr^{-1}.

  1. Ensembl 2004.

    Science.gov (United States)

    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.

  2. Ensembl 2017

    OpenAIRE

    Aken, Bronwen L.; Achuthan, Premanand; Akanni, Wasiu; Amode, M. Ridwan; Bernsdorff, Friederike; Bhai, Jyothish; Billis, Konstantinos; Carvalho-Silva, Denise; Cummins, Carla; Clapham, Peter; Gil, Laurent; Gir?n, Carlos Garc?a; Gordon, Leo; Hourlier, Thibaut; Hunt, Sarah E.

    2016-01-01

    Ensembl (www.ensembl.org) is a database and genome browser for enabling research on vertebrate genomes. We import, analyse, curate and integrate a diverse collection of large-scale reference data to create a more comprehensive view of genome biology than would be possible from any individual dataset. Our extensive data resources include evidence-based gene and regulatory region annotation, genome variation and gene trees. An accompanying suite of tools, infrastructure and programmatic access ...

  3. Ensemble Sampling

    OpenAIRE

    Lu, Xiuyuan; Van Roy, Benjamin

    2017-01-01

    Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applica...

  4. A Mass-Flux Scheme View of a High-Resolution Simulation of a Transition from Shallow to Deep Cumulus Convection.

    Science.gov (United States)

    Kuang, Zhiming; Bretherton, Christopher S.

    2006-07-01

    In this paper, an idealized, high-resolution simulation of a gradually forced transition from shallow, nonprecipitating to deep, precipitating cumulus convection is described; how the cloud and transport statistics evolve as the convection deepens is explored; and the collected statistics are used to evaluate assumptions in current cumulus schemes. The statistical analysis methodologies that are used do not require tracing the history of individual clouds or air parcels; instead they rely on probing the ensemble characteristics of cumulus convection in the large model dataset. They appear to be an attractive way for analyzing outputs from cloud-resolving numerical experiments. Throughout the simulation, it is found that 1) the initial thermodynamic properties of the updrafts at the cloud base have rather tight distributions; 2) contrary to the assumption made in many cumulus schemes, nearly undiluted air parcels are too infrequent to be relevant to any stage of the simulated convection; and 3) a simple model with a spectrum of entraining plumes appears to reproduce most features of the cloudy updrafts, but significantly overpredicts the mass flux as the updrafts approach their levels of zero buoyancy. A buoyancy-sorting model was suggested as a potential remedy. The organized circulations of cold pools seem to create clouds with larger-sized bases and may correspondingly contribute to their smaller lateral entrainment rates. Our results do not support a mass-flux closure based solely on convective available potential energy (CAPE), and are in general agreement with a convective inhibition (CIN)-based closure. The general similarity in the ensemble characteristics of shallow and deep convection and the continuous evolution of the thermodynamic structure during the transition provide justification for developing a single unified cumulus parameterization that encompasses both shallow and deep convection.

  5. Simulation of solar radiative transfer in cumulus clouds

    Energy Technology Data Exchange (ETDEWEB)

    Zuev, V.E.; Titov, G.A. [Institute of Atmospheric Optics, Tomsk (Russian Federation)

    1996-04-01

    This work presents a 3-D model of radiative transfer which is used to study the relationship between the spatial distribution of cumulus clouds and fluxes (albedo and transmittance) of visible solar radiation.

  6. Taking "O" Level GCE Examinations: The Strategies Employed by Candidates and Their Teachers.

    Science.gov (United States)

    Francis, J.C.

    1981-01-01

    Examines the relationship of study techniques and test-taking strategies to success on the "O" level of the British General Certificate of Education (GCE) examination. Findings showed that teachers and students felt that course reviews, including study of past examinations, was the best preparation. (AM)

  7. Environmental Studies and Environmental Science at GCE '0' and 'A' Level.

    Science.gov (United States)

    Gayford, Christopher G.

    1983-01-01

    Reports on environmental studies/science at General Certificate of Examination (GCE) ordinary ("0") and advanced ("A") levels. Questionnaires were used to survey teachers (focusing on their professional training and why they teach environmental studies/science courses) and to determine the relationship between environmental…

  8. The Effect of Cumulus Cloud Field Anisotropy on Domain-Averaged Solar Fluxes and Atmospheric Heating Rates

    Science.gov (United States)

    Hinkelman, Laura M.; Evans, K. Franklin; Clothiaux, Eugene E.; Ackerman, Thomas P.; Stackhouse, Paul W., Jr.

    2006-01-01

    Cumulus clouds can become tilted or elongated in the presence of wind shear. Nevertheless, most studies of the interaction of cumulus clouds and radiation have assumed these clouds to be isotropic. This paper describes an investigation of the effect of fair-weather cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rate profiles. A stochastic field generation algorithm was used to produce twenty three-dimensional liquid water content fields based on the statistical properties of cloud scenes from a large eddy simulation. Progressively greater degrees of x-z plane tilting and horizontal stretching were imposed on each of these scenes, so that an ensemble of scenes was produced for each level of distortion. The resulting scenes were used as input to a three-dimensional Monte Carlo radiative transfer model. Domain-average transmission, reflection, and absorption of broadband solar radiation were computed for each scene along with the average heating rate profile. Both tilt and horizontal stretching were found to significantly affect calculated fluxes, with the amount and sign of flux differences depending strongly on sun position relative to cloud distortion geometry. The mechanisms by which anisotropy interacts with solar fluxes were investigated by comparisons to independent pixel approximation and tilted independent pixel approximation computations for the same scenes. Cumulus anisotropy was found to most strongly impact solar radiative transfer by changing the effective cloud fraction, i.e., the cloud fraction when the field is projected on a surface perpendicular to the direction of the incident solar beam.

  9. Microphysical imprint of entrainment in warm cumulus

    Directory of Open Access Journals (Sweden)

    Jennifer D. Small

    2013-07-01

    Full Text Available We analyse the cloud microphysical response to entrainment mixing in warm cumulus clouds observed from the CIRPAS Twin Otter during the GoMACCS field campaign near Houston, Texas, in summer 2006. Cloud drop size distributions and cloud liquid water contents from the Artium Flight phase-Doppler interferometer in conjunction with meteorological observations are used to investigate the degree to which inhomogeneous versus homogeneous mixing is preferred as a function of height above cloud base, distance from cloud edge and aerosol concentration. Using four complete days of data with 101 cloud penetrations (minimum 300 m in length, we find that inhomogeneous mixing primarily explains liquid water variability in these clouds. Furthermore, we show that there is a tendency for mixing to be more homogeneous towards the cloud top, which we attribute to the combination of increased turbulent kinetic energy and cloud drop size with altitude which together cause the Damköhler number to increase by a factor of between 10 and 30 from cloud base to cloud top. We also find that cloud edges appear to be air from cloud centres that have been diluted solely through inhomogeneous mixing. Theory predicts the potential for aerosol to affect mixing type via changes in drop size over the range of aerosol concentrations experienced (moderately polluted rural sites to highly polluted urban sites. However, the observations, while consistent with this hypothesis, do not show a statistically significant effect of aerosol on mixing type.

  10. EVALUATING THE EFFECTIVENESS OF TEACHING METHODS USED FOR GCE AND SSC LEVELS

    OpenAIRE

    Bhatti, Muhammad Safdar; Mukhtar, Rafia; Bajwa, Shahla

    2017-01-01

    Thepresent research focuses on comparative study of the Secondary SchoolCertificate (SSC) and the General Certificate of Education-Ordinary level(GCE-O level) English language course to trace out the problems andshortcomings of the curriculum objectives and teaching methods. The objectivesof the study were to analyze the objectives of teaching English of SSC and GCEO-level to critically review the teaching methodologies of both the courses.The population of the study comprised of all the teac...

  11. Progesterone from the cumulus cells is the sperm chemoattractant secreted by the rabbit oocyte cumulus complex.

    Directory of Open Access Journals (Sweden)

    Héctor Alejandro Guidobaldi

    Full Text Available Sperm chemotaxis in mammals have been identified towards several female sources as follicular fluid (FF, oviduct fluid, and conditioned medium from the cumulus oophorus (CU and the oocyte (O. Though several substances were confirmed as sperm chemoattractant, Progesterone (P seems to be the best chemoattractant candidate, because: 1 spermatozoa express a cell surface P receptor, 2 capacitated spermatozoa are chemotactically attracted in vitro by gradients of low quantities of P; 3 the CU cells produce and secrete P after ovulation; 4 a gradient of P may be kept stable along the CU; and 5 the most probable site for sperm chemotaxis in vivo could be near and/or inside the CU. The aim of this study was to verify whether P is the sperm chemoattractant secreted by the rabbit oocyte-cumulus complex (OCC in the rabbit, as a mammalian animal model. By means of videomicroscopy and computer image analysis we observed that only the CU are a stable source of sperm attractants. The CU produce and secrete P since the hormone was localized inside these cells by immunocytochemistry and in the conditioned medium by enzyme immunoassay. In addition, rabbit spermatozoa express a cell surface P receptor detected by western blot and localized over the acrosomal region by immunocytochemistry. To confirm that P is the sperm chemoattractant secreted by the CU, the sperm chemotactic response towards the OCC conditioned medium was inhibited by three different approaches: P from the OCC conditioned medium was removed with an anti-P antibody, the attractant gradient of the OCC conditioned medium was disrupted by a P counter gradient, and the sperm P receptor was blocked with a specific antibody. We concluded that only the CU but not the oocyte secretes P, and the latter chemoattract spermatozoa by means of a cell surface receptor. Our findings may be of interest in assisted reproduction procedures in humans, animals of economic importance and endangered species.

  12. The beneficial effects of cumulus cells and oocyte-cumulus cell gap junctions depends on oocyte maturation and fertilization methods in mice

    Directory of Open Access Journals (Sweden)

    Cheng-Jie Zhou

    2016-03-01

    Full Text Available Cumulus cells are a group of closely associated granulosa cells that surround and nourish oocytes. Previous studies have shown that cumulus cells contribute to oocyte maturation and fertilization through gap junction communication. However, it is not known how this gap junction signaling affects in vivo versus in vitro maturation of oocytes, and their subsequent fertilization and embryonic development following insemination. Therefore, in our study, we performed mouse oocyte maturation and insemination using in vivo- or in vitro-matured oocyte-cumulus complexes (OCCs, which retain gap junctions between the cumulus cells and the oocytes, in vitro-matured, denuded oocytes co-cultured with cumulus cells (DCs, which lack gap junctions between the cumulus cells and the oocytes, and in vitro-matured, denuded oocytes without cumulus cells (DOs. Using these models, we were able to analyze the effects of gap junction signaling on oocyte maturation, fertilization, and early embryo development. We found that gap junctions were necessary for both in vivo and in vitro oocyte maturation. In addition, for oocytes matured in vivo, the presence of cumulus cells during insemination improved fertilization and blastocyst formation, and this improvement was strengthened by gap junctions. Moreover, for oocytes matured in vitro, the presence of cumulus cells during insemination improved fertilization, but not blastocyst formation, and this improvement was independent of gap junctions. Our results demonstrate, for the first time, that the beneficial effect of gap junction signaling from cumulus cells depends on oocyte maturation and fertilization methods.

  13. Hotelli Cumulus Mikkelin majoitusasiakkaiden tyytyväisyys

    OpenAIRE

    Kinnunen, Jenni Ljuba

    2016-01-01

    Tämän opinnäytetyön tavoitteena on tutkia majoitusasiakkaiden tyytyväisyyttä hotelli Cumulus Mikkelissä keskittyen pääosin hotellin vastaanottoon, hotellihuoneeseen, Huviretki-ravintolaan ja aamiaiseen. Opinnäytetyön toimeksiantaja on hotelli Cumulus Mikkeli. Tässä opinnäytetyössä käytetään kvalitatiivista tutkimusmenetelmää ja tutkimusaineisto kerättiin haastattelemalla hotellin majoitusasiakkaita yksitellen kyselylomakkeen kanssa. Haastateltujen asiakkaiden määrä oli 20, joista 10 ...

  14. Impact of cloud microphysics and cumulus parameterization on ...

    Indian Academy of Sciences (India)

    2007-10-09

    Oct 9, 2007 ... Bangladesh. Weather Research and Forecast (WRF–ARW version) modelling system with six dif- .... tem intensified rapidly into a land depression over southern part of ... Impact of cloud microphysics and cumulus parameterization on heavy rainfall. 261 .... tent and temperature and is represented as a sum.

  15. Laboratory simulations of cumulus cloud flows explain the entrainment anomaly

    Science.gov (United States)

    Narasimha, Roddam; Diwan, Sourabh S.; Subrahmanyam, Duvvuri; Sreenivas, K. R.; Bhat, G. S.

    2010-11-01

    In the present laboratory experiments, cumulus cloud flows are simulated by starting plumes and jets subjected to off-source heat addition in amounts that are dynamically similar to latent heat release due to condensation in real clouds. The setup permits incorporation of features like atmospheric inversion layers and the active control of off-source heat addition. Herein we report, for the first time, simulation of five different cumulus cloud types (and many shapes), including three genera and three species (WMO Atlas 1987), which show striking resemblance to real clouds. It is known that the rate of entrainment in cumulus cloud flows is much less than that in classical plumes - the main reason for the failure of early entrainment models. Some of the previous studies on steady-state jets and plumes (done in a similar setup) have attributed this anomaly to the disruption of the large-scale turbulent structures upon the addition of off-source heat. We present estimates of entrainment coefficients from these measurements which show a qualitatively consistent variation with height. We propose that this explains the observed entrainment anomaly in cumulus clouds; further experiments are planned to address this question in the context of starting jets and plumes.

  16. Comparison of gene expression patterns between porcine cumulus ...

    African Journals Online (AJOL)

    These results suggest that the aberrant of gene expression patterns detected in the oocytes of NOs compared with COCs explains their reduced quality in terms of development and maturation. In conclusion, these differentially expressed mRNAs may be involved in cellular interactions between oocytes and cumulus cells ...

  17. The human cumulus--oocyte complex gene-expression profile

    Science.gov (United States)

    Assou, Said; Anahory, Tal; Pantesco, Véronique; Le Carrour, Tanguy; Pellestor, Franck; Klein, Bernard; Reyftmann, Lionel; Dechaud, Hervé; De Vos, John; Hamamah, Samir

    2006-01-01

    BACKGROUND The understanding of the mechanisms regulating human oocyte maturation is still rudimentary. We have identified transcripts differentially expressed between immature and mature oocytes, and cumulus cells. METHODS Using oligonucleotides microarrays, genome wide gene expression was studied in pooled immature and mature oocytes or cumulus cells from patients who underwent IVF. RESULTS In addition to known genes such as DAZL, BMP15 or GDF9, oocytes upregulated 1514 genes. We show that PTTG3 and AURKC are respectively the securin and the Aurora kinase preferentially expressed during oocyte meiosis. Strikingly, oocytes overexpressed previously unreported growth factors such as TNFSF13/APRIL, FGF9, FGF14, and IL4, and transcription factors including OTX2, SOX15 and SOX30. Conversely, cumulus cells, in addition to known genes such as LHCGR or BMPR2, overexpressed cell-tocell signaling genes including TNFSF11/RANKL, numerous complement components, semaphorins (SEMA3A, SEMA6A, SEMA6D) and CD genes such as CD200. We also identified 52 genes progressively increasing during oocyte maturation, comprising CDC25A and SOCS7. CONCLUSION The identification of genes up and down regulated during oocyte maturation greatly improves our understanding of oocyte biology and will provide new markers that signal viable and competent oocytes. Furthermore, genes found expressed in cumulus cells are potential markers of granulosa cell tumors. PMID:16571642

  18. Cumulus parameterizations in chemical transport models

    Science.gov (United States)

    Mahowald, Natalie M.; Rasch, Philip J.; Prinn, Ronald G.

    1995-12-01

    Global three-dimensional chemical transport models (CTMs) are valuable tools for studying processes controlling the distribution of trace constituents in the atmosphere. A major uncertainty in these models is the subgrid-scale parametrization of transport by cumulus convection. This study seeks to define the range of behavior of moist convective schemes and point toward more reliable formulations for inclusion in chemical transport models. The emphasis is on deriving convective transport from meteorological data sets (such as those from the forecast centers) which do not routinely include convective mass fluxes. Seven moist convective parameterizations are compared in a column model to examine the sensitivity of the vertical profile of trace gases to the parameterization used in a global chemical transport model. The moist convective schemes examined are the Emanuel scheme [Emanuel, 1991], the Feichter-Crutzen scheme [Feichter and Crutzen, 1990], the inverse thermodynamic scheme (described in this paper), two versions of a scheme suggested by Hack [Hack, 1994], and two versions of a scheme suggested by Tiedtke (one following the formulation used in the ECMWF (European Centre for Medium-Range Weather Forecasting) and ECHAM3 (European Centre and Hamburg Max-Planck-Institut) models [Tiedtke, 1989], and one formulated as in the TM2 (Transport Model-2) model (M. Heimann, personal communication, 1992). These convective schemes vary in the closure used to derive the mass fluxes, as well as the cloud model formulation, giving a broad range of results. In addition, two boundary layer schemes are compared: a state-of-the-art nonlocal boundary layer scheme [Holtslag and Boville, 1993] and a simple adiabatic mixing scheme described in this paper. Three tests are used to compare the moist convective schemes against observations. Although the tests conducted here cannot conclusively show that one parameterization is better than the others, the tests are a good measure of the

  19. Early Detection of Rapidly Developing Cumulus Area using HIMAWARI-8

    Science.gov (United States)

    Yamada, Y.; Kadosaki, G.

    2017-12-01

    In recent years, many disasters have been occured by influence of meteorological change in Japan. So, it becomes more important to inform rapid weather change caused by cumulus which brings concentrated heavy rain/hail, wind gust, lightning in a short period. These severe events should inclease in the future by global warming. Therefore we are developping the alert system for Rapidly Developing Cumulus Area (RDCA) detection using Japanese new satellite. At July 2015, Japan Meteorological Agency started operation of new geostationary meteorological satellite "Himawari-8". This satellite has optical imager named Advanced Himawari Imager (AHI). It can observe Japan area every 2.5 minutes. The frequently infrared image with high resolution (2km) is the key of our alert system. We took some special functions in the algorithm of this system. One of the points is cloud location which shifts to north from true location around Japan by viewing angle from the satellite above the equator. We moved clouds to the correct position using geometric correction method according to its height and latitude. This algorithm also follows a movement of cloud every 2.5 minutes during several observations. It derives the information about degree of the development of cumulus. The prototype system gives the alert before 30 to 60 minutes in advance to the first lightning in typical cumulus case. However, we understand that there are some difficult cases to alert. For example, winter low cloud over the Japan Sea which brings a winter lightning, and tornado (although it is not cumulus). Now, we are adjusting some parameters of the algorithm. In the near future, our algorithm will be used in weather information delivery service to the customer.

  20. Cumulus Cell Expansion, Its Role in Oocyte Biology and Perspectives of Measurement: A Review

    Directory of Open Access Journals (Sweden)

    Nevoral J.

    2015-01-01

    Full Text Available Cumulus expansion of the cumulus-oocyte complex is necessary for meiotic maturation and acquiring developmental competence. Cumulus expansion is based on extracellular matrix synthesis by cumulus cells. Hyaluronic acid is the most abundant component of this extracellular matrix. Cumulus expansion takes place during meiotic oocyte maturation under in vivo and in vitro conditions. Quantification and measurement of cumulus expansion intensity is one possible method of determining oocyte quality and optimizing conditions for in vitro cultivation. Currently, subjective methods of expanded area and more exact cumulus expansion measurement by hyaluronic acid assessment are available. Among the methods of hyaluronic acid measurement is the use of radioactively labelled synthesis precursors. Alternatively, immunological and analytical methods, including enzyme-linked immunosorbent assay (ELISA, spectrophotometry, and high-performance liquid chromatography (HPLC in UV light, could be utilized. The high sensitivity of these methods could provide a precise analysis of cumulus expansion without the use of radioisotopes. Therefore, the aim of this review is to summarize and compare available approaches of cumulus expansion measurement, respecting special biological features of expanded cumuli, and to suggest possible solutions for exact cumulus expansion analysis.

  1. Laboratory Studies of Anomalous Entrainment in Cumulus Cloud Flows

    Science.gov (United States)

    Diwan, Sourabh S.; Narasimha, Roddam; Bhat, G. S.; Sreenivas, K. R.

    2011-12-01

    Entrainment in cumulus clouds has been a subject of investigation for the last sixty years, and continues to be a central issue in current research. The development of a laboratory facility that can simulate cumulus cloud evolution enables us to shed light on the problem. The apparatus for the purpose is based on a physical model of cloud flow as a plume with off-source diabatic heating that is dynamically similar to the effect of latent-heat release in natural clouds. We present a critical review of the experimental data so far obtained in such facilities on the variation of the entrainment coefficient in steady diabatic jets and plumes. Although there are some unexplained differences among different data sets, the dominant trend of the results compares favourably with recent numerical simulations on steady-state deep convection, and helps explain certain puzzles in the fluid dynamics of clouds.

  2. Laboratory Studies of Anomalous Entrainment in Cumulus Cloud Flows

    International Nuclear Information System (INIS)

    Diwan, Sourabh S; Narasimha, Roddam; Sreenivas, K R; Bhat, G S

    2011-01-01

    Entrainment in cumulus clouds has been a subject of investigation for the last sixty years, and continues to be a central issue in current research. The development of a laboratory facility that can simulate cumulus cloud evolution enables us to shed light on the problem. The apparatus for the purpose is based on a physical model of cloud flow as a plume with off-source diabatic heating that is dynamically similar to the effect of latent-heat release in natural clouds. We present a critical review of the experimental data so far obtained in such facilities on the variation of the entrainment coefficient in steady diabatic jets and plumes. Although there are some unexplained differences among different data sets, the dominant trend of the results compares favourably with recent numerical simulations on steady-state deep convection, and helps explain certain puzzles in the fluid dynamics of clouds.

  3. Continuous growth of cloud droplets in cumulus cloud

    International Nuclear Information System (INIS)

    Gotoh, Toshiyuki; Suehiro, Tamotsu; Saito, Izumi

    2016-01-01

    A new method to seamlessly simulate the continuous growth of droplets advected by turbulent flow inside a cumulus cloud was developed from first principle. A cubic box ascending with a mean updraft inside a cumulus cloud was introduced and the updraft velocity was self-consistently determined in such a way that the mean turbulent velocity within the box vanished. All the degrees of freedom of the cloud droplets and turbulence fields were numerically integrated. The box ascended quickly inside the cumulus cloud due to the updraft and the mean radius of the droplets grew from 10 to 24 μ m for about 10 min. The turbulent flow tended to slow down the time evolutions of the updraft velocity, the box altitude and the mean cloud droplet radius. The size distribution of the cloud droplets in the updraft case was narrower than in the absence of the updraft. It was also found that the wavenumeber spectra of the variances of the temperature and water vapor mixing ratio were nearly constant in the low wavenumber range. The future development of the new method was argued. (paper)

  4. Entrainment in Laboratory Simulations of Cumulus Cloud Flows

    Science.gov (United States)

    Narasimha, R.; Diwan, S.; Subrahmanyam, D.; Sreenivas, K. R.; Bhat, G. S.

    2010-12-01

    A variety of cumulus cloud flows, including congestus (both shallow bubble and tall tower types), mediocris and fractus have been generated in a water tank by simulating the release of latent heat in real clouds. The simulation is achieved through ohmic heating, injected volumetrically into the flow by applying suitable voltages between diametral cross-sections of starting jets and plumes of electrically conducting fluid (acidified water). Dynamical similarity between atmospheric and laboratory cloud flows is achieved by duplicating values of an appropriate non-dimensional heat release number. Velocity measurements, made by laser instrumentation, show that the Taylor entrainment coefficient generally increases just above the level of commencement of heat injection (corresponding to condensation level in the real cloud). Subsequently the coefficient reaches a maximum before declining to the very low values that characterize tall cumulus towers. The experiments also simulate the protected core of real clouds. Cumulus Congestus : Atmospheric cloud (left), simulated laboratory cloud (right). Panels below show respectively total heat injected and vertical profile of heating in the laboratory cloud.

  5. World Music Ensemble: Kulintang

    Science.gov (United States)

    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…

  6. Shallow cumuli ensemble statistics for development of a stochastic parameterization

    Science.gov (United States)

    Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs

    2014-05-01

    According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a

  7. All Above-Board: A Comparativist Looks at the Advanced Level French Syllabuses of the Nine GCE Boards.

    Science.gov (United States)

    Weil, Robert

    1978-01-01

    Advanced level French syllabuses of the nine GCE Boards in the United Kingdom are examined. The Southern Universities Joint Board has recently introduced the most radical innovations. As an alternative to its traditional examination it offers Syllabus "B" which dispenses with prescribed tests, but where each student must produce for the…

  8. Institutional Disparities in the Cost Effectiveness of GCE A-Level Provision: A Multi-Level Approach.

    Science.gov (United States)

    Fielding, A.

    1995-01-01

    Reanalyzes H. Thomas's 1980s data, which used teaching group as the unit of analysis and illuminated some institutional disparities in provision of General Certificate of Education (GCE) A-levels. Uses multilevel analysis to focus on individual students in a hierarchical framework. Among the study institutions, school sixth forms appear less…

  9. Teaching Groups as Foci for Evaluating Performance in Cost-Effectiveness of GCE Advanced Level Provision: Some Practical Methodological Innovations.

    Science.gov (United States)

    Fielding, Antony

    2002-01-01

    Analyzes subject teaching-group effectiveness in English and Welsh General Certification of Education (GCE) Advanced Level prior to a linking to resources; suggests cross-classified multilevel models with weighted random effects for disentangling student, group, and teacher effects; finds that teacher effects are considerable, but cannot find…

  10. Power in Operation: A Case Study Focussing on How Subject-Based Knowledge Is Constrained by the Methods of Assessment in GCE A Level Dance

    Science.gov (United States)

    Sanders, Lorna

    2008-01-01

    The General Certificate of Education (GCE) A Level Dance specification, offered by the Assessment and Qualifications Alliance (AQA), is the only GCE course of study in the UK that focuses solely on dance. Acquisition of subject specific knowledge is a feature of its aims, while assessment, as constructed by its objectives, is assumed to be a…

  11. Cumulus Kuopion työmatkustajien asiakastyytyväisyys

    OpenAIRE

    Lampinen, Miia; Lamminmäki, Roosa-Maria

    2015-01-01

    Eri hotelliryhmissä asiakkaat erotellaan heidän tarpeidensa ja toiveidensa mukaan. Asiakas on se, joka määrittelee yrityksen laadun. Business-asiakkaat valitsevat usein kansallisen tai kansainvälisen ketjuhotellin, joka täyttää tietyt laatustandardit. Yleensä he myös sitoutuvat ketjun kanta-asiakasohjelmiin. Kanta-asiakasjärjestelmät sisältävät yleensä edullisempien majoitusten lisäksi muitakin etuja. Cumulus Kuopio on hotelli hyvien kulkuyhteyksien päässä, aivan Kuopion rautatieaseman vieres...

  12. Effect of cumulus-oocyte complexes (COCs) culture duration on in ...

    African Journals Online (AJOL)

    We investigated and optimized the cumulus-oocyte complexes (COCs) culture duration for pig oocyte in vitro maturation and produced a number of high-quality metaphase-II (M-II) oocytes for generation of parthenotes. The present study graded the COCs into levels A, B and C according to layers of cumulus cells, which ...

  13. Effects of selected endocrine disruptors on meiotic maturation, cumulus expansion, syntesis of hyaluronan and progesterone by porcine oocyte-cumulus complexes

    Czech Academy of Sciences Publication Activity Database

    Mlynarčíková, A.; Nagyová, Eva; Ficková, M.; Scsuková, S.

    2009-01-01

    Roč. 23, - (2009), s. 371-377 ISSN 0887-2333 R&D Projects: GA ČR GA305/05/0960 Grant - others:VEGA(SK) 2/6171/26; EU(XE) QLK4-CT-2002-02637 Institutional research plan: CEZ:AV0Z50450515 Keywords : oocyte-cumulus complex * meiotic maturation * cumulus expansion Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.060, year: 2009

  14. BMP15 Prevents Cumulus Cell Apoptosis Through CCL2 and FBN1 in Porcine Ovaries

    Directory of Open Access Journals (Sweden)

    Bo Zhai

    2013-07-01

    Full Text Available Background: Bone morphogenetic protein-15 (BMP15 is a maternal gene necessary for mammalian reproduction. BMP15 expression increased in oocytes accompanied by follicle growth and development. The function and regulation mechanism of BMP15 in porcine cumulus cell apoptosis process is still unclear now. Methods: In this study, flow cytometry (FCM was used to analyze the effects of BMP15 with different concentrations to cumulus cell apoptosis. High-throughput sequencing technology was carried out to screen regulatory genes linked closely with BMP15. In order to confirm the function of (MCP-1/CCL2 and FBN1 in cumulus cell apoptosis, RNA interference (RNAi method was used to inhibit the expression of (MCP-1/CCL2 and FBN1. Apoptosis and proliferation of cumulus cell treated with siRNA transfection technology were measured by FCM, 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide, quantitative real time-PCR (RT-qPCR and western blotting. Results: The results showed that the apoptosis levels of cumulus cell treated by BMP15 decreased significantly in a dose-dependent manner. The expression of related genes protein 1 (MCP-1/CCL2 and fibrillin1 (FBN1 were both regulated by BMP15. After transfection, the proliferation of porcine cumulus cells increased significantly and apoptosis of cumulus cells was prevented while FBN1 was silenced after BMP15 treatment. The proliferation of cumulus cells decreased significantly and apoptosis rate of cumulus cells increased significantly while CCL2 was silenced. Conclusion: The results obtained in this study firstly demonstrated that CCL2 and FBN1 are important regulatory factors of BMP15 in preventing cumulus cell apoptosis in porcine ovaries.

  15. A Heuristic Parameterization for the Integrated Vertical Overlap of Cumulus and Stratus

    Science.gov (United States)

    Park, Sungsu

    2017-10-01

    The author developed a heuristic parameterization to handle the contrasting vertical overlap structures of cumulus and stratus in an integrated way. The parameterization assumes that cumulus is maximum-randomly overlapped with adjacent cumulus; stratus is maximum-randomly overlapped with adjacent stratus; and radiation and precipitation areas at each model interface are grouped into four categories, that is, convective, stratiform, mixed, and clear areas. For simplicity, thermodynamic scalars within individual portions of cloud, radiation, and precipitation areas are assumed to be internally homogeneous. The parameterization was implemented into the Seoul National University Atmosphere Model version 0 (SAM0) in an offline mode and tested over the globe. The offline control simulation reasonably reproduces the online surface precipitation flux and longwave cloud radiative forcing (LWCF). Although the cumulus fraction is much smaller than the stratus fraction, cumulus dominantly contributes to precipitation production in the tropics. For radiation, however, stratus is dominant. Compared with the maximum overlap, the random overlap of stratus produces stronger LWCF and, surprisingly, more precipitation flux due to less evaporation of convective precipitation. Compared with the maximum overlap, the random overlap of cumulus simulates stronger LWCF and weaker precipitation flux. Compared with the control simulation with separate cumulus and stratus, the simulation with a single-merged cloud substantially enhances the LWCF in the tropical deep convection and midlatitude storm track regions. The process-splitting treatment of convective and stratiform precipitation with an independent precipitation approximation (IPA) simulates weaker surface precipitation flux than the control simulation in the tropical region.

  16. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey; Hoel, Haakon; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  17. Entropy of network ensembles

    Science.gov (United States)

    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.

  18. Multilevel ensemble Kalman filter

    KAUST Repository

    Chernov, Alexey

    2016-01-06

    This work embeds a multilevel Monte Carlo (MLMC) sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF). In terms of computational cost vs. approximation error the asymptotic performance of the multilevel ensemble Kalman filter (MLEnKF) is superior to the EnKF s.

  19. The Ensembl REST API: Ensembl Data for Any Language.

    Science.gov (United States)

    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.

  20. Cumulus cell mitochondrial activity in relation to body mass index in women undergoing assisted reproductive therapy

    Directory of Open Access Journals (Sweden)

    Victoria K. Gorshinova

    2017-06-01

    Full Text Available Most studies have considered the negative influence of obesity on fertility in both genders. In the present study, we assessed mitochondrial activity expressed as the mitochondrial potential index (MPI in cumulus cells from obese women and women with a normal body mass index (BMI during assisted reproductive therapy. The results revealed a significant reduction of MPI with increased body mass. The lower MPI levels in cumulus cells from obese women may reflect mitochondrial dysfunction caused by oxidative stress, which can affect the cumulus-oocyte complex and have an impact on oocyte development.

  1. Musical ensembles in Ancient Mesapotamia

    NARCIS (Netherlands)

    Krispijn, T.J.H.; Dumbrill, R.; Finkel, I.

    2010-01-01

    Identification of musical instruments from ancient Mesopotamia by comparing musical ensembles attested in Sumerian and Akkadian texts with depicted ensembles. Lexicographical contributions to the Sumerian and Akkadian lexicon.

  2. Expression of apoptotic genes in immature and in vitro matured equine oocytes and cumulus cells.

    Science.gov (United States)

    Leon, P M M; Campos, V F; Kaefer, C; Begnini, K R; McBride, A J A; Dellagostin, O A; Seixas, F K; Deschamps, J C; Collares, T

    2013-08-01

    The gene expression of Bax, Bcl-2, survivin and p53, following in vitro maturation of equine oocytes, was compared in morphologically distinct oocytes and cumulus cells. Cumulus-oocyte complexes (COC) were harvested and divided into two groups: G1 - morphologically healthy cells; and G2 - less viable cells or cells with some degree of atresia. Total RNA was isolated from both immature and in vitro matured COC and real-time reverse transcription polymerase chain reaction (qRT-PCR) was used to quantify gene expression. Our results showed there was significantly higher expression of survivin (P < 0.05) and lower expression of p53 (P < 0.01) in oocytes compared with cumulus cells in G1. No significant difference in gene expression was observed following in vitro maturation or in COC derived from G1 and G2. However, expression of the Bax gene was significantly higher in cumulus cells from G1 (P < 0.02).

  3. Layer-by-layer construction of graphene/cobalt phthalocyanine composite film on activated GCE for application as a nitrite sensor

    International Nuclear Information System (INIS)

    Cui, Lili; Pu, Tao; Liu, Ying; He, Xingquan

    2013-01-01

    Graphical abstract: A novel nitrite sensor was prepared by using LBL technique which for the first time used the activated positively charged glassy carbon electrode (A-GCE) as the substrate. The nitrite sensor shows super stability for consecutive CV testing and rather low detection limit. -- Abstract: In this paper, a novel graphene/cobalt phthalocyanine composite film was prepared by layer-by-layer (LBL) technique which for the first time used the activated positively charged glassy carbon electrode (A-GCE) as the substrate. The surface morphology of graphene/cobalt phthalocyanine composite film was characterized by scanning electron microscopy (SEM) and atomic force microscope (AFM). It is found that graphene/cobalt phthalocyanine composite film modified GCE exhibits good catalytic activity toward the oxidation of nitrite. The oxidation current barely decreases in consecutive CV test. Furthermore, the modified GCE shows long-term stability after 70 days. The super good stability can be attributed to the immobilization and dispersion of electroactive cobalt phthalocyanine by graphene, and using A-GCE as substrate which can enhance the interaction force between GCE and electroactive cobalt phthalocyanine. The nitrite sensor shows rather low detection limit of 0.084 μM at a signal-to-noise ratio = 3 (S/N = 3)

  4. Cumulus-specific genes are transcriptionally silent following somatic cell nuclear transfer in a mouse model*

    OpenAIRE

    Tong, Guo-qing; Heng, Boon-chin; Ng, Soon-chye

    2007-01-01

    This study investigated whether four cumulus-specific genes: follicular stimulating hormone receptor (FSHr), hyaluronan synthase 2 (Has2), prostaglandin synthase 2 (Ptgs2) and steroidogenic acute regulator protein (Star), were correctly reprogrammed to be transcriptionally silent following somatic cell nuclear transfer (SCNT) in a murine model. Cumulus cells of C57×CBA F1 female mouse were injected into enucleated oocytes, followed by activation in 10 µmol/L strontium chloride for 5 h and sub...

  5. Effect of exogenous progesterone on cumulus characteristics of buffalo oocytes by allowing passage of more number of sperm through cumulus but not essentially fertilization

    Directory of Open Access Journals (Sweden)

    Madhusmita Panda

    2018-03-01

    Full Text Available Objective: To understand the level of progesterone (P4 in different quality of buffalo cumulus oocyte complexes (COCs and further to evaluate the effect of exogenous P4 supplementation on maturation and subsequent developmental ability of poor quality brilliant cresyl blue (BCB- COCs. Methods: Progesterone secreted by different quality of buffalo oocytes was estimated by enzyme linked immunosorbent assay and the concentration differences were translated into P4 doses to be incorporated in the maturation medium of BCB-ve COCs followed by expression analysis of genes involved in the cumulus expansion, extracellular matrix disintegration and progesterone receptor signalling. In addition, the study also evaluated the effect of exogenous P4 on sperm-cumulus interaction. Results: More than 10-fold upregulated expression of progesterone receptor in P4 supplemented oocytes signified that P4 might be acting predominantly through this receptor. Also, exogenous P4 supplementation had significant effect on transcatheter arterial chemoembolization protease regulated by P4- progesterone receptor pathway which in turn had an important role in extracellular matrix disintegration. On the contrary, cumulus expansion genes HAS2, TNFAIP6, AREG were not altered upon P4 supplementation. Also, it was observed that P4 addition did facilitate passage of significantly more number of spermatozoa through P4 treated cumulus cells. Further, incorporation of different doses of P4 did not improve significantly the cleavage and blastocyst rates of BCB-ve COCs. Conclusions: Different qualities of buffalo COCs secrete substantially diverse levels of P4, and its supplementation has a role in oocyte maturation via modulation of cumulus characteristics but perhaps not fertilization.

  6. Mitochondrial dysfunction and apoptosis in cumulus cells of type I diabetic mice.

    Directory of Open Access Journals (Sweden)

    Qiang Wang

    2010-12-01

    Full Text Available Impaired oocyte quality has been demonstrated in diabetic mice; however, the potential pathways by which maternal diabetes exerts its effects on the oocyte are poorly understood. Cumulus cells are in direct contact with the oocyte via gap junctions and provide essential nutrients to support oocyte development. In this study, we investigated the effects of maternal diabetes on the mitochondrial status in cumulus cells. We found an increased frequency of fragmented mitochondria, a decreased transmembrane potential and an aggregated distribution of mitochondria in cumulus cells from diabetic mice. Furthermore, while mitochondrial biogenesis in cumulus cells was induced by maternal diabetes, their metabolic function was disrupted as evidenced by lower ATP and citrate levels. Moreover, we present evidence suggesting that the mitochondrial impairments induced by maternal diabetes, at least in part, lead to cumulus cell apoptosis through the release of cytochrome c. Together the deleterious effects on cumulus cells may disrupt trophic and signaling interactions with the oocyte, contributing to oocyte incompetence and thus poor pregnancy outcomes in diabetic females.

  7. Effect of Acrylamide on Oocyte Nuclear Maturation and Cumulus Cells Apoptosis in Mouse In Vitro.

    Directory of Open Access Journals (Sweden)

    Shuzhen Liu

    Full Text Available Acrylamide (ACR is a chemical compound with severe neurotoxicity, genotoxicity, carcinogenicity and reproductive toxicity. Recent studies showed that ACR impairs the function of reproductive organs, e.g., epididymis and testes. In vitro maturation of mouse oocyte is a sensitive assay to identify potential chemical hazard to female fertility. The aim of this study was to evaluate the adverse effects of ACR on the nuclear maturation and cumulus cells apoptosis of mouse oocytes in vitro. Cumulus-oocyte complexes were incubated in a maturation medium containing 0, 5, 10 and 20 μM of ACR. Chromosome alignment and spindle morphology of oocytes was determined by immunofluorescence and confocal microscopy. Our results showed that oocytes exposed to different doses of ACR in vitro were associated with a significant decrease of oocyte maturation, significant increase of chromosome misalignment rate, occurrence of abnormal spindle configurations, and the inhibition of oocyte parthenogenetic activation. Furthermore, apoptosis of cumulus cells was determined by TUNEL and CASPASE-3 assay. Results showed that apoptosis in cumulus cells was enhanced and the expression of CASPASE-3 was increased after cumulus-oocyte complexes were exposed to ACR. Therefore, ACR may affect the nuclear maturation of oocytes via the apoptosis of cumulus cells in vitro.

  8. Ensemble Data Mining Methods

    Science.gov (United States)

    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.

  9. Ensemble Data Mining Methods

    Data.gov (United States)

    National Aeronautics and Space Administration — 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...

  10. Ensembl variation resources

    Directory of Open Access Journals (Sweden)

    Marin-Garcia Pablo

    2010-05-01

    Full Text Available Abstract 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.

  11. Spectral cumulus parameterization based on cloud-resolving model

    Science.gov (United States)

    Baba, Yuya

    2018-02-01

    We have developed a spectral cumulus parameterization using a cloud-resolving model. This includes a new parameterization of the entrainment rate which was derived from analysis of the cloud properties obtained from the cloud-resolving model simulation and was valid for both shallow and deep convection. The new scheme was examined in a single-column model experiment and compared with the existing parameterization of Gregory (2001, Q J R Meteorol Soc 127:53-72) (GR scheme). The results showed that the GR scheme simulated more shallow and diluted convection than the new scheme. To further validate the physical performance of the parameterizations, Atmospheric Model Intercomparison Project (AMIP) experiments were performed, and the results were compared with reanalysis data. The new scheme performed better than the GR scheme in terms of mean state and variability of atmospheric circulation, i.e., the new scheme improved positive bias of precipitation in western Pacific region, and improved positive bias of outgoing shortwave radiation over the ocean. The new scheme also simulated better features of convectively coupled equatorial waves and Madden-Julian oscillation. These improvements were found to be derived from the modification of parameterization for the entrainment rate, i.e., the proposed parameterization suppressed excessive increase of entrainment, thus suppressing excessive increase of low-level clouds.

  12. Numerical simulation of a rare winter hailstorm event over Delhi, India on 17 January 2013

    KAUST Repository

    Chevuturi, A.; Dimri, A. P.; Gunturu, Udaya

    2014-01-01

    January 2013 (16:00–18:00 UTC) occurring over NCR is investigated. The storm is simulated using the Weather Research and Forecasting (WRF) model with the Goddard Cumulus Ensemble (GCE) microphysics scheme with two different options: hail and graupel

  13. Synthesis of novel amperometric urea-sensor using hybrid synthesized NiO-NPs/GO modified GCE in aqueous solution of cetrimonium bromide.

    Science.gov (United States)

    Parsaee, Zohreh

    2018-06-01

    In this study NiO nanostructures were synthesized via combinational synthetic method (ultrasound-assisted biosynthesis) and immobilized on the glassy carbon electrode (GCE) as a highly sensitive and selective enzyme-less sensor for urea detection. NiO-NPs were fully characterized using SEM, EDX, XRD, BET, TGA, FT-IR, UV-vis and Raman methods which revealed the formation of NiO nanostructures in the form of cotton like porous material and crystalline in nature with the average size of 3.8 nm. GCE was modified with NiO-NPs in aqueous solution of cetrimonium bromide(CTAB). Highly adhesive NiO/CTAB/GO nanocomposite membrane has been formed on GCE by immersing NiO/CTAB modified GCE in GO suspension. CTAB has a major role in the production and immobilization of the nanocomposites on the GCE surface and the binding NiO nanoparticles on GO plates. In addition, CTAB/GO composition made a highly adhesive surface on the GCE. The resulting NiO/CTAB/GO/GCE contains potently sensitive to urea in aqueous environments. The response of as developed amperometric sensor was linear in the range of 100-1200 µM urea with R 2 value of 0.991 and limit of detection (LOD), 8 µM. The sensor responded negligibly to various interfering species like glucose, uric acid and ascorbic acid. This sensor was applied successfully for determining urea in real water samples such as mineral water, tap water and river water with acceptable recovery. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Proteolytic Activity of the 26S Proteasome is required for the Meiotic Resumption, Germinal Vesicle Breakdown and Cumulus Expansion of Porcine Cumulus-Oocyte Complexes Matured In Vitro

    Czech Academy of Sciences Publication Activity Database

    Yi, Y. J.; Nagyová, Eva; Manandhar, G.; Procházka, Radek; Šutovsky, M.; Park, C. S.; Šutovský, P.

    2008-01-01

    Roč. 78, - (2008), s. 115-126 ISSN 0006-3363 R&D Projects: GA ČR GA305/05/0960 Institutional research plan: CEZ:AV0Z50450515 Keywords : cumulus expansion * FSH * germinal vesicle breakdown Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.469, year: 2008

  15. Proteasomal activity has multiple functions in oocyte meiosis, in cumulus expansion, in synthesis and processing of cumulus extracellular matrix and steroidogenesis

    Czech Academy of Sciences Publication Activity Database

    Nagyová, Eva

    2014-01-01

    Roč. 3, č. 2 (2014), s. 163-163 ISSN 2161-1017. [International Conference on Endocrinology /2./. 20.10.2014-22.10.2014, Chicago] Institutional support: RVO:67985904 Keywords : oocyte-cumulus complexes Subject RIV: EB - Genetics ; Molecular Biology

  16. Effects of TGF-beta and GDF-9 on cumulus expension and progesterone production by oocytectomized oocyte-cumulus cell complexes

    Czech Academy of Sciences Publication Activity Database

    Vanderhyden, B. C.; Nagyová, Eva; Dhawan, D.

    2001-01-01

    Roč. 64, č. 1 (2001), s. 56 ISSN 0006-3363. [Society for the Study of Reproduction - Annual Meeting /34./. 28.07.2001-01.08.2001, Ottawa] Institutional research plan: CEZ:AV0Z5045916 Keywords : cumulus cells * oocytes Subject RIV: EB - Genetics ; Molecular Biology

  17. Spermatozoa of the shrew, Suncus murinus, undergo the acrosome reaction and then selectively kill cells in penetrating the cumulus oophorus.

    Science.gov (United States)

    Kaneko, T; Iida, H; Bedford, J M; Mōri, T

    2001-08-01

    In the musk shrew, Suncus murinus (and other shrews), the cumulus oophorus is ovulated as a discrete, compact, matrix-free ball of cells linked by specialized junctions. In examining how they penetrate the cumulus, Suncus spermatozoa were observed to first bind consistently by the ventral face over the acrosomal region to the exposed smooth surface of a peripheral cumulus cell. This was apparently followed by point fusions between the plasma and outer acrosomal membranes. Thereafter, spermatozoa without acrosomes were observed within cumulus cells that displayed signs of necrosis, as did some radially neighboring cumulus cells linked by zona adherens and gap junctions. Eventually, penetration of spermatozoa as far as the perizonal space around the zona pellucida left linear tracks of locally necrotic cells flanked by normal cumulus cells. Based on these and previous observations, we conclude that the acrosome reaction in Suncus is always induced by cumulus cells, and that reacted spermatozoa penetrate the cumulus by selective invasion and killing of cumulus cells along a linear track. Loss of the acrosome also exposes an apical body/perforatorium that is covered with barbs that appear to assist reacted fertilizing spermatozoa in binding to the zona pellucida. Because fertilized eggs displayed no other spermatozoa within or bound to the zona, an efficient block to polyspermy must prevent such binding of additional spermatozoa.

  18. Melatonin-Mediated Development of Ovine Cumulus Cells, Perhaps by Regulation of DNA Methylation

    Directory of Open Access Journals (Sweden)

    Yi Fang

    2018-02-01

    Full Text Available Cumulus cells of pre-pubertal domestic animals are dysfunctional, perhaps due to age-specific epigenetic events. This study was designed to determine effects of melatonin treatment of donors on methylation modification of pre-pubertal cumulus cells. Cumulus cells from germinal vesicle stage cumulus oocyte complexes (COCs were collected from eighteen lambs which were randomly divided into control group (C and melatonin group given an 18 mg melatonin implant subcutaneous (M. Compared to the C group, the M group had higher concentrations of melatonin in plasma and follicular fluid (p < 0.05, greater superovulation, a higher proportion of fully expanded COCs, and a lower proportion of apoptotic cumulus cells (p < 0.05. Real-time PCR results showed that melatonin up-regulated expression of genes MT1, Bcl2, DNMT1, DNMT3a and DNMT3b, but down-regulated expression of genes p53, Caspase 3 and Bax (p < 0.05. Furthermore, melatonin increased FI of FITC (global methylation level on cumulus cells (p < 0.05. To understand the regulation mechanism, the DNMTs promoter methylation sequence were analyzed. Compared to the C group, although there was less methylation at two CpG sites of DNMT1 (p < 0.05 and higher methylation at two CpG sites of DNMT3a (p < 0.05, there were no significant differences in methylation of the detected DNMT1 and DNMT3a promoter regions. However, there were lower methylation levels at five CpG sites of DNMT3b, which decreased methylation of detected DNMT3b promoter region on M group (p < 0.05. In conclusion, alterations of methylation regulated by melatonin may mediate development of cumulus cells in lambs.

  19. 'Lazy' quantum ensembles

    International Nuclear Information System (INIS)

    Parfionov, George; Zapatrin, Roman

    2006-01-01

    We compare different strategies aimed to prepare an ensemble with a given density matrix ρ. Preparing the ensemble of eigenstates of ρ with appropriate probabilities can be treated as 'generous' strategy: it provides maximal accessible information about the state. Another extremity is the so-called 'Scrooge' ensemble, which is mostly stingy in sharing the information. We introduce 'lazy' ensembles which require minimal effort to prepare the density matrix by selecting pure states with respect to completely random choice. We consider two parties, Alice and Bob, playing a kind of game. Bob wishes to guess which pure state is prepared by Alice. His null hypothesis, based on the lack of any information about Alice's intention, is that Alice prepares any pure state with equal probability. Then, the average quantum state measured by Bob turns out to be ρ, and he has to make a new hypothesis about Alice's intention solely based on the information that the observed density matrix is ρ. The arising 'lazy' ensemble is shown to be the alternative hypothesis which minimizes type I error

  20. The semantic similarity ensemble

    Directory of Open Access Journals (Sweden)

    Andrea Ballatore

    2013-12-01

    Full Text Available Computational measures of semantic similarity between geographic terms provide valuable support across geographic information retrieval, data mining, and information integration. To date, a wide variety of approaches to geo-semantic similarity have been devised. A judgment of similarity is not intrinsically right or wrong, but obtains a certain degree of cognitive plausibility, depending on how closely it mimics human behavior. Thus selecting the most appropriate measure for a specific task is a significant challenge. To address this issue, we make an analogy between computational similarity measures and soliciting domain expert opinions, which incorporate a subjective set of beliefs, perceptions, hypotheses, and epistemic biases. Following this analogy, we define the semantic similarity ensemble (SSE as a composition of different similarity measures, acting as a panel of experts having to reach a decision on the semantic similarity of a set of geographic terms. The approach is evaluated in comparison to human judgments, and results indicate that an SSE performs better than the average of its parts. Although the best member tends to outperform the ensemble, all ensembles outperform the average performance of each ensemble's member. Hence, in contexts where the best measure is unknown, the ensemble provides a more cognitively plausible approach.

  1. Embryo quality predictive models based on cumulus cells gene expression

    Directory of Open Access Journals (Sweden)

    Devjak R

    2016-06-01

    Full Text Available Since the introduction of in vitro fertilization (IVF in clinical practice of infertility treatment, the indicators for high quality embryos were investigated. Cumulus cells (CC have a specific gene expression profile according to the developmental potential of the oocyte they are surrounding, and therefore, specific gene expression could be used as a biomarker. The aim of our study was to combine more than one biomarker to observe improvement in prediction value of embryo development. In this study, 58 CC samples from 17 IVF patients were analyzed. This study was approved by the Republic of Slovenia National Medical Ethics Committee. Gene expression analysis [quantitative real time polymerase chain reaction (qPCR] for five genes, analyzed according to embryo quality level, was performed. Two prediction models were tested for embryo quality prediction: a binary logistic and a decision tree model. As the main outcome, gene expression levels for five genes were taken and the area under the curve (AUC for two prediction models were calculated. Among tested genes, AMHR2 and LIF showed significant expression difference between high quality and low quality embryos. These two genes were used for the construction of two prediction models: the binary logistic model yielded an AUC of 0.72 ± 0.08 and the decision tree model yielded an AUC of 0.73 ± 0.03. Two different prediction models yielded similar predictive power to differentiate high and low quality embryos. In terms of eventual clinical decision making, the decision tree model resulted in easy-to-interpret rules that are highly applicable in clinical practice.

  2. Impacts of Wind Farms on Cumulus Cloud Development in the Central Great Plains

    Science.gov (United States)

    Mahoney, L. C.; Wagner, T. J.; L'Ecuyer, T. S.; Kulie, M.

    2014-12-01

    Cumulus clouds have a net cooling effect on the surface radiative balance by reflecting more downwelling solar radiation than absorbing upwelling terrestrial radiation. As boundary layer cumuli form from buoyant, moist plumes ascending from the surface, their growth may be hindered by the turbulent deformation of the plume by wind farms. A natural laboratory to study the impact of wind farms on cumulus formation are the states of Iowa and Nebraska. Despite their prime location for wind resources and similar synoptic forcings, regulatory issues cause these two states to vary vastly in their wind power offerings. In 2013, Iowa ranked 3rd in the nation for total megawatts installed and generates over a quarter of its electricity from wind energy, more than any other state. In contrast, Nebraska has an order of magnitude fewer turbines installed, and less than five percent of the state's electrical load is wind-generated. This variance in wind power in close proximity makes Iowa and Nebraska a prime area for initial research. This study uses Geostationary Operational Environmental Satellite (GOES) visible satellite imagery from the summer of 2009 to 2013 to investigate cumulus development in these adjacent states, as the majority of large-scale wind farms in Iowa were completed by 2009. Image reflectances in Nebraska and Iowa are compared to determine the magnitude of cumulus growth. Preliminary analysis indicates a reduction in cumulus development near the existing wind farms; a synoptic investigation of these cases will be completed to determine causality.

  3. An Economical Analytical Equation for the Integrated Vertical Overlap of Cumulus and Stratus

    Science.gov (United States)

    Park, Sungsu

    2018-03-01

    By extending the previously proposed heuristic parameterization, the author derived an analytical equation computing the overlap areas between the precipitation (or radiation) areas and the cloud areas in a cloud system consisting of cumulus and stratus. The new analytical equation is accurate and much more efficient than the previous heuristic equation, which suffers from the truncation error in association with the digitalization of the overlap areas. Global test simulations with the new analytical formula in an offline mode showed that the maximum cumulus overlap simulates more surface precipitation flux than the random cumulus overlap. On the other hand, the maximum stratus overlap simulates less surface precipitation flux than random stratus overlap, which is due to the increase in the evaporation rate of convective precipitation from the random to maximum stratus overlap. The independent precipitation approximation (IPA) marginally decreases the surface precipitation flux, implying that IPA works well with other parameterizations. In contrast to the net production rate of precipitation and surface precipitation flux that increase when the cumulus and stratus are maximally and randomly overlapped, respectively, the global mean net radiative cooling and longwave cloud radiative forcing (LWCF) increase when the cumulus and stratus are randomly overlapped. On the global average, the vertical cloud overlap exerts larger impacts on the precipitation flux than on the radiation flux. The radiation scheme taking the subgrid variability of water vapor between the cloud and clear portions into account substantially increases the global mean LWCF in tropical deep convection and midlatitude storm track regions.

  4. The Development of Storm Surge Ensemble Prediction System and Case Study of Typhoon Meranti in 2016

    Science.gov (United States)

    Tsai, Y. L.; Wu, T. R.; Terng, C. T.; Chu, C. H.

    2017-12-01

    Taiwan is under the threat of storm surge and associated inundation, which is located at a potentially severe storm generation zone. The use of ensemble prediction can help forecasters to know the characteristic of storm surge under the uncertainty of track and intensity. In addition, it can help the deterministic forecasting. In this study, the kernel of ensemble prediction system is based on COMCOT-SURGE (COrnell Multi-grid COupled Tsunami Model - Storm Surge). COMCOT-SURGE solves nonlinear shallow water equations in Open Ocean and coastal regions with the nested-grid scheme and adopts wet-dry-cell treatment to calculate potential inundation area. In order to consider tide-surge interaction, the global TPXO 7.1 tide model provides the tidal boundary conditions. After a series of validations and case studies, COMCOT-SURGE has become an official operating system of Central Weather Bureau (CWB) in Taiwan. In this study, the strongest typhoon in 2016, Typhoon Meranti, is chosen as a case study. We adopt twenty ensemble members from CWB WRF Ensemble Prediction System (CWB WEPS), which differs from parameters of microphysics, boundary layer, cumulus, and surface. From box-and-whisker results, maximum observed storm surges were located in the interval of the first and third quartile at more than 70 % gauge locations, e.g. Toucheng, Chengkung, and Jiangjyun. In conclusion, the ensemble prediction can effectively help forecasters to predict storm surge especially under the uncertainty of storm track and intensity

  5. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon

    2016-01-08

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  6. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  7. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

    2016-01-01

    The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

  8. A MODIFIED CUMULUS PARAMETERIZATION SCHEME AND ITS APPLICATION IN THE SIMULATIONS OF THE HEAVY PRECIPITATION CASES

    Institute of Scientific and Technical Information of China (English)

    PING Fan; TANG Xi-ba; YIN Lei

    2016-01-01

    According to the characteristics of organized cumulus convective precipitation in China,a cumulus parameterization scheme suitable for describing the organized convective precipitation in East Asia is presented and modified.The Kain-Fristch scheme is chosen as the scheme to be modified based on analyses and comparisons of simulated precipitation in East Asia by several commonly-used mesoscale parameterization schemes.A key dynamic parameter to dynamically control the cumulus parameterization is then proposed to improve the Kain-Fristch scheme.Numerical simulations of a typhoon case and a Mei-yu front rainfall case are carried out with the improved scheme,and the results show that the improved version performs better than the original in simulating the track and intensity of the typhoons,as well as the distribution of Mei-yu front precipitation.

  9. Improvement and implementation of a parameterization for shallow cumulus in the global climate model ECHAM5-HAM

    Science.gov (United States)

    Isotta, Francesco; Spichtinger, Peter; Lohmann, Ulrike; von Salzen, Knut

    2010-05-01

    Convection is a crucial component of weather and climate. Its parameterization in General Circulation Models (GCMs) is one of the largest sources of uncertainty. Convection redistributes moisture and heat, affects the radiation budget and transports tracers from the PBL to higher levels. Shallow convection is very common over the globe, in particular over the oceans in the trade wind regions. A recently developed shallow convection scheme by von Salzen and McFarlane (2002) is implemented in the ECHAM5-HAM GCM instead of the standard convection scheme by Tiedtke (1989). The scheme of von Salzen and McFarlane (2002) is a bulk parameterization for an ensemble of transient shallow cumuli. A life cycle is considered, as well as inhomogeneities in the horizontal distribution of in-cloud properties due to mixing. The shallow convection scheme is further developed to take the ice phase and precipitation in form of rain and snow into account. The double moment microphysics scheme for cloud droplets and ice crystals implemented is consistent with the stratiform scheme and with the other types of convective clouds. The ice phase permits to alter the criterion to distinguish between shallow convection and the other two types of convection, namely deep and mid-level, which are still calculated by the Tiedtke (1989) scheme. The lunching layer of the test parcel in the shallow convection scheme is chosen as the one with maximum moist static energy in the three lowest levels. The latter is modified to the ``frozen moist static energy'' to account for the ice phase. Moreover, tracers (e.g. aerosols) are transported in the updraft and scavenged in and below clouds. As a first test of the performance of the new scheme and the interaction with the rest of the model, the Barbados Oceanographic and Meteorological EXperiment (BOMEX) and the Rain In Cumulus over the Ocean experiment (RICO) case are simulated with the single column model (SCM) and the results are compared with large eddy

  10. Organization of the expanded cumulus-extracellular matrix in preovulatory follicles: arole for inter-alpha-trypsin inhibitor.

    Czech Academy of Sciences Publication Activity Database

    Nagyová, Eva

    2015-01-01

    Roč. 49, č. 1 (2015), s. 37-45 ISSN 1210-0668 R&D Projects: GA ČR GA305/05/0960 Institutional support: RVO:67985904 Keywords : cumulus expansion * cumulus-extracellular matrix * hyaluronan Subject RIV: ED - Physiology

  11. Bovine cumulus-granulosa cells contain biologically active retinoid receptors that can respond to retinoic acid

    Directory of Open Access Journals (Sweden)

    Malayer Jerry

    2003-11-01

    Full Text Available Abstract Retinoids, a class of compounds that include retinol and its metabolite, retinoic acid, are absolutely essential for ovarian steroid production, oocyte maturation, and early embryogenesis. Previous studies have detected high concentrations of retinol in bovine large follicles. Further, administration of retinol in vivo and supplementation of retinoic acid during in vitro maturation results in enhanced embryonic development. In the present study, we hypothesized that retinoids administered either in vivo previously or in vitro can exert receptor-mediated effects in cumulus-granulosa cells. Total RNA extracted from in vitro cultured cumulus-granulosa cells was subjected to reverse transcription polymerase chain reaction (RT-PCR and mRNA expression for retinol binding protein (RBP, retinoic acid receptor alpha (RARalpha, retinoic acid receptor beta (RARbeta, retinoic acid receptor gamma (RARgamma, retinoid X receptor alpha (RXRalpha, retinoid X receptor beta (RXRbeta, retinaldehyde dehydrogenase-2 (RALDH-2, and peroxisome proliferator activated receptor gamma (PPARgamma. Transcripts were detected for RBP, RARalpha, RARgamma, RXRalpha, RXRbeta, RALDH-2, and PPARgamma. Expression of RARbeta was not detected in cumulus-granulosa cells. Using western blotting, immunoreactive RARalpha, and RXRbeta protein was also detected in bovine cumulus-granulosa cells. The biological activity of these endogenous retinoid receptors was tested using a transient reporter assay using the pAAV-MCS-betaRARE-Luc vector. Addition of 0.5 and 1 micro molar all-trans retinoic acid significantly (P trans retinol stimulated a mild increase in reporter activity, however, the increase was not statistically significant. Based on these results we conclude that cumulus cells contain endogenously active retinoid receptors and may also be competent to synthesize retinoic acid using the precursor, retinol. These results also indirectly provide evidence that retinoids

  12. Representing Color Ensembles.

    Science.gov (United States)

    Chetverikov, Andrey; Campana, Gianluca; Kristjánsson, Árni

    2017-10-01

    Colors are rarely uniform, yet little is known about how people represent color distributions. We introduce a new method for studying color ensembles based on intertrial learning in visual search. Participants looked for an oddly colored diamond among diamonds with colors taken from either uniform or Gaussian color distributions. On test trials, the targets had various distances in feature space from the mean of the preceding distractor color distribution. Targets on test trials therefore served as probes into probabilistic representations of distractor colors. Test-trial response times revealed a striking similarity between the physical distribution of colors and their internal representations. The results demonstrate that the visual system represents color ensembles in a more detailed way than previously thought, coding not only mean and variance but, most surprisingly, the actual shape (uniform or Gaussian) of the distribution of colors in the environment.

  13. Tailored Random Graph Ensembles

    International Nuclear Information System (INIS)

    Roberts, E S; Annibale, A; Coolen, A C C

    2013-01-01

    Tailored graph ensembles are a developing bridge between biological networks and statistical mechanics. The aim is to use this concept to generate a suite of rigorous tools that can be used to quantify and compare the topology of cellular signalling networks, such as protein-protein interaction networks and gene regulation networks. We calculate exact and explicit formulae for the leading orders in the system size of the Shannon entropies of random graph ensembles constrained with degree distribution and degree-degree correlation. We also construct an ergodic detailed balance Markov chain with non-trivial acceptance probabilities which converges to a strictly uniform measure and is based on edge swaps that conserve all degrees. The acceptance probabilities can be generalized to define Markov chains that target any alternative desired measure on the space of directed or undirected graphs, in order to generate graphs with more sophisticated topological features.

  14. Aerosol microphysical and radiative effects on continental cloud ensembles

    Science.gov (United States)

    Wang, Yuan; Vogel, Jonathan M.; Lin, Yun; Pan, Bowen; Hu, Jiaxi; Liu, Yangang; Dong, Xiquan; Jiang, Jonathan H.; Yung, Yuk L.; Zhang, Renyi

    2018-02-01

    Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.

  15. Comparative Analyses of the Teaching Methods and Evaluation Practices in English Subject at Secondary School Certificate (SSC) and General Certificate of Education (GCE O-Level) in Pakistan

    Science.gov (United States)

    Behlol, Malik Ghulam; Anwar, Mohammad

    2011-01-01

    The study was conducted to compare the teaching methods and evaluation practices in English subject at secondary school certificate (SSC) and general certificate of education GCE-O-level in Pakistan. The population of the study was students, teachers and experts at SSC and 0-level in the Punjab province. Purposive and random sampling techniques…

  16. Electrooxidation of Indomethacin at Multiwalled Carbon Nanotubes-Modified GCE and Its Determination in Pharmaceutical Dosage Form and Human Biological Fluids

    OpenAIRE

    Sataraddi, Sanjeevaraddi R.; Patil, Shreekant M.; Bagoji, Atmanand M.; Pattar, Vijay P.; Nandibewoor, Sharanappa T.

    2014-01-01

    A simple, rapid, selective, and sensitive electrochemical method for the direct determination of indomethacin was developed. The electrochemical behavior of indomethacin was carried at multiwalled carbon nanotube- (MWCNTs-) modified glassy carbon electrode (GCE). The cyclic voltammetric results indicated that MWCNT-modified glassy carbon electrode remarkably enhanced electrocatalytic activity towards the oxidation of indomethacin in slightly acidic solutions. It led to a considerable improvem...

  17. Inhibitory effect of cadmium and tobacco alkaloids on expansion of porcine oocyte-cumulus complexes

    Czech Academy of Sciences Publication Activity Database

    Mlynarčíková, A.; Scsuková, S.; Vršanská, S.; Nagyová, Eva; Ficková, M.; Kolena, J.

    2004-01-01

    Roč. 12, - (2004), S62-64 ISSN 1210-7778 R&D Projects: GA AV ČR IAA5045102 Grant - others:VEGA(XX) 2/7179/20; VEGA(XX) 2/3052/23 Institutional research plan: CEZ:AV0Z5045916 Keywords : porcine follicles * cumulus expansion * hyaluronic acid Subject RIV: ED - Physiology

  18. A simple method for assessing hyaluronic acid production by cumulus-oocyte complexes

    Czech Academy of Sciences Publication Activity Database

    Zámostná, K.; Nevoral, J.; Kott, T.; Procházka, Radek; Orsák, M.; Šulc, M.; Pajkošová, V.; Pavlík, V.; Žalmanová, T.; Hošková, K.; Jílek, F.; Klein, P.

    2016-01-01

    Roč. 61, č. 6 (2016), s. 251-261 ISSN 1212-1819 R&D Projects: GA MZe(CZ) QJ1510138 Institutional support: RVO:67985904 Keywords : oocyte * meiotic maturation * cumulus expanssion Subject RIV: GI - Animal Husbandry ; Breeding Impact factor: 0.741, year: 2016

  19. Components of Cigarette Smoke Inhibit Expansion of Oocyte-Cumulus Comlexes from Porcine Follicles

    Czech Academy of Sciences Publication Activity Database

    Vršanská, S.; Nagyová, Eva; Mlynarčíková, A.; Ficková, M.; Kolena, J.

    2003-01-01

    Roč. 52, č. 3 (2003), s. 383-387 ISSN 0862-8408 R&D Projects: GA AV ČR IAA5045102 Institutional research plan: CEZ:AV0Z5045916 Keywords : porcine ovary * cigarette alkaloids * cumulus expansion Subject RIV: ED - Physiology Impact factor: 0.939, year: 2003

  20. Effects of Mitochondrial Uncoupling Protein 2 Inhibition by Genipin in Human Cumulus Cells

    Directory of Open Access Journals (Sweden)

    Hongshan Ge

    2015-01-01

    Full Text Available UCP2 plays a physiological role by regulating mitochondrial biogenesis, maintaining energy balance, ROS elimination, and regulating cellular autophagy in numerous tissues. But the exact roles of UCP2 in cumulus cells are still not clear. Genipin, a special UCP2 inhibitor, was added into the cultural medium to explore the roles of UCP2 in human cumulus cells. There were no significant differences in ATP and mitochondrial membrane potential levels in cumulus cells from UCP2 inhibiting groups as compared with the control. The levels of ROS and Mn-SOD were markedly elevated after UCP2 inhibited Genipin. However, the ratio of reduced GSH to GSSG significantly declined after treatment with Genipin. UCP2 inhibition by Genipin also resulted in obvious increase in the active caspase-3, which accompanied the decline of caspase-3 mRNA. The level of progesterone in culture medium declined obviously after Genipin treatment. But there was no significant difference in estradiol concentrations. This study indicated that UCP2 is expressed in human cumulus cells and plays important roles on mediate ROS production, apoptotic process, and steroidogenesis, suggesting UCP2 may be involved in regulation of follicle development and oocyte maturation and quality.

  1. New pathway of stratocumulus to cumulus transition via aerosol-cloud-precipitation interaction

    Science.gov (United States)

    Yamaguchi, T.; Feingold, G.; Kazil, J.

    2017-12-01

    The stratocumulus to cumulus transition (SCT) is typically considered to be a slow, multi-day process, caused primarily by dry air entrainment associated with overshooting cumulus rising under stratocumulus, with minor influence of precipitation. In this presentation, we show rapid SCT induced by a strong precipitation-induced modulation with Lagrangian SCT large eddy simulations. A large eddy model is coupled with a two-moment bulk microphysics scheme that predicts aerosol and droplet number concentrations. Moderate aerosol concentrations (100-250 cm-3) produce little to no drizzle from the stratocumulus deck. Large amounts of rain eventually form and wash out stratocumulus and much of the aerosol, and a cumulus state appears for approximately 10 hours. Initiation of strong rain formation is identified in penetrative cumulus clouds which are much deeper than stratocumulus, and they are able to condense large amounts of water. We show that prediction of cloud droplet number is necessary for this fast SCT since it is a result of a positive feedback of collision-coalescence induced aerosol depletion enhancing drizzle formation. Simulations with fixed droplet concentrations that bracket the time varying aerosol/drop concentrations are therefore not representative of the role of drizzle in the SCT.

  2. The possible FAT1-mediated apoptotic pathways in porcine cumulus cells

    NARCIS (Netherlands)

    Wu, Xinhui; Fu, Yao; Liu, Chang; Chai, Menglong; Chen, Chengzhen; Dai, Lisheng; Gao, Yan; Jiang, Hao; Zhang, Jiabao

    Porcine cumulus cells are localized around oocytes and act as a specific type of granulosa that plays essential roles in the development and maturation of oocytes, the development and atresia of follicles, and the development of embryos. Studies of FAT1 have demonstrated its functions in cell-cell

  3. Imprinting and recalling cortical ensembles.

    Science.gov (United States)

    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.

  4. GCE Data Toolbox for MATLAB - a software framework for automating environmental data processing, quality control and documentation

    Science.gov (United States)

    Sheldon, W.; Chamblee, J.; Cary, R. H.

    2013-12-01

    Environmental scientists are under increasing pressure from funding agencies and journal publishers to release quality-controlled data in a timely manner, as well as to produce comprehensive metadata for submitting data to long-term archives (e.g. DataONE, Dryad and BCO-DMO). At the same time, the volume of digital data that researchers collect and manage is increasing rapidly due to advances in high frequency electronic data collection from flux towers, instrumented moorings and sensor networks. However, few pre-built software tools are available to meet these data management needs, and those tools that do exist typically focus on part of the data management lifecycle or one class of data. The GCE Data Toolbox has proven to be both a generalized and effective software solution for environmental data management in the Long Term Ecological Research Network (LTER). This open source MATLAB software library, developed by the Georgia Coastal Ecosystems LTER program, integrates metadata capture, creation and management with data processing, quality control and analysis to support the entire data lifecycle. Raw data can be imported directly from common data logger formats (e.g. SeaBird, Campbell Scientific, YSI, Hobo), as well as delimited text files, MATLAB files and relational database queries. Basic metadata are derived from the data source itself (e.g. parsed from file headers) and by value inspection, and then augmented using editable metadata templates containing boilerplate documentation, attribute descriptors, code definitions and quality control rules. Data and metadata content, quality control rules and qualifier flags are then managed together in a robust data structure that supports database functionality and ensures data validity throughout processing. A growing suite of metadata-aware editing, quality control, analysis and synthesis tools are provided with the software to support managing data using graphical forms and command-line functions, as well as

  5. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon

    2016-06-14

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  6. Multilevel ensemble Kalman filtering

    KAUST Repository

    Hoel, Hakon; Law, Kody J. H.; Tempone, Raul

    2016-01-01

    This work embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discrete-time observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. The resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.

  7. Cumulus expansion, nuclear maturation and connexin 43, cyclooxygenase-2 and FSH receptor mRNA expression in equine cumulus-oocyte complexes cultured in vitro in the presence of FSH and precursors for hyaluronic acid synthesis

    Directory of Open Access Journals (Sweden)

    Aiudi Giulio

    2004-06-01

    Full Text Available Abstract The aim of this study was to investigate cumulus expansion, nuclear maturation and expression of connexin 43, cyclooxygenase-2 and FSH receptor transcripts in equine cumuli oophori during in vivo and in vitro maturation in the presence of equine FSH (eFSH and precursors for hyaluronic acid synthesis. Equine cumulus-oocyte complexes (COC were cultured in a control defined medium supplemented with eFSH (0 to 5 micrograms/ml, Fetal Calf Serum (FCS, precursors for hyaluronic acid synthesis or glutamine according to the experiments. After in vitro maturation, the cumulus expansion rate was increased with 1 microgram/ml eFSH, and was the highest with 20% FCS. It was not influenced by precursors for hyaluronic acid synthesis or glutamine. The expression of transcripts related to cumulus expansion was analyzed in equine cumulus cells before maturation, and after in vivo and in vitro maturation, by using reverse transcription-polymerase chain reaction (RT-PCR with specific primers. Connexin 43, cyclooxygenase-2 (COX-2 and FSH receptor (FSHr mRNA were detected in equine cumulus cells before and after maturation. Their level did not vary during in vivo or in vitro maturation and was influenced neither by FSH nor by precursors for hyaluronic acid synthesis. Results indicate that previously reported regulation of connexin 43 and COX-2 proteins during equine COC maturation may involve post-transcriptional mechanisms.

  8. Diversity in random subspacing ensembles

    NARCIS (Netherlands)

    Tsymbal, A.; Pechenizkiy, M.; Cunningham, P.; Kambayashi, Y.; Mohania, M.K.; Wöß, W.

    2004-01-01

    Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. It was shown experimentally and theoretically that in order for an ensemble to be effective, it should consist of classifiers having diversity in their predictions. A number of ways are

  9. PSO-Ensemble Demo Application

    DEFF Research Database (Denmark)

    2004-01-01

    Within the framework of the PSO-Ensemble project (FU2101) a demo application has been created. The application use ECMWF ensemble forecasts. Two instances of the application are running; one for Nysted Offshore and one for the total production (except Horns Rev) in the Eltra area. The output...

  10. New concept of statistical ensembles

    International Nuclear Information System (INIS)

    Gorenstein, M.I.

    2009-01-01

    An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution is introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.

  11. Ensembl 2002: accommodating comparative genomics.

    Science.gov (United States)

    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.

  12. Determination of the vapor–liquid transition of square-well particles using a novel generalized-canonical-ensemble-based method

    International Nuclear Information System (INIS)

    Zhao Liang; Tu Yu-Song; Xu Shun; Zhou Xin

    2017-01-01

    The square-well (SW) potential is one of the simplest pair potential models and its phase behavior has been clearly revealed, therefore it has become a benchmark for checking new theories or numerical methods. We introduce the generalized canonical ensemble (GCE) into the isobaric replica exchange Monte Carlo (REMC) algorithm to form a novel isobaric GCE-REMC method, and apply it to the study of vapor–liquid transition of SW particles. It is validated that this method can reproduce the vapor–liquid diagram of SW particles by comparing the estimated vapor–liquid binodals and the critical point with those from the literature. The notable advantage of this method is that the unstable vapor–liquid coexisting states, which cannot be detected using conventional sampling techniques, are accessed with a high sampling efficiency. Besides, the isobaric GCE-REMC method can visit all the possible states, including stable, metastable or unstable states during the phase transition over a wide pressure range, providing an effective pathway to understand complex phase transitions during the nucleation or crystallization process in physical or biological systems. (paper)

  13. NASA's EOSDIS Cumulus: Ingesting, Archiving, Managing, and Distributing from Commercial Cloud

    Science.gov (United States)

    Baynes, K.; Ramachandran, R.; Pilone, D.; Quinn, P.; Schuler, I.; Gilman, J.; Jazayeri, A.

    2017-12-01

    NASA's Earth Observing System Data and Information System (EOSDIS) has been working towards a vision of a cloud-based, highly-flexible, ingest, archive, management, and distribution system for its ever-growing and evolving data holdings. This system, Cumulus, is emerging from its prototyping stages and is poised to make a huge impact on how NASA manages and disseminates its Earth science data. This talk will outline the motivation for this work, present the achievements and hurdles of the past 18 months and will chart a course for the future expansion of the Cumulus expansion. We will explore on not just the technical, but also the socio-technical challenges that we face in evolving a system of this magnitude into the cloud and how we are rising to meet those challenges through open collaboration and intentional stakeholder engagement.

  14. NASA's EOSDIS Cumulus: Ingesting, Archiving, Managing, and Distributing Earth Science Data from the Commercial Cloud

    Science.gov (United States)

    Baynes, Katie; Ramachandran, Rahul; Pilone, Dan; Quinn, Patrick; Gilman, Jason; Schuler, Ian; Jazayeri, Alireza

    2017-01-01

    NASA's Earth Observing System Data and Information System (EOSDIS) has been working towards a vision of a cloud-based, highly-flexible, ingest, archive, management, and distribution system for its ever-growing and evolving data holdings. This system, Cumulus, is emerging from its prototyping stages and is poised to make a huge impact on how NASA manages and disseminates its Earth science data. This talk will outline the motivation for this work, present the achievements and hurdles of the past 18 months and will chart a course for the future expansion of the Cumulus expansion. We will explore on not just the technical, but also the socio-technical challenges that we face in evolving a system of this magnitude into the cloud and how we are rising to meet those challenges through open collaboration and intentional stakeholder engagement.

  15. The role of cloud-scale resolution on radiative properties of oceanic cumulus clouds

    International Nuclear Information System (INIS)

    Kassianov, Evgueni; Ackerman, Thomas; Kollias, Pavlos

    2005-01-01

    Both individual and combined effects of the horizontal and vertical variability of cumulus clouds on solar radiative transfer are investigated using a two-dimensional (x- and z-directions) cloud radar dataset. This high-resolution dataset of typical fair-weather marine cumulus is derived from ground-based 94GHz cloud radar observations. The domain-averaged (along x-direction) radiative properties are computed by a Monte Carlo method. It is shown that (i) different cloud-scale resolutions can be used for accurate calculations of the mean absorption, upward and downward fluxes; (ii) the resolution effects can depend strongly on the solar zenith angle; and (iii) a few cloud statistics can be successfully applied for calculating the averaged radiative properties

  16. On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

    KAUST Repository

    Luo, Xiaodong

    2010-09-19

    The ensemble square root filter (EnSRF) [1, 2, 3, 4] is a popular method for data assimilation in high dimensional systems (e.g., geophysics models). Essentially the EnSRF is a Monte Carlo implementation of the conventional Kalman filter (KF) [5, 6]. It is mainly different from the KF at the prediction steps, where it is some ensembles, rather then the means and covariance matrices, of the system state that are propagated forward. In doing this, the EnSRF is computationally more efficient than the KF, since propagating a covariance matrix forward in high dimensional systems is prohibitively expensive. In addition, the EnSRF is also very convenient in implementation. By propagating the ensembles of the system state, the EnSRF can be directly applied to nonlinear systems without any change in comparison to the assimilation procedures in linear systems. However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

  17. Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review

    Science.gov (United States)

    Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela

    2017-11-01

    Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using

  18. Transition Metal Chelator Induces Progesterone Production in Mouse Cumulus-Oocyte Complexes and Corpora Lutea.

    Science.gov (United States)

    Tian, X; Anthony, K; Diaz, Francisco J

    2017-04-01

    Progesterone production is upregulated in granulosa cells (cumulus and mural) after the LH surge, but the intra-follicular mechanisms regulating this transition are not completely known. Recent findings show that the transition metal chelator, N,N,N',N'-tetrakis-(2-pyridylmethyl)-ethylenediamine (TPEN), impairs ovarian function. In this study, we provide evidence that chelating transition metals, including zinc, enhances progesterone production. The findings show that TPEN (transition metal chelator) increases abundance of Cyp11a1 and Star messenger RNA (mRNA) between 8- and 20-fold and progesterone production more than 3-fold in cultured cumulus-oocyte complexes (COC). Feeding a zinc-deficient diet for 10 days, but not 3 days, increased Star, Hsd3b, and prostaglandin F2 alpha receptor (Ptgfr) mRNA ~2.5-fold, suggesting that the effect of TPEN is through modulation of zinc availability. Progesterone from cumulus cells promotes oocyte developmental potential. Blocking progesterone production with epostane during maturation reduced subsequent blastocyst formation from 89 % in control to 18 % in epostane-treated complexes, but supplementation with progesterone restored blastocyst developmental potential to 94 %. Feeding a zinc-deficient diet for 5 days before ovulation did not affect the number of CL, STAR protein, or serum progesterone. However, incubating luteal tissue with TPEN increased abundance of Star, Hsd3b, and Ptgfr mRNA 2-3-fold and increased progesterone production 3-fold. TPEN is known to abolish SMAD2/3 signaling in cumulus cells. However, treatment of COC with the SMAD2/3 phosphorylation inhibitor, SB421542, did not by itself induce steroidogenic transcripts but did potentiate EGF-induced Star mRNA expression. Collectively, the results show that depletion of transition metals with TPEN acutely enhances progesterone biosynthesis in COC and luteal tissue.

  19. Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review

    Science.gov (United States)

    Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela

    Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using

  20. Understanding aerosol-cloud interactions in the development of orographic cumulus congestus during IPHEx

    Science.gov (United States)

    Barros, A. P.; Duan, Y.

    2017-12-01

    A new cloud parcel model (CPM) including activation, condensation, collision-coalescence, and lateral entrainment processes is presented here to investigate aerosol-cloud interactions (ACI) in cumulus development prior to rainfall onset. The CPM was employed along with ground based radar and surface aerosol measurements to predict the vertical structure of cloud formation at early stages and evaluated against airborne observations of cloud microphysics and thermodynamic conditions during the Integrated Precipitation and Hydrology Experiment (IPHEx) over the Southern Appalachian Mountains. Further, the CPM was applied to explore the space of ACI physical parameters controlling cumulus congestus growth not available from measurements, and to examine how variations in aerosol properties and microphysical processes influence the evolution and thermodynamic state of clouds over complex terrain via sensitivity analysis. Modeling results indicate that simulated spectra with a low value of condensation coefficient (0.01) are in good agreement with IPHEx aircraft observations around the same altitude. This is in contrast with high values reported in previous studies assuming adiabatic conditions. Entrainment is shown to govern the vertical development of clouds and the change of droplet numbers with height, and the sensitivity analysis suggests that there is a trade-off between entrainment strength and condensation process. Simulated CDNC also exhibits high sensitivity to variations in initial aerosol concentration at cloud base, but weak sensitivity to aerosol hygroscopicity. Exploratory multiple-parcel simulations capture realistic time-scales of vertical development of cumulus congestus (deeper clouds and faster droplet growth). These findings provide new insights into determinant factors of mid-day cumulus congestus formation that can explain a large fraction of warm season rainfall in mountainous regions.

  1. GHI calculation sensitivity on microphysics, land- and cumulus parameterization in WRF over the Reunion Island

    Science.gov (United States)

    De Meij, A.; Vinuesa, J.-F.; Maupas, V.

    2018-05-01

    The sensitivity of different microphysics and dynamics schemes on calculated global horizontal irradiation (GHI) values in the Weather Research Forecasting (WRF) model is studied. 13 sensitivity simulations were performed for which the microphysics, cumulus parameterization schemes and land surface models were changed. Firstly we evaluated the model's performance by comparing calculated GHI values for the Base Case with observations for the Reunion Island for 2014. In general, the model calculates the largest bias during the austral summer. This indicates that the model is less accurate in timing the formation and dissipation of clouds during the summer, when higher water vapor quantities are present in the atmosphere than during the austral winter. Secondly, the model sensitivity on changing the microphysics, cumulus parameterization and land surface models on calculated GHI values is evaluated. The sensitivity simulations showed that changing the microphysics from the Thompson scheme (or Single-Moment 6-class scheme) to the Morrison double-moment scheme, the relative bias improves from 45% to 10%. The underlying reason for this improvement is that the Morrison double-moment scheme predicts the mass and number concentrations of five hydrometeors, which help to improve the calculation of the densities, size and lifetime of the cloud droplets. While the single moment schemes only predicts the mass for less hydrometeors. Changing the cumulus parameterization schemes and land surface models does not have a large impact on GHI calculations.

  2. Juvenile hormone counteracts the bHLH-PAS transcription factors MET and GCE to prevent caspase-dependent programmed cell death in Drosophila.

    Science.gov (United States)

    Liu, Ying; Sheng, Zhentao; Liu, Hanhan; Wen, Di; He, Qianyu; Wang, Sheng; Shao, Wei; Jiang, Rong-Jing; An, Shiheng; Sun, Yaning; Bendena, William G; Wang, Jian; Gilbert, Lawrence I; Wilson, Thomas G; Song, Qisheng; Li, Sheng

    2009-06-01

    Juvenile hormone (JH) regulates many developmental and physiological events in insects, but its molecular mechanism remains conjectural. Here we report that genetic ablation of the corpus allatum cells of the Drosophila ring gland (the JH source) resulted in JH deficiency, pupal lethality and precocious and enhanced programmed cell death (PCD) of the larval fat body. In the fat body of the JH-deficient animals, Dronc and Drice, two caspase genes that are crucial for PCD induced by the molting hormone 20-hydroxyecdysone (20E), were significantly upregulated. These results demonstrated that JH antagonizes 20E-induced PCD by restricting the mRNA levels of Dronc and Drice. The antagonizing effect of JH on 20E-induced PCD in the fat body was further confirmed in the JH-deficient animals by 20E treatment and RNA interference of the 20E receptor EcR. Moreover, MET and GCE, the bHLH-PAS transcription factors involved in JH action, were shown to induce PCD by upregulating Dronc and Drice. In the Met- and gce-deficient animals, Dronc and Drice were downregulated, whereas in the Met-overexpression fat body, Dronc and Drice were significantly upregulated leading to precocious and enhanced PCD, and this upregulation could be suppressed by application of the JH agonist methoprene. For the first time, we demonstrate that JH counteracts MET and GCE to prevent caspase-dependent PCD in controlling fat body remodeling and larval-pupal metamorphosis in Drosophila.

  3. Contact planarization of ensemble nanowires

    Science.gov (United States)

    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.

  4. Aberrant expression of long noncoding RNAs in cumulus cells isolated from PCOS patients.

    Science.gov (United States)

    Huang, Xin; Hao, Cuifang; Bao, Hongchu; Wang, Meimei; Dai, Huangguan

    2016-01-01

    To describe the long noncoding RNA (lncRNA) profiles in cumulus cells isolated from polycystic ovary syndrome (PCOS) patients by employing a microarray and in-depth bioinformatics analysis. This information will help us understand the occurrence and development of PCOS. In this study, we used a microarray to describe lncRNA profiles in cumulus cells isolated from ten patients (five PCOS and five normal women). Several differentially expressed lncRNAs were chosen to validate the microarray results by quantitative RT-PCR (qRT-PCR). Then, the differentially expressed lncRNAs were classified into three subgroups (HOX loci lncRNA, enhancer-like lncRNA, and lincRNA) to deduce their potential features. Furthermore, a lncRNA/mRNA co-expression network was constructed by using the Cytoscape software (V2.8.3, http://www.cytoscape.org/ ). We observed that 623 lncRNAs and 260 messenger RNAs (mRNAs) were significantly up- or down-regulated (≥2-fold change), and these differences could be used to discriminate cumulus cells of PCOS from those of normal patients. Five differentially expressed lncRNAs (XLOC_011402, ENST00000454271, ENST00000433673, ENST00000450294, and ENST00000432431) were selected to validate the microarray results using quantitative RT-PCR (qRT-PCR). The qRT-PCR results were consistent with the microarray data. Further analysis indicated that many differentially expressed lncRNAs were transcribed from chromosome 2 and may act as enhancers to regulate their neighboring protein-coding genes. Forty-three lncRNAs and 29 mRNAs were used to construct the coding-non-coding gene co-expression network. Most pairs positively correlated, and one mRNA correlated with one or more lncRNAs. Our study is the first to determine genome-wide lncRNA expression patterns in cumulus cells isolated from PCOS patients by microarray. The results show that clusters of lncRNAs were aberrantly expressed in cumulus cells of PCOS patients compared with those of normal women, which revealed

  5. On Ensemble Nonlinear Kalman Filtering with Symmetric Analysis Ensembles

    KAUST Repository

    Luo, Xiaodong; Hoteit, Ibrahim; Moroz, Irene M.

    2010-01-01

    However, by adopting the Monte Carlo method, the EnSRF also incurs certain sampling errors. One way to alleviate this problem is to introduce certain symmetry to the ensembles, which can reduce the sampling errors and spurious modes in evaluation of the means and covariances of the ensembles [7]. In this contribution, we present two methods to produce symmetric ensembles. One is based on the unscented transform [8, 9], which leads to the unscented Kalman filter (UKF) [8, 9] and its variant, the ensemble unscented Kalman filter (EnUKF) [7]. The other is based on Stirling’s interpolation formula (SIF), which results in the divided difference filter (DDF) [10]. Here we propose a simplified divided difference filter (sDDF) in the context of ensemble filtering. The similarity and difference between the sDDF and the EnUKF will be discussed. Numerical experiments will also be conducted to investigate the performance of the sDDF and the EnUKF, and compare them to a well‐established EnSRF, the ensemble transform Kalman filter (ETKF) [2].

  6. Ensemble manifold regularization.

    Science.gov (United States)

    Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng

    2012-06-01

    We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.

  7. The unusual state of the cumulus oophorus and of sperm behaviour within it, in the musk shrew, Suncus murinus.

    Science.gov (United States)

    Bedford, J M; Mori, T; Oda, S

    1997-05-01

    In the musk shrew, Suncus murinus, the behaviour of the cumulus-egg complex and its interaction with spermatozoa were unusual in several respects. The cumulus oophorus was ovulated about 15.5 h after mating or treatment with hCG as a hyaluronidase-insensitive matrix-free ball of cells which remained for relatively long periods of about 14 h around fertilized, and for about 24 h around unfertilized eggs. As a probable function of the small number of up to about 10 or 20 spermatozoa that generally reached the oviduct ampulla from isthmic crypts, there was often a delay of up to 10 h after ovulation before most eggs were penetrated. Soon after ovulation, however, the corona radiata retreated progressively from the zona pellucida, creating a closed perizonal space within the cumulus oophorus. Usually, most spermatozoa that did reach the ampulla were found within a cumulus and generally within that perizonal space. However, whereas the acrosome was intact among the few free ampullary spermatozoa, and in those adhering to the zona of cumulus-free eggs after delayed mating, all spermatozoa seen moving within the cumulus or adhering to the zona of unfertilized eggs had shed the giant acrosome. In accord with current observations in other shrews, the cumulus in Suncus may therefore function not only to sequester spermatozoa, but also as an essential mediator of fertilization-probably by inducing the acrosome reaction. In the absence of the acrosomal carapace that expresses the zona receptors in most mammals, fertilizing Suncus spermatozoa could use an unusual array of barbs on the exposed perforatorium to attach to the zona pellucida.

  8. The Ensembl genome database project.

    Science.gov (United States)

    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.

  9. The canonical ensemble redefined - 1: Formalism

    International Nuclear Information System (INIS)

    Venkataraman, R.

    1984-12-01

    For studying the thermodynamic properties of systems we propose an ensemble that lies in between the familiar canonical and microcanonical ensembles. We point out the transition from the canonical to microcanonical ensemble and prove from a comparative study that all these ensembles do not yield the same results even in the thermodynamic limit. An investigation of the coupling between two or more systems with these ensembles suggests that the state of thermodynamical equilibrium is a special case of statistical equilibrium. (author)

  10. Heat stress effects on the cumulus cells surrounding the bovine oocyte during maturation: altered matrix metallopeptidase 9 and progesterone production.

    Science.gov (United States)

    Rispoli, L A; Payton, R R; Gondro, C; Saxton, A M; Nagle, K A; Jenkins, B W; Schrick, F N; Edwards, J L

    2013-08-01

    When the effects of heat stress are detrimental during maturation, cumulus cells are intimately associated with the oocyte. To determine the extent to which heat stress affects these cells, in this study, transcriptome profiles of the cumulus that surrounded control and heat-stressed oocytes (41 °C during the first 12 h only and then shifted back to 38.5 °C) during in vitro maturation (IVM) were compared using Affymetrix bovine microarrays. The comparison of cumulus-derived profiles revealed a number of transcripts whose levels were increased (n=11) or decreased (n=13) ≥ twofold after heat stress exposure (P1.7-fold decrease in the protein levels of latent matrix metallopeptidase 9 (proMMP9). Heat-induced reductions in transcript levels were noted at 6 h IVM with reductions in proMMP9 protein levels at 18 h IVM (P=0.0002). Independent of temperature, proMMP9 levels at 24 h IVM were positively correlated with the development rate of blastocysts (R²=0.36; P=0.002). The production of progesterone increased during maturation; heat-induced increases were evident by 12 h IVM (P=0.002). Both MMP9 and progesterone are associated with the developmental competence of the oocyte; thus, it seems plausible for some of the negative consequences of heat stress on the cumulus-oocyte complex to be mediated through heat-induced perturbations occurring in the surrounding cumulus.

  11. Structural characterization of PTX3 disulfide bond network and its multimeric status in cumulus matrix organization.

    Science.gov (United States)

    Inforzato, Antonio; Rivieccio, Vincenzo; Morreale, Antonio P; Bastone, Antonio; Salustri, Antonietta; Scarchilli, Laura; Verdoliva, Antonio; Vincenti, Silvia; Gallo, Grazia; Chiapparino, Caterina; Pacello, Lucrezia; Nucera, Eleonora; Serlupi-Crescenzi, Ottaviano; Day, Anthony J; Bottazzi, Barbara; Mantovani, Alberto; De Santis, Rita; Salvatori, Giovanni

    2008-04-11

    PTX3 is an acute phase glycoprotein that plays key roles in resistance to certain pathogens and in female fertility. PTX3 exerts its functions by interacting with a number of structurally unrelated molecules, a capacity that is likely to rely on its complex multimeric structure stabilized by interchain disulfide bonds. In this study, PAGE analyses performed under both native and denaturing conditions indicated that human recombinant PTX3 is mainly composed of covalently linked octamers. The network of disulfide bonds supporting this octameric assembly was resolved by mass spectrometry and Cys to Ser site-directed mutagenesis. Here we report that cysteine residues at positions 47, 49, and 103 in the N-terminal domain form three symmetric interchain disulfide bonds stabilizing four protein subunits in a tetrameric arrangement. Additional interchain disulfide bonds formed by the C-terminal domain cysteines Cys(317) and Cys(318) are responsible for linking the PTX3 tetramers into octamers. We also identified three intrachain disulfide bonds within the C-terminal domain that we used as structural constraints to build a new three-dimensional model for this domain. Previously it has been shown that PTX3 is a key component of the cumulus oophorus extracellular matrix, which forms around the oocyte prior to ovulation, because cumuli from PTX3(-/-) mice show defective matrix organization. Recombinant PTX3 is able to restore the normal phenotype ex vivo in cumuli from PTX3(-/-) mice. Here we demonstrate that PTX3 Cys to Ser mutants, mainly assembled into tetramers, exhibited wild type rescue activity, whereas a mutant, predominantly composed of dimers, had impaired functionality. These findings indicate that protein oligomerization is essential for PTX3 activity within the cumulus matrix and implicate PTX3 tetramers as the functional molecular units required for cumulus matrix organization and stabilization.

  12. Cumulus cells steroidogenesis is influenced by the degree of oocyte maturation

    Directory of Open Access Journals (Sweden)

    Barboni Barbara

    2003-05-01

    Full Text Available Abstract Background The possibility to predict the ability of a germ cell to properly sustain embryo development in vitro or in vivo as early as possible is undoubtedly the main problem of reproductive technologies. To date, only the achievement of nuclear maturation and cumulus expansion is feasible, as all the studies on cytoplasmic maturation are too invasive and have been complicated by the death of the cells analyzed. The authors studied the possibility to test the cytoplasmic quality of pig oocytes by evaluating their ability to produce steroidogenesis enabling factor(s. To this aim, oocytes matured under different culture conditions that allowed to obtain gradable level of cytoplasmic maturation, were used to produce conditioned media (OCM. The secretion of the factor(s in conditioned media was then recorded by evaluating the ability of the spent media to direct granulosa cells (GC steroidogenesis. Methods In order to obtain germ cells characterized by a different degree of developmental competence, selected pig oocytes from prepubertal gilts ovaries were cultured under different IVM protocols; part of the matured oocytes were used to produce OCM, while those remaining were submitted to in vitro fertilization trials to confirm their ability to sustain male pronuclear decondensation. The OCM collected were finally used on cumulus cells grown as monolayers for 5 days. The demonstration that oocytes secreted factor(s can influence GC steroidogenesis in the pig was confirmed in our lab by studying E2 and P4 production by cumulus cells monolayers using a radioimmunoassay technique. Results Monolayers obtained by growing GC surrounding the oocytes for five days represent a tool, which is practical, stable and available in most laboratories; by using this bioassay, we detected the antiluteal effect of immature oocytes, and for the first time, demonstrated that properly matured germ cells are able to direct cumulus cells steroidogenesis by

  13. Ecological Promises and Execution in hotel chains. Case: Restel Cumulus and Scandic

    OpenAIRE

    Järvenpää, Mona

    2012-01-01

    During the last decade the terms ‘eco’ and ‘green’ have created a trend in the tourism indus-try. This research focuses on two hotel chains that operate in Finland. One of the target chains is Finnish Restel Cumulus hotels and the other chain is originally Swedish, Scandic. This research studies the basic facts and the eco promises of these two hotel chains and the terms that this topic includes, for example sustainability, eco-label, ecological and eco-tourism. This research aims to find th...

  14. Quantum ensembles of quantum classifiers.

    Science.gov (United States)

    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.

  15. Role of Fas-Mediated Apoptosis and Follicle-Stimulating Hormone on the Developmental Capacity of Bovine Cumulus Oocyte Complexes in Vitro

    NARCIS (Netherlands)

    Pomar, F.J.; Roelen, B.A.J.; Slot, K.A.; Tol, van H.T.A.; Colenbrander, B.; Teerds, K.J.

    2004-01-01

    Follicular atresia is believed to be largely regulated by apoptosis. To further understand how apoptosis can affect cumulus cells and oocytes we have evaluated the incidence and regulation of apoptosis affecting bovine cumulus oocyte complexes in vitro. Expression of components of the Fas signaling

  16. Enhancement of Bovine oocyte maturation by leptin is accompanied by an upregulation in mRNA expression of leptin receptor isoforms in cumulus cells

    NARCIS (Netherlands)

    van Tol, Helena T A; van Eerdenburg, Frank J C M; Colenbrander, Ben; Roelen, Bernard A J

    In this study, the mechanisms of supposed leptin action on oocyte maturation were examined. Expression of leptin mRNA, as determined with RT-PCR, was present in oocytes but not in cumulus cells. The long isoform of the leptin receptor (ObR-L) was expressed exclusively in cumulus cells after 7 and 23

  17. Ensemble forecasting of species distributions.

    Science.gov (United States)

    Araújo, Miguel B; New, Mark

    2007-01-01

    Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately.

  18. Implication of the oligomeric state of the N-terminal PTX3 domain in cumulus matrix assembly.

    Science.gov (United States)

    Ievoli, Elena; Lindstedt, Ragnar; Inforzato, Antonio; Camaioni, Antonella; Palone, Francesca; Day, Anthony J; Mantovani, Alberto; Salvatori, Giovanni; Salustri, Antonietta

    2011-06-01

    Pentraxin 3 (PTX3) plays a key role in the formation of the hyaluronan-rich matrix of the cumulus oophorus surrounding ovulated eggs that is required for successful fertilization and female fertility. PTX3 is a multimeric protein consisting of eight identical protomers held together by a combination of non-covalent interactions and disulfide bonds. Recent findings suggest that the oligomeric status of PTX3 is important for stabilizing the cumulus matrix. Because the role of PTX3 in the cumulus resides in the unique N-terminal sequence of the protomer, we investigated further this issue by testing the ability of distinct Cys/Ser mutants of recombinant N-terminal region of PTX3 (N(_)PTX3) with different oligomeric arrangement to promote in vitro normal expansion in cumuli from Ptx3-null mice. Here we report that the dimer of the N(_)PTX3 is unable to rescue cumulus matrix organization, and that the tetrameric assembly of the protein is the minimal oligomeric state required for accomplishing this function. We have previously demonstrated that PTX3 binds to HCs of IαI and TSG-6, which are essential for cumulus matrix formation and able to interact with hyaluronan. Interestingly, here we show by solid-phase binding experiments that the dimer of the N(_)PTX3 retains the ability to bind to both IαI and TSG-6, suggesting that the octameric structure of PTX3 provides multiple binding sites for each of these ligands. These findings support the hypothesis that PTX3 contributes to cumulus matrix organization by cross-linking HA polymers through interactions with multiple HCs of IαI and/or TSG-6. The N-terminal PTX3 tetrameric oligomerization was recently reported to be also required for recognition and inhibition of FGF2. Given that this growth factor has been detected in the mammalian preovulatory follicle, we wondered whether FGF2 negatively influences cumulus expansion and PTX3 may also serve in vivo to antagonize its activity. We found that a molar excess of FGF2, above

  19. Ensemble method for dengue prediction.

    Science.gov (United States)

    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.

  20. Ensemble method for dengue prediction.

    Directory of Open Access Journals (Sweden)

    Anna L Buczak

    Full Text Available 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.

  1. Advanced Atmospheric Ensemble Modeling Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Chiswell, S. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Kurzeja, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Maze, G. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Viner, B. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Werth, D. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-09-29

    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 release 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.

  2. An artificially induced follicle stimulating hormone surge at the time of human chorionic gonadotrophin administration in controlled ovarian stimulation cycles has no effect on cumulus expansion, fertilization rate, embryo quality and implantation rate

    NARCIS (Netherlands)

    Vermeiden, J. P.; Roseboom, T. J.; Goverde, A. J.; Suchartwatnachai, C.; Schoute, E.; Braat, D. D.; Schats, R.

    1997-01-01

    In the spontaneous menstrual cycle, the mid-cycle gonadotrophin surge causes maturation of the cumulus-oocyte complex, mucification of cumulus cells and expansion of the cumulus oophorus, resumption of meiosis and maturation of the cytoplasm of the oocyte. Whether this is an effect purely of

  3. A treatment for the stratocumulus-to-cumulus transition in GCMs

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Heng; Mechoso, C.R. [University of California, Department of Atmospheric and Oceanic Sciences, Los Angeles, CA (United States); Wu, Chien-Ming [National Taiwan University, Department of Atmospheric Sciences, Taipei (China); Ma, Hsi-Yen [Lawrence Livermore National Laboratory, Program for Climate Model Diagnosis and Intercomparison, Livermore, CA (United States)

    2012-12-15

    Numerical models of climate have great difficulties with the simulation of marine low clouds in the subtropical Pacific and Atlantic Oceans. It has been especially difficult to reproduce the observed geographical distributions of the different cloud regimes in those regions. The present study discusses mechanisms proposed in previous works for changing one regime into another. One criterion is based on the theory of stratocumulus destruction through cloud top entrainment instability due to buoyancy reversal - situations in which the mixture of two air parcels becomes denser than either of the original parcels due to evaporation of cloud water. Another criterion is based on the existence of decoupling in the boundary layer. When decoupled, the stratocumulus regime changes to another in which these clouds can still exist together with cumulus. In a LES study, the authors have suggested that a combination of those two criteria can be used to diagnose whether, at a location, the cloud regime corresponds to a well-mixed stratocumulus regime, a shallow cumulus regime, or to a transitional regime where the boundary layer is decoupled. The concept is tested in the framework of an atmospheric general circulation model (GCM). It is found that several outstanding features of disagreement between simulation and observation can be interpreted as misrepresentations of the cloud regimes by the GCM. A novel criterion for switching among regimes is proposed to alleviate the effects of these misrepresentations. (orig.)

  4. Project Overview: Cumulus Humilis Aerosol Processing Study (CHAPS): Proposed Summer 2007 ASP Field Campaign

    Energy Technology Data Exchange (ETDEWEB)

    Berkowitz, Carl M.; Berg, Larry K.; Ogren, J. A.; Hostetler, Chris A.; Ferrare, Richard

    2006-05-18

    This white paper presents the scientific motivation and preliminary logistical plans for a proposed ASP field campaign to be carried out in the summer of 2007. The primary objective of this campaign is to use the DOE Gulfstream-1 aircraft to make measurements characterizing the chemical, physical and optical properties of aerosols below, within and above large fields of fair weather cumulus and to use the NASA Langley Research Center’s High Spectral Resolution Lidar (HSRL) to make independent measurements of aerosol backscatter and extinction profiles in the vicinity of these fields. Separate from the science questions to be addressed by these observations will be information to add in the development of a parameterized cumulus scheme capable of including multiple cloud fields within a regional or global scale model. We will also be able to compare and contrast the cloud and aerosol properties within and outside the Oklahoma City plume to study aerosol processes within individual clouds. Preliminary discussions with the Cloud and Land Surface Interaction Campaign (CLASIC) science team have identified overlap between the science questions posed for the CLASIC Intensive Operation Period (IOP) and the proposed ASP campaign, suggesting collaboration would benefit both teams.

  5. Experimental study of starting plumes simulating cumulus cloud flows in the atmosphere

    Science.gov (United States)

    Subrahmanyam, Duvvuri; Sreenivas, K. R.; Bhat, G. S.; Diwan, S. S.; Narasimha, Roddam

    2009-11-01

    Turbulent jets and plumes subjected to off-source volumetric heating have been studied experimentally and numerically by Narasimha and co-workers and others over the past two decades. The off-source heating attempts to simulate the latent heat release that occurs in cumulus clouds on condensation of water vapour. This heat release plays a crucial role in determining the overall cloud shape among other things. Previous studies investigated steady state jets and plumes that had attained similarity upstream of heat injection. A better understanding and appreciation of the fluid dynamics of cumulus clouds should be possible by study of starting plumes. Experiments have been set up at JNCASR (Bangalore) using experimental techniques developed previously but incorporating various improvements. Till date, experiments have been performed on plumes at Re of 1000 and 2250, with three different heating levels in each case. Axial sections of the flow have been studied using standard PLIF techniques. The flow visualization provides us with data on the temporal evolution of the starting plume. It is observed that the broad nature of the effect of off-source heating on the starting plumes is generally consistent with the results obtained previously on steady state flows. More complete results and a critical discussion will be presented at the upcoming meeting.

  6. Laboratory simulations show diabatic heating drives cumulus-cloud evolution and entrainment

    Science.gov (United States)

    Narasimha, Roddam; Diwan, Sourabh Suhas; Duvvuri, Subrahmanyam; Sreenivas, K. R.; Bhat, G. S.

    2011-01-01

    Clouds are the largest source of uncertainty in climate science, and remain a weak link in modeling tropical circulation. A major challenge is to establish connections between particulate microphysics and macroscale turbulent dynamics in cumulus clouds. Here we address the issue from the latter standpoint. First we show how to create bench-scale flows that reproduce a variety of cumulus-cloud forms (including two genera and three species), and track complete cloud life cycles—e.g., from a “cauliflower” congestus to a dissipating fractus. The flow model used is a transient plume with volumetric diabatic heating scaled dynamically to simulate latent-heat release from phase changes in clouds. Laser-based diagnostics of steady plumes reveal Riehl–Malkus type protected cores. They also show that, unlike the constancy implied by early self-similar plume models, the diabatic heating raises the Taylor entrainment coefficient just above cloud base, depressing it at higher levels. This behavior is consistent with cloud-dilution rates found in recent numerical simulations of steady deep convection, and with aircraft-based observations of homogeneous mixing in clouds. In-cloud diabatic heating thus emerges as the key driver in cloud development, and could well provide a major link between microphysics and cloud-scale dynamics. PMID:21918112

  7. Impact of Representing Model Error in a Hybrid Ensemble-Variational Data Assimilation System for Track Forecast of Tropical Cyclones over the Bay of Bengal

    Science.gov (United States)

    Kutty, Govindan; Muraleedharan, Rohit; Kesarkar, Amit P.

    2018-03-01

    Uncertainties in the numerical weather prediction models are generally not well-represented in ensemble-based data assimilation (DA) systems. The performance of an ensemble-based DA system becomes suboptimal, if the sources of error are undersampled in the forecast system. The present study examines the effect of accounting for model error treatments in the hybrid ensemble transform Kalman filter—three-dimensional variational (3DVAR) DA system (hybrid) in the track forecast of two tropical cyclones viz. Hudhud and Thane, formed over the Bay of Bengal, using Advanced Research Weather Research and Forecasting (ARW-WRF) model. We investigated the effect of two types of model error treatment schemes and their combination on the hybrid DA system; (i) multiphysics approach, which uses different combination of cumulus, microphysics and planetary boundary layer schemes, (ii) stochastic kinetic energy backscatter (SKEB) scheme, which perturbs the horizontal wind and potential temperature tendencies, (iii) a combination of both multiphysics and SKEB scheme. Substantial improvements are noticed in the track positions of both the cyclones, when flow-dependent ensemble covariance is used in 3DVAR framework. Explicit model error representation is found to be beneficial in treating the underdispersive ensembles. Among the model error schemes used in this study, a combination of multiphysics and SKEB schemes has outperformed the other two schemes with improved track forecast for both the tropical cyclones.

  8. Teaching Strategies for Specialized Ensembles.

    Science.gov (United States)

    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)

  9. Multimodel ensembles of wheat growth

    DEFF Research Database (Denmark)

    Martre, Pierre; Wallach, Daniel; Asseng, Senthold

    2015-01-01

    , but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24...

  10. Spectral Diagonal Ensemble Kalman Filters

    Czech Academy of Sciences Publication Activity Database

    Kasanický, Ivan; Mandel, Jan; Vejmelka, Martin

    2015-01-01

    Roč. 22, č. 4 (2015), s. 485-497 ISSN 1023-5809 R&D Projects: GA ČR GA13-34856S Grant - others:NSF(US) DMS-1216481 Institutional support: RVO:67985807 Keywords : data assimilation * ensemble Kalman filter * spectral representation Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.321, year: 2015

  11. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    Marquardt algorithm by varying conditions such as inputs, hidden neurons, initialization, training sets and random Gaussian noise injection to ... Several such ensembles formed the population which was evolved to generate the fittest ensemble.

  12. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  13. Localization of atomic ensembles via superfluorescence

    International Nuclear Information System (INIS)

    Macovei, Mihai; Evers, Joerg; Keitel, Christoph H.; Zubairy, M. Suhail

    2007-01-01

    The subwavelength localization of an ensemble of atoms concentrated to a small volume in space is investigated. The localization relies on the interaction of the ensemble with a standing wave laser field. The light scattered in the interaction of the standing wave field and the atom ensemble depends on the position of the ensemble relative to the standing wave nodes. This relation can be described by a fluorescence intensity profile, which depends on the standing wave field parameters and the ensemble properties and which is modified due to collective effects in the ensemble of nearby particles. We demonstrate that the intensity profile can be tailored to suit different localization setups. Finally, we apply these results to two localization schemes. First, we show how to localize an ensemble fixed at a certain position in the standing wave field. Second, we discuss localization of an ensemble passing through the standing wave field

  14. Squeezing of Collective Excitations in Spin Ensembles

    DEFF Research Database (Denmark)

    Kraglund Andersen, Christian; Mølmer, Klaus

    2012-01-01

    We analyse the possibility to create two-mode spin squeezed states of two separate spin ensembles by inverting the spins in one ensemble and allowing spin exchange between the ensembles via a near resonant cavity field. We investigate the dynamics of the system using a combination of numerical an...

  15. Anti-Müllerian hormone remains highly expressed in human cumulus cells during the final stages of folliculogenesis

    DEFF Research Database (Denmark)

    Grøndahl, M L; Nielsen, M Eilsø; Dal Canto, M B

    2011-01-01

    This study evaluated whether anti-Müllerian hormone (AMH) was differentially expressed in cumulus (CC) and granulosa (GC) cells from large antral and pre-ovulatory follicles collected from individual follicles in women undergoing in-vitro maturation (IVM) or IVF treatment. Expression studies of A...

  16. Remodeling of Donor Nuclei, DNA-Synthesis, and Ploidy of Bovine Cumulus Cell Nuclear Transfer Embryos: Effect of Activation Protocol

    Czech Academy of Sciences Publication Activity Database

    Alberio, R.; Brero, A.; Motlík, Jan; Cremer, T.; Wolf, E.; Zakhartchenko, V.

    2001-01-01

    Roč. 59, č. 2 (2001), s. 371-379 ISSN 1040-452X R&D Projects: GA AV ČR KSK5052113 Grant - others:WO(DE) 685/2-1; WO(DE) 685/3-1 Keywords : nuclear transfer * cumulus cells * activation Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.296, year: 2001

  17. Inhibition of proteasomal proteolysis affects expression of extracellular matrix components and steroidogenesis in porcine oocyte-cumulus complexes

    Czech Academy of Sciences Publication Activity Database

    Nagyová, Eva; Scsuková, S.; Němcová, Lucie; Mlynarčíková, A.; Yi, Y.J.; Sutovky, M.; Sutovsky, P.

    2012-01-01

    Roč. 42, č. 1 (2012), s. 50-62 ISSN 0739-7240 R&D Projects: GA ČR GAP502/11/0593 Institutional research plan: CEZ:AV0Z50450515 Keywords : Oocyte-cumulus complex * TNFAIP6 * HAS2 * Progesterone * Ubiquitin * Proteasome Subject RIV: ED - Physiology Impact factor: 2.377, year: 2012

  18. Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields

    Science.gov (United States)

    Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.

    1992-12-01

    During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards

  19. Eigenfunction statistics of Wishart Brownian ensembles

    International Nuclear Information System (INIS)

    Shukla, Pragya

    2017-01-01

    We theoretically analyze the eigenfunction fluctuation measures for a Hermitian ensemble which appears as an intermediate state of the perturbation of a stationary ensemble by another stationary ensemble of Wishart (Laguerre) type. Similar to the perturbation by a Gaussian stationary ensemble, the measures undergo a diffusive dynamics in terms of the perturbation parameter but the energy-dependence of the fluctuations is different in the two cases. This may have important consequences for the eigenfunction dynamics as well as phase transition studies in many areas of complexity where Brownian ensembles appear. (paper)

  20. Influence of follicular fluid and cumulus cells on oocyte quality: clinical implications.

    Science.gov (United States)

    Da Broi, M G; Giorgi, V S I; Wang, F; Keefe, D L; Albertini, D; Navarro, P A

    2018-03-02

    An equilibrium needs to be established by the cellular and acellular components of the ovarian follicle if developmental competence is to be acquired by the oocyte. Both cumulus cells (CCs) and follicular fluid (FF) are critical determinants for oocyte quality. Understanding how CCs and FF influence oocyte quality in the presence of deleterious systemic or pelvic conditions may impact clinical decisions in the course of managing infertility. Given that the functional integrities of FF and CCs are susceptible to concurrent pathological conditions, it is important to understand how pathophysiological factors influence natural fertility and the outcomes of pregnancy arising from the use of assisted reproduction technologies (ARTs). Accordingly, this review discusses the roles of CCs and FF in ensuring oocyte competence and present new insights on pathological conditions that may interfere with oocyte quality by altering the intrafollicular environment.

  1. Macrophysical properties of continental cumulus clouds from active and passive remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Kassianov, Evgueni I.; Riley, Erin A.; Kleiss, Jessica; Long, Charles N.; Riihimaki, Laura D.; Flynn, Donna M.; Flynn, Connor J M.; Berg, Larry K.

    2017-10-06

    Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOV ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that a root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.

  2. Dynamics, thermodynamics, radiation, and cloudiness associated with cumulus-topped marine boundary layers

    Energy Technology Data Exchange (ETDEWEB)

    Ghate, Virendra P. [Argonne National Lab. (ANL), Argonne, IL (United States); Miller, Mark [Rutgers Univ., New Brunswick, NJ (United States)

    2016-11-01

    The overall goal of this project was to improve the understanding of marine boundary clouds by using data collected at the Atmospheric Radiation Measurement (ARM) sites, so that they can be better represented in global climate models (GCMs). Marine boundary clouds are observed regularly over the tropical and subtropical oceans. They are an important element of the Earth’s climate system because they have substantial impact on the radiation budget together with the boundary layer moisture, and energy transports. These clouds also have an impact on large-scale precipitation features like the Inter Tropical Convergence Zone (ITCZ). Because these clouds occur at temporal and spatial scales much smaller than those relevant to GCMs, their effects and the associated processes need to be parameterized in GCM simulations aimed at predicting future climate and energy needs. Specifically, this project’s objectives were to (1) characterize the surface turbulent fluxes, boundary layer thermodynamics, radiation field, and cloudiness associated with cumulus-topped marine boundary layers; (2) explore the similarities and differences in cloudiness and boundary layer conditions observed in the tropical and trade-wind regions; and (3) understand similarities and differences by using a simple bulk boundary layer model. In addition to working toward achieving the project’s three objectives, we also worked on understanding the role played by different forcing mechanisms in maintaining turbulence within cloud-topped boundary layers We focused our research on stratocumulus clouds during the first phase of the project, and cumulus clouds during the rest of the project. Below is a brief description of manuscripts published in peer-reviewed journals that describe results from our analyses.

  3. Nonequilibrium statistical mechanics ensemble method

    CERN Document Server

    Eu, Byung Chan

    1998-01-01

    In this monograph, nonequilibrium statistical mechanics is developed by means of ensemble methods on the basis of the Boltzmann equation, the generic Boltzmann equations for classical and quantum dilute gases, and a generalised Boltzmann equation for dense simple fluids The theories are developed in forms parallel with the equilibrium Gibbs ensemble theory in a way fully consistent with the laws of thermodynamics The generalised hydrodynamics equations are the integral part of the theory and describe the evolution of macroscopic processes in accordance with the laws of thermodynamics of systems far removed from equilibrium Audience This book will be of interest to researchers in the fields of statistical mechanics, condensed matter physics, gas dynamics, fluid dynamics, rheology, irreversible thermodynamics and nonequilibrium phenomena

  4. Statistical Analysis of Protein Ensembles

    Science.gov (United States)

    Máté, Gabriell; Heermann, Dieter

    2014-04-01

    As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

  5. Ensemble methods for handwritten digit recognition

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Liisberg, Christian; Salamon, P.

    1992-01-01

    Neural network ensembles are applied to handwritten digit recognition. The individual networks of the ensemble are combinations of sparse look-up tables (LUTs) with random receptive fields. It is shown that the consensus of a group of networks outperforms the best individual of the ensemble....... It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...... by optimizing the receptive fields. It is concluded that it is possible to improve performance significantly by introducing moderate-size ensembles; in particular, a 20-25% improvement has been found. The ensemble random LUTs, when trained on a medium-size database, reach a performance (without rejects) of 94...

  6. Benchmarking Commercial Conformer Ensemble Generators.

    Science.gov (United States)

    Friedrich, Nils-Ole; de Bruyn Kops, Christina; Flachsenberg, Florian; Sommer, Kai; Rarey, Matthias; Kirchmair, Johannes

    2017-11-27

    We assess and compare the performance of eight commercial conformer ensemble generators (ConfGen, ConfGenX, cxcalc, iCon, MOE LowModeMD, MOE Stochastic, MOE Conformation Import, and OMEGA) and one leading free algorithm, the distance geometry algorithm implemented in RDKit. The comparative study is based on a new version of the Platinum Diverse Dataset, a high-quality benchmarking dataset of 2859 protein-bound ligand conformations extracted from the PDB. Differences in the performance of commercial algorithms are much smaller than those observed for free algorithms in our previous study (J. Chem. Inf. 2017, 57, 529-539). For commercial algorithms, the median minimum root-mean-square deviations measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers are between 0.46 and 0.61 Å. Commercial conformer ensemble generators are characterized by their high robustness, with at least 99% of all input molecules successfully processed and few or even no substantial geometrical errors detectable in their output conformations. The RDKit distance geometry algorithm (with minimization enabled) appears to be a good free alternative since its performance is comparable to that of the midranked commercial algorithms. Based on a statistical analysis, we elaborate on which algorithms to use and how to parametrize them for best performance in different application scenarios.

  7. Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

    Science.gov (United States)

    Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

    2018-06-01

    Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute

  8. Multi-ensemble regional simulation of Indian monsoon during contrasting rainfall years: role of convective schemes and nested domain

    Science.gov (United States)

    Devanand, Anjana; Ghosh, Subimal; Paul, Supantha; Karmakar, Subhankar; Niyogi, Dev

    2017-08-01

    Regional simulations of the seasonal Indian summer monsoon rainfall (ISMR) require an understanding of the model sensitivities to physics and resolution, and its effect on the model uncertainties. It is also important to quantify the added value in the simulated sub-regional precipitation characteristics by a regional climate model (RCM), when compared to coarse resolution rainfall products. This study presents regional model simulations of ISMR at seasonal scale using the Weather Research and Forecasting (WRF) model with the synoptic scale forcing from ERA-interim reanalysis, for three contrasting monsoon seasons, 1994 (excess), 2002 (deficit) and 2010 (normal). Impact of four cumulus schemes, viz., Kain-Fritsch (KF), Betts-Janjić-Miller, Grell 3D and modified Kain-Fritsch (KFm), and two micro physical parameterization schemes, viz., WRF Single Moment Class 5 scheme and Lin et al. scheme (LIN), with eight different possible combinations are analyzed. The impact of spectral nudging on model sensitivity is also studied. In WRF simulations using spectral nudging, improvement in model rainfall appears to be consistent in regions with topographic variability such as Central Northeast and Konkan Western Ghat sub-regions. However the results are also dependent on choice of cumulus scheme used, with KF and KFm providing relatively good performance and the eight member ensemble mean showing better results for these sub-regions. There is no consistent improvement noted in Northeast and Peninsular Indian monsoon regions. Results indicate that the regional simulations using nested domains can provide some improvements on ISMR simulations. Spectral nudging is found to improve upon the model simulations in terms of reducing the intra ensemble spread and hence the uncertainty in the model simulated precipitation. The results provide important insights regarding the need for further improvements in the regional climate simulations of ISMR for various sub-regions and contribute

  9. PENGGUNAAN SKEMA KONVEKTIF MODEL CUACA WRF (BETTS MILLER JANJIC, KAIN FRITSCH DAN GRELL 3D ENSEMBLE (Studi kasus: Surabaya dan Jakarta

    Directory of Open Access Journals (Sweden)

    Roni Kurniawan

    2015-01-01

    Full Text Available Pada kajian ini dilakukan evaluasi penggunaan beberapa skema konvektif pada model WRF (Weather Research and Forecasting untuk prediksi cuaca di wilayah Indonesia. Terdapat tiga skema konvektif yang akan dievaluasi yaitu; skema konvektif cumulus BMJ (Betts Miller Janjic, KF (Kain Fritsch, dan GD (Grell 3D ensemble. Data yang digunakan untuk evaluasi adalah data curah hujan per 3 jam dan data angin per 12 jam (level ketinggian; permukaan, 850, 500, 250 mb dari hasil pengolahan model WRF dan observasi selama periode bulan Agustus 2011 dan Februari 2012 di stasiun Juanda-Surabaya dan Cengkareng-Jakarta. Hasil verifikasi dari tiga skema konvektif pada model WRF terhadap data observasi menunjukkan bahwa untuk prakiraan curah hujan, penggunaan skema konvektif BMJ lebih baik dari skema KF dan GD, dan untuk prakiraan arah dan kecepatan angin skema BMJ dan GD relatif lebih baik dari skema KF. Berdasarkan analisis hasil verifikasi yang diperoleh, pemilihan skema konvektif cumulus BMJ cenderung lebih baik dari skema konvektif KF dan GD untuk di aplikasikan pada model WRF.   In this study, the use of some convective schemes on the model WRF (Weather Research and Forecasting for weather prediction in Indonesian region has been evaluated. There are two models evaluated; BMJ cumulus convective scheme (Betts Miller Janjic, KF (Kain Fritsch, and GD (Grell 3D ensemble. The data used in the evaluation are the 3 hourly rainfall data, and the 12 hourly wind data (level height; surface, 850, 500, 250mb from the WRF models and observation processing during August 2011 and February 2012 period at the Juanda-Surabaya and Cengkareng-Jakarta stations. The results of the verification of the three convective schemes in WRF models against observation data indicate that for precipitation forecasts, the application of the BMJ convective scheme is better than the KF and GD schemes, and for direction and wind speed forecast, BMJ and GD schemes is relatively better than the KF

  10. The presence of acylated ghrelin during in vitro maturation of bovine oocytes induces cumulus cell DNA damage and apoptosis, and impairs early embryo development.

    Science.gov (United States)

    Sirini, Matias A; Anchordoquy, Juan Mateo; Anchordoquy, Juan Patricio; Pascua, Ana M; Nikoloff, Noelia; Carranza, Ana; Relling, Alejandro E; Furnus, Cecilia C

    2017-10-01

    The aim of this study was to investigate the effects of acylated ghrelin supplementation during in vitro maturation (IVM) of bovine oocytes. IVM medium was supplemented with 20, 40 or 60 pM acylated ghrelin concentrations. Cumulus expansion area and oocyte nuclear maturation were studied as maturation parameters. Cumulus-oocyte complexes (COC) were assessed with the comet, apoptosis and viability assays. The in vitro effects of acylated ghrelin on embryo developmental capacity and embryo quality were also evaluated. Results demonstrated that acylated ghrelin did not affect oocyte nuclear maturation and cumulus expansion area. However, it induced cumulus cell (CC) death, apoptosis and DNA damage. The damage increased as a function of the concentration employed. Additionally, the percentages of blastocyst yield, hatching and embryo quality decreased with all acylated ghrelin concentrations tested. Our study highlights the importance of acylated ghrelin in bovine reproduction, suggesting that this metabolic hormone could function as a signal that prevents the progress to reproductive processes.

  11. Measuring social interaction in music ensembles.

    Science.gov (United States)

    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).

  12. Statistical ensembles in quantum mechanics

    International Nuclear Information System (INIS)

    Blokhintsev, D.

    1976-01-01

    The interpretation of quantum mechanics presented in this paper is based on the concept of quantum ensembles. This concept differs essentially from the canonical one by that the interference of the observer into the state of a microscopic system is of no greater importance than in any other field of physics. Owing to this fact, the laws established by quantum mechanics are not of less objective character than the laws governing classical statistical mechanics. The paradoxical nature of some statements of quantum mechanics which result from the interpretation of the wave functions as the observer's notebook greatly stimulated the development of the idea presented. (Auth.)

  13. Wind Power Prediction using Ensembles

    DEFF Research Database (Denmark)

    Giebel, Gregor; Badger, Jake; Landberg, Lars

    2005-01-01

    offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

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

    KAUST Repository

    Rapakoulia, Trisevgeni; Theofilatos, Konstantinos A.; Kleftogiannis, Dimitrios A.; Likothanasis, Spiridon D.; Tsakalidis, Athanasios K.; Mavroudi, Seferina P.

    2014-01-01

    do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep algorithm, which in its first step applies a novel

  15. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    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.

  16. Urban runoff forecasting with ensemble weather predictions

    DEFF Research Database (Denmark)

    Pedersen, Jonas Wied; Courdent, Vianney Augustin Thomas; Vezzaro, Luca

    This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice.......This research shows how ensemble weather forecasts can be used to generate urban runoff forecasts up to 53 hours into the future. The results highlight systematic differences between ensemble members that needs to be accounted for when these forecasts are used in practice....

  17. Prostaglandin E2 stimulates the expression of cumulus expansion-related genes in pigs: the role of protein kinase B

    Czech Academy of Sciences Publication Activity Database

    Blaha, Milan; Procházka, Radek; Adámková, K.; Nevoral, J.; Němcová, Lucie

    2017-01-01

    Roč. 130, č. 2 (2017), s. 38-46 ISSN 1098-8823 R&D Projects: GA MZe(CZ) QJ1510138; GA MŠk EF15_003/0000460 Institutional support: RVO:67985904 Keywords : cumulus * oocyte * prostaglandin E2 * protein kinase B Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Reproductive biology (medical aspects to be 3) Impact factor: 2.640, year: 2016

  18. Human sperm bioassay has potential in evaluating the quality of cumulus-oocyte complexes.

    Science.gov (United States)

    Hossain, A M; Rizk, B; Huff, C; Helvacioglu, A; Thorneycroft, I H

    1996-01-01

    Human sperm bioassay is routinely used as a quality control check for the culture media. This is one of the three bioassays chosen by the College of American Pathologists (CAP) for interlaboratory proficiency testing to assess the standards of in vitro fertilization (IVF) and andrology laboratories. This study utilized sperm bioassay to assess the quality of cumulus-oocyte complexes (COCs) retrieved in IVF procedures COCs, harvested from the female partner of IVF couples, undergoing identical ovarian stimulation protocols, were individually inseminated with the sperm of the corresponding male partner. Sperm motility in sperm-COC cocultures were compared. Cocultures were established by inseminating the 103 COCs, retrieved from 18 IVF couples with 1 x 10(5) to 2 x 10(5) sperm of the corresponding male partners of the couples. In all 18 cases, the sperm were prepared identically using the Percoll wash method. The cocultures were maintained for 48 h but the oocytes were removed immediately after the fertilization check (approximately 16 h). The motility of sperm in the cocultures and in the insemination stocks were noted and 17 of 18 sperm stocks used for insemination had similar high preinsemination motility (90.2 +/- 5.0%). At 48 h the sperm motility had significantly decreased in the cocultures compared to the insemination stocks; 52.7 +/- 19.9% versus 67.2 +/- 10.4%. There was no difference in the motility among the small, medium, and large COCs (56.4 +/- 24.6%, 52.5 +/- 17.9%, and 50.8 +/- 20.9%, respectively). In 45% of IVF cases, the motility in cocultures varied widely, falling below as well as above that of their corresponding insemination stocks. Furthermore, the sperm motility varied among the cocultures in both pregnant and nonpregnant patients but the extent of variation appears to be greater in the latter. The inter-COC coculture sperm motility variation most likely is due to the differences in the quality of cumulus-oocyte complexes.

  19. Competence Classification of Cumulus and Granulosa Cell Transcriptome in Embryos Matched by Morphology and Female Age.

    Directory of Open Access Journals (Sweden)

    Rehannah Borup

    Full Text Available By focussing on differences in the mural granulosa cell (MGC and cumulus cell (CC transcriptomes from follicles resulting in competent (live birth and non-competent (no pregnancy oocytes the study aims on defining a competence classifier expression profile in the two cellular compartments.A case-control study.University based facilities for clinical services and research.MGC and CC samples from 60 women undergoing IVF treatment following the long GnRH-agonist protocol were collected. Samples from 16 oocytes where live birth was achieved and 16 age- and embryo morphology matched incompetent oocytes were included in the study.MGC and CC were isolated immediately after oocyte retrieval. From the 16 competent and non-competent follicles, mRNA was extracted and expression profile generated on the Human Gene 1.0 ST Affymetrix array. Live birth prediction analysis using machine learning algorithms (support vector machines with performance estimation by leave-one-out cross validation and independent validation on an external data set.We defined a signature of 30 genes expressed in CC predictive of live birth. This live birth prediction model had an accuracy of 81%, a sensitivity of 0.83, a specificity of 0.80, a positive predictive value of 0.77, and a negative predictive value of 0.86. Receiver operating characteristic analysis found an area under the curve of 0.86, significantly greater than random chance. When applied on 3 external data sets with the end-point outcome measure of blastocyst formation, the signature resulted in 62%, 75% and 88% accuracy, respectively. The genes in the classifier are primarily connected to apoptosis and involvement in formation of extracellular matrix. We were not able to define a robust MGC classifier signature that could classify live birth with accuracy above random chance level.We have developed a cumulus cell classifier, which showed a promising performance on external data. This suggests that the gene signature at

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

    Science.gov (United States)

    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…

  1. Comparative Gene Expression Profiling in Human Cumulus Cells according to Ovarian Gonadotropin Treatments

    Directory of Open Access Journals (Sweden)

    Said Assou

    2013-01-01

    Full Text Available In in vitro fertilization cycles, both HP-hMG and rFSH gonadotropin treatments are widely used to control human follicle development. The objectives of this study are (i to characterize and compare gene expression profiles in cumulus cells (CCs of periovulatory follicles obtained from patients stimulated with HP-hMG or rFSH in a GnRH antagonist cycle and (ii to examine their relationship with in vitro embryo development, using Human Genome U133 Plus 2.0 microarrays. Genes that were upregulated in HP-hMG-treated CCs are involved in lipid metabolism (GM2A and cell-to-cell interactions (GJA5. Conversely, genes upregulated in rFSH-treated CCs are implicated in cell assembly and organization (COL1A1 and COL3A1. Interestingly, some genes specific to each gonadotropin treatment (NPY1R and GM2A for HP-hMG; GREM1 and OSBPL6 for rFSH were associated with day 3 embryo quality and blastocyst grade at day 5, while others (STC2 and PTX3 were related to in vitro embryo quality in both gonadotropin treatments. These genes may prove valuable as biomarkers of in vitro embryo quality.

  2. The Route to Raindrop Formation in a Shallow Cumulus Cloud Simulated by a Lagrangian Cloud Model

    Science.gov (United States)

    Noh, Yign; Hoffmann, Fabian; Raasch, Siegfried

    2017-11-01

    The mechanism of raindrop formation in a shallow cumulus cloud is investigated using a Lagrangian cloud model (LCM). The analysis is focused on how and under which conditions a cloud droplet grows to a raindrop by tracking the history of individual Lagrangian droplets. It is found that the rapid collisional growth, leading to raindrop formation, is triggered when single droplets with a radius of 20 μm appear in the region near the cloud top, characterized by a large liquid water content, strong turbulence, large mean droplet size, a broad drop size distribution (DSD), and high supersaturations. Raindrop formation easily occurs when turbulence-induced collision enhancement(TICE) is considered, with or without any extra broadening of the DSD by another mechanism (such as entrainment and mixing). In contrast, when TICE is not considered, raindrop formation is severely delayed if no other broadening mechanism is active. The reason leading to the difference is clarified by the additional analysis of idealized box-simulations of the collisional growth process for different DSDs in varied turbulent environments. It is found that TICE does not accelerate the timing of the raindrop formation for individual droplets, but it enhances the collisional growth rate significantly afterward. KMA R & D Program (Korea), DFG (Germany).

  3. Optimizing the Betts-Miller-Janjic cumulus parameterization with Intel Many Integrated Core (MIC) architecture

    Science.gov (United States)

    Huang, Melin; Huang, Bormin; Huang, Allen H.-L.

    2015-10-01

    The schemes of cumulus parameterization are responsible for the sub-grid-scale effects of convective and/or shallow clouds, and intended to represent vertical fluxes due to unresolved updrafts and downdrafts and compensating motion outside the clouds. Some schemes additionally provide cloud and precipitation field tendencies in the convective column, and momentum tendencies due to convective transport of momentum. The schemes all provide the convective component of surface rainfall. Betts-Miller-Janjic (BMJ) is one scheme to fulfill such purposes in the weather research and forecast (WRF) model. National Centers for Environmental Prediction (NCEP) has tried to optimize the BMJ scheme for operational application. As there are no interactions among horizontal grid points, this scheme is very suitable for parallel computation. With the advantage of Intel Xeon Phi Many Integrated Core (MIC) architecture, efficient parallelization and vectorization essentials, it allows us to optimize the BMJ scheme. If compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670, the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.4x and 17.0x, respectively.

  4. APOPTOSIS RATE IN CUMULUS CELLS AS POSSIBLE MOLECULAR BIOMARKER FOR OOCYTE COMPETENCE.

    Directory of Open Access Journals (Sweden)

    Liana Bosco

    2017-04-01

    Full Text Available Several lines of evidence showed that apoptosis rate of cumulus cells in oocytes derived by assisted reproductive technologies could be used as an indicator of fertilizing gamete quality. Aim of the study was to investigate the effects of three different ovarian stimulation protocols on the biological and clinical outcome in hyporesponder patients. Collected data showed a higher significant rate of DNA fragmentation index (DFI in U group (patients treated with Highly Purified human Menopausal Gonadotrophin than in P group (treated with recombinant human Follicle Stimulating Hormone (r-hFSH combined with recombinant human Luteinizing Hormone (r-hLH. Both groups R (treated with r-hFSH alone and P showed a significant increase in collected and fertilized oocytes number, embryo quality number. This study showed that combined r-hFSH/r-hLH therapy could represent the best pharmacological strategy for controlled ovarian stimulation and suggests to use DFI as a biomarker of ovarian function in hyporesponder patients.

  5. Transcriptomic Analysis and Meta-Analysis of Human Granulosa and Cumulus Cells.

    Directory of Open Access Journals (Sweden)

    Tanja Burnik Papler

    Full Text Available Specific gene expression in oocytes and its surrounding cumulus (CC and granulosa (GC cells is needed for successful folliculogenesis and oocyte maturation. The aim of the present study was to compare genome-wide gene expression and biological functions of human GC and CC. Individual GC and CC were derived from 37 women undergoing IVF procedures. Gene expression analysis was performed using microarrays, followed by a meta-analysis. Results were validated using quantitative real-time PCR. There were 6029 differentially expressed genes (q < 10-4; of which 650 genes had a log2 FC ≥ 2. After the meta-analysis there were 3156 genes differentially expressed. Among these there were genes that have previously not been reported in human somatic follicular cells, like prokineticin 2 (PROK2, higher expressed in GC, and pregnancy up-regulated nonubiquitous CaM kinase (PNCK, higher expressed in CC. Pathways like inflammatory response and angiogenesis were enriched in GC, whereas in CC, cell differentiation and multicellular organismal development were among enriched pathways. In conclusion, transcriptomes of GC and CC as well as biological functions, are distinctive for each cell subpopulation. By describing novel genes like PROK2 and PNCK, expressed in GC and CC, we upgraded the existing data on human follicular biology.

  6. Female Aging Alters Expression of Human Cumulus Cells Genes that Are Essential for Oocyte Quality

    Directory of Open Access Journals (Sweden)

    Tamadir Al-Edani

    2014-01-01

    Full Text Available Impact of female aging is an important issue in human reproduction. There was a need for an extensive analysis of age impact on transcriptome profile of cumulus cells (CCs to link oocyte quality and developmental potential with patient’s age. CCs from patients of three age groups were analyzed individually using microarrays. RT-qPCR validation was performed on independent CC cohorts. We focused here on pathways affected by aging in CCs that may explain the decline of oocyte quality with age. In CCs collected from patients >37 years, angiogenic genes including ANGPTL4, LEPR, TGFBR3, and FGF2 were significantly overexpressed compared to patients of the two younger groups. In contrast genes implicated in TGF-β signaling pathway such as AMH, TGFB1, inhibin, and activin receptor were underexpressed. CCs from patients whose ages are between 31 and 36 years showed an overexpression of genes related to insulin signaling pathway such as IGFBP3, PIK3R1, and IGFBP5. A bioinformatic analysis was performed to identify the microRNAs that are potential regulators of the differentially expressed genes of the study. It revealed that the pathways impacted by age were potential targets of specific miRNAs previously identified in our CCs small RNAs sequencing.

  7. Popular Music and the Instrumental Ensemble.

    Science.gov (United States)

    Boespflug, George

    1999-01-01

    Discusses popular music, the role of the musical performer as a creator, and the styles of jazz and popular music. Describes the pop ensemble at the college level, focusing on improvisation, rehearsals, recording, and performance. Argues that pop ensembles be used in junior and senior high school. (CMK)

  8. Layered Ensemble Architecture for Time Series Forecasting.

    Science.gov (United States)

    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.

  9. Ensemble methods for seasonal limited area forecasts

    DEFF Research Database (Denmark)

    Arritt, Raymond W.; Anderson, Christopher J.; Takle, Eugene S.

    2004-01-01

    The ensemble prediction methods used for seasonal limited area forecasts were examined by comparing methods for generating ensemble simulations of seasonal precipitation. The summer 1993 model over the north-central US was used as a test case. The four methods examined included the lagged-average...

  10. Topological quantization of ensemble averages

    International Nuclear Information System (INIS)

    Prodan, Emil

    2009-01-01

    We define the current of a quantum observable and, under well-defined conditions, we connect its ensemble average to the index of a Fredholm operator. The present work builds on a formalism developed by Kellendonk and Schulz-Baldes (2004 J. Funct. Anal. 209 388) to study the quantization of edge currents for continuous magnetic Schroedinger operators. The generalization given here may be a useful tool to scientists looking for novel manifestations of the topological quantization. As a new application, we show that the differential conductance of atomic wires is given by the index of a certain operator. We also comment on how the formalism can be used to probe the existence of edge states

  11. Characterizing Ensembles of Superconducting Qubits

    Science.gov (United States)

    Sears, Adam; Birenbaum, Jeff; Hover, David; Rosenberg, Danna; Weber, Steven; Yoder, Jonilyn L.; Kerman, Jamie; Gustavsson, Simon; Kamal, Archana; Yan, Fei; Oliver, William

    We investigate ensembles of up to 48 superconducting qubits embedded within a superconducting cavity. Such arrays of qubits have been proposed for the experimental study of Ising Hamiltonians, and efficient methods to characterize and calibrate these types of systems are still under development. Here we leverage high qubit coherence (> 70 μs) to characterize individual devices as well as qubit-qubit interactions, utilizing the common resonator mode for a joint readout. This research was funded by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) under Air Force Contract No. FA8721-05-C-0002. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of ODNI, IARPA, or the US Government.

  12. Sensitive warfarin sensor based on cobalt oxide nanoparticles electrodeposited at multi-walled carbon nanotubes modified glassy carbon electrode (CoxOyNPs/MWCNTs/GCE)

    International Nuclear Information System (INIS)

    Gholivand, Mohammad Bagher; Solgi, Mohammad

    2017-01-01

    In this work, cobalt oxide nanoparticles were electrodeposited on multi-walled carbon nanotubes modified glassy carbon electrode (MWCNTs/GCE) to develop a new sensor for warfarin determination. The modified electrodes were characterized by cyclic voltammetry, scanning electron microscopy (SEM) along with energy dispersive x-ray spectroscopy (EDS), and electrochemical impedance spectroscopy (EIS). The presence of cobalt oxide nanoparticles on the electrode surface enhanced the warfarin accumulation and its result was the improvement in the electrochemical response. The effect of various parameters such as pH, scan rate, accumulation potential, accumulation time and pulse amplitude on the sensor response were investigated. Under optimal conditions, the differential pulse adsorptive anodic stripping voltammetric (DPASV) response of the modified electrode was linear in the ranges of 8 nM to 50 μM and 50 μM to 800 μM with correlation coefficients greater than 0.998. The limit of detection of the proposed method was 3.3 nM. The proposed sensor was applied to determine warfarin in urine and plasma samples.

  13. Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

    Science.gov (United States)

    Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

    2017-12-01

    This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

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

    Science.gov (United States)

    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.

  15. Preliminary Optical And Electric Field Pulse Statistics From Storm Overflights During The Altus Cumulus Electrification Study

    Science.gov (United States)

    Mach, D. A.; Blakeslee, R. J.; Bailey, J. C.; Farrell, W. M.; Goldberg, R. A.; Desch, M. D.; Houser, J. G.

    2003-01-01

    The Altus Cumulus Electrification Study (ACES) was conducted during the month of August, 2002 in an area near Key West, Florida. One of the goals of this uninhabited aerial vehicle (UAV) study was to collect high resolution optical pulse and electric field data from thunderstorms. During the month long campaign, we acquired 5294 lightning generated optical pulses with associated electric field changes. Most of these observations were made while close to the top of the storms. We found filtered mean and median 10-10% optical pulse widths of 875 and 830 microns respectively while the 50-50% mean and median optical pulse widths are 422 and 365 microns respectively. These values are similar to previous results as are the 10-90% mean and median rise times of 327 and 265 microns. The peak electrical to optical pulse delay mean and median were 209 and 145 microns which is longer than one would expect from theoretical results. The results of the pulse analysis will contribute to further validation of the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS) satellites. Pre-launch estimates of the flash detection efficiency were based on a small sample of optical pulse measurements associated with less than 350 lightning discharges collected by NASA U-2 aircraft in the early 1980s. Preliminary analyses of the ACES measurements show that we have greatly increased the number of optical pulses available for validation of the LIS and other orbital lightning optical sensors. Since the Altus was often close to the cloud tops, many of the optical pulses are from low-energy pulses. From these low-energy pulses, we can determine the fraction of optical lightning pulses below the thresholds of LIS, OTD, and any future satellite-based optical sensors such as the geostationary Lightning Mapping Sensor.

  16. Impacts of solar-absorbing aerosol layers on the transition of stratocumulus to trade cumulus clouds

    Directory of Open Access Journals (Sweden)

    X. Zhou

    2017-10-01

    Full Text Available The effects of an initially overlying layer of solar-absorbing aerosol on the transition of stratocumulus to trade cumulus clouds are examined using large-eddy simulations. For lightly drizzling cloud the transition is generally hastened, resulting mainly from increased cloud droplet number concentration (Nc induced by entrained aerosol. The increased Nc slows sedimentation of cloud droplets and shortens their relaxation time for diffusional growth, both of which accelerate entrainment of overlying air and thereby stratocumulus breakup. However, the decrease in albedo from cloud breakup is more than offset by redistributing cloud water over a greater number of droplets, such that the diurnal-average shortwave forcing at the top of the atmosphere is negative. The negative radiative forcing is enhanced by sizable longwave contributions, which result from the greater cloud breakup and a reduced boundary layer height associated with aerosol heating. A perturbation of moisture instead of aerosol aloft leads to a greater liquid water path and a more gradual transition. Adding absorbing aerosol to that atmosphere results in substantial reductions in liquid water path (LWP and cloud cover that lead to positive shortwave and negative longwave forcings on average canceling each other. Only for heavily drizzling clouds is the breakup delayed, as inhibition of precipitation overcomes cloud water loss from enhanced entrainment. Considering these simulations as an imperfect proxy for biomass burning plumes influencing Namibian stratocumulus, we expect regional indirect plus semi-direct forcings to be substantially negative to negligible at the top of the atmosphere, with its magnitude sensitive to background and perturbation properties.

  17. DNA Double-Strand Breaks Induce the Nuclear Actin Filaments Formation in Cumulus-Enclosed Oocytes but Not in Denuded Oocytes.

    Directory of Open Access Journals (Sweden)

    Ming-Hong Sun

    Full Text Available As a gamete, oocyte needs to maintain its genomic integrity and passes this haploid genome to the next generation. However, fully-grown mouse oocyte cannot respond to DNA double-strand breaks (DSBs effectively and it is also unable to repair them before the meiosis resumption. To compensate for this disadvantage and control the DNA repair events, oocyte needs the cooperation with its surrounding cumulus cells. Recently, evidences have shown that nuclear actin filament formation plays roles in cellular DNA DSB repair. To explore whether these nuclear actin filaments are formed in the DNA-damaged oocytes, here, we labeled the filament actins in denuded oocytes (DOs and cumulus-enclosed oocytes (CEOs. We observed that the nuclear actin filaments were formed only in the DNA-damaged CEOs, but not in DOs. Formation of actin filaments in the nucleus was an event downstream to the DNA damage response. Our data also showed that the removal of cumulus cells led to a reduction in the nuclear actin filaments in oocytes. Knocking down of the Adcy1 gene in cumulus cells did not affect the formation of nuclear actin filaments in oocytes. Notably, we also observed that the nuclear actin filaments in CEOs could be induced by inhibition of gap junctions. From our results, it was confirmed that DNA DSBs induce the nuclear actin filament formation in oocyte and which is controlled by the cumulus cells.

  18. Creating ensembles of decision trees through sampling

    Science.gov (United States)

    Kamath, Chandrika; Cantu-Paz, Erick

    2005-08-30

    A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.

  19. Derivation of Mayer Series from Canonical Ensemble

    International Nuclear Information System (INIS)

    Wang Xian-Zhi

    2016-01-01

    Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula. (paper)

  20. Derivation of Mayer Series from Canonical Ensemble

    Science.gov (United States)

    Wang, Xian-Zhi

    2016-02-01

    Mayer derived the Mayer series from both the canonical ensemble and the grand canonical ensemble by use of the cluster expansion method. In 2002, we conjectured a recursion formula of the canonical partition function of a fluid (X.Z. Wang, Phys. Rev. E 66 (2002) 056102). In this paper we give a proof for this formula by developing an appropriate expansion of the integrand of the canonical partition function. We further derive the Mayer series solely from the canonical ensemble by use of this recursion formula.

  1. Future changes in tropical cyclone activity projected by multi-physics and multi-SST ensemble experiments using the 60-km-mesh MRI-AGCM

    Energy Technology Data Exchange (ETDEWEB)

    Murakami, Hiroyuki [Japan Agency for Marine-Earth Science and Technology (JAMSTEC)/Meteorological Research Institute (MRI), Tsukuba, Ibaraki (Japan); University of Hawaii at Manoa, International Pacific Research Center, School of Ocean and Earth Science and Technology, Honolulu, Hawaii (United States); Mizuta, Ryo; Shindo, Eiki [Meteorological Research Institute (MRI), Climate Research Department, Tsukuba, Ibaraki (Japan)

    2012-11-15

    Uncertainties in projected future changes in tropical cyclone (TC) activity are investigated using future (2075-2099) ensemble projections of global warming under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. Twelve ensemble experiments are performed using three different cumulus convection schemes and four different assumptions for prescribed future sea surface temperatures (SSTs). All ensemble experiments consistently project significant reductions in global and hemispheric TC genesis numbers as well as reductions in TC frequency of occurrence (TCF) and TC genesis frequency (TGF) in the western North Pacific, South Indian Ocean, and South Pacific Ocean. TCF and TGF are projected to increase over the central Pacific which is consistent with the findings of Li et al. (2010). Inter-experimental variations of projected future changes in TGF and TC genesis number are caused mainly by differences in large-scale dynamical parameters and SST anomalies. Thermodynamic parameters are of secondary importance for variations in TGF and TC genesis number. These results imply that differences in SST spatial patterns can cause substantial variations and uncertainties in projected future changes of TGF and TC numbers at ocean-basin scales. (orig.)

  2. Effects of stratocumulus, cumulus, and cirrus clouds on the UV-B diffuse to global ratio: Experimental and modeling results

    International Nuclear Information System (INIS)

    López, María Laura; Palancar, Gustavo G.; Toselli, Beatriz M.

    2012-01-01

    Broadband measurements of global and diffuse UV-B irradiance (280-315 nm) together with modeled and measured diffuse to global ratios (DGR) have been used to characterize the influence of different types of clouds on irradiance at the surface. Measurements were carried out during 2000-2001 in Córdoba City, Argentina. The Tropospheric Ultraviolet Visible (TUV) model was used to analyze the behavior of the modeled DGRs for different cloud optical depths and at different altitudes and solar zenith angles (SZA). Different cloud altitudes were also tested, although only the results for a cloud placed at 1.5-2.5 km of altitude are shown. A total of 16 day with stratocumulus, 12 with cumulus, and 16 with cirrus have been studied and compared among them and also against 21 clear sky days. Different behaviors were clearly detected and also differentiated through the analysis of the averages and the standard deviations of the DGRs: 1.02±0.06 for stratocumulus, 0.74±0.18 for cumulus, 0.63±0.12 for cirrus, and 0.60±0.13 for the clear sky days, respectively. Stratocumulus clouds showed a low variability in the DGR values, which were concentrated close to one at all SZAs. DGR values for cumulus clouds presented a large variability at all SZAs, mostly associated with the different optical depths. Finally, the closeness between the DGR values for cirrus clouds and the DGR values for clear days showed that these clouds generally do not strongly affect the UV-B irradiance at the surface at any SZA. In the opposite side, stratocumulus clouds were identified as those with the largest effects, at all SZAs, on the UV-B irradiance at the surface.

  3. Ensemble Weight Enumerators for Protograph LDPC Codes

    Science.gov (United States)

    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.

  4. Ensemble Kalman filtering with residual nudging

    KAUST Repository

    Luo, X.; Hoteit, Ibrahim

    2012-01-01

    Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work

  5. Ensemble Machine Learning Methods and Applications

    CERN Document Server

    Ma, Yunqian

    2012-01-01

    It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

  6. AUC-Maximizing Ensembles through Metalearning.

    Science.gov (United States)

    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.

  7. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, Marc G.

    2015-01-01

    the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function

  8. Polarized ensembles of random pure states

    International Nuclear Information System (INIS)

    Cunden, Fabio Deelan; Facchi, Paolo; Florio, Giuseppe

    2013-01-01

    A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise. (paper)

  9. Polarized ensembles of random pure states

    Science.gov (United States)

    Deelan Cunden, Fabio; Facchi, Paolo; Florio, Giuseppe

    2013-08-01

    A new family of polarized ensembles of random pure states is presented. These ensembles are obtained by linear superposition of two random pure states with suitable distributions, and are quite manageable. We will use the obtained results for two purposes: on the one hand we will be able to derive an efficient strategy for sampling states from isopurity manifolds. On the other, we will characterize the deviation of a pure quantum state from separability under the influence of noise.

  10. Quark ensembles with infinite correlation length

    OpenAIRE

    Molodtsov, S. V.; Zinovjev, G. M.

    2014-01-01

    By studying quark ensembles with infinite correlation length we formulate the quantum field theory model that, as we show, is exactly integrable and develops an instability of its standard vacuum ensemble (the Dirac sea). We argue such an instability is rooted in high ground state degeneracy (for 'realistic' space-time dimensions) featuring a fairly specific form of energy distribution, and with the cutoff parameter going to infinity this inherent energy distribution becomes infinitely narrow...

  11. Orbital magnetism in ensembles of ballistic billiards

    International Nuclear Information System (INIS)

    Ullmo, D.; Richter, K.; Jalabert, R.A.

    1993-01-01

    The magnetic response of ensembles of small two-dimensional structures at finite temperatures is calculated. Using semiclassical methods and numerical calculation it is demonstrated that only short classical trajectories are relevant. The magnetic susceptibility is enhanced in regular systems, where these trajectories appear in families. For ensembles of squares large paramagnetic susceptibility is obtained, in good agreement with recent measurements in the ballistic regime. (authors). 20 refs., 2 figs

  12. Multivariate localization methods for ensemble Kalman filtering

    OpenAIRE

    S. Roh; M. Jun; I. Szunyogh; M. G. Genton

    2015-01-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of ...

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

    Science.gov (United States)

    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.

  14. Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique

    Directory of Open Access Journals (Sweden)

    Jan D. Keller

    2008-12-01

    Full Text Available The quantitative forecast of precipitation requires a probabilistic background particularly with regard to forecast lead times of more than 3 days. As only ensemble simulations can provide useful information of the underlying probability density function, we built a new ensemble forecasting system (GME-EFS based on the GME model of the German Meteorological Service (DWD. For the generation of appropriate initial ensemble perturbations we chose the breeding technique developed by Toth and Kalnay (1993, 1997, which develops perturbations by estimating the regions of largest model error induced uncertainty. This method is applied and tested in the framework of quasi-operational forecasts for a three month period in 2007. The performance of the resulting ensemble forecasts are compared to the operational ensemble prediction systems ECMWF EPS and NCEP GFS by means of ensemble spread of free atmosphere parameters (geopotential and temperature and ensemble skill of precipitation forecasting. This comparison indicates that the GME ensemble forecasting system (GME-EFS provides reasonable forecasts with spread skill score comparable to that of the NCEP GFS. An analysis with the continuous ranked probability score exhibits a lack of resolution for the GME forecasts compared to the operational ensembles. However, with significant enhancements during the 3 month test period, the first results of our work with the GME-EFS indicate possibilities for further development as well as the potential for later operational usage.

  15. Effect of Cumulus cell co-culture and Protein Supplement on Success of in vitro Fertilization and Development of Pre-implanted Embryos in mice

    Directory of Open Access Journals (Sweden)

    Muhammad-Baqir M-R. Fakhrildin

    2005-06-01

    Full Text Available Successful oocyte fertilization and normal embryonic development of mice were considered the most important diagnostic criteria for the safety of materials and tools used for human in vitro fertilization and embryo transfer (IVF-ET. Therefore, we studied the influence of cumulus cells co-culture and protein supplement within culture medium on percentages of in vitro fertilization (IVF and normal development of early stages of mouse embryo later. Oocytes were collected and treated with hyaluronidase to remove cumulus cells. Oocytes were divided into four groups namely: Group-1: Oocytes incubated within modified Earl’s medium (MEM supplied with 10% inactivated bovine amniotic fluid as a protein source and cumulus cells; Group-2: Oocytes incubated with MEM supplied with cumulus cells only; Group-3: Oocytes incubated with MEM supplied with 10% inactivated bovine amniotic fluid only; and Group-4: Oocytes  incubated with MEM free of both protein source and cumulus cells. For IVF, 5-6 oocytes were incubated with active spermatozoa under paraffin oil for 18-20 hours at 37° oC in 5% CO2. Percentages of IVF and embryonic development were then recorded. Best results for IVF and normal embryonic development were achieved from oocytes of Group-1 when compared to the other groups. As compared to Group-1, the percentage of IVF for Group-2 and Group-3 were decreased insignificantly and significantly (P<0.002, respectively. Significant (P<0.01 reduction in the percentages of IVF and normal embryonic development were reported in Group-4 as compared to Group-1. Therefore, it was concluded that the presence of cumulus cells co-culture and bovine amniotic fluid as a protein source within culture medium may have an important role on the fertilizing capacity of spermatozoa and oocytes and normal development of pre-implanted mouse embryo later.

  16. Conductor gestures influence evaluations of ensemble performance.

    Science.gov (United States)

    Morrison, Steven J; Price, Harry E; Smedley, Eric M; Meals, Cory D

    2014-01-01

    Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor's gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance: articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and non-majors (N = 285) viewed sixteen 30 s performances and evaluated the quality of the ensemble's articulation, dynamics, technique, and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble's performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

  17. Rotationally invariant family of Levy-like random matrix ensembles

    International Nuclear Information System (INIS)

    Choi, Jinmyung; Muttalib, K A

    2009-01-01

    We introduce a family of rotationally invariant random matrix ensembles characterized by a parameter λ. While λ = 1 corresponds to well-known critical ensembles, we show that λ ≠ 1 describes 'Levy-like' ensembles, characterized by power-law eigenvalue densities. For λ > 1 the density is bounded, as in Gaussian ensembles, but λ < 1 describes ensembles characterized by densities with long tails. In particular, the model allows us to evaluate, in terms of a novel family of orthogonal polynomials, the eigenvalue correlations for Levy-like ensembles. These correlations differ qualitatively from those in either the Gaussian or the critical ensembles. (fast track communication)

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

    KAUST Repository

    Toye, Habib

    2017-05-26

    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.

  19. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    Science.gov (United States)

    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.

  20. In vitro production of bovine embryos: cumulus/granulosa cell gene expression patterns point to early atresia as beneficial for oocyte competence

    DEFF Research Database (Denmark)

    Mazzoni, Gianluca; Razza, Eduardo; Pedersen, Hanne S.

    2017-01-01

    In vitro production (IW) of bovine embryos has become widespread technology implemented in cattle breeding and production. Here, we review novel data on cumulus/granulosa cell gene expression, as determined by RNAseq on cellular material from pooled follicular fluids at the single animal level...

  1. Molecular mechanisms of insulin-like growth factor 1 promoted synthesis and retention of hyaluronic acid in porcine oocyte-cumulus complexes

    Czech Academy of Sciences Publication Activity Database

    Němcová, Lucie; Nagyová, Eva; Petlach, Michal; Tománek, M.; Procházka, Radek

    2007-01-01

    Roč. 76, - (2007), s. 1016-1024 ISSN 0006-3363 R&D Projects: GA ČR GA523/04/0574 Institutional research plan: CEZ:AV0Z50450515 Keywords : cumulus cells * expansion * follicle-stimulating hormone Subject RIV: ED - Physiology Impact factor: 3.670, year: 2007

  2. Gene expression analysis of pig cumulus-oocyte complexes stimulated in vitro with follicle stimulating hormone or epidermal growth factor-like peptides

    Czech Academy of Sciences Publication Activity Database

    Blaha, Milan; Němcová, Lucie; Vodičková Kepková, Kateřina; Vodička, P.; Procházka, Radek

    2015-01-01

    Roč. 13, č. 113 (2015) ISSN 1477-7827 R&D Projects: GA ČR GAP502/11/0593; GA MZe(CZ) QJ1510138 Institutional support: RVO:67985904 Keywords : FSH * growth factors * cumulus cell Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.147, year: 2015

  3. Increased expression of pentraxin 3 after in vivo and in vitro stimulation with gonadotropins in porcine oocyte-cumulus complexes and granulosa cells

    Czech Academy of Sciences Publication Activity Database

    Nagyová, Eva; Kalous, Jaroslav; Němcová, Lucie

    2016-01-01

    Roč. 56, č. 1 (2016), s. 29-35 ISSN 0739-7240 R&D Projects: GA ČR GA305/05/0960 Institutional support: RVO:67985904 Keywords : oocyte-cumulus complex * granulosa cells * pentraxin 3 Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.644, year: 2016

  4. RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

    Science.gov (United States)

    Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; Fridlind, Ann; Endo, Satoshi; Song, Hua; Feng, Sha; Toto, Tami; Li, Zhijin; Zhang, Minghua

    2015-01-01

    Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

  5. Understanding ensemble protein folding at atomic detail

    International Nuclear Information System (INIS)

    Wallin, Stefan; Shakhnovich, Eugene I

    2008-01-01

    Although far from routine, simulating the folding of specific short protein chains on the computer, at a detailed atomic level, is starting to become a reality. This remarkable progress, which has been made over the last decade or so, allows a fundamental aspect of the protein folding process to be addressed, namely its statistical nature. In order to make quantitative comparisons with experimental kinetic data a complete ensemble view of folding must be achieved, with key observables averaged over the large number of microscopically different folding trajectories available to a protein chain. Here we review recent advances in atomic-level protein folding simulations and the new insight provided by them into the protein folding process. An important element in understanding ensemble folding kinetics are methods for analyzing many separate folding trajectories, and we discuss techniques developed to condense the large amount of information contained in an ensemble of trajectories into a manageable picture of the folding process. (topical review)

  6. Lattice gauge theory in the microcanonical ensemble

    International Nuclear Information System (INIS)

    Callaway, D.J.E.; Rahman, A.

    1983-01-01

    The microcanonical-ensemble formulation of lattice gauge theory proposed recently is examined in detail. Expectation values in this new ensemble are determined by solving a large set of coupled ordinary differential equations, after the fashion of a molecular dynamics simulation. Following a brief review of the microcanonical ensemble, calculations are performed for the gauge groups U(1), SU(2), and SU(3). The results are compared and contrasted with standard methods of computation. Several advantages of the new formalism are noted. For example, no random numbers are required to update the system. Also, this update is performed in a simultaneous fashion. Thus the microcanonical method presumably adapts well to parallel processing techniques, especially when the p action is highly nonlocal (such as when fermions are included)

  7. Ensemble Network Architecture for Deep Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Xi-liang Chen

    2018-01-01

    Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.

  8. Embedded random matrix ensembles in quantum physics

    CERN Document Server

    Kota, V K B

    2014-01-01

    Although used with increasing frequency in many branches of physics, random matrix ensembles are not always sufficiently specific to account for important features of the physical system at hand. One refinement which retains the basic stochastic approach but allows for such features consists in the use of embedded ensembles.  The present text is an exhaustive introduction to and survey of this important field. Starting with an easy-to-read introduction to general random matrix theory, the text then develops the necessary concepts from the beginning, accompanying the reader to the frontiers of present-day research. With some notable exceptions, to date these ensembles have primarily been applied in nuclear spectroscopy. A characteristic example is the use of a random two-body interaction in the framework of the nuclear shell model. Yet, topics in atomic physics, mesoscopic physics, quantum information science and statistical mechanics of isolated finite quantum systems can also be addressed using these ensemb...

  9. Transcriptome dynamics and molecular cross-talk between bovine oocyte and its companion cumulus cells

    Directory of Open Access Journals (Sweden)

    Looft C

    2011-01-01

    Full Text Available Abstract Background The bi-directional communication between the oocyte and its companion cumulus cells (CCs is crucial for development and functions of both cell types. Transcripts that are exclusively expressed either in oocytes or CCs and molecular mechanisms affected due to removal of the communication axis between the two cell types is not investigated at a larger scale. The main objectives of this study were: 1. To identify transcripts exclusively expressed either in oocyte or CCs and 2. To identify those which are differentially expressed when the oocyte is cultured with or without its companion CCs and vice versa. Results We analyzed transcriptome profile of different oocyte and CC samples using Affymetrix GeneChip Bovine Genome array containing 23000 transcripts. Out of 13162 genes detected in germinal vesicle (GV oocytes and their companion CCs, 1516 and 2727 are exclusively expressed in oocytes and CCs, respectively, while 8919 are expressed in both. Similarly, of 13602 genes detected in metaphase II (MII oocytes and CCs, 1423 and 3100 are exclusively expressed in oocytes and CCs, respectively, while 9079 are expressed in both. A total of 265 transcripts are differentially expressed between oocytes cultured with (OO + CCs and without (OO - CCs CCs, of which 217 and 48 are over expressed in the former and the later groups, respectively. Similarly, 566 transcripts are differentially expressed when CCs mature with (CCs + OO or without (CCs - OO their enclosed oocytes. Of these, 320 and 246 are over expressed in CCs + OO and CCs - OO, respectively. While oocyte specific transcripts include those involved in transcription (IRF6, POU5F1, MYF5, MED18, translation (EIF2AK1, EIF4ENIF1 and CCs specific ones include those involved in carbohydrate metabolism (HYAL1, PFKL, PYGL, MPI, protein metabolic processes (IHH, APOA1, PLOD1, steroid biosynthetic process (APOA1, CYP11A1, HSD3B1, HSD3B7. Similarly, while transcripts over expressed in OO + CCs

  10. Investigating the Variability in Cumulus Cloud Number as a Function of Subdomain Size and Organization using large-domain LES

    Science.gov (United States)

    Neggers, R.

    2017-12-01

    Recent advances in supercomputing have introduced a "grey zone" in the representation of cumulus convection in general circulation models, in which this process is partially resolved. Cumulus parameterizations need to be made scale-aware and scale-adaptive to be able to conceptually and practically deal with this situation. A potential way forward are schemes formulated in terms of discretized Cloud Size Densities, or CSDs. Advantages include i) the introduction of scale-awareness at the foundation of the scheme, and ii) the possibility to apply size-filtering of parameterized convective transport and clouds. The CSD is a new variable that requires closure; this concerns its shape, its range, but also variability in cloud number that can appear due to i) subsampling effects and ii) organization in a cloud field. The goal of this study is to gain insight by means of sub-domain analyses of various large-domain LES realizations of cumulus cloud populations. For a series of three-dimensional snapshots, each with a different degree of organization, the cloud size distribution is calculated in all subdomains, for a range of subdomain sizes. The standard deviation of the number of clouds of a certain size is found to decrease with the subdomain size, following a powerlaw scaling corresponding to an inverse-linear dependence. Cloud number variability also increases with cloud size; this reflects that subsampling affects the largest clouds first, due to their typically larger neighbor spacing. Rewriting this dependence in terms of two dimensionless groups, by dividing by cloud number and cloud size respectively, yields a data collapse. Organization in the cloud field is found to act on top of this primary dependence, by enhancing the cloud number variability at the smaller sizes. This behavior reflects that small clouds start to "live" on top of larger structures such as cold pools, favoring or inhibiting their formation (as illustrated by the attached figure of cloud mask

  11. Ensemble Kalman methods for inverse problems

    International Nuclear Information System (INIS)

    Iglesias, Marco A; Law, Kody J H; Stuart, Andrew M

    2013-01-01

    The ensemble Kalman filter (EnKF) was introduced by Evensen in 1994 (Evensen 1994 J. Geophys. Res. 99 10143–62) as a novel method for data assimilation: state estimation for noisily observed time-dependent problems. Since that time it has had enormous impact in many application domains because of its robustness and ease of implementation, and numerical evidence of its accuracy. In this paper we propose the application of an iterative ensemble Kalman method for the solution of a wide class of inverse problems. In this context we show that the estimate of the unknown function that we obtain with the ensemble Kalman method lies in a subspace A spanned by the initial ensemble. Hence the resulting error may be bounded above by the error found from the best approximation in this subspace. We provide numerical experiments which compare the error incurred by the ensemble Kalman method for inverse problems with the error of the best approximation in A, and with variants on traditional least-squares approaches, restricted to the subspace A. In so doing we demonstrate that the ensemble Kalman method for inverse problems provides a derivative-free optimization method with comparable accuracy to that achieved by traditional least-squares approaches. Furthermore, we also demonstrate that the accuracy is of the same order of magnitude as that achieved by the best approximation. Three examples are used to demonstrate these assertions: inversion of a compact linear operator; inversion of piezometric head to determine hydraulic conductivity in a Darcy model of groundwater flow; and inversion of Eulerian velocity measurements at positive times to determine the initial condition in an incompressible fluid. (paper)

  12. Cluster ensembles, quantization and the dilogarithm

    DEFF Research Database (Denmark)

    Fock, Vladimir; Goncharov, Alexander B.

    2009-01-01

    A cluster ensemble is a pair of positive spaces (i.e. varieties equipped with positive atlases), coming with an action of a symmetry group . The space is closely related to the spectrum of a cluster algebra [ 12 ]. The two spaces are related by a morphism . The space is equipped with a closed -form......, possibly degenerate, and the space has a Poisson structure. The map is compatible with these structures. The dilogarithm together with its motivic and quantum avatars plays a central role in the cluster ensemble structure. We define a non-commutative -deformation of the -space. When is a root of unity...

  13. Ensemble computing for the petroleum industry

    International Nuclear Information System (INIS)

    Annaratone, M.; Dossa, D.

    1995-01-01

    Computer downsizing is one of the most often used buzzwords in today's competitive business, and the petroleum industry is at the forefront of this revolution. Ensemble computing provides the key for computer downsizing with its first incarnation, i.e., workstation farms. This paper concerns the importance of increasing the productivity cycle and not just the execution time of a job. The authors introduce the concept of ensemble computing and workstation farms. The they discuss how different computing paradigms can be addressed by workstation farms

  14. A class of energy-based ensembles in Tsallis statistics

    International Nuclear Information System (INIS)

    Chandrashekar, R; Naina Mohammed, S S

    2011-01-01

    A comprehensive investigation is carried out on the class of energy-based ensembles. The eight ensembles are divided into two main classes. In the isothermal class of ensembles the individual members are at the same temperature. A unified framework is evolved to describe the four isothermal ensembles using the currently accepted third constraint formalism. The isothermal–isobaric, grand canonical and generalized ensembles are illustrated through a study of the classical nonrelativistic and extreme relativistic ideal gas models. An exact calculation is possible only in the case of the isothermal–isobaric ensemble. The study of the ideal gas models in the grand canonical and the generalized ensembles has been carried out using a perturbative procedure with the nonextensivity parameter (1 − q) as the expansion parameter. Though all the thermodynamic quantities have been computed up to a particular order in (1 − q) the procedure can be extended up to any arbitrary order in the expansion parameter. In the adiabatic class of ensembles the individual members of the ensemble have the same value of the heat function and a unified formulation to described all four ensembles is given. The nonrelativistic and the extreme relativistic ideal gases are studied in the isoenthalpic–isobaric ensemble, the adiabatic ensemble with number fluctuations and the adiabatic ensemble with number and particle fluctuations

  15. Embodied Making and Design Learning - Special Issue from the Learn X Design-conference DRS/CUMULUS, Chicago 2015

    Directory of Open Access Journals (Sweden)

    Marte Sørebø Gulliksen

    2016-06-01

    Full Text Available This issue of FORMakademisk features selected articles developed from papers presented at the symposium Embodied Making and Design Learning at the DRS/CUMULUS-conference LearnXDesign in Chicago, Illinois, June 28–30, 2015. This special issue was developed as an initiative by the symposium conveners. The symposium was developed by researchers from research groups in Norway, Finland and Canada to explore various aspects of embodied making in relation to design learning. The symposium was a full-day event with four sessions, seven paper presentations, a roundtable discussion, a plenary discussion and a workshop. The symposium received positive feedback, attracting many participants and stimulating engaged discussions throughout the conference. This indicates a growing awareness of the topic of embodied making and design learning. This special issue features five articles that together highlight a variety of approaches and examples of current research endeavours in relation to the theme. 

  16. Gene expression microarray profiles of cumulus cells in lean and overweight-obese polycystic ovary syndrome patients.

    Science.gov (United States)

    Kenigsberg, Shlomit; Bentov, Yaakov; Chalifa-Caspi, Vered; Potashnik, Gad; Ofir, Rivka; Birk, Ohad S

    2009-02-01

    The aim of this work was to study gene expression patterns of cultured cumulus cells from lean and overweight-obese polycystic ovary syndrome (PCOS) patients using genome-wide oligonucleotide microarray. The study included 25 patients undergoing in vitro fertilization and intra-cytoplasmic sperm injection: 12 diagnosed with PCOS and 13 matching controls. Each of the groups was subdivided into lean (body mass index (BMI) 27) subgroups. The following comparisons of gene expression data were made: lean PCOS versus lean controls, lean PCOS versus overweight PCOS, all PCOS versus all controls, overweight PCOS versus overweight controls, overweight controls versus lean controls and all overweight versus all lean. The largest number of differentially expressed genes (DEGs), with fold change (FC) |FC| >or= 1.5 and P-value lean PCOS versus lean controls comparison (487) with most of these genes being down-regulated in PCOS. The second largest group of DEGs originated from the comparison of lean PCOS versus overweight PCOS (305). The other comparisons resulted in a much smaller number of DEGs (174, 109, 125 and 12, respectively). In the comparison of lean PCOS with lean controls, most DEGs were transcription factors and components of the extracellular matrix and two pathways, Wnt/beta-catenin and mitogen-activated protein kinase. When comparing overweight PCOS with overweight controls, most DEGs were of pathways related to insulin signaling, metabolism and energy production. The finding of unique gene expression patterns in cumulus cells from the two PCOS subtypes is in agreement with other studies that have found the two to be separate entities with potentially different pathophysiologies.

  17. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    Science.gov (United States)

    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.

  18. A method for ensemble wildland fire simulation

    Science.gov (United States)

    Mark A. Finney; Isaac C. Grenfell; Charles W. McHugh; Robert C. Seli; Diane Trethewey; Richard D. Stratton; Stuart Brittain

    2011-01-01

    An ensemble simulation system that accounts for uncertainty in long-range weather conditions and two-dimensional wildland fire spread is described. Fuel moisture is expressed based on the energy release component, a US fire danger rating index, and its variation throughout the fire season is modeled using time series analysis of historical weather data. This analysis...

  19. The Phantasmagoria of Competition in School Ensembles

    Science.gov (United States)

    Abramo, Joseph Michael

    2017-01-01

    Participation in competition festivals--where students and ensembles compete against each other for high scores and accolades--is a widespread practice in North American formal music education. In this article, I use Marx's theories of labor, value, and phantasmagoria to suggest a capitalist logic that structures these competitions. Marx's…

  20. Ensembl Genomes 2016: more genomes, more complexity.

    Science.gov (United States)

    Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

    2016-01-04

    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 set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  1. NYYD Ensemble ja Riho Sibul / Anneli Remme

    Index Scriptorium Estoniae

    Remme, Anneli, 1968-

    2001-01-01

    Gavin Bryarsi teos "Jesus' Blood Never Failed Me Yet" NYYD Ensemble'i ja Riho Sibula esituses 27. detsembril Pauluse kirikus Tartus ja 28. detsembril Rootsi- Mihkli kirikus Tallinnas. Kaastegevad Tartu Ülikooli Kammerkoor (Tartus) ja kammerkoor Voces Musicales (Tallinnas). Kunstiline juht Olari Elts

  2. Conductor gestures influence evaluations of ensemble performance

    Directory of Open Access Journals (Sweden)

    Steven eMorrison

    2014-07-01

    Full Text Available Previous research has found that listener evaluations of ensemble performances vary depending on the expressivity of the conductor’s gestures, even when performances are otherwise identical. It was the purpose of the present study to test whether this effect of visual information was evident in the evaluation of specific aspects of ensemble performance, articulation and dynamics. We constructed a set of 32 music performances that combined auditory and visual information and were designed to feature a high degree of contrast along one of two target characteristics: articulation and dynamics. We paired each of four music excerpts recorded by a chamber ensemble in both a high- and low-contrast condition with video of four conductors demonstrating high- and low-contrast gesture specifically appropriate to either articulation or dynamics. Using one of two equivalent test forms, college music majors and nonmajors (N = 285 viewed sixteen 30-second performances and evaluated the quality of the ensemble’s articulation, dynamics, technique and tempo along with overall expressivity. Results showed significantly higher evaluations for performances featuring high rather than low conducting expressivity regardless of the ensemble’s performance quality. Evaluations for both articulation and dynamics were strongly and positively correlated with evaluations of overall ensemble expressivity.

  3. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    NJD

    Improvements in neural network calibration models by a novel approach using neural network ensemble (NNE) for the simultaneous ... process by training a number of neural networks. .... Matlab® version 6.1 was employed for building principal component ... provide a fair simulation of calibration data set with some degree.

  4. A Theoretical Analysis of Why Hybrid Ensembles Work

    Directory of Open Access Journals (Sweden)

    Kuo-Wei Hsu

    2017-01-01

    Full Text Available 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.

  5. Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

    Institute of Scientific and Technical Information of China (English)

    Zhaoxia PU; Joshua HACKER

    2009-01-01

    This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

  6. Ensemble of classifiers based network intrusion detection system performance bound

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-11-01

    Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

  7. Global Ensemble Forecast System (GEFS) [2.5 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  8. Using ensemble forecasting for wind power

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Landberg, L.; Badger, J. [Risoe National Lab., Roskilde (Denmark); Sattler, K.

    2003-07-01

    Short-term prediction of wind power has a long tradition in Denmark. It is an essential tool for the operators to keep the grid from becoming unstable in a region like Jutland, where more than 27% of the electricity consumption comes from wind power. This means that the minimum load is already lower than the maximum production from wind energy alone. Danish utilities have therefore used short-term prediction of wind energy since the mid-90ies. However, the accuracy is still far from being sufficient in the eyes of the utilities (used to have load forecasts accurate to within 5% on a one-week horizon). The Ensemble project tries to alleviate the dependency of the forecast quality on one model by using multiple models, and also will investigate the possibilities of using the model spread of multiple models or of dedicated ensemble runs for a prediction of the uncertainty of the forecast. Usually, short-term forecasting works (especially for the horizon beyond 6 hours) by gathering input from a Numerical Weather Prediction (NWP) model. This input data is used together with online data in statistical models (this is the case eg in Zephyr/WPPT) to yield the output of the wind farms or of a whole region for the next 48 hours (only limited by the NWP model horizon). For the accuracy of the final production forecast, the accuracy of the NWP prediction is paramount. While many efforts are underway to increase the accuracy of the NWP forecasts themselves (which ultimately are limited by the amount of computing power available, the lack of a tight observational network on the Atlantic and limited physics modelling), another approach is to use ensembles of different models or different model runs. This can be either an ensemble of different models output for the same area, using different data assimilation schemes and different model physics, or a dedicated ensemble run by a large institution, where the same model is run with slight variations in initial conditions and

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

    KAUST Repository

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

    2017-01-01

    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

  10. Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

    KAUST Repository

    Luo, Xiaodong; Hoteit, Ibrahim

    2011-01-01

    A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used

  11. Quantum canonical ensemble: A projection operator approach

    Science.gov (United States)

    Magnus, Wim; Lemmens, Lucien; Brosens, Fons

    2017-09-01

    Knowing the exact number of particles N, and taking this knowledge into account, the quantum canonical ensemble imposes a constraint on the occupation number operators. The constraint particularly hampers the systematic calculation of the partition function and any relevant thermodynamic expectation value for arbitrary but fixed N. On the other hand, fixing only the average number of particles, one may remove the above constraint and simply factorize the traces in Fock space into traces over single-particle states. As is well known, that would be the strategy of the grand-canonical ensemble which, however, comes with an additional Lagrange multiplier to impose the average number of particles. The appearance of this multiplier can be avoided by invoking a projection operator that enables a constraint-free computation of the partition function and its derived quantities in the canonical ensemble, at the price of an angular or contour integration. Introduced in the recent past to handle various issues related to particle-number projected statistics, the projection operator approach proves beneficial to a wide variety of problems in condensed matter physics for which the canonical ensemble offers a natural and appropriate environment. In this light, we present a systematic treatment of the canonical ensemble that embeds the projection operator into the formalism of second quantization while explicitly fixing N, the very number of particles rather than the average. Being applicable to both bosonic and fermionic systems in arbitrary dimensions, transparent integral representations are provided for the partition function ZN and the Helmholtz free energy FN as well as for two- and four-point correlation functions. The chemical potential is not a Lagrange multiplier regulating the average particle number but can be extracted from FN+1 -FN, as illustrated for a two-dimensional fermion gas.

  12. RACORO continental boundary layer cloud investigations: 1. Case study development and ensemble large-scale forcings

    Science.gov (United States)

    Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang; Li, Zhijin; Xie, Shaocheng; Ackerman, Andrew S.; Zhang, Minghua; Khairoutdinov, Marat

    2015-06-01

    Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be 0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in "trial" large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

  13. RACORO Continental Boundary Layer Cloud Investigations: 1. Case Study Development and Ensemble Large-Scale Forcings

    Science.gov (United States)

    Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang; hide

    2015-01-01

    Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, kappa, are derived from observations to be approximately 0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in "trial" large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary

  14. The classicality and quantumness of a quantum ensemble

    International Nuclear Information System (INIS)

    Zhu Xuanmin; Pang Shengshi; Wu Shengjun; Liu Quanhui

    2011-01-01

    In this Letter, we investigate the classicality and quantumness of a quantum ensemble. We define a quantity called ensemble classicality based on classical cloning strategy (ECCC) to characterize how classical a quantum ensemble is. An ensemble of commuting states has a unit ECCC, while a general ensemble can have a ECCC less than 1. We also study how quantum an ensemble is by defining a related quantity called quantumness. We find that the classicality of an ensemble is closely related to how perfectly the ensemble can be cloned, and that the quantumness of the ensemble used in a quantum key distribution (QKD) protocol is exactly the attainable lower bound of the error rate in the sifted key. - Highlights: → A quantity is defined to characterize how classical a quantum ensemble is. → The classicality of an ensemble is closely related to the cloning performance. → Another quantity is also defined to investigate how quantum an ensemble is. → This quantity gives the lower bound of the error rate in a QKD protocol.

  15. Exploring and Listening to Chinese Classical Ensembles in General Music

    Science.gov (United States)

    Zhang, Wenzhuo

    2017-01-01

    Music diversity is valued in theory, but the extent to which it is efficiently presented in music class remains limited. Within this article, I aim to bridge this gap by introducing four genres of Chinese classical ensembles--Qin and Xiao duets, Jiang Nan bamboo and silk ensembles, Cantonese ensembles, and contemporary Chinese orchestras--into the…

  16. Critical Listening in the Ensemble Rehearsal: A Community of Learners

    Science.gov (United States)

    Bell, Cindy L.

    2018-01-01

    This article explores a strategy for engaging ensemble members in critical listening analysis of performances and presents opportunities for improving ensemble sound through rigorous dialogue, reflection, and attentive rehearsing. Critical listening asks ensemble members to draw on individual playing experience and knowledge to describe what they…

  17. INFLUÊNCIA DA TEMPERATURA DE FECUNDAÇÃO IN VITRO E DAS CÉLULAS DO Cumulus oophorus SOBRE A TAXA DE POLISPERMIA E DESENVOLVIMENTO EMBRIONÁRIO

    Directory of Open Access Journals (Sweden)

    Melissa Savoia Castilho Cunha

    2010-06-01

    Full Text Available Effects of in vitro fertilization (IVF temperature andcumulus oophorus cells removal after IVF or 12 h of embryoculture (IVC on polyspermy and embryo development rates wereevaluated in swine. Oocytes and spermatozoa were incubated at37 or 38.5ºC during IVF procedure. Cumulus oophorus cells wereremoved from 50% of zygotes of each group 8 hours after IVF andall zygotes were cultured with NCSU23 media. Polyspermy rateswere assessed after 12 hours of IVC, when cumulus oophorus cellswere removed from the rest of zygotes. In a second experiment,embryos remained in culture for the evaluation of embryodevelopment. No effects of IVF temperature or cumulus oophoruscells removal were observed after 12 hours of IVC on polyspermyand embryo development (p<0.05. In conclusion, IVF temperatureand the presence of cumulus oophorus cells after IVF do notinterfere on polyspermy and embryo development rates.

  18. Improving Climate Projections Using "Intelligent" Ensembles

    Science.gov (United States)

    Baker, Noel C.; Taylor, Patrick C.

    2015-01-01

    Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and

  19. Demonstrating the value of larger ensembles in forecasting physical systems

    Directory of Open Access Journals (Sweden)

    Reason L. Machete

    2016-12-01

    Full Text Available Ensemble simulation propagates a collection of initial states forward in time in a Monte Carlo fashion. Depending on the fidelity of the model and the properties of the initial ensemble, the goal of ensemble simulation can range from merely quantifying variations in the sensitivity of the model all the way to providing actionable probability forecasts of the future. Whatever the goal is, success depends on the properties of the ensemble, and there is a longstanding discussion in meteorology as to the size of initial condition ensemble most appropriate for Numerical Weather Prediction. In terms of resource allocation: how is one to divide finite computing resources between model complexity, ensemble size, data assimilation and other components of the forecast system. One wishes to avoid undersampling information available from the model's dynamics, yet one also wishes to use the highest fidelity model available. Arguably, a higher fidelity model can better exploit a larger ensemble; nevertheless it is often suggested that a relatively small ensemble, say ~16 members, is sufficient and that larger ensembles are not an effective investment of resources. This claim is shown to be dubious when the goal is probabilistic forecasting, even in settings where the forecast model is informative but imperfect. Probability forecasts for a ‘simple’ physical system are evaluated at different lead times; ensembles of up to 256 members are considered. The pure density estimation context (where ensemble members are drawn from the same underlying distribution as the target differs from the forecasting context, where one is given a high fidelity (but imperfect model. In the forecasting context, the information provided by additional members depends also on the fidelity of the model, the ensemble formation scheme (data assimilation, the ensemble interpretation and the nature of the observational noise. The effect of increasing the ensemble size is quantified by

  20. Data assimilation in integrated hydrological modeling using ensemble Kalman filtering

    DEFF Research Database (Denmark)

    Rasmussen, Jørn; Madsen, H.; Jensen, Karsten Høgh

    2015-01-01

    Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members...... and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data...

  1. Statistical ensembles for money and debt

    Science.gov (United States)

    Viaggiu, Stefano; Lionetto, Andrea; Bargigli, Leonardo; Longo, Michele

    2012-10-01

    We build a statistical ensemble representation of two economic models describing respectively, in simplified terms, a payment system and a credit market. To this purpose we adopt the Boltzmann-Gibbs distribution where the role of the Hamiltonian is taken by the total money supply (i.e. including money created from debt) of a set of interacting economic agents. As a result, we can read the main thermodynamic quantities in terms of monetary ones. In particular, we define for the credit market model a work term which is related to the impact of monetary policy on credit creation. Furthermore, with our formalism we recover and extend some results concerning the temperature of an economic system, previously presented in the literature by considering only the monetary base as a conserved quantity. Finally, we study the statistical ensemble for the Pareto distribution.

  2. ABCD of Beta Ensembles and Topological Strings

    CERN Document Server

    Krefl, Daniel

    2012-01-01

    We study beta-ensembles with Bn, Cn, and Dn eigenvalue measure and their relation with refined topological strings. Our results generalize the familiar connections between local topological strings and matrix models leading to An measure, and illustrate that all those classical eigenvalue ensembles, and their topological string counterparts, are related one to another via various deformations and specializations, quantum shifts and discrete quotients. We review the solution of the Gaussian models via Macdonald identities, and interpret them as conifold theories. The interpolation between the various models is plainly apparent in this case. For general polynomial potential, we calculate the partition function in the multi-cut phase in a perturbative fashion, beyond tree-level in the large-N limit. The relation to refined topological string orientifolds on the corresponding local geometry is discussed along the way.

  3. Quark ensembles with the infinite correlation length

    Science.gov (United States)

    Zinov'ev, G. M.; Molodtsov, S. V.

    2015-01-01

    A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble.

  4. Quark ensembles with the infinite correlation length

    International Nuclear Information System (INIS)

    Zinov’ev, G. M.; Molodtsov, S. V.

    2015-01-01

    A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble

  5. Quark ensembles with the infinite correlation length

    Energy Technology Data Exchange (ETDEWEB)

    Zinov’ev, G. M. [National Academy of Sciences of Ukraine, Bogoliubov Institute for Theoretical Physics (Ukraine); Molodtsov, S. V., E-mail: molodtsov@itep.ru [Joint Institute for Nuclear Research (Russian Federation)

    2015-01-15

    A number of exactly integrable (quark) models of quantum field theory with the infinite correlation length have been considered. It has been shown that the standard vacuum quark ensemble—Dirac sea (in the case of the space-time dimension higher than three)—is unstable because of the strong degeneracy of a state, which is due to the character of the energy distribution. When the momentum cutoff parameter tends to infinity, the distribution becomes infinitely narrow, leading to large (unlimited) fluctuations. Various vacuum ensembles—Dirac sea, neutral ensemble, color superconductor, and BCS state—have been compared. In the case of the color interaction between quarks, the BCS state has been certainly chosen as the ground state of the quark ensemble.

  6. Various multistage ensembles for prediction of heating energy consumption

    Directory of Open Access Journals (Sweden)

    Radisa Jovanovic

    2015-04-01

    Full Text Available Feedforward neural network models are created for prediction of daily heating energy consumption of a NTNU university campus Gloshaugen using actual measured data for training and testing. Improvement of prediction accuracy is proposed by using neural network ensemble. Previously trained feed-forward neural networks are first separated into clusters, using k-means algorithm, and then the best network of each cluster is chosen as member of an ensemble. Two conventional averaging methods for obtaining ensemble output are applied; simple and weighted. In order to achieve better prediction results, multistage ensemble is investigated. As second level, adaptive neuro-fuzzy inference system with various clustering and membership functions are used to aggregate the selected ensemble members. Feedforward neural network in second stage is also analyzed. It is shown that using ensemble of neural networks can predict heating energy consumption with better accuracy than the best trained single neural network, while the best results are achieved with multistage ensemble.

  7. Online Learning of Commission Avoidant Portfolio Ensembles

    OpenAIRE

    Uziel, Guy; El-Yaniv, Ran

    2016-01-01

    We present a novel online ensemble learning strategy for portfolio selection. The new strategy controls and exploits any set of commission-oblivious portfolio selection algorithms. The strategy handles transaction costs using a novel commission avoidance mechanism. We prove a logarithmic regret bound for our strategy with respect to optimal mixtures of the base algorithms. Numerical examples validate the viability of our method and show significant improvement over the state-of-the-art.

  8. Modeling Coordination Problems in a Music Ensemble

    DEFF Research Database (Denmark)

    Frimodt-Møller, Søren R.

    2008-01-01

    This paper considers in general terms, how musicians are able to coordinate through rational choices in a situation of (temporary) doubt in an ensemble performance. A fictitious example involving a 5-bar development in an unknown piece of music is analyzed in terms of epistemic logic, more...... to coordinate. Such coordination can be described in terms of Michael Bacharach's theory of variable frames as an aid to solve game theoretic coordination problems....

  9. Microcanonical ensemble formulation of lattice gauge theory

    International Nuclear Information System (INIS)

    Callaway, D.J.E.; Rahman, A.

    1982-01-01

    A new formulation of lattice gauge theory without explicit path integrals or sums is obtained by using the microcanonical ensemble of statistical mechanics. Expectation values in the new formalism are calculated by solving a large set of coupled, nonlinear, ordinary differential equations. The average plaquette for compact electrodynamics calculated in this fashion agrees with standard Monte Carlo results. Possible advantages of the microcanonical method in applications to fermionic systems are discussed

  10. Ensemble forecasts of road surface temperatures

    Czech Academy of Sciences Publication Activity Database

    Sokol, Zbyněk; Bližňák, Vojtěch; Sedlák, Pavel; Zacharov, Petr, jr.; Pešice, Petr; Škuthan, M.

    2017-01-01

    Roč. 187, 1 May (2017), s. 33-41 ISSN 0169-8095 R&D Projects: GA ČR GA13-34856S; GA TA ČR(CZ) TA01031509 Institutional support: RVO:68378289 Keywords : ensemble prediction * road surface temperature * road weather forecast Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences Impact factor: 3.778, year: 2016 http://www.sciencedirect.com/science/article/pii/S0169809516307311

  11. Microcanonical ensemble extensive thermodynamics of Tsallis statistics

    International Nuclear Information System (INIS)

    Parvan, A.S.

    2005-01-01

    The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics.The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ = 1/q - 1 in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z bar = 1/(q - 1)N = const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

  12. Modeling polydispersive ensembles of diamond nanoparticles

    International Nuclear Information System (INIS)

    Barnard, Amanda S

    2013-01-01

    While significant progress has been made toward production of monodispersed samples of a variety of nanoparticles, in cases such as diamond nanoparticles (nanodiamonds) a significant degree of polydispersivity persists, so scaling-up of laboratory applications to industrial levels has its challenges. In many cases, however, monodispersivity is not essential for reliable application, provided that the inevitable uncertainties are just as predictable as the functional properties. As computational methods of materials design are becoming more widespread, there is a growing need for robust methods for modeling ensembles of nanoparticles, that capture the structural complexity characteristic of real specimens. In this paper we present a simple statistical approach to modeling of ensembles of nanoparticles, and apply it to nanodiamond, based on sets of individual simulations that have been carefully selected to describe specific structural sources that are responsible for scattering of fundamental properties, and that are typically difficult to eliminate experimentally. For the purposes of demonstration we show how scattering in the Fermi energy and the electronic band gap are related to different structural variations (sources), and how these results can be combined strategically to yield statistically significant predictions of the properties of an entire ensemble of nanodiamonds, rather than merely one individual ‘model’ particle or a non-representative sub-set. (paper)

  13. Ensemble Clustering using Semidefinite Programming with Applications.

    Science.gov (United States)

    Singh, Vikas; Mukherjee, Lopamudra; Peng, Jiming; Xu, Jinhui

    2010-05-01

    In this paper, we study the ensemble clustering problem, where the input is in the form of multiple clustering solutions. The goal of ensemble clustering algorithms is to aggregate the solutions into one solution that maximizes the agreement in the input ensemble. We obtain several new results for this problem. Specifically, we show that the notion of agreement under such circumstances can be better captured using a 2D string encoding rather than a voting strategy, which is common among existing approaches. Our optimization proceeds by first constructing a non-linear objective function which is then transformed into a 0-1 Semidefinite program (SDP) using novel convexification techniques. This model can be subsequently relaxed to a polynomial time solvable SDP. In addition to the theoretical contributions, our experimental results on standard machine learning and synthetic datasets show that this approach leads to improvements not only in terms of the proposed agreement measure but also the existing agreement measures based on voting strategies. In addition, we identify several new application scenarios for this problem. These include combining multiple image segmentations and generating tissue maps from multiple-channel Diffusion Tensor brain images to identify the underlying structure of the brain.

  14. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-12-03

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  15. Decimated Input Ensembles for Improved Generalization

    Science.gov (United States)

    Tumer, Kagan; Oza, Nikunj C.; Norvig, Peter (Technical Monitor)

    1999-01-01

    Recently, many researchers have demonstrated that using classifier ensembles (e.g., averaging the outputs of multiple classifiers before reaching a classification decision) leads to improved performance for many difficult generalization problems. However, in many domains there are serious impediments to such "turnkey" classification accuracy improvements. Most notable among these is the deleterious effect of highly correlated classifiers on the ensemble performance. One particular solution to this problem is generating "new" training sets by sampling the original one. However, with finite number of patterns, this causes a reduction in the training patterns each classifier sees, often resulting in considerably worsened generalization performance (particularly for high dimensional data domains) for each individual classifier. Generally, this drop in the accuracy of the individual classifier performance more than offsets any potential gains due to combining, unless diversity among classifiers is actively promoted. In this work, we introduce a method that: (1) reduces the correlation among the classifiers; (2) reduces the dimensionality of the data, thus lessening the impact of the 'curse of dimensionality'; and (3) improves the classification performance of the ensemble.

  16. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-05-08

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  17. Multivariate localization methods for ensemble Kalman filtering

    Science.gov (United States)

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

    2015-12-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  18. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, Marc G.

    2015-01-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  19. Microcanonical ensemble extensive thermodynamics of Tsallis statistics

    International Nuclear Information System (INIS)

    Parvan, A.S.

    2006-01-01

    The microscopic foundation of the generalized equilibrium statistical mechanics based on the Tsallis entropy is given by using the Gibbs idea of statistical ensembles of the classical and quantum mechanics. The equilibrium distribution functions are derived by the thermodynamic method based upon the use of the fundamental equation of thermodynamics and the statistical definition of the functions of the state of the system. It is shown that if the entropic index ξ=1/(q-1) in the microcanonical ensemble is an extensive variable of the state of the system, then in the thermodynamic limit z-bar =1/(q-1)N=const the principle of additivity and the zero law of thermodynamics are satisfied. In particular, the Tsallis entropy of the system is extensive and the temperature is intensive. Thus, the Tsallis statistics completely satisfies all the postulates of the equilibrium thermodynamics. Moreover, evaluation of the thermodynamic identities in the microcanonical ensemble is provided by the Euler theorem. The principle of additivity and the Euler theorem are explicitly proved by using the illustration of the classical microcanonical ideal gas in the thermodynamic limit

  20. Differential expression and localization of glycosidic residues in in vitro- and in vivo-matured cumulus-oocyte complexes in equine and porcine species.

    Science.gov (United States)

    Accogli, Gianluca; Douet, Cécile; Ambruosi, Barbara; Martino, Nicola Antonio; Uranio, Manuel Filioli; Deleuze, Stefan; Dell'Aquila, Maria Elena; Desantis, Salvatore; Goudet, Ghylène

    2014-12-01

    Glycoprotein oligosaccharides play major roles during reproduction, yet their function in gamete interactions is not fully elucidated. Identification and comparison of the glycan pattern in cumulus-oocyte complexes (COCs) from species with different efficiencies of in vitro spermatozoa penetration through the zona pellucida (ZP) could help clarify how oligosaccharides affect gamete interactions. We compared the expression and localization of 12 glycosidic residues in equine and porcine in vitro-matured (IVM) and preovulatory COCs by means of lectin histochemistry. The COCs glycan pattern differed between animals and COC source (IVM versus preovulatory). Among the 12 carbohydrate residues investigated, the IVM COCs from these two species shared: (a) sialo- and βN-acetylgalactosamine (GalNAc)-terminating glycans in the ZP; (b) sialylated and fucosylated glycans in cumulus cells; and (c) GalNAc and N-acetylglucosamine (GlcNAc) glycans in the ooplasm. Differences in the preovulatory COCs of the two species included: (a) sialoglycans and GlcNAc terminating glycans in the equine ZP versus terminal GalNAc and internal GlcNAc in the porcine ZP; (b) terminal galactosides in equine cumulus cells versus terminal GlcNAc and fucose in porcine cohorts; and (c) fucose in the mare ooplasm versus lactosamine and internal GlcNAc in porcine oocyte cytoplasm. Furthermore, equine and porcine cumulus cells and oocytes contributed differently to the synthesis of ZP glycoproteins. These results could be attributed to the different in vitro fertilization efficiencies between these two divergent, large-animal models. © 2014 Wiley Periodicals, Inc.

  1. Expression pattern of G protein‑coupled estrogen receptor 1 (GPER) in human cumulus granulosa cells (CGCs) of patients with PCOS.

    Science.gov (United States)

    Zang, Lili; Zhang, Quan; Zhou, Yi; Zhao, Yan; Lu, Linlin; Jiang, Zhou; Peng, Zhen; Zou, Shuhua

    2016-06-01

    Estradiol mediates its actions by binding to classical nuclear receptors, estrogen receptor α (ER-α) and estrogen receptor β (ER-β), and the non-classical G protein-coupled estrogen receptor 1(GPER). Several gene knockdown models have shown the importance of the receptors for growth of the oocyte and for ovulation. The aim of our study was to identify the pattern of GPER expression in human cumulus granulosa cells (CGCs) from ovarian follicles at different stages of oocyte maturation, and the differences of GPER expression between polycystic ovary syndrome (PCOS) patients and non-PCOS women. Thirty-eight cases of PCOS patients and a control group of thirty-two infertile women without PCOS were used in this study. GPER's location in CGCs was investigated by immunohistochemistry. Quantitative RT-PCR and western blot were used to identify the quantify GPER expression. Here we demonstrated that GPER was expressed in CGCs of both PCOS patients and non-PCOS women, and the expression of GPER was decreased significantly during oocyte maturation. But the expression levels of GPER in CGCs of PCOS patients and non-PCOS women were not significantly different. The data indicate that GPER may play a role during human oocyte maturation through its action in cumulus granulosa cells. AMHRIIs: anti-Mullerian hormone type II receptors; BMI: body mass index; CGCs: cumulus granulosa cells; COH: controlled ovarian hyperstimulation; E2: estradiol; EGFR: epidermal growth factor receptor; ER-α: estrogen receptor; ER-β: estrogen receptor β; FF: follicular fluid; FSH: follicle-stimulating hormone; GCs: granulosa cells; GPER: G protein-coupled estrogen receptor 1; GV: germinal vesicle; GVBD: germinal vesicle breakdown; HCG: human chorionic gonadotropin; IRS: immunoreactive score; IVF-ET: in vitro fertilization and embryo transfer; MI: metaphase I; MII: metaphase II; MAPK: mitogen-activated protein kinase; OCCCs: oocyte corona cumulus complexes; PCOS: polycystic ovarian syndrome; q

  2. Evaluating The Effect of Melatonin on HAS2, and PGR expression, as well as Cumulus Expansion, and Fertility Potential in Mice.

    Science.gov (United States)

    Ezzati, Maryam; Roshangar, Leila; Soleimani Rad, Jafar; Karimian, Nahid

    2018-04-01

    Infertility is a worldwide health problem which affects approximately 15% of sexually active couples. One of the factors influencing the fertility is melatonin. Also, protection of oocytes and embryos from oxidative stress inducing chemicals in the culture medium is important. The aim of the present study was to investigate if melatonin could regulate hyaluronan synthase-2 (HAS2) and Progesterone receptor (PGR) expressions in the cumulus cells of mice oocytes and provide an in vitro fertilization (IVF) approach. In this experimental study, for this purpose, 30 adult female mice and 15 adult male mice were used. The female mice were superovulated using 10 U of pregnant mare serum gonadotropin (PMSG) and 24 hours later, 10 U of human chorionic gonadotropin (hCG) were injected. Next, cumulus oocyte complexes (COCs) were collected from the oviducts of the female mice by using a matrix-flushing method. The cumulus cells were cultured with melatonin 10 μM for 6 hours and for real-time reverse transcription-polymerase chain reaction (RT-PCR) was used for evaluation of HAS2 and PGR expression levels. The fertilization rate was evaluated through IVF. All the data were analyzed using a t test. The results of this study showed that HAS2 and PGR expressions in the cumulus cells of the mice receiving melatonin increased in comparison to the control groups. Also, IVF results revealed an enhancement in fertilization rate in the experimental groups compared to the control groups. To improve the oocyte quality and provide new approaches for infertility treatment, administration of melatonin as an antioxidant, showed promising results. Thus, it is concluded that fertility outcomes can be improved by melatonin it enhances PGR. Copyright© by Royan Institute. All rights reserved.

  3. Assessing the Resolution Adaptability of the Zhang-McFarlane Cumulus Parameterization With Spatial and Temporal Averaging: RESOLUTION ADAPTABILITY OF ZM SCHEME

    Energy Technology Data Exchange (ETDEWEB)

    Yun, Yuxing [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China; Fan, Jiwen [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Xiao, Heng [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Zhang, Guang J. [Scripps Institution of Oceanography, University of California, San Diego CA USA; Ghan, Steven J. [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Xu, Kuan-Man [NASA Langley Research Center, Hampton VA USA; Ma, Po-Lun [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA; Gustafson, William I. [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland WA USA

    2017-11-01

    Realistic modeling of cumulus convection at fine model resolutions (a few to a few tens of km) is problematic since it requires the cumulus scheme to adapt to higher resolution than they were originally designed for (~100 km). To solve this problem, we implement the spatial averaging method proposed in Xiao et al. (2015) and also propose a temporal averaging method for the large-scale convective available potential energy (CAPE) tendency in the Zhang-McFarlane (ZM) cumulus parameterization. The resolution adaptability of the original ZM scheme, the scheme with spatial averaging, and the scheme with both spatial and temporal averaging at 4-32 km resolution is assessed using the Weather Research and Forecasting (WRF) model, by comparing with Cloud Resolving Model (CRM) results. We find that the original ZM scheme has very poor resolution adaptability, with sub-grid convective transport and precipitation increasing significantly as the resolution increases. The spatial averaging method improves the resolution adaptability of the ZM scheme and better conserves the total transport of moist static energy and total precipitation. With the temporal averaging method, the resolution adaptability of the scheme is further improved, with sub-grid convective precipitation becoming smaller than resolved precipitation for resolution higher than 8 km, which is consistent with the results from the CRM simulation. Both the spatial distribution and time series of precipitation are improved with the spatial and temporal averaging methods. The results may be helpful for developing resolution adaptability for other cumulus parameterizations that are based on quasi-equilibrium assumption.

  4. Covalent transfer of heavy chains of inter-alpha-trypsin inhibitor family proteins to hyaluronan in in vivo and in vitro expanded porcine oocyte-cumulus complexes

    Czech Academy of Sciences Publication Activity Database

    Nagyová, Eva; Camaioni, A.; Procházka, Radek; Salustri, A.

    2004-01-01

    Roč. 71, - (2004), s. 1838-1843 ISSN 0006-3363 R&D Projects: GA AV ČR IAA5045102; GA ČR GA523/04/0574; GA AV ČR KSK5052113 Institutional research plan: CEZ:AV0Z5045916 Keywords : cumulus cells * fertilization * follicle-stimulating Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.550, year: 2004

  5. Research resources: comparative microRNA profiles in human corona radiata cells and cumulus oophorus cells detected by next-generation small RNA sequencing.

    Directory of Open Access Journals (Sweden)

    Xian-Hong Tong

    Full Text Available During folliculogenesis, cumulus cells surrounding the oocyte differentiate into corona radiata cells (CRCs and cumulus oophorus cells (COCs, which are involved in gonadal steroidogenesis and the development of germ cells. Several studies suggested that microRNAs (miRNAs play an important regulatory role at the post-transcriptional level in cumulus cells. However, comparative miRNA profiles and associated processes in human CRCs and COCs have not been reported before. In this study, miRNA profiles were obtained from CRCs and COCs using next generation sequencing in women undergoing controlled ovarian stimulation for IVF. A total of 785 and 799 annotated miRNAs were identified in CRCs and COCs, while high expression levels of six novel miRNAs were detected both in CRCs and in COCs. In addition, different expression patterns in CRCs and COCs were detected in 72 annotated miRNAs. To confirm the miRNA profile in COCs and CRCs, quantitative real-time PCR was used to validate the expression of annotated miRNAs, differentially expressed miRNAs, and novel miRNAs. The miRNAs in the let-7 family were found to be involved in the regulation of a broad range of biological processes in both cumulus cell populations, which was accompanied by a large amount of miRNA editing. Bioinformatics analysis showed that amino acid and energy metabolism were targeted significantly by miRNAs that were differentially expressed between CRCs and COCs. Our work extends the current knowledge of the regulatory role of miRNAs and their targeted pathways in folliculogenesis, and provides novel candidates for molecular biomarkers in the research of female infertility.

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

    Energy Technology Data Exchange (ETDEWEB)

    Shu, Qingya; Guo, Hanqi; Che, Limei; Yuan, Xiaoru; Liu, Junfeng; Liang, Jie

    2016-04-19

    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 on 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.

  7. Exposure to α-Tocopherol, Lutein or Ascorbic Acid improve Cumulus Expansion, Viability and Maturation of Swine Oocytes

    Directory of Open Access Journals (Sweden)

    Ileana Miclea

    2010-05-01

    Full Text Available Protection of the fatty acid and lipid components of oocytes that render them susceptible to free radical or other oxidative injury may prevent the damage currently associated with culture. The goal of this study was to establish the influence of several α-tocopherol, lutein and ascorbic acid concentrations on swine oocyte maturation, viability and the function of cumulus cells in order to improve culture media. Pig oocytes were cultured for 45 hours at 37°C in 5% CO2 atmosphere; in M199 containing several α-tocopherol (5, 10, 20, 40, 80 μM, lutein (2.5, 4, 5, 8, 10 M or ascorbic acid (50, 150, 250, 500, 750 μM concentrations and cumulus expansion was assessed. Afterwards oocytes were coloured using FDA, PI and Hoechst 33258. The differences between treatments were analyzed by the analysis of variance and interpreted using the Newman-Keuls method. When cultured in α-tocopherol supplemented medium the number of expanded COCs to be scored as 3 was significantly greater (p<0.05 for the 5 and 40 μM concentrations. The addition of 8 M lutein to the maturation medium lead to a significant (p<0.05 increase in the number of COCs that were scored at 4. For both α-tocopherol and lutein additions the numbers of oocytes stained by FDA, as well as those stained by Hoechst were greater than the control without being statistically significant. When cultured in 150 and 500 μM ascorbic acid the percentages of COCs scored at 4 were significantly lower (p<0.05 than the control. Also, significantly (p<0.05 fewer oocytes were stained with FDA when matured in 500 μM. Differences between the control and the several concentrations were significant (p<0.05 for 150 and 750 μM and distinctly significant (p<0.01 for 250 μM.

  8. Interação entre células do cumulus e atividade da proteína quinase C em diferentes fases da maturação nuclear de oócitos bovinos Interaction between cumulus cells and the activity of protein kinase C at different stages of bovine oocyte nuclear maturation

    Directory of Open Access Journals (Sweden)

    A.C. Bertagnolli

    2004-08-01

    Full Text Available Verificou-se a influência da proteína quinase C (PK-C no reinício e na progressão da meiose em oócitos bovinos, determinando se as células do cumulus são mediadoras da PK-C na regulação da maturação dos oócitos. Complexos cumulus-oócitos (CCO e oócitos desnudos (OD, distribuídos aleatoriamente em seis tratamentos (T com base na presença de um ativador da PK-C (PMA (T1 e T2, de um forbol éster incapaz de ativar a PK-C (4alfa-PDD-controle (T3 e T4 ou de apenas o meio básico (TCM-199-controle (T5 e T6, foram cultivados por 7, 9, 12, 18 e 22 horas. A percentagem de rompimento da vesícula germinativa no grupo cultivado com PMA foi maior do que nos dois grupos controle, com e sem células do cumulus. O cultivo de CCO e OD por 12 e 18 horas demonstrou que a PK-C influencia a progressão para os estádios de metáfase I (MI e metáfase II (MII de maneira dependente das células do cumulus. Nos períodos de 9 e 22 horas, não foi possível observar diferença entre os grupos quanto aos diferentes estádios de maturação. A ativação da PK-C acelera o reinício da meiose independentemente das células somáticas e acelera a progressão até os estádios de MI e MII na dependência das células do cumulus.The aim of this study was to evaluate the effect of protein kinase C (PK-C on the meiotic resumption and progression in bovine oocyte, and to determine if the cumulus cells mediate the PK-C action in the regulation of bovine oocyte nuclear maturation. Cumulus-oocyte complexes (COC and denuded oocytes (DO, randomly allotted to 6 treatments (T based on the presence of an activator of PK-C (PMA (T1 and T2, or a phorbol ester unable to activate PK-C (4alphaPDD-control (T3 and T4 or a basic culture medium (T5 and T6, were cultivated for 7, 9, 12, 18 and 22 hours. The percentage of germinal vesicle breakdown (GVBD was higher when the oocytes were cultured with PMA than in the control groups with and without cumulus cells. However, PK-C was

  9. Monthly ENSO Forecast Skill and Lagged Ensemble Size

    Science.gov (United States)

    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.

  10. Shallow cumulus convection = Ondiepe cumulus convectie

    NARCIS (Netherlands)

    Neggers, R.

    2002-01-01

    Clouds play an important role in the earth's climate. Firstly, they are important in the radiative energy budget of the global atmosphere. Clouds absorb and reflect ultraviolet solar radiation, and emit infrared radiation depending on their temperature. Secondly, an

  11. Generation of scenarios from calibrated ensemble forecasts with a dual ensemble copula coupling approach

    DEFF Research Database (Denmark)

    Ben Bouallègue, Zied; Heppelmann, Tobias; Theis, Susanne E.

    2016-01-01

    the original ensemble forecasts. Based on the assumption of error stationarity, parametric methods aim to fully describe the forecast dependence structures. In this study, the concept of ECC is combined with past data statistics in order to account for the autocorrelation of the forecast error. The new...... approach, called d-ECC, is applied to wind forecasts from the high resolution ensemble system COSMO-DE-EPS run operationally at the German weather service. Scenarios generated by ECC and d-ECC are compared and assessed in the form of time series by means of multivariate verification tools and in a product...

  12. 3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields

    Science.gov (United States)

    Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.

    2007-01-01

    3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

  13. Simulation of heavy precipitation episode over eastern Peninsular Malaysia using MM5: sensitivity to cumulus parameterization schemes

    Science.gov (United States)

    Salimun, Ester; Tangang, Fredolin; Juneng, Liew

    2010-06-01

    A comparative study has been conducted to investigate the skill of four convection parameterization schemes, namely the Anthes-Kuo (AK), the Betts-Miller (BM), the Kain-Fritsch (KF), and the Grell (GR) schemes in the numerical simulation of an extreme precipitation episode over eastern Peninsular Malaysia using the Pennsylvania State University—National Center for Atmospheric Research Center (PSU-NCAR) Fifth Generation Mesoscale Model (MM5). The event is a commonly occurring westward propagating tropical depression weather system during a boreal winter resulting from an interaction between a cold surge and the quasi-stationary Borneo vortex. The model setup and other physical parameterizations are identical in all experiments and hence any difference in the simulation performance could be associated with the cumulus parameterization scheme used. From the predicted rainfall and structure of the storm, it is clear that the BM scheme has an edge over the other schemes. The rainfall intensity and spatial distribution were reasonably well simulated compared to observations. The BM scheme was also better in resolving the horizontal and vertical structures of the storm. Most of the rainfall simulated by the BM simulation was of the convective type. The failure of other schemes (AK, GR and KF) in simulating the event may be attributed to the trigger function, closure assumption, and precipitation scheme. On the other hand, the appropriateness of the BM scheme for this episode may not be generalized for other episodes or convective environments.

  14. No specific gene expression signature in human granulosa and cumulus cells for prediction of oocyte fertilisation and embryo implantation.

    Directory of Open Access Journals (Sweden)

    Tanja Burnik Papler

    Full Text Available In human IVF procedures objective and reliable biomarkers of oocyte and embryo quality are needed in order to increase the use of single embryo transfer (SET and thus prevent multiple pregnancies. During folliculogenesis there is an intense bi-directional communication between oocyte and follicular cells. For this reason gene expression profile of follicular cells could be an important indicator and biomarker of oocyte and embryo quality. The objective of this study was to identify gene expression signature(s in human granulosa (GC and cumulus (CC cells predictive of successful embryo implantation and oocyte fertilization. Forty-one patients were included in the study and individual GC and CC samples were collected; oocytes were cultivated separately, allowing a correlation with IVF outcome and elective SET was performed. Gene expression analysis was performed using microarrays, followed by a quantitative real-time PCR validation. After statistical analysis of microarray data, there were no significantly differentially expressed genes (FDR<0,05 between non-fertilized and fertilized oocytes and non-implanted and implanted embryos in either of the cell type. Furthermore, the results of quantitative real-time PCR were in consent with microarray data as there were no significant differences in gene expression of genes selected for validation. In conclusion, we did not find biomarkers for prediction of oocyte fertilization and embryo implantation in IVF procedures in the present study.

  15. Mesoscale modeling of smoke transport from equatorial Southeast Asian Maritime Continent to the Philippines: First comparison of ensemble analysis with in situ observations

    Science.gov (United States)

    Ge, Cui; Wang, Jun; Reid, Jeffrey S.; Posselt, Derek J.; Xian, Peng; Hyer, Edward

    2017-05-01

    Atmospheric transport of smoke from equatorial Southeast Asian Maritime Continent (Indonesia, Singapore, and Malaysia) to the Philippines was recently verified by the first-ever measurement of aerosol composition in the region of the Sulu Sea from a research vessel named Vasco. However, numerical modeling of such transport can have large uncertainties due to the lack of observations for parameterization schemes and for describing fire emission and meteorology in this region. These uncertainties are analyzed here, for the first time, with an ensemble of 24 Weather Research and Forecasting model with Chemistry (WRF-Chem) simulations. The ensemble reproduces the time series of observed surface nonsea-salt PM2.5 concentrations observed from the Vasco vessel during 17-30 September 2011 and overall agrees with satellite (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Moderate Resolution Imaging Spectroradiometer (MODIS)) and Aerosol Robotic Network (AERONET) data. The difference of meteorology between National Centers for Environmental Prediction (NCEP's) Final (FNL) and European Center for Medium range Weather Forecasting (ECMWF's) ERA renders the biggest spread in the ensemble (up to 20 μg m-3 or 200% in surface PM2.5), with FNL showing systematically superior results. The second biggest uncertainty is from fire emissions; the 2 day maximum Fire Locating and Modelling of Burning Emissions (FLAMBE) emission is superior than the instantaneous one. While Grell-Devenyi (G3) and Betts-Miller-Janjić cumulus schemes only produce a difference of 3 μg m-3 of surface PM2.5 over the Sulu Sea, the ensemble mean agrees best with Climate Prediction Center (CPC) MORPHing (CMORPH)'s spatial distribution of precipitation. Simulation with FNL-G3, 2 day maximum FLAMBE, and 800 m injection height outperforms other ensemble members. Finally, the global transport model (Navy Aerosol Analysis and Prediction System (NAAPS)) outperforms all WRF

  16. Ensemble-Based Data Assimilation in Reservoir Characterization: A Review

    Directory of Open Access Journals (Sweden)

    Seungpil Jung

    2018-02-01

    Full Text Available This paper presents a review of ensemble-based data assimilation for strongly nonlinear problems on the characterization of heterogeneous reservoirs with different production histories. It concentrates on ensemble Kalman filter (EnKF and ensemble smoother (ES as representative frameworks, discusses their pros and cons, and investigates recent progress to overcome their drawbacks. The typical weaknesses of ensemble-based methods are non-Gaussian parameters, improper prior ensembles and finite population size. Three categorized approaches, to mitigate these limitations, are reviewed with recent accomplishments; improvement of Kalman gains, add-on of transformation functions, and independent evaluation of observed data. The data assimilation in heterogeneous reservoirs, applying the improved ensemble methods, is discussed on predicting unknown dynamic data in reservoir characterization.

  17. Supersymmetry applied to the spectrum edge of random matrix ensembles

    International Nuclear Information System (INIS)

    Andreev, A.V.; Simons, B.D.; Taniguchi, N.

    1994-01-01

    A new matrix ensemble has recently been proposed to describe the transport properties in mesoscopic quantum wires. Both analytical and numerical studies have shown that the ensemble of Laguerre or of chiral random matrices provides a good description of scattering properties in this class of systems. Until now only conventional methods of random matrix theory have been used to study statistical properties within this ensemble. We demonstrate that the supersymmetry method, already employed in the study Dyson ensembles, can be extended to treat this class of random matrix ensembles. In developing this approach we investigate both new, as well as verify known statistical measures. Although we focus on ensembles in which T-invariance is violated our approach lays the foundation for future studies of T-invariant systems. ((orig.))

  18. Bioactive focus in conformational ensembles: a pluralistic approach

    Science.gov (United States)

    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.

  19. Grand Canonical Ensembles in General Relativity

    International Nuclear Information System (INIS)

    Klein, David; Yang, Wei-Shih

    2012-01-01

    We develop a formalism for general relativistic, grand canonical ensembles in space-times with timelike Killing fields. Using that, we derive ideal gas laws, and show how they depend on the geometry of the particular space-times. A systematic method for calculating Newtonian limits is given for a class of these space-times, which is illustrated for Kerr space-time. In addition, we prove uniqueness of the infinite volume Gibbs measure, and absence of phase transitions for a class of interaction potentials in anti-de Sitter space.

  20. A Lagrangian formalism for nonequilibrium ensembles

    International Nuclear Information System (INIS)

    Sobouti, Y.

    1989-08-01

    It is suggested to formulate a nonequilibrium ensemble theory by maximizing a time-integrated entropy constrained by Liouville's equation. This leads to distribution functions of the form f = Z -1 exp(-g/kT), where g(p,q,t) is a solution of Liouville's equation. A further requirement that the entropy should be an additivie functional of the integrals of Liouville's equation, limits the choice of g to linear superpositions of the nonlinearly independent integrals of motion. Time-dependent and time-independent integrals may participate in this superposition. (author). 14 refs

  1. Extension of the GHJW theorem for operator ensembles

    International Nuclear Information System (INIS)

    Choi, Jeong Woon; Hong, Dowon; Chang, Ku-Young; Chi, Dong Pyo; Lee, Soojoon

    2011-01-01

    The Gisin-Hughston-Jozsa-Wootters theorem plays an important role in analyzing various theories about quantum information, quantum communication, and quantum cryptography. It means that any purifications on the extended system which yield indistinguishable state ensembles on their subsystem should have a specific local unitary relation. In this Letter, we show that the local relation is also established even when the indistinguishability of state ensembles is extended to that of operator ensembles.

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

    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 of 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.

  4. Convergence of the Square Root Ensemble Kalman Filter in the Large Ensemble Limit

    Czech Academy of Sciences Publication Activity Database

    Kwiatkowski, E.; Mandel, Jan

    2015-01-01

    Roč. 3, č. 1 (2015), s. 1-17 ISSN 2166-2525 R&D Projects: GA ČR GA13-34856S Institutional support: RVO:67985807 Keywords : data assimilation * Lp laws of large numbers * Hilbert space * ensemble Kalman filter Subject RIV: IN - Informatics, Computer Science

  5. New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

    Science.gov (United States)

    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.

  6. Ensemble-based forecasting at Horns Rev: Ensemble conversion and kernel dressing

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    . The obtained ensemble forecasts of wind power are then converted into predictive distributions with an original adaptive kernel dressing method. The shape of the kernels is driven by a mean-variance model, the parameters of which are recursively estimated in order to maximize the overall skill of obtained...

  7. Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles

    Science.gov (United States)

    Treue, Stefan

    2018-01-01

    Abstract Single neurons in the primate lateral prefrontal cortex (LPFC) encode information about the allocation of visual attention and the features of visual stimuli. However, how this compares to the performance of neuronal ensembles at encoding the same information is poorly understood. Here, we recorded the responses of neuronal ensembles in the LPFC of two macaque monkeys while they performed a task that required attending to one of two moving random dot patterns positioned in different hemifields and ignoring the other pattern. We found single units selective for the location of the attended stimulus as well as for its motion direction. To determine the coding of both variables in the population of recorded units, we used a linear classifier and progressively built neuronal ensembles by iteratively adding units according to their individual performance (best single units), or by iteratively adding units based on their contribution to the ensemble performance (best ensemble). For both methods, ensembles of relatively small sizes (n decoding performance relative to individual single units. However, the decoder reached similar performance using fewer neurons with the best ensemble building method compared with the best single units method. Our results indicate that neuronal ensembles within the LPFC encode more information about the attended spatial and nonspatial features of visual stimuli than individual neurons. They further suggest that efficient coding of attention can be achieved by relatively small neuronal ensembles characterized by a certain relationship between signal and noise correlation structures. PMID:29568798

  8. Bayesian ensemble refinement by replica simulations and reweighting

    Science.gov (United States)

    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.

  9. Design ensemble machine learning model for breast cancer diagnosis.

    Science.gov (United States)

    Hsieh, Sheau-Ling; Hsieh, Sung-Huai; Cheng, Po-Hsun; Chen, Chi-Huang; Hsu, Kai-Ping; Lee, I-Shun; Wang, Zhenyu; Lai, Feipei

    2012-10-01

    In this paper, we classify the breast cancer of medical diagnostic data. Information gain has been adapted for feature selections. Neural fuzzy (NF), k-nearest neighbor (KNN), quadratic classifier (QC), each single model scheme as well as their associated, ensemble ones have been developed for classifications. In addition, a combined ensemble model with these three schemes has been constructed for further validations. The experimental results indicate that the ensemble learning performs better than individual single ones. Moreover, the combined ensemble model illustrates the highest accuracy of classifications for the breast cancer among all models.

  10. Ensemble atmospheric dispersion calculations for decision support systems

    International Nuclear Information System (INIS)

    Borysiewicz, M.; Potempski, S.; Galkowski, A.; Zelazny, R.

    2003-01-01

    This document describes two approaches to long-range atmospheric dispersion of pollutants based on the ensemble concept. In the first part of the report some experiences related to the exercises undertaken under the ENSEMBLE project of the European Union are presented. The second part is devoted to the implementation of mesoscale numerical prediction models RAMS and atmospheric dispersion model HYPACT on Beowulf cluster and theirs usage for ensemble forecasting and long range atmospheric ensemble dispersion calculations based on available meteorological data from NCEO, NOAA (USA). (author)

  11. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    Science.gov (United States)

    Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne

    2012-01-01

    Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low clean concentration and a high dirty concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

  12. Estudo estereológico comparativo de complexos cumulus-ovócito aspirados de folículos durante o ciclo estral em bovinos Comparative stereological study of cumulus-oocyte complexes aspirated from follicles during the estrous cycle in bovine

    Directory of Open Access Journals (Sweden)

    A.M. Calado

    2005-08-01

    Full Text Available Realizou-se uma análise estereológica comparativa de complexos cumulus-ovócito (COCs de bovino da raça Holtein-Friesian aspirados de folículos antrais pequenos (com diâmetro de 1-4mm e médios (com diâmetro de 4-8mm durante as fases de metaestro, diestro e de proestro. Foram estimados o volume médio dos COCs, dos ovócitos (com e sem zona pelúcida, dos núcleos dos ovócitos e das células foliculares e seus respectivos núcleos. Estimou-se a espessura da zona pelúcida e calculou-se a percentagem relativa da freqüência dos diferentes tipos de células foliculares encontradas no cumulus. Os folículos pequenos apresentaram crescimento acelerado e sem sincronia entre o volume do citoplasma e o do núcleo. No folículo médio ocorreu expansão harmoniosa núcleo-citoplasmática. Identificaram-se três populações de células foliculares (C1, C2 e C3, cuja distribuição na massa do cumulus é independente de sua posição relativamente ao ovócito. Durante o ciclo estral, as células C1 foram progressivamente substituídas por C2 e estas, por C3.A comparative stereological analysis was performed in cumulus-oocyte complexes from Holstein-Friesian cows, aspirated from small (with diameter of 1-4mm and medium (with diameter of 4-8mm antral follicles during metestrous, diestrous and proestrous. The mean volumes of COCs, oocytes (with and without zona pellucida, nucleus of the oocyte, as well as the volumes of the follicular cells and their nucleus were estimated. The mean thickness of the zona pellucida and the relative percentage of the three follicular cell types in the cumulus mass were also obtained. Small antral follicles had an accelerate growth without synchrony between the volume of the oocyte and the respective nucleus, while in medium antral follicles an harmonious nucleus-cytoplasmic expansion was observed. These follicular cell populations were classified in their types, C1, C2 and C3, which the distribution in the cumulus mass

  13. DroidEnsemble: Detecting Android Malicious Applications with Ensemble of String and Structural Static Features

    KAUST Repository

    Wang, Wei

    2018-05-11

    Android platform has dominated the Operating System of mobile devices. However, the dramatic increase of Android malicious applications (malapps) has caused serious software failures to Android system and posed a great threat to users. The effective detection of Android malapps has thus become an emerging yet crucial issue. Characterizing the behaviors of Android applications (apps) is essential to detecting malapps. Most existing work on detecting Android malapps was mainly based on string static features such as permissions and API usage extracted from apps. There also exists work on the detection of Android malapps with structural features, such as Control Flow Graph (CFG) and Data Flow Graph (DFG). As Android malapps have become increasingly polymorphic and sophisticated, using only one type of static features may result in false negatives. In this work, we propose DroidEnsemble that takes advantages of both string features and structural features to systematically and comprehensively characterize the static behaviors of Android apps and thus build a more accurate detection model for the detection of Android malapps. We extract each app’s string features, including permissions, hardware features, filter intents, restricted API calls, used permissions, code patterns, as well as structural features like function call graph. We then use three machine learning algorithms, namely, Support Vector Machine (SVM), k-Nearest Neighbor (kNN) and Random Forest (RF), to evaluate the performance of these two types of features and of their ensemble. In the experiments, We evaluate our methods and models with 1386 benign apps and 1296 malapps. Extensive experimental results demonstrate the effectiveness of DroidEnsemble. It achieves the detection accuracy as 95.8% with only string features and as 90.68% with only structural features. DroidEnsemble reaches the detection accuracy as 98.4% with the ensemble of both types of features, reducing 9 false positives and 12 false

  14. Cluster Ensemble-Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Xiaoru Wang

    2013-07-01

    Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

  15. Nanobiosensing with Arrays and Ensembles of Nanoelectrodes

    Directory of Open Access Journals (Sweden)

    Najmeh Karimian

    2016-12-01

    Full Text Available Since the first reports dating back to the mid-1990s, ensembles and arrays of nanoelectrodes (NEEs and NEAs, respectively have gained an important role as advanced electroanalytical tools thank to their unique characteristics which include, among others, dramatically improved signal/noise ratios, enhanced mass transport and suitability for extreme miniaturization. From the year 2000 onward, these properties have been exploited to develop electrochemical biosensors in which the surfaces of NEEs/NEAs have been functionalized with biorecognition layers using immobilization modes able to take the maximum advantage from the special morphology and composite nature of their surface. This paper presents an updated overview of this field. It consists of two parts. In the first, we discuss nanofabrication methods and the principles of functioning of NEEs/NEAs, focusing, in particular, on those features which are important for the development of highly sensitive and miniaturized biosensors. In the second part, we review literature references dealing the bioanalytical and biosensing applications of sensors based on biofunctionalized arrays/ensembles of nanoelectrodes, focusing our attention on the most recent advances, published in the last five years. The goal of this review is both to furnish fundamental knowledge to researchers starting their activity in this field and provide critical information on recent achievements which can stimulate new ideas for future developments to experienced scientists.

  16. Ensemble Kalman filtering with residual nudging

    KAUST Repository

    Luo, X.

    2012-10-03

    Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF) by (in effect) adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.

  17. Deterministic Mean-Field Ensemble Kalman Filtering

    KAUST Repository

    Law, Kody

    2016-05-03

    The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.

  18. Online cross-validation-based ensemble learning.

    Science.gov (United States)

    Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

    2018-01-30

    Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  19. Performance Analysis of Local Ensemble Kalman Filter

    Science.gov (United States)

    Tong, Xin T.

    2018-03-01

    Ensemble Kalman filter (EnKF) is an important data assimilation method for high-dimensional geophysical systems. Efficient implementation of EnKF in practice often involves the localization technique, which updates each component using only information within a local radius. This paper rigorously analyzes the local EnKF (LEnKF) for linear systems and shows that the filter error can be dominated by the ensemble covariance, as long as (1) the sample size exceeds the logarithmic of state dimension and a constant that depends only on the local radius; (2) the forecast covariance matrix admits a stable localized structure. In particular, this indicates that with small system and observation noises, the filter error will be accurate in long time even if the initialization is not. The analysis also reveals an intrinsic inconsistency caused by the localization technique, and a stable localized structure is necessary to control this inconsistency. While this structure is usually taken for granted for the operation of LEnKF, it can also be rigorously proved for linear systems with sparse local observations and weak local interactions. These theoretical results are also validated by numerical implementation of LEnKF on a simple stochastic turbulence in two dynamical regimes.

  20. Ensemble Kalman filtering with residual nudging

    Directory of Open Access Journals (Sweden)

    Xiaodong Luo

    2012-10-01

    Full Text Available Covariance inflation and localisation are two important techniques that are used to improve the performance of the ensemble Kalman filter (EnKF by (in effect adjusting the sample covariances of the estimates in the state space. In this work, an additional auxiliary technique, called residual nudging, is proposed to monitor and, if necessary, adjust the residual norms of state estimates in the observation space. In an EnKF with residual nudging, if the residual norm of an analysis is larger than a pre-specified value, then the analysis is replaced by a new one whose residual norm is no larger than a pre-specified value. Otherwise, the analysis is considered as a reasonable estimate and no change is made. A rule for choosing the pre-specified value is suggested. Based on this rule, the corresponding new state estimates are explicitly derived in case of linear observations. Numerical experiments in the 40-dimensional Lorenz 96 model show that introducing residual nudging to an EnKF may improve its accuracy and/or enhance its stability against filter divergence, especially in the small ensemble scenario.

  1. Deterministic Mean-Field Ensemble Kalman Filtering

    KAUST Repository

    Law, Kody; Tembine, Hamidou; Tempone, Raul

    2016-01-01

    The proof of convergence of the standard ensemble Kalman filter (EnKF) from Le Gland, Monbet, and Tran [Large sample asymptotics for the ensemble Kalman filter, in The Oxford Handbook of Nonlinear Filtering, Oxford University Press, Oxford, UK, 2011, pp. 598--631] is extended to non-Gaussian state-space models. A density-based deterministic approximation of the mean-field limit EnKF (DMFEnKF) is proposed, consisting of a PDE solver and a quadrature rule. Given a certain minimal order of convergence k between the two, this extends to the deterministic filter approximation, which is therefore asymptotically superior to standard EnKF for dimension d<2k. The fidelity of approximation of the true distribution is also established using an extension of the total variation metric to random measures. This is limited by a Gaussian bias term arising from nonlinearity/non-Gaussianity of the model, which arises in both deterministic and standard EnKF. Numerical results support and extend the theory.

  2. Activation of PKA, p38 MAPK and ERK1/2 by gonadotropins in cumulus cells is critical for induction of EGF-like factor and TACE/ADAM17 gene expression during in vitro maturation of porcine COCs

    Directory of Open Access Journals (Sweden)

    Yamashita Yasuhisa

    2009-12-01

    Full Text Available Abstract Objectives During ovulation, it has been shown that LH stimulus induces the expression of numerous genes via PKA, p38 MAPK, PI3K and ERK1/2 in cumulus cells and granulosa cells. Our recent study showed that EGF-like factor and its protease (TACE/ADAM17 are required for the activation of EGF receptor (EGFR, cumulus expansion and oocyte maturation of porcine cumulus-oocyte complexes (COCs. In the present study, we investigated which signaling pathways are involved in the gene expression of EGF-like factor and in Tace/Adam17 expression in cumulus cells of porcine COC during in vitro maturation. Methods Areg, Ereg, Tace/Adam17, Has2, Tnfaip6 and Ptgs2 mRNA expressions were detected in cumulus cells of porcine COCs by RT-PCR. Protein level of ERK1/2 phosphorylation in cultured cumulus cells was analyzed by westernblotting. COCs were visualized using a phase-contrast microscope. Results When COCs were cultured with FSH and LH up to 2.5 h, Areg, Ereg and Tace/Adam17 mRNA were expressed in cumulus cells of COCs. Areg, Ereg and Tace/Adam17 gene expressions were not suppressed by PI3K inhibitor (LY294002, whereas PKA inhibitor (H89, p38 MAPK inhibitor (SB203580 and MEK inhibitor (U0126 significantly suppressed these gene expressions. Phosphorylation of ERK1/2, and the gene expression of Has2, Tnfaip6 and Ptgs2 were also suppressed by H89, SB203580 and U0126, however, these negative effects were overcome by the addition of EGF to the medium, but not in the U0126 treatment group. Conclusion The results showed that PKA, p38 MAPK and ERK1/2 positively controlled the expression of EGF-like factor and TACE/ADMA17, the latter of which impacts the cumulus expansion and oocyte maturation of porcine COCs via the EGFR-ERK1/2 pathway in cumulus cells.

  3. In vitro maturation of cumulus-oocyte complexes for efficient isolation of oocytes from outbred deer mice.

    Directory of Open Access Journals (Sweden)

    Jung Kyu Choi

    Full Text Available The outbred (as with humans deer mice have been a useful animal model of research on human behavior and biology including that of the reproductive system. One of the major challenges in using this species is that the yield of oocyte isolation via superovulation is dismal according to the literature to date less than ∼5 oocytes per animal can be obtained so far.The goal of this study is to improve the yield of oocyte isolation from outbred deer mice close to that of most laboratory mice by in vitro maturation (IVM of cumulus-oocyte complexes (COCs.Oocytes were isolated by both superovulation and IVM. For the latter, COCs were obtained by follicular puncture of antral follicles in both the surface and inner cortical layers of ovaries. Immature oocytes in the COCs were then cultured in vitro under optimized conditions to obtain metaphase II (MII oocytes. Quality of the oocytes from IVM and superovulation was tested by in vitro fertilization (IVF and embryo development.Less than ∼5 oocytes per animal could be isolated by superovulation only. However, we successfully obtained 20.3±2.9 oocytes per animal by IVM (16.0±2.5 and superovulation (4.3±1.3 in this study. Moreover, IVF and embryo development studies suggest that IVM oocytes have even better quality than that from superovulation The latter never developed to beyond 2-cell stage as usual while 9% of the former developed to 4-cells.We have successfully established the protocol for isolating oocytes from deer mice with high yield by IVM. Moreover, this is the first ever success to develop in vitro fertilized deer mice oocytes beyond the 2-cell stage in vitro. Therefore, this study is of significance to the use of deer mice for reproductive biology research.

  4. Effects of exogenous hyaluronic acid and serum on matrix organization and stability in the mouse cumulus cell-oocyte complex.

    Science.gov (United States)

    Camaioni, A; Hascall, V C; Yanagishita, M; Salustri, A

    1993-09-25

    Compact cumulus cell-oocyte complexes (COCs) isolated from preovulatory mouse follicles undergo expansion in vitro when high levels of hyaluronic acid (HA) are synthesized and organized into an extracellular matrix. We studied the effects of fetal bovine serum (FBS) and of exogenous HA and HA-oligomers on the expansion process. Maximum retention of HA in the COC matrix, and hence complete COC expansion, occurs when 1% FBS is continuously present during the first 18 h of culture. Irrespective of the culture time, HA synthesized when serum is absent is primarily in the medium, whereas HA synthesized when serum is present is primarily in the cell matrix. These findings support the hypothesis that the serum factor, identified as an inter-alpha-trypsin inhibitor by Chen et al. (Chen, L., Mao, S. J., and Larsen, W. J. (1992) J. Biol. Chem. 267, 12380-12386), is a structural component of the matrix. Addition of exogenous HA or of HA oligomers of decasaccharide size (GlcUA-GlcNAc)5 or larger effectively displaces endogenously synthesized HA from the matrix into the medium, thereby preventing COC expansion. Addition of exogenous chondroitin sulfate affects neither matrix organization nor COC expansion, thus indicating specificity of the binding of some structural component(s) to HA. Fully expanded COCs disassemble when cultured longer than 18 h, a process which occurs also in vivo and which correlates with loss of oocyte fertilizability both in vivo and in vitro. This process involves release of macromolecular HA from the matrix into the medium, with loss of 50% of the HA in the first 8 h of incubation after full expansion. The release is not facilitated when HA oligomers, long enough to prevent matrix formation, are added to the culture medium after the COCs are fully expanded. This suggests that cooperative binding to HA of either the serum factor, an endogenously synthesized factor(s), or both is required to stabilize the fully expanded COC matrix.

  5. Crossover ensembles of random matrices and skew-orthogonal polynomials

    International Nuclear Information System (INIS)

    Kumar, Santosh; Pandey, Akhilesh

    2011-01-01

    Highlights: → We study crossover ensembles of Jacobi family of random matrices. → We consider correlations for orthogonal-unitary and symplectic-unitary crossovers. → We use the method of skew-orthogonal polynomials and quaternion determinants. → We prove universality of spectral correlations in crossover ensembles. → We discuss applications to quantum conductance and communication theory problems. - Abstract: In a recent paper (S. Kumar, A. Pandey, Phys. Rev. E, 79, 2009, p. 026211) we considered Jacobi family (including Laguerre and Gaussian cases) of random matrix ensembles and reported exact solutions of crossover problems involving time-reversal symmetry breaking. In the present paper we give details of the work. We start with Dyson's Brownian motion description of random matrix ensembles and obtain universal hierarchic relations among the unfolded correlation functions. For arbitrary dimensions we derive the joint probability density (jpd) of eigenvalues for all transitions leading to unitary ensembles as equilibrium ensembles. We focus on the orthogonal-unitary and symplectic-unitary crossovers and give generic expressions for jpd of eigenvalues, two-point kernels and n-level correlation functions. This involves generalization of the theory of skew-orthogonal polynomials to crossover ensembles. We also consider crossovers in the circular ensembles to show the generality of our method. In the large dimensionality limit, correlations in spectra with arbitrary initial density are shown to be universal when expressed in terms of a rescaled symmetry breaking parameter. Applications of our crossover results to communication theory and quantum conductance problems are also briefly discussed.

  6. A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

    KAUST Repository

    Altaf, Muhammad

    2014-08-01

    This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

  7. Conductor and Ensemble Performance Expressivity and State Festival Ratings

    Science.gov (United States)

    Price, Harry E.; Chang, E. Christina

    2005-01-01

    This study is the second in a series examining the relationship between conducting and ensemble performance. The purpose was to further examine the associations among conductor, ensemble performance expressivity, and festival ratings. Participants were asked to rate the expressivity of video-only conducting and parallel audio-only excerpts from a…

  8. An iterative ensemble Kalman filter for reservoir engineering applications

    NARCIS (Netherlands)

    Krymskaya, M.V.; Hanea, R.G.; Verlaan, M.

    2009-01-01

    The study has been focused on examining the usage and the applicability of ensemble Kalman filtering techniques to the history matching procedures. The ensemble Kalman filter (EnKF) is often applied nowadays to solving such a problem. Meanwhile, traditional EnKF requires assumption of the

  9. Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

    Science.gov (United States)

    Ye, Qiang

    2010-01-01

    Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

  10. A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

    KAUST Repository

    Altaf, Muhammad; Butler, T.; Mayo, T.; Luo, X.; Dawson, C.; Heemink, A. W.; Hoteit, Ibrahim

    2014-01-01

    This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

  11. Ensemble dispersion forecasting - Part 2. Application and evaluation

    DEFF Research Database (Denmark)

    Galmarini, S.; Bianconi, R.; Addis, R.

    2004-01-01

    of the dispersion of ETEX release 1 and the model ensemble is compared with the monitoring data. The scope of the comparison is to estimate to what extent the ensemble analysis is an improvement with respect to the single model results and represents a superior analysis of the process evolution. (C) 2004 Elsevier...

  12. Adaptive calibration of (u,v)‐wind ensemble forecasts

    DEFF Research Database (Denmark)

    Pinson, Pierre

    2012-01-01

    of sufficient reliability. The original framework introduced here allows for an adaptive bivariate calibration of these ensemble forecasts. The originality of this methodology lies in the fact that calibrated ensembles still consist of a set of (space–time) trajectories, after translation and dilation...... of translation and dilation factors are discussed. Copyright © 2012 Royal Meteorological Society...

  13. Ensemble-based Probabilistic Forecasting at Horns Rev

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    2009-01-01

    forecasting methodology. In a first stage, ensemble forecasts of meteorological variables are converted to power through a suitable power curve model. This modelemploys local polynomial regression, and is adoptively estimated with an orthogonal fitting method. The obtained ensemble forecasts of wind power...

  14. Programming in the Zone: Repertoire Selection for the Large Ensemble

    Science.gov (United States)

    Hopkins, Michael

    2013-01-01

    One of the great challenges ensemble directors face is selecting high-quality repertoire that matches the musical and technical levels of their ensembles. Thoughtful repertoire selection can lead to increased student motivation as well as greater enthusiasm for the music program from parents, administrators, teachers, and community members. Common…

  15. Probabilistic Determination of Native State Ensembles of Proteins

    DEFF Research Database (Denmark)

    Olsson, Simon; Vögeli, Beat Rolf; Cavalli, Andrea

    2014-01-01

    ensembles of proteins by the combination of physical force fields and experimental data through modern statistical methodology. As an example, we use NMR residual dipolar couplings to determine a native state ensemble of the extensively studied third immunoglobulin binding domain of protein G (GB3...

  16. Preferences of and Attitudes toward Treble Choral Ensembles

    Science.gov (United States)

    Wilson, Jill M.

    2012-01-01

    In choral ensembles, a pursuit where females far outnumber males, concern exists that females are being devalued. Attitudes of female choral singers may be negatively affected by the gender imbalance that exists in mixed choirs and by the placement of the mixed choir as the most select ensemble in a program. The purpose of this research was to…

  17. Modality-Driven Classification and Visualization of Ensemble Variance

    Energy Technology Data Exchange (ETDEWEB)

    Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

    2016-10-01

    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 information 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.

  18. Comparison of Different Vitrification Procedures on Developmental Competence of Mouse Germinal Vesicle Oocytes in the Presence or Absence of Cumulus Cells

    Directory of Open Access Journals (Sweden)

    Mojdeh Salehnia

    2009-01-01

    Full Text Available Background: An evaluation of the developmental competence of vitrified mouse germinal vesicle(GV oocytes with various equilibration and vitrification times; in the presence or absence ofcumulus cells and by comparison between the cryotop method and straws was performed.Materials and Methods: Mouse GV oocytes were considered in cumulus-denuded oocytes(CDOs and cumulus-oocyte complexes (COCs groups. Their survival and developmental rateswere studied in the following experiments: (I exposure to different equilibration times (0, 3 and5 minutes and vitrification (1, 3 and 5 minutes without plunging in LN2 as toxicity tests, (IIoocytes were vitrified using straws followed by exposure to equilibration solution for 0, 3 and 5minutes and vitrification solution for 1 and 3 minutes, and (III oocytes were vitrified by cryotopfollowing exposure to equilibration for 5 minutes and vitrification for 1 minute, respectively.Results: Maturation and developmental rates of the COCs were higher than CDOs in the nonvitrifiedgroup (p<0.05. The survival and maturation rates were low in all oocytes exposed tovitrification solution for 5 minutes (p <0.05. In vitrified CDOs and COCs using straws, the survivalrates ranged from 56.9% to 85.4% and 44.0% to 84.5%, and the maturation rates from 35.3% to56.8% and 25.8% to 56.2%, respectively; which were lower than non-vitrified samples (p <0.05.Cryotop vitrified oocytes showed higher survival, maturation and fertilization rates when comparedto straw in both CDOs and COCs (p <0.05.Conclusion: The presence of cumulus cells improves developmental competence of GV oocytesin control groups but it did not affect the vitrified group. Vitrification of mouse GV oocytes usingcryotop was more effective than straws, however both vitrification techniques did not improve thecleavage rate.

  19. An educational model for ensemble streamflow simulation and uncertainty analysis

    Directory of Open Access Journals (Sweden)

    A. AghaKouchak

    2013-02-01

    Full Text Available This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.

  20. Ensemble inequivalence: Landau theory and the ABC model

    International Nuclear Information System (INIS)

    Cohen, O; Mukamel, D

    2012-01-01

    It is well known that systems with long-range interactions may exhibit different phase diagrams when studied within two different ensembles. In many of the previously studied examples of ensemble inequivalence, the phase diagrams differ only when the transition in one of the ensembles is first order. By contrast, in a recent study of a generalized ABC model, the canonical and grand-canonical ensembles of the model were shown to differ even when they both exhibit a continuous transition. Here we show that the order of the transition where ensemble inequivalence may occur is related to the symmetry properties of the order parameter associated with the transition. This is done by analyzing the Landau expansion of a generic model with long-range interactions. The conclusions drawn from the generic analysis are demonstrated for the ABC model by explicit calculation of its Landau expansion. (paper)

  1. Nonlocal inhomogeneous broadening in plasmonic nanoparticle ensembles

    DEFF Research Database (Denmark)

    Tserkezis, Christos; Maack, Johan Rosenkrantz; Liu, Z.

    Nonclassical effects are increasingly more relevant in plasmonics as modern nanofabrication techniques rapidly approach the extreme nanoscale limits, for which departing from classical electrodynamics becomes important. One of the largest-scale necessary corrections towards this direction...... is to abandon the local response approximation (LRA) and take the nonlocal response of the metal into account, typically through the simple hydrodynamic Drude model (HDM), which predicts a sizedependent deviation of plasmon modes from the quasistatic (QS) limit. While this behaviour has been explored for simple...... metallic nanoparticles (NPs) or NP dimers, the possibility of inhomogeneous resonance broadening due to size variation in a large NP collection and the resulting spectral overlap of modes (as depicted in Fig. 1), has been so far overlooked. Here we study theoretically the effect of nonlocality on ensemble...

  2. Dynamical Engineering of Interactions in Qudit Ensembles

    Science.gov (United States)

    Choi, Soonwon; Yao, Norman Y.; Lukin, Mikhail D.

    2017-11-01

    We propose and analyze a method to engineer effective interactions in an ensemble of d -level systems (qudits) driven by global control fields. In particular, we present (i) a necessary and sufficient condition under which a given interaction can be decoupled, (ii) the existence of a universal sequence that decouples any (cancelable) interaction, and (iii) an efficient algorithm to engineer a target Hamiltonian from an initial Hamiltonian (if possible). We illustrate the potential of this method with two examples. Specifically, we present a 6-pulse sequence that decouples effective spin-1 dipolar interactions and demonstrate that a spin-1 Ising chain can be engineered to study transitions among three distinct symmetry protected topological phases. Our work enables new approaches for the realization of both many-body quantum memories and programmable analog quantum simulators using existing experimental platforms.

  3. La crise du vivre-ensemble

    DEFF Research Database (Denmark)

    Schultz, Nils Voisin

    2014-01-01

    Cet article examine les caractères idéologique et affectif de deux essais écrits respectivement par Alain Finkielkraut et Richard Millet sur la crise actuelle du vivre-ensemble en France. Les deux penseurs critiquent la société multiculturelle, mais alors que pour Finkielkraut cette société est une...... chance pour la France à condition que le dialogue interculturel soit renforcé et que l’idée d’une culture française y garde sa place, elle reste pour Millet une impossibilité. L’enjeu de l’analyse est de dévoiler la capacité des discours à générer par l’affectivité une peur capable d’intensifier l’argumentation...

  4. Dynamic principle for ensemble control tools.

    Science.gov (United States)

    Samoletov, A; Vasiev, B

    2017-11-28

    Dynamical equations describing physical systems in contact with a thermal bath are commonly extended by mathematical tools called "thermostats." These tools are designed for sampling ensembles in statistical mechanics. Here we propose a dynamic principle underlying a range of thermostats which is derived using fundamental laws of statistical physics and ensures invariance of the canonical measure. The principle covers both stochastic and deterministic thermostat schemes. Our method has a clear advantage over a range of proposed and widely used thermostat schemes that are based on formal mathematical reasoning. Following the derivation of the proposed principle, we show its generality and illustrate its applications including design of temperature control tools that differ from the Nosé-Hoover-Langevin scheme.

  5. Global Optimization Ensemble Model for Classification Methods

    Science.gov (United States)

    Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab

    2014-01-01

    Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382

  6. Global Optimization Ensemble Model for Classification Methods

    Directory of Open Access Journals (Sweden)

    Hina Anwar

    2014-01-01

    Full Text Available Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity.

  7. Uncertainty in dispersion forecasts using meteorological ensembles

    International Nuclear Information System (INIS)

    Chin, H N; Leach, M J

    1999-01-01

    The usefulness of dispersion forecasts depends on proper interpretation of results. Understanding the uncertainty in model predictions and the range of possible outcomes is critical for determining the optimal course of action in response to terrorist attacks. One of the objectives for the Modeling and Prediction initiative is creating tools for emergency planning for special events such as the upcoming the Olympics. Meteorological forecasts hours to days in advance are used to estimate the dispersion at the time of the event. However, there is uncertainty in any meteorological forecast, arising from both errors in the data (both initial conditions and boundary conditions) and from errors in the model. We use ensemble forecasts to estimate the uncertainty in the forecasts and the range of possible outcomes

  8. Data assimilation the ensemble Kalman filter

    CERN Document Server

    Evensen, Geir

    2007-01-01

    Data Assimilation comprehensively covers data assimilation and inverse methods, including both traditional state estimation and parameter estimation. This text and reference focuses on various popular data assimilation methods, such as weak and strong constraint variational methods and ensemble filters and smoothers. It is demonstrated how the different methods can be derived from a common theoretical basis, as well as how they differ and/or are related to each other, and which properties characterize them, using several examples. Rather than emphasize a particular discipline such as oceanography or meteorology, it presents the mathematical framework and derivations in a way which is common for any discipline where dynamics is merged with measurements. The mathematics level is modest, although it requires knowledge of basic spatial statistics, Bayesian statistics, and calculus of variations. Readers will also appreciate the introduction to the mathematical methods used and detailed derivations, which should b...

  9. Skill of ship-following large-eddy simulations in reproducing MAGIC observations across the northeast Pacific stratocumulus to cumulus transition region

    Science.gov (United States)

    McGibbon, J.; Bretherton, C. S.

    2017-06-01

    During the Marine ARM GPCI Investigation of Clouds (MAGIC) in October 2011 to September 2012, a container ship making periodic cruises between Los Angeles, CA, and Honolulu, HI, was instrumented with surface meteorological, aerosol and radiation instruments, a cloud radar and ceilometer, and radiosondes. Here large-eddy simulation (LES) is performed in a ship-following frame of reference for 13 four day transects from the MAGIC field campaign. The goal is to assess if LES can skillfully simulate the broad range of observed cloud characteristics and boundary layer structure across the subtropical stratocumulus to cumulus transition region sampled during different seasons and meteorological conditions. Results from Leg 15A, which sampled a particularly well-defined stratocumulus to cumulus transition, demonstrate the approach. The LES reproduces the observed timing of decoupling and transition from stratocumulus to cumulus and matches the observed evolution of boundary layer structure, cloud fraction, liquid water path, and precipitation statistics remarkably well. Considering the simulations of all 13 cruises, the LES skillfully simulates the mean diurnal variation of key measured quantities, including liquid water path (LWP), cloud fraction, measures of decoupling, and cloud radar-derived precipitation. The daily mean quantities are well represented, and daily mean LWP and cloud fraction show the expected correlation with estimated inversion strength. There is a -0.6 K low bias in LES near-surface air temperature that results in a high bias of 5.6 W m-2 in sensible heat flux (SHF). Overall, these results build confidence in the ability of LES to represent the northeast Pacific stratocumulus to trade cumulus transition region.Plain Language SummaryDuring the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign in October 2011 to September 2012, a cargo container ship making regular cruises between Los Angeles, CA, and Honolulu, HI, was fitted with tools to

  10. Multicomponent ensemble models to forecast induced seismicity

    Science.gov (United States)

    Király-Proag, E.; Gischig, V.; Zechar, J. D.; Wiemer, S.

    2018-01-01

    In recent years, human-induced seismicity has become a more and more relevant topic due to its economic and social implications. Several models and approaches have been developed to explain underlying physical processes or forecast induced seismicity. They range from simple statistical models to coupled numerical models incorporating complex physics. We advocate the need for forecast testing as currently the best method for ascertaining if models are capable to reasonably accounting for key physical governing processes—or not. Moreover, operational forecast models are of great interest to help on-site decision-making in projects entailing induced earthquakes. We previously introduced a standardized framework following the guidelines of the Collaboratory for the Study of Earthquake Predictability, the Induced Seismicity Test Bench, to test, validate, and rank induced seismicity models. In this study, we describe how to construct multicomponent ensemble models based on Bayesian weightings that deliver more accurate forecasts than individual models in the case of Basel 2006 and Soultz-sous-Forêts 2004 enhanced geothermal stimulation projects. For this, we examine five calibrated variants of two significantly different model groups: (1) Shapiro and Smoothed Seismicity based on the seismogenic index, simple modified Omori-law-type seismicity decay, and temporally weighted smoothed seismicity; (2) Hydraulics and Seismicity based on numerically modelled pore pressure evolution that triggers seismicity using the Mohr-Coulomb failure criterion. We also demonstrate how the individual and ensemble models would perform as part of an operational Adaptive Traffic Light System. Investigating seismicity forecasts based on a range of potential injection scenarios, we use forecast periods of different durations to compute the occurrence probabilities of seismic events M ≥ 3. We show that in the case of the Basel 2006 geothermal stimulation the models forecast hazardous levels

  11. Ensemble Bayesian forecasting system Part I: Theory and algorithms

    Science.gov (United States)

    Herr, Henry D.; Krzysztofowicz, Roman

    2015-05-01

    The ensemble Bayesian forecasting system (EBFS), whose theory was published in 2001, is developed for the purpose of quantifying the total uncertainty about a discrete-time, continuous-state, non-stationary stochastic process such as a time series of stages, discharges, or volumes at a river gauge. The EBFS is built of three components: an input ensemble forecaster (IEF), which simulates the uncertainty associated with random inputs; a deterministic hydrologic model (of any complexity), which simulates physical processes within a river basin; and a hydrologic uncertainty processor (HUP), which simulates the hydrologic uncertainty (an aggregate of all uncertainties except input). It works as a Monte Carlo simulator: an ensemble of time series of inputs (e.g., precipitation amounts) generated by the IEF is transformed deterministically through a hydrologic model into an ensemble of time series of outputs, which is next transformed stochastically by the HUP into an ensemble of time series of predictands (e.g., river stages). Previous research indicated that in order to attain an acceptable sampling error, the ensemble size must be on the order of hundreds (for probabilistic river stage forecasts and probabilistic flood forecasts) or even thousands (for probabilistic stage transition forecasts). The computing time needed to run the hydrologic model this many times renders the straightforward simulations operationally infeasible. This motivates the development of the ensemble Bayesian forecasting system with randomization (EBFSR), which takes full advantage of the analytic meta-Gaussian HUP and generates multiple ensemble members after each run of the hydrologic model; this auxiliary randomization reduces the required size of the meteorological input ensemble and makes it operationally feasible to generate a Bayesian ensemble forecast of large size. Such a forecast quantifies the total uncertainty, is well calibrated against the prior (climatic) distribution of

  12. Robust Ensemble Filtering and Its Relation to Covariance Inflation in the Ensemble Kalman Filter

    KAUST Repository

    Luo, Xiaodong

    2011-12-01

    A robust ensemble filtering scheme based on the H∞ filtering theory is proposed. The optimal H∞ filter is derived by minimizing the supremum (or maximum) of a predefined cost function, a criterion different from the minimum variance used in the Kalman filter. By design, the H∞ filter is more robust than the Kalman filter, in the sense that the estimation error in the H∞ filter in general has a finite growth rate with respect to the uncertainties in assimilation, except for a special case that corresponds to the Kalman filter. The original form of the H∞ filter contains global constraints in time, which may be inconvenient for sequential data assimilation problems. Therefore a variant is introduced that solves some time-local constraints instead, and hence it is called the time-local H∞ filter (TLHF). By analogy to the ensemble Kalman filter (EnKF), the concept of ensemble time-local H∞ filter (EnTLHF) is also proposed. The general form of the EnTLHF is outlined, and some of its special cases are discussed. In particular, it is shown that an EnKF with certain covariance inflation is essentially an EnTLHF. In this sense, the EnTLHF provides a general framework for conducting covariance inflation in the EnKF-based methods. Some numerical examples are used to assess the relative robustness of the TLHF–EnTLHF in comparison with the corresponding KF–EnKF method.

  13. Short-range ensemble predictions based on convection perturbations in the Eta Model for the Serra do Mar region in Brazil

    Science.gov (United States)

    Bustamante, J. F. F.; Chou, S. C.; Gomes, J. L.

    2009-04-01

    The Southeast Brazil, in the coastal and mountain region called Serra do Mar, between Sao Paulo and Rio de Janeiro, is subject to frequent events of landslides and floods. The Eta Model has been producing good quality forecasts over South America at about 40-km horizontal resolution. For that type of hazards, however, more detailed and probabilistic information on the risks should be provided with the forecasts. Thus, a short-range ensemble prediction system (SREPS) based on the Eta Model is being constructed. Ensemble members derived from perturbed initial and lateral boundary conditions did not provide enough spread for the forecasts. Members with model physics perturbation are being included and tested. The objective of this work is to construct more members for the Eta SREPS by adding physics perturbed members. The Eta Model is configured at 10-km resolution and 38 layers in the vertical. The domain covered is most of Southeast Brazil, centered over the Serra do Mar region. The constructed members comprise variations of the cumulus parameterization Betts-Miller-Janjic (BMJ) and Kain-Fritsch (KF) schemes. Three members were constructed from the BMJ scheme by varying the deficit of saturation pressure profile over land and sea, and 2 members of the KF scheme were included using the standard KF and a momentum flux added to KF scheme version. One of the runs with BMJ scheme is the control run as it was used for the initial condition perturbation SREPS. The forecasts were tested for 6 cases of South America Convergence Zone (SACZ) events. The SACZ is a common summer season feature of Southern Hemisphere that causes persistent rain for a few days over the Southeast Brazil and it frequently organizes over Serra do Mar region. These events are particularly interesting because of the persistent rains that can accumulate large amounts and cause generalized landslides and death. With respect to precipitation, the KF scheme versions have shown to be able to reach the

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

    Science.gov (United States)

    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.

  15. Decadal climate predictions improved by ocean ensemble dispersion filtering

    Science.gov (United States)

    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.Plain Language SummaryDecadal predictions aim to predict the climate several years in advance. Atmosphere-ocean interaction plays an important role for such climate forecasts. The ocean memory due to its heat capacity holds big potential skill. In recent years, more precise initialization techniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions. Ensembles are another important aspect. Applying slightly perturbed predictions to trigger the famous butterfly effect results in an ensemble. Instead of evaluating one prediction, but the whole ensemble with its

  16. A mass-flux cumulus parameterization scheme for large-scale models: description and test with observations

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Tongwen [China Meteorological Administration (CMA), National Climate Center (Beijing Climate Center), Beijing (China)

    2012-02-15

    A simple mass-flux cumulus parameterization scheme suitable for large-scale atmospheric models is presented. The scheme is based on a bulk-cloud approach and has the following properties: (1) Deep convection is launched at the level of maximum moist static energy above the top of the boundary layer. It is triggered if there is positive convective available potential energy (CAPE) and relative humidity of the air at the lifting level of convection cloud is greater than 75%; (2) Convective updrafts for mass, dry static energy, moisture, cloud liquid water and momentum are parameterized by a one-dimensional entrainment/detrainment bulk-cloud model. The lateral entrainment of the environmental air into the unstable ascending parcel before it rises to the lifting condensation level is considered. The entrainment/detrainment amount for the updraft cloud parcel is separately determined according to the increase/decrease of updraft parcel mass with altitude, and the mass change for the adiabatic ascent cloud parcel with altitude is derived from a total energy conservation equation of the whole adiabatic system in which involves the updraft cloud parcel and the environment; (3) The convective downdraft is assumed saturated and originated from the level of minimum environmental saturated equivalent potential temperature within the updraft cloud; (4) The mass flux at the base of convective cloud is determined by a closure scheme suggested by Zhang (J Geophys Res 107(D14)), in which the increase/decrease of CAPE due to changes of the thermodynamic states in the free troposphere resulting from convection approximately balances the decrease/increase resulting from large-scale processes. Evaluation of the proposed convection scheme is performed by using a single column model (SCM) forced by the Atmospheric Radiation Measurement Program's (ARM) summer 1995 and 1997 Intensive Observing Period (IOP) observations, and field observations from the Global Atmospheric Research

  17. An Efficient Ensemble Learning Method for Gene Microarray Classification

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  18. Selecting a climate model subset to optimise key ensemble properties

    Directory of Open Access Journals (Sweden)

    N. Herger

    2018-02-01

    Full Text Available End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

  19. Selecting a climate model subset to optimise key ensemble properties

    Science.gov (United States)

    Herger, Nadja; Abramowitz, Gab; Knutti, Reto; Angélil, Oliver; Lehmann, Karsten; Sanderson, Benjamin M.

    2018-02-01

    End users studying impacts and risks caused by human-induced climate change are often presented with large multi-model ensembles of climate projections whose composition and size are arbitrarily determined. An efficient and versatile method that finds a subset which maintains certain key properties from the full ensemble is needed, but very little work has been done in this area. Therefore, users typically make their own somewhat subjective subset choices and commonly use the equally weighted model mean as a best estimate. However, different climate model simulations cannot necessarily be regarded as independent estimates due to the presence of duplicated code and shared development history. Here, we present an efficient and flexible tool that makes better use of the ensemble as a whole by finding a subset with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments. This approach is illustrated with one set of optimisation criteria but we also highlight the flexibility of cost functions, depending on the focus of different users. The technique is useful for a range of applications that, for example, minimise present-day bias to obtain an accurate ensemble mean, reduce dependence in ensemble spread, maximise future spread, ensure good performance of individual models in an ensemble, reduce the ensemble size while maintaining important ensemble characteristics, or optimise several of these at the same time. As in any calibration exercise, the final ensemble is sensitive to the metric, observational product, and pre-processing steps used.

  20. Modeling task-specific neuronal ensembles improves decoding of grasp

    Science.gov (United States)

    Smith, Ryan J.; Soares, Alcimar B.; Rouse, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

    2018-06-01

    Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more

  1. Single-cell analysis of differences in transcriptomic profiles of oocytes and cumulus cells at GV, MI, MII stages from PCOS patients.

    Science.gov (United States)

    Liu, Qiwei; Li, Yumei; Feng, Yun; Liu, Chaojie; Ma, Jieliang; Li, Yifei; Xiang, Huifen; Ji, Yazhong; Cao, Yunxia; Tong, Xiaowen; Xue, Zhigang

    2016-12-22

    Polycystic ovary syndrome (PCOS) is a common frequent endocrine disorder among women of reproductive age. Although assisted reproductive techniques (ARTs) are used to address subfertility in PCOS women, their effectiveness is not clear. Our aim was to compare transcriptomic profiles of oocytes and cumulus cells (CCs) between women with and without PCOS, and assess the effectiveness of ARTs in treating PCOS patients. We collected oocytes and CCs from 16 patients with and without PCOS patients to categorize them into 6 groups according to oocyte nuclear maturation. Transcriptional gene expression of oocyte and CCs was determined via single-cell RNA sequencing. The ratio of fertilization and cleavage was higher in PCOS patients than in non-PCOS patients undergoing ARTs, and there was no difference in the number of high-quality embryos between the groups. Differentially expressed genes including PPP2R1A, PDGFRA, EGFR, GJA1, PTGS2, TNFAIP6, TGF-β1, CAV1, INHBB et al. were investigated as potential causes of PCOS oocytes and CCs disorder at early stages, but their expression returned to the normal level at the metaphase II (MII) stage via ARTs. In conclusion, ARTs can improve the quality of cumulus-oocyte complex (COC) and increase the ratio of fertilization and cleavage in PCOS women.

  2. Expression of the bone morphogenetic protein-2 (BMP2 in the human cumulus cells as a biomarker of oocytes and embryo quality

    Directory of Open Access Journals (Sweden)

    Sirin B Demiray

    2017-01-01

    Full Text Available Background: The members of the transforming growth factor-B superfamily, as the bone morphogenetic proteins (BMPs subfamily and anti-Müllerian hormone (AMH, play a role during follicular development, and the bone morphogenetic protein-2 (BMP2, AMH, and THY1 are expressed in ovaries. Aim: This study was designed to define whether or not the expressions of these proteins in human cumulus cells (CCs can be used as predictors of the oocyte and embryo competence. Settings and Design: The study included nine female patients who were diagnosed as idiopathic infertility, aged 25–33 years (median 30 years and underwent Assisted Reproductive Technologies. Materials and Methods: The CCs from 60 oocyte–cumulus complexes obtained from the nine patients were evaluated with immunofluorescence staining in respect of BMPs, AMH and THY1 markers. The CCs surrounding the same oocytes were evaluated separately according to the oocyte and embryo quality. Statistical Analysis: Quantitative data were statistically analyzed for differences using the two-sided Mann–Whitney U test (P < 0.05. Results and Conclusions: Significant differences in immunofluorescence staining were observed in oocyte quality and embryo quality for the BMP2 only (P < 0.05. No significant differences were observed for AMH or CD90/THY1. Conclusion: These results demonstrated that there is a significant difference in the expression of BMP2 in the CCs of good quality oocytes and subsequently a good embryo.

  3. Effect of glycine and alanine supplementation on development of cattle embryos cultured in CR1aa medium with or without cumulus cells

    Directory of Open Access Journals (Sweden)

    Kr. BREDBACKA

    2008-12-01

    Full Text Available The effect of alanine (1 mM and glycine (10 mM supplementation on bovine embryo development in vitro was investigated. Presumptive bovine zygotes, produced by in vitro maturation and insemination of oocytes, were cultured for 144 h in CR1aa medium in the absence (Experiments 1 and 2 or presence of cumulus cells (Experiment 3. In Experiment 1, the proportion of morulae and blastocysts of cleaved embryos in glycine-supplemented medium was not different from that of the control medium (34% in both mediaglycine-enriched medium (69.5 vs. 53.3, P = 0.016. In Experiment 2, addition of alanine did not improve the formation of morulae and blastocysts (13% vs. 21% in control medium, and the mean cell numbers in morulae and blastocysts were lower than those in the control group (34.3 vs. 68.7, P = 0.007. In the presence of cumulus cells, the combined supplementation of glycine and alanine increased the proportion of morulae and blastocysts over that in the control medium (31% vs. 14%, P = 0.003.;

  4. Ensemble Deep Learning for Biomedical Time Series Classification

    Directory of Open Access Journals (Sweden)

    Lin-peng Jin

    2016-01-01

    Full Text Available Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.

  5. Device and Method for Gathering Ensemble Data Sets

    Science.gov (United States)

    Racette, Paul E. (Inventor)

    2014-01-01

    An ensemble detector uses calibrated noise references to produce ensemble sets of data from which properties of non-stationary processes may be extracted. The ensemble detector comprising: a receiver; a switching device coupled to the receiver, the switching device configured to selectively connect each of a plurality of reference noise signals to the receiver; and a gain modulation circuit coupled to the receiver and configured to vary a gain of the receiver based on a forcing signal; whereby the switching device selectively connects each of the plurality of reference noise signals to the receiver to produce an output signal derived from the plurality of reference noise signals and the forcing signal.

  6. Parallel quantum computing in a single ensemble quantum computer

    International Nuclear Information System (INIS)

    Long Guilu; Xiao, L.

    2004-01-01

    We propose a parallel quantum computing mode for ensemble quantum computer. In this mode, some qubits are in pure states while other qubits are in mixed states. It enables a single ensemble quantum computer to perform 'single-instruction-multidata' type of parallel computation. Parallel quantum computing can provide additional speedup in Grover's algorithm and Shor's algorithm. In addition, it also makes a fuller use of qubit resources in an ensemble quantum computer. As a result, some qubits discarded in the preparation of an effective pure state in the Schulman-Varizani and the Cleve-DiVincenzo algorithms can be reutilized

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

    Science.gov (United States)

    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

  8. Scalable quantum information processing with atomic ensembles and flying photons

    International Nuclear Information System (INIS)

    Mei Feng; Yu Yafei; Feng Mang; Zhang Zhiming

    2009-01-01

    We present a scheme for scalable quantum information processing with atomic ensembles and flying photons. Using the Rydberg blockade, we encode the qubits in the collective atomic states, which could be manipulated fast and easily due to the enhanced interaction in comparison to the single-atom case. We demonstrate that our proposed gating could be applied to generation of two-dimensional cluster states for measurement-based quantum computation. Moreover, the atomic ensembles also function as quantum repeaters useful for long-distance quantum state transfer. We show the possibility of our scheme to work in bad cavity or in weak coupling regime, which could much relax the experimental requirement. The efficient coherent operations on the ensemble qubits enable our scheme to be switchable between quantum computation and quantum communication using atomic ensembles.

  9. HIGH-RESOLUTION ATMOSPHERIC ENSEMBLE MODELING AT SRNL

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R.; Werth, D.; Chiswell, S.; Etherton, B.

    2011-05-10

    The High-Resolution Mid-Atlantic Forecasting Ensemble (HME) is a federated effort to improve operational forecasts related to precipitation, convection and boundary layer evolution, and fire weather utilizing data and computing resources from a diverse group of cooperating institutions in order to create a mesoscale ensemble from independent members. Collaborating organizations involved in the project include universities, National Weather Service offices, and national laboratories, including the Savannah River National Laboratory (SRNL). The ensemble system is produced from an overlapping numerical weather prediction model domain and parameter subsets provided by each contributing member. The coordination, synthesis, and dissemination of the ensemble information are performed by the Renaissance Computing Institute (RENCI) at the University of North Carolina-Chapel Hill. This paper discusses background related to the HME effort, SRNL participation, and example results available from the RENCI website.

  10. Relation between native ensembles and experimental structures of proteins

    DEFF Research Database (Denmark)

    Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.

    2006-01-01

    Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest...... heterogeneity of the native state in solution. We find that different NMR measurements probing structure and dynamics of given proteins in solution, including order parameters, scalar couplings, and residual dipolar couplings, are remarkably well reproduced by their respective high-sequence similarity Protein...

  11. Time-dependent generalized Gibbs ensembles in open quantum systems

    Science.gov (United States)

    Lange, Florian; Lenarčič, Zala; Rosch, Achim

    2018-04-01

    Generalized Gibbs ensembles have been used as powerful tools to describe the steady state of integrable many-particle quantum systems after a sudden change of the Hamiltonian. Here, we demonstrate numerically that they can be used for a much broader class of problems. We consider integrable systems in the presence of weak perturbations which break both integrability and drive the system to a state far from equilibrium. Under these conditions, we show that the steady state and the time evolution on long timescales can be accurately described by a (truncated) generalized Gibbs ensemble with time-dependent Lagrange parameters, determined from simple rate equations. We compare the numerically exact time evolutions of density matrices for small systems with a theory based on block-diagonal density matrices (diagonal ensemble) and a time-dependent generalized Gibbs ensemble containing only a small number of approximately conserved quantities, using the one-dimensional Heisenberg model with perturbations described by Lindblad operators as an example.

  12. Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

    Science.gov (United States)

    Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

    2017-06-01

    Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

  13. Probing RNA native conformational ensembles with structural constraints

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; van den Bedem, Henry; Bernauer, Julie

    2016-01-01

    substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined...

  14. Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms

    KAUST Repository

    Aman, Beshir M.

    2012-01-01

    Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step

  15. An ensemble classifier to predict track geometry degradation

    International Nuclear Information System (INIS)

    Cárdenas-Gallo, Iván; Sarmiento, Carlos A.; Morales, Gilberto A.; Bolivar, Manuel A.; Akhavan-Tabatabaei, Raha

    2017-01-01

    Railway operations are inherently complex and source of several problems. In particular, track geometry defects are one of the leading causes of train accidents in the United States. This paper presents a solution approach which entails the construction of an ensemble classifier to forecast the degradation of track geometry. Our classifier is constructed by solving the problem from three different perspectives: deterioration, regression and classification. We considered a different model from each perspective and our results show that using an ensemble method improves the predictive performance. - Highlights: • We present an ensemble classifier to forecast the degradation of track geometry. • Our classifier considers three perspectives: deterioration, regression and classification. • We construct and test three models and our results show that using an ensemble method improves the predictive performance.

  16. Dissipation induced asymmetric steering of distant atomic ensembles

    Science.gov (United States)

    Cheng, Guangling; Tan, Huatang; Chen, Aixi

    2018-04-01

    The asymmetric steering effects of separated atomic ensembles denoted by the effective bosonic modes have been explored by the means of quantum reservoir engineering in the setting of the cascaded cavities, in each of which an atomic ensemble is involved. It is shown that the steady-state asymmetric steering of the mesoscopic objects is unconditionally achieved via the dissipation of the cavities, by which the nonlocal interaction occurs between two atomic ensembles, and the direction of steering could be easily controlled through variation of certain tunable system parameters. One advantage of the present scheme is that it could be rather robust against parameter fluctuations, and does not require the accurate control of evolution time and the original state of the system. Furthermore, the double-channel Raman transitions between the long-lived atomic ground states are used and the atomic ensembles act as the quantum network nodes, which makes our scheme insensitive to the collective spontaneous emission of atoms.

  17. Probability Maps for the Visualization of Assimilation Ensemble Flow Data

    KAUST Repository

    Hollt, Thomas; Hadwiger, Markus; Knio, Omar; Hoteit, Ibrahim

    2015-01-01

    resampling, every member can follow up on any of the members before resampling. Tracking behavior over time, such as all possible paths of a particle in an ensemble vector field, becomes very difficult, as the number of combinations rises exponentially

  18. Developing of Thai Classical Music Ensemble in Rattanakosin Period

    OpenAIRE

    Pansak Vandee

    2013-01-01

    The research titled “Developing of Thai Classical Music Ensemble in Rattanakosin Period" aimed 1) to study the history of Thai Classical Music Ensemble in Rattanakosin Period and 2) to analyze changing in each period of Rattanakosin Era. This is the historical and documentary research. The data was collected by in-depth interview those musicians, and academic music experts and field study. The focus group discussion was conducted to analyze and conclude the findings. The research found that t...

  19. Weight Distribution for Non-binary Cluster LDPC Code Ensemble

    Science.gov (United States)

    Nozaki, Takayuki; Maehara, Masaki; Kasai, Kenta; Sakaniwa, Kohichi

    In this paper, we derive the average weight distributions for the irregular non-binary cluster low-density parity-check (LDPC) code ensembles. Moreover, we give the exponential growth rate of the average weight distribution in the limit of large code length. We show that there exist $(2,d_c)$-regular non-binary cluster LDPC code ensembles whose normalized typical minimum distances are strictly positive.

  20. On the distribution of eigenvalues of certain matrix ensembles

    International Nuclear Information System (INIS)

    Bogomolny, E.; Bohigas, O.; Pato, M.P.

    1995-01-01

    Invariant random matrix ensembles with weak confinement potentials of the eigenvalues, corresponding to indeterminate moment problems, are investigated. These ensembles are characterized by the fact that the mean density of eigenvalues tends to a continuous function with increasing matrix dimension contrary to the usual cases where it grows indefinitely. It is demonstrated that the standard asymptotic formulae are not applicable in these cases and that the asymptotic distribution of eigenvalues can deviate from the classical ones. (author)

  1. A Separation between Divergence and Holevo Information for Ensembles

    OpenAIRE

    Jain, Rahul; Nayak, Ashwin; Su, Yi

    2007-01-01

    The notion of divergence information of an ensemble of probability distributions was introduced by Jain, Radhakrishnan, and Sen in the context of the ``substate theorem''. Since then, divergence has been recognized as a more natural measure of information in several situations in quantum and classical communication. We construct ensembles of probability distributions for which divergence information may be significantly smaller than the more standard Holevo information. As a result, we establ...

  2. ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

    OpenAIRE

    Mikkelsen, Torben; Galmarini, S.; Bianconi, R.; French, S.

    2003-01-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an a...

  3. Spectral statistics in semiclassical random-matrix ensembles

    International Nuclear Information System (INIS)

    Feingold, M.; Leitner, D.M.; Wilkinson, M.

    1991-01-01

    A novel random-matrix ensemble is introduced which mimics the global structure inherent in the Hamiltonian matrices of autonomous, ergodic systems. Changes in its parameters induce a transition between a Poisson and a Wigner distribution for the level spacings, P(s). The intermediate distributions are uniquely determined by a single scaling variable. Semiclassical constraints force the ensemble to be in a regime with Wigner P(s) for systems with more than two freedoms

  4. An automated approach to network features of protein structure ensembles

    Science.gov (United States)

    Bhattacharyya, Moitrayee; Bhat, Chanda R; Vishveshwara, Saraswathi

    2013-01-01

    Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html. PMID:23934896

  5. Extending prematuration with cAMP modulators enhances the cumulus contribution to oocyte antioxidant defence and oocyte quality via gap junctions.

    Science.gov (United States)

    Li, H J; Sutton-McDowall, M L; Wang, X; Sugimura, S; Thompson, J G; Gilchrist, R B

    2016-04-01

    Can bovine oocyte antioxidant defence and oocyte quality be improved by extending the duration of pre-in vitro maturation (IVM) with cyclic adenosine mono-phosphate (cAMP) modulators? Lengthening the duration of cAMP-modulated pre-IVM elevates intra-oocyte reduced glutathione (GSH) content and reduces hydrogen peroxide (H2O2) via increased cumulus cell-oocyte gap-junctional communication (GJC), associated with an improvement in subsequent embryo development and quality. Oocytes are susceptible to oxidative stress and the oocyte's most important antioxidant glutathione is supplied, at least in part, by cumulus cells. A temporary inhibition of spontaneous meiotic resumption in oocytes can be achieved by preventing a fall in cAMP, and cyclic AMP-modulated pre-IVM maintains cumulus-oocyte GJC and improves subsequent embryo development. This study consisted of a series of 10 experiments using bovine oocytes in vitro, each with multiple replicates. A range of pre-IVM durations were examined as the key study treatments which were compared with a control. The study was designed to examine if one of the oocyte's major antioxidant defences can be enhanced by pre-IVM with cAMP modulators, and to examine the contribution of cumulus-oocyte GJC on these processes. Immature bovine cumulus-oocyte complexes were treated in vitro without (control) or with the cAMP modulators; 100 µM forskolin (FSK) and 500 µM 3-isobutyl-1-methyxanthine (IBMX), for 0, 2, 4 or 6 h (pre-IVM phase) prior to IVM. Oocyte developmental competence was assessed by embryo development and quality post-IVM/IVF. Cumulus-oocyte GJC, intra-oocyte GSH and H2O2 were quantified at various time points during pre-IVM and IVM, in the presence and the absence of functional inhibitors: carbenoxolone (CBX) to block GJC and buthionine sulfoximide (BSO) to inhibit glutathione synthesis. Pre-IVM with FSK + IBMX increased subsequent blastocyst formation rate and quality compared with standard IVM (P gap junctions between

  6. SVM and SVM Ensembles in Breast Cancer Prediction.

    Science.gov (United States)

    Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

    2017-01-01

    Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

  7. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  8. Impact of ensemble learning in the assessment of skeletal maturity.

    Science.gov (United States)

    Cunha, Pedro; Moura, Daniel C; Guevara López, Miguel Angel; Guerra, Conceição; Pinto, Daniela; Ramos, Isabel

    2014-09-01

    The assessment of the bone age, or skeletal maturity, is an important task in pediatrics that measures the degree of maturation of children's bones. Nowadays, there is no standard clinical procedure for assessing bone age and the most widely used approaches are the Greulich and Pyle and the Tanner and Whitehouse methods. Computer methods have been proposed to automatize the process; however, there is a lack of exploration about how to combine the features of the different parts of the hand, and how to take advantage of ensemble techniques for this purpose. This paper presents a study where the use of ensemble techniques for improving bone age assessment is evaluated. A new computer method was developed that extracts descriptors for each joint of each finger, which are then combined using different ensemble schemes for obtaining a final bone age value. Three popular ensemble schemes are explored in this study: bagging, stacking and voting. Best results were achieved by bagging with a rule-based regression (M5P), scoring a mean absolute error of 10.16 months. Results show that ensemble techniques improve the prediction performance of most of the evaluated regression algorithms, always achieving best or comparable to best results. Therefore, the success of the ensemble methods allow us to conclude that their use may improve computer-based bone age assessment, offering a scalable option for utilizing multiple regions of interest and combining their output.

  9. Concrete ensemble Kalman filters with rigorous catastrophic filter divergence.

    Science.gov (United States)

    Kelly, David; Majda, Andrew J; Tong, Xin T

    2015-08-25

    The ensemble Kalman filter and ensemble square root filters are data assimilation methods used to combine high-dimensional, nonlinear dynamical models with observed data. Ensemble methods are indispensable tools in science and engineering and have enjoyed great success in geophysical sciences, because they allow for computationally cheap low-ensemble-state approximation for extremely high-dimensional turbulent forecast models. From a theoretical perspective, the dynamical properties of these methods are poorly understood. One of the central mysteries is the numerical phenomenon known as catastrophic filter divergence, whereby ensemble-state estimates explode to machine infinity, despite the true state remaining in a bounded region. In this article we provide a breakthrough insight into the phenomenon, by introducing a simple and natural forecast model that transparently exhibits catastrophic filter divergence under all ensemble methods and a large set of initializations. For this model, catastrophic filter divergence is not an artifact of numerical instability, but rather a true dynamical property of the filter. The divergence is not only validated numerically but also proven rigorously. The model cleanly illustrates mechanisms that give rise to catastrophic divergence and confirms intuitive accounts of the phenomena given in past literature.

  10. On the forecast skill of a convection-permitting ensemble

    Science.gov (United States)

    Schellander-Gorgas, Theresa; Wang, Yong; Meier, Florian; Weidle, Florian; Wittmann, Christoph; Kann, Alexander

    2017-01-01

    The 2.5 km convection-permitting (CP) ensemble AROME-EPS (Applications of Research to Operations at Mesoscale - Ensemble Prediction System) is evaluated by comparison with the regional 11 km ensemble ALADIN-LAEF (Aire Limitée Adaption dynamique Développement InterNational - Limited Area Ensemble Forecasting) to show whether a benefit is provided by a CP EPS. The evaluation focuses on the abilities of the ensembles to quantitatively predict precipitation during a 3-month convective summer period over areas consisting of mountains and lowlands. The statistical verification uses surface observations and 1 km × 1 km precipitation analyses, and the verification scores involve state-of-the-art statistical measures for deterministic and probabilistic forecasts as well as novel spatial verification methods. The results show that the convection-permitting ensemble with higher-resolution AROME-EPS outperforms its mesoscale counterpart ALADIN-LAEF for precipitation forecasts. The positive impact is larger for the mountainous areas than for the lowlands. In particular, the diurnal precipitation cycle is improved in AROME-EPS, which leads to a significant improvement of scores at the concerned times of day (up to approximately one-third of the scored verification measure). Moreover, there are advantages for higher precipitation thresholds at small spatial scales, which are due to the improved simulation of the spatial structure of precipitation.

  11. Ensembles of a small number of conformations with relative populations

    Energy Technology Data Exchange (ETDEWEB)

    Vammi, Vijay, E-mail: vsvammi@iastate.edu; Song, Guang, E-mail: gsong@iastate.edu [Iowa State University, Bioinformatics and Computational Biology Program, Department of Computer Science (United States)

    2015-12-15

    In our previous work, we proposed a new way to represent protein native states, using ensembles of a small number of conformations with relative Populations, or ESP in short. Using Ubiquitin as an example, we showed that using a small number of conformations could greatly reduce the potential of overfitting and assigning relative populations to protein ensembles could significantly improve their quality. To demonstrate that ESP indeed is an excellent alternative to represent protein native states, in this work we compare the quality of two ESP ensembles of Ubiquitin with several well-known regular ensembles or average structure representations. Extensive amount of significant experimental data are employed to achieve a thorough assessment. Our results demonstrate that ESP ensembles, though much smaller in size comparing to regular ensembles, perform equally or even better sometimes in all four different types of experimental data used in the assessment, namely, the residual dipolar couplings, residual chemical shift anisotropy, hydrogen exchange rates, and solution scattering profiles. This work further underlines the significance of having relative populations in describing the native states.

  12. Three-model ensemble wind prediction in southern Italy

    Science.gov (United States)

    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.

  13. Protein folding simulations by generalized-ensemble algorithms.

    Science.gov (United States)

    Yoda, Takao; Sugita, Yuji; Okamoto, Yuko

    2014-01-01

    In the protein folding problem, conventional simulations in physical statistical mechanical ensembles, such as the canonical ensemble with fixed temperature, face a great difficulty. This is because there exist a huge number of local-minimum-energy states in the system and the conventional simulations tend to get trapped in these states, giving wrong results. Generalized-ensemble algorithms are based on artificial unphysical ensembles and overcome the above difficulty by performing random walks in potential energy, volume, and other physical quantities or their corresponding conjugate parameters such as temperature, pressure, etc. The advantage of generalized-ensemble simulations lies in the fact that they not only avoid getting trapped in states of energy local minima but also allows the calculations of physical quantities as functions of temperature or other parameters from a single simulation run. In this article we review the generalized-ensemble algorithms. Four examples, multicanonical algorithm, replica-exchange method, replica-exchange multicanonical algorithm, and multicanonical replica-exchange method, are described in detail. Examples of their applications to the protein folding problem are presented.

  14. SVM and SVM Ensembles in Breast Cancer Prediction.

    Directory of Open Access Journals (Sweden)

    Min-Wei Huang

    Full Text Available Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

  15. Co-culture of human embryos with autologous cumulus cell clusters and its beneficial impact of secreted growth factors on preimplantation development as compared to standard embryo culture in assisted reproductive technologies (ART

    Directory of Open Access Journals (Sweden)

    Alexandros Vithoulkas

    2017-12-01

    Conclusion(s: The investigated factors, among other substances, may be causally connected to the beneficial effect observed on embryo development. Our findings suggest that co-culture with autologous cumulus cell clusters improves the outcome of embryo culture in IVF programs.

  16. On evaluation of ensemble precipitation forecasts with observation-based ensembles

    Directory of Open Access Journals (Sweden)

    S. Jaun

    2007-04-01

    Full Text Available Spatial interpolation of precipitation data is uncertain. How important is this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation forecasts? These questions are discussed by experimental evaluation of the COSMO consortium's limited-area ensemble prediction system COSMO-LEPS. The applied performance measure is the often used Brier skill score (BSS. The observational references in the evaluation are (a analyzed rain gauge data by ordinary Kriging and (b ensembles of interpolated rain gauge data by stochastic simulation. This permits the consideration of either a deterministic reference (the event is observed or not with 100% certainty or a probabilistic reference that makes allowance for uncertainties in spatial averaging. The evaluation experiments show that the evaluation uncertainties are substantial even for the large area (41 300 km2 of Switzerland with a mean rain gauge distance as good as 7 km: the one- to three-day precipitation forecasts have skill decreasing with forecast lead time but the one- and two-day forecast performances differ not significantly.

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

    KAUST Repository

    Rapakoulia, Trisevgeni

    2014-04-26

    Motivation: 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 ofmissing values, imbalance between the learning datasets and most of them do not support their predictions with confidence scores. Results: To overcome these limitations, a novel ensemble computational methodology is proposed. EnsembleGASVR facilitates a twostep 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. © The Author 2014.

  18. Crossover between the Gaussian orthogonal ensemble, the Gaussian unitary ensemble, and Poissonian statistics.

    Science.gov (United States)

    Schweiner, Frank; Laturner, Jeanine; Main, Jörg; Wunner, Günter

    2017-11-01

    Until now only for specific crossovers between Poissonian statistics (P), the statistics of a Gaussian orthogonal ensemble (GOE), or the statistics of a Gaussian unitary ensemble (GUE) have analytical formulas for the level spacing distribution function been derived within random matrix theory. We investigate arbitrary crossovers in the triangle between all three statistics. To this aim we propose an according formula for the level spacing distribution function depending on two parameters. Comparing the behavior of our formula for the special cases of P→GUE, P→GOE, and GOE→GUE with the results from random matrix theory, we prove that these crossovers are described reasonably. Recent investigations by F. Schweiner et al. [Phys. Rev. E 95, 062205 (2017)2470-004510.1103/PhysRevE.95.062205] have shown that the Hamiltonian of magnetoexcitons in cubic semiconductors can exhibit all three statistics in dependence on the system parameters. Evaluating the numerical results for magnetoexcitons in dependence on the excitation energy and on a parameter connected with the cubic valence band structure and comparing the results with the formula proposed allows us to distinguish between regular and chaotic behavior as well as between existent or broken antiunitary symmetries. Increasing one of the two parameters, transitions between different crossovers, e.g., from the P→GOE to the P→GUE crossover, are observed and discussed.

  19. Kinetics of particle ensembles with variable charges

    International Nuclear Information System (INIS)

    Ivlev, A. V.; Zhdanov, S.; Klumov, B.; Morfill, G.; Tsytovich, V. N.; Angelis, U. de

    2005-01-01

    One of the remarkable features distinguishing complex (dusty) plasmas from usual plasmas is that charges on the grains are not constant, but fluctuate in time around some equilibrium value which, in then, is some function of spatial coordinates. Generally, ensembles of particles with variable charges are non-Hamiltonian systems where the mutual collisions do not conserve energy. Therefore, the use of thermodynamic potentials to describe such systems is not really valid. An appropriate way to investigate their evolution is to employ the kinetic approach. We studied (both analytical and numerically) two cases: (a) inhomogeneous charge-it depends on the particle coordinate but does not change in time, and (b)fluctuating charge-it changes in time around the equilibrium value, which is constant in space. For both cases we used the Fokker-Planck approach to derive the collision integral which describes the momentum and energy transfer in mutual particle collisions as well as in the collisions with neutrals. We obtained that the mean particle energy grows in time when the neutral friction is below a certain threshold (as shown in Fig. 1). In case (a) the energy changes as ∞(t c r-t)''2, in case (b) it scales as ∞(t c r-t)''-1, exhibiting the explosion-like growth with t c r a critical time scale. The obtained solutions can be of significant importance for laboratory dusty plasmas as well as for space plasma environments, where inhomogeneous charge distributions are often present. For instance, the instability can cause dust heating in low-pressure complex plasma experiments, it can be responsible for the melting of plasma crystals, it might operate in protoplanetary disks and effect the kinetics of the planet formation, etc. (Author)

  20. Random ensemble learning for EEG classification.

    Science.gov (United States)

    Hosseini, Mohammad-Parsa; Pompili, Dario; Elisevich, Kost; Soltanian-Zadeh, Hamid

    2018-01-01

    Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rapid detection of seizure onset. A new method of feature selection and classification for rapid and precise seizure detection is discussed wherein informative components of electroencephalogram (EEG)-derived data are extracted and an automatic method is presented using infinite independent component analysis (I-ICA) to select independent features. The feature space is divided into subspaces via random selection and multichannel support vector machines (SVMs) are used to classify these subspaces. The result of each classifier is then combined by majority voting to establish the final output. In addition, a random subspace ensemble using a combination of SVM, multilayer perceptron (MLP) neural network and an extended k-nearest neighbors (k-NN), called extended nearest neighbor (ENN), is developed for the EEG and electrocorticography (ECoG) big data problem. To evaluate the solution, a benchmark ECoG of eight patients with temporal and extratemporal epilepsy was implemented in a distributed computing framework as a multitier cloud-computing architecture. Using leave-one-out cross-validation, the accuracy, sensitivity, specificity, and both false positive and false negative ratios of the proposed method were found to be 0.97, 0.98, 0.96, 0.04, and 0.02, respectively. Application of the solution to cases under investigation with ECoG has also been effected to demonstrate its utility. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Combining 2-m temperature nowcasting and short range ensemble forecasting

    Directory of Open Access Journals (Sweden)

    A. Kann

    2011-12-01

    Full Text Available During recent years, numerical ensemble prediction systems have become an important tool for estimating the uncertainties of dynamical and physical processes as represented in numerical weather models. The latest generation of limited area ensemble prediction systems (LAM-EPSs allows for probabilistic forecasts at high resolution in both space and time. However, these systems still suffer from systematic deficiencies. Especially for nowcasting (0–6 h applications the ensemble spread is smaller than the actual forecast error. This paper tries to generate probabilistic short range 2-m temperature forecasts by combining a state-of-the-art nowcasting method and a limited area ensemble system, and compares the results with statistical methods. The Integrated Nowcasting Through Comprehensive Analysis (INCA system, which has been in operation at the Central Institute for Meteorology and Geodynamics (ZAMG since 2006 (Haiden et al., 2011, provides short range deterministic forecasts at high temporal (15 min–60 min and spatial (1 km resolution. An INCA Ensemble (INCA-EPS of 2-m temperature forecasts is constructed by applying a dynamical approach, a statistical approach, and a combined dynamic-statistical method. The dynamical method takes uncertainty information (i.e. ensemble variance from the operational limited area ensemble system ALADIN-LAEF (Aire Limitée Adaptation Dynamique Développement InterNational Limited Area Ensemble Forecasting which is running operationally at ZAMG (Wang et al., 2011. The purely statistical method assumes a well-calibrated spread-skill relation and applies ensemble spread according to the skill of the INCA forecast of the most recent past. The combined dynamic-statistical approach adapts the ensemble variance gained from ALADIN-LAEF with non-homogeneous Gaussian regression (NGR which yields a statistical mbox{correction} of the first and second moment (mean bias and dispersion for Gaussian distributed continuous

  2. Developing an Ensemble Prediction System based on COSMO-DE

    Science.gov (United States)

    Theis, S.; Gebhardt, C.; Buchhold, M.; Ben Bouallègue, Z.; Ohl, R.; Paulat, M.; Peralta, C.

    2010-09-01

    The numerical weather prediction model COSMO-DE is a configuration of the COSMO model with a horizontal grid size of 2.8 km. It has been running operationally at DWD since 2007, it covers the area of Germany and produces forecasts with a lead time of 0-21 hours. The model COSMO-DE is convection-permitting, which means that it does without a parametrisation of deep convection and simulates deep convection explicitly. One aim is an improved forecast of convective heavy rain events. Convection-permitting models are in operational use at several weather services, but currently not in ensemble mode. It is expected that an ensemble system could reveal the advantages of a convection-permitting model even better. The probabilistic approach is necessary, because the explicit simulation of convective processes for more than a few hours cannot be viewed as a deterministic forecast anymore. This is due to the chaotic behaviour and short life cycle of the processes which are simulated explicitly now. In the framework of the project COSMO-DE-EPS, DWD is developing and implementing an ensemble prediction system (EPS) for the model COSMO-DE. The project COSMO-DE-EPS comprises the generation of ensemble members, as well as the verification and visualization of the ensemble forecasts and also statistical postprocessing. A pre-operational mode of the EPS with 20 ensemble members is foreseen to start in 2010. Operational use is envisaged to start in 2012, after an upgrade to 40 members and inclusion of statistical postprocessing. The presentation introduces the project COSMO-DE-EPS and describes the design of the ensemble as it is planned for the pre-operational mode. In particular, the currently implemented method for the generation of ensemble members will be explained and discussed. The method includes variations of initial conditions, lateral boundary conditions, and model physics. At present, pragmatic methods are applied which resemble the basic ideas of a multi-model approach

  3. On the proper use of Ensembles for Predictive Uncertainty assessment

    Science.gov (United States)

    Todini, Ezio; Coccia, Gabriele; Ortiz, Enrique

    2015-04-01

    Probabilistic forecasting has become popular in the last decades. Hydrological probabilistic forecasts have been based either on uncertainty processors (Krzysztofowic, 1999; Todini, 2004; Todini, 2008) or on ensembles, following meteorological traditional approaches and the establishment of the HEPEX program (http://hepex.irstea.fr. Unfortunately, the direct use of ensembles as a measure of the predictive density is an incorrect practice, because the ensemble measures the spread of the forecast instead of, following the definition of predictive uncertainty, the conditional probability of the future outcome conditional on the forecast. Only few correct approaches are reported in the literature, which correctly use the ensemble to estimate an expected conditional predictive density (Reggiani et al., 2009), similarly to what is done when several predictive models are available as in the BMA (Raftery et al., 2005) or MCP(Todini, 2008; Coccia and Todini, 2011) approaches. A major problem, limiting the correct use of ensembles, is in fact the difficulty of defining the time dependence of the ensemble members, due to the lack of a consistent ranking: in other words, when dealing with multiple models, the ith model remains the ith model regardless to the time of forecast, while this does not happen when dealing with ensemble members, since there is no definition for the ith member of an ensemble. Nonetheless, the MCP approach (Todini, 2008; Coccia and Todini, 2011), essentially based on a multiple regression in the Normal space, can be easily extended to use ensembles to represent the local (in time) smaller or larger conditional predictive uncertainty, as a function of the ensemble spread. This is done by modifying the classical linear regression equations, impliying perfectly observed predictors, to alternative regression equations similar to the Kalman filter ones, allowing for uncertain predictors. In this way, each prediction in time accounts for both the predictive

  4. Regionalization of post-processed ensemble runoff forecasts

    Directory of Open Access Journals (Sweden)

    J. O. Skøien

    2016-05-01

    Full Text Available 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.

  5. A multi-model ensemble approach to seabed mapping

    Science.gov (United States)

    Diesing, Markus; Stephens, David

    2015-06-01

    Seabed habitat mapping based on swath acoustic data and ground-truth samples is an emergent and active marine science discipline. Significant progress could be achieved by transferring techniques and approaches that have been successfully developed and employed in such fields as terrestrial land cover mapping. One such promising approach is the multiple classifier system, which aims at improving classification performance by combining the outputs of several classifiers. Here we present results of a multi-model ensemble applied to multibeam acoustic data covering more than 5000 km2 of seabed in the North Sea with the aim to derive accurate spatial predictions of seabed substrate. A suite of six machine learning classifiers (k-Nearest Neighbour, Support Vector Machine, Classification Tree, Random Forest, Neural Network and Naïve Bayes) was trained with ground-truth sample data classified into seabed substrate classes and their prediction accuracy was assessed with an independent set of samples. The three and five best performing models were combined to classifier ensembles. Both ensembles led to increased prediction accuracy as compared to the best performing single classifier. The improvements were however not statistically significant at the 5% level. Although the three-model ensemble did not perform significantly better than its individual component models, we noticed that the five-model ensemble did perform significantly better than three of the five component models. A classifier ensemble might therefore be an effective strategy to improve classification performance. Another advantage is the fact that the agreement in predicted substrate class between the individual models of the ensemble could be used as a measure of confidence. We propose a simple and spatially explicit measure of confidence that is based on model agreement and prediction accuracy.

  6. Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

    Science.gov (United States)

    Luo, Yali; Krueger, Steven K.; Xu, Kuan-Man

    2005-01-01

    This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

  7. Effects of RU486 and indomethacin on meiotic maturation, formation of extracellular matrix, and progesterone production by porcine oocyte-cumulus complexes.

    Science.gov (United States)

    Nagyova, E; Scsukova, S; Kalous, J; Mlynarcikova, A

    2014-07-01

    This study was designed to determine whether inhibition of either cyclooxygenase-2 (COX-2) by indomethacin or progesterone receptor (PR) by PR antagonist, RU486, affects oocyte maturation, progesterone production, and covalent binding between hyaluronan (HA) and heavy chains of inter-α trypsin inhibitor, as well as expression of cumulus expansion-associated proteins (HA-binding protein, tumor necrosis factor α-induced protein 6, pentraxin 3) in oocyte-cumulus complexes (OCCs). The experiments were based on freshly isolated porcine OCC cultures in which the consequences of PR and COX-2 inhibition on the final processes of oocyte maturation were determined. Granulosa cells (GCs) and OCCs were cultured in medium supplemented with FSH/LH (both 100 ng/mL) in the presence/absence of RU486 or indomethacin. Western blot analysis, (3)H-glucosamine hydrochloride assay, immunofluorescence, and radioimmunoassay were performed. Only treatment with RU486 (25 μM) caused a decrease in the number of oocytes that reached germinal vesicle breakdown and metaphase II stage compared with indomethacin (100 μM) or FSH/LH treatment alone after 44 h. All treated OCCs synthesized an almost equal amount of HA. Heavy chains (of inter-α trypsin inhibitor)-HA covalent complexes were formed during in vitro FSH/LH-stimulated expansion in RU486- or indomethacin-treated OCCs. Follicle-stimulating hormone/LH-induced progesterone production by OCCs was increased in the presence of RU486 after 44 h. In contrast, a decrease of FSH/LH-stimulated progesterone production by GCs was detected in the presence of either RU486 or indomethacin after 72 h. We suggest that the PR-dependent pathway may be involved in the regulation of oocyte maturation. Both PR and COX-2 regulate FSH/LH-stimulated progesterone production by OCCs and GCs. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Implementation of single qubit in QD ensembles

    International Nuclear Information System (INIS)

    Alegre, T.P. Mayer

    2004-01-01

    Full text: During the last decades the semiconductor industry has achieved the production of exponentially shrinking components. This fact points to fundamental limits of integration, making computation with single atoms or particles like an electron an ultimate goal. To get to this limit, quantum systems in solid state have to be manipulated in a controllable fashion. The assessment of quantum degrees of freedom for information processing may allow exponentially faster performance for certain classes of problems. The essential aspect to be explored in quantum information processing resides in the superposition of states that allows resources such as entangled states to be envisaged. The quest for the optimal system to host a quantum variable that is sufficiently isolated from the environment encompasses implementations spanning optical, atomic, molecular and solid state systems. In the solid state, a variety of proposals have come forth, each one having its own advantages and disadvantages. The main conclusion from these e efforts is that there is no decisive technology upon which quantum information devices will be built. Self-assembled quantum dots (SAQDs or QDs), can be grown with size uniformity that enables the observation of single electron loading events. They can in turn be used to controllably trap single electrons into discrete levels, atom-like, with their corresponding shells. Hund's rules and Pauli exclusion principle are observed in these nanostructures and are key in allowing and preserving a particular quantum state. Provided that one can trap one electron in a QD ensemble, the corresponding spin can be manipulated by an external magnetic field by either conventional Electron Spin Resonance (ESR) techniques or g-tensor modulation resonance (g-TMR). By analogy with Nuclear Magnetic Resonance, single qubit operations are proposed, which at some point in time should be scaled, provided that spin-spin interactions can be controlled. Read out can be

  9. Operational hydrological forecasting in Bavaria. Part II: Ensemble forecasting

    Science.gov (United States)

    Ehret, U.; Vogelbacher, A.; Moritz, K.; Laurent, S.; Meyer, I.; Haag, I.

    2009-04-01

    In part I of this study, the operational flood forecasting system in Bavaria and an approach to identify and quantify forecast uncertainty was introduced. The approach is split into the calculation of an empirical 'overall error' from archived forecasts and the calculation of an empirical 'model error' based on hydrometeorological forecast tests, where rainfall observations were used instead of forecasts. The 'model error' can especially in upstream catchments where forecast uncertainty is strongly dependent on the current predictability of the atrmosphere be superimposed on the spread of a hydrometeorological ensemble forecast. In Bavaria, two meteorological ensemble prediction systems are currently tested for operational use: the 16-member COSMO-LEPS forecast and a poor man's ensemble composed of DWD GME, DWD Cosmo-EU, NCEP GFS, Aladin-Austria, MeteoSwiss Cosmo-7. The determination of the overall forecast uncertainty is dependent on the catchment characteristics: 1. Upstream catchment with high influence of weather forecast a) A hydrological ensemble forecast is calculated using each of the meteorological forecast members as forcing. b) Corresponding to the characteristics of the meteorological ensemble forecast, each resulting forecast hydrograph can be regarded as equally likely. c) The 'model error' distribution, with parameters dependent on hydrological case and lead time, is added to each forecast timestep of each ensemble member d) For each forecast timestep, the overall (i.e. over all 'model error' distribution of each ensemble member) error distribution is calculated e) From this distribution, the uncertainty range on a desired level (here: the 10% and 90% percentile) is extracted and drawn as forecast envelope. f) As the mean or median of an ensemble forecast does not necessarily exhibit meteorologically sound temporal evolution, a single hydrological forecast termed 'lead forecast' is chosen and shown in addition to the uncertainty bounds. This can be

  10. Ensemble Kalman filtering with one-step-ahead smoothing

    KAUST Repository

    Raboudi, Naila F.

    2018-01-11

    The ensemble Kalman filter (EnKF) is widely used for sequential data assimilation. It operates as a succession of forecast and analysis steps. In realistic large-scale applications, EnKFs are implemented with small ensembles and poorly known model error statistics. This limits their representativeness of the background error covariances and, thus, their performance. This work explores the efficiency of the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem to enhance the data assimilation performance of EnKFs. Filtering with OSA smoothing introduces an updated step with future observations, conditioning the ensemble sampling with more information. This should provide an improved background ensemble in the analysis step, which may help to mitigate the suboptimal character of EnKF-based methods. Here, the authors demonstrate the efficiency of a stochastic EnKF with OSA smoothing for state estimation. They then introduce a deterministic-like EnKF-OSA based on the singular evolutive interpolated ensemble Kalman (SEIK) filter. The authors show that the proposed SEIK-OSA outperforms both SEIK, as it efficiently exploits the data twice, and the stochastic EnKF-OSA, as it avoids observational error undersampling. They present extensive assimilation results from numerical experiments conducted with the Lorenz-96 model to demonstrate SEIK-OSA’s capabilities.

  11. Universal critical wrapping probabilities in the canonical ensemble

    Directory of Open Access Journals (Sweden)

    Hao Hu

    2015-09-01

    Full Text Available Universal dimensionless quantities, such as Binder ratios and wrapping probabilities, play an important role in the study of critical phenomena. We study the finite-size scaling behavior of the wrapping probability for the Potts model in the random-cluster representation, under the constraint that the total number of occupied bonds is fixed, so that the canonical ensemble applies. We derive that, in the limit L→∞, the critical values of the wrapping probability are different from those of the unconstrained model, i.e. the model in the grand-canonical ensemble, but still universal, for systems with 2yt−d>0 where yt=1/ν is the thermal renormalization exponent and d is the spatial dimension. Similar modifications apply to other dimensionless quantities, such as Binder ratios. For systems with 2yt−d≤0, these quantities share same critical universal values in the two ensembles. It is also derived that new finite-size corrections are induced. These findings apply more generally to systems in the canonical ensemble, e.g. the dilute Potts model with a fixed total number of vacancies. Finally, we formulate an efficient cluster-type algorithm for the canonical ensemble, and confirm these predictions by extensive simulations.

  12. Curve Boxplot: Generalization of Boxplot for Ensembles of Curves.

    Science.gov (United States)

    Mirzargar, Mahsa; Whitaker, Ross T; Kirby, Robert M

    2014-12-01

    In simulation science, computational scientists often study the behavior of their simulations by repeated solutions with variations in parameters and/or boundary values or initial conditions. Through such simulation ensembles, one can try to understand or quantify the variability or uncertainty in a solution as a function of the various inputs or model assumptions. In response to a growing interest in simulation ensembles, the visualization community has developed a suite of methods for allowing users to observe and understand the properties of these ensembles in an efficient and effective manner. An important aspect of visualizing simulations is the analysis of derived features, often represented as points, surfaces, or curves. In this paper, we present a novel, nonparametric method for summarizing ensembles of 2D and 3D curves. We propose an extension of a method from descriptive statistics, data depth, to curves. We also demonstrate a set of rendering and visualization strategies for showing rank statistics of an ensemble of curves, which is a generalization of traditional whisker plots or boxplots to multidimensional curves. Results are presented for applications in neuroimaging, hurricane forecasting and fluid dynamics.

  13. Skill forecasting from different wind power ensemble prediction methods

    International Nuclear Information System (INIS)

    Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

    2007-01-01

    This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

  14. Fluctuation, stationarity, and ergodic properties of random-matrix ensembles

    International Nuclear Information System (INIS)

    Pandey, A.

    1979-01-01

    The properties of random-matrix ensembles and the application of such ensembles to energy-level fluctuations and strength fluctuations are discussed. The two-point correlation function for complex spectra described by the three standard Gaussian ensembles is calculated, and its essential simplicity, displayed by an elementary procedure that derives from the dominance of binary correlations. The resultant function is exact for the unitary case and a very good approximation to the orthogonal and symplectic cases. The same procedure yields the spectrum for a Gaussian orthogonal ensemble (GOE) deformed by a pairing interaction. Several extensions are given and relationships to other problems of current interest are discussed. The standard fluctuation measures are rederived for the GOE, and their extensions to the unitary and symplectic cases are given. The measures are shown to derive, for the most part, from the two-point function, and new relationships between them are established, answering some long-standing questions. Some comparisons with experimental values are also made. All the cluster functions, and therefore the fluctuation measures, are shown to be stationary and strongly ergodic, thus justifying the use of random matrices for individual spectra. Strength fluctuations in the orthogonal ensemble are also considered. The Porter-Thomas distribution in its various forms is rederived and its ergodicity is established

  15. Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

    Science.gov (United States)

    Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

    2018-01-01

    In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

  16. The Ensembl Web site: mechanics of a genome browser.

    Science.gov (United States)

    Stalker, James; Gibbins, Brian; Meidl, Patrick; Smith, James; Spooner, William; Hotz, Hans-Rudolf; Cox, Antony V

    2004-05-01

    The Ensembl Web site (http://www.ensembl.org/) is the principal user interface to the data of the Ensembl project, and currently serves >500,000 pages (approximately 2.5 million hits) per week, providing access to >80 GB (gigabyte) of data to users in more than 80 countries. Built atop an open-source platform comprising Apache/mod_perl and the MySQL relational database management system, it is modular, extensible, and freely available. It is being actively reused and extended in several different projects, and has been downloaded and installed in companies and academic institutions worldwide. Here, we describe some of the technical features of the site, with particular reference to its dynamic configuration that enables it to handle disparate data from multiple species.

  17. Deviations from Wick's theorem in the canonical ensemble

    Science.gov (United States)

    Schönhammer, K.

    2017-07-01

    Wick's theorem for the expectation values of products of field operators for a system of noninteracting fermions or bosons plays an important role in the perturbative approach to the quantum many-body problem. A finite-temperature version holds in the framework of the grand canonical ensemble, but not for the canonical ensemble appropriate for systems with fixed particle number such as ultracold quantum gases in optical lattices. Here we present formulas for expectation values of products of field operators in the canonical ensemble using a method in the spirit of Gaudin's proof of Wick's theorem for the grand canonical case. The deviations from Wick's theorem are examined quantitatively for two simple models of noninteracting fermions.

  18. Statistical ensembles and molecular dynamics studies of anisotropic solids. II

    International Nuclear Information System (INIS)

    Ray, J.R.; Rahman, A.

    1985-01-01

    We have recently discussed how the Parrinello--Rahman theory can be brought into accord with the theory of the elastic and thermodynamic behavior of anisotropic media. This involves the isoenthalpic--isotension ensemble of statistical mechanics. Nose has developed a canonical ensemble form of molecular dynamics. We combine Nose's ideas with the Parrinello--Rahman theory to obtain a canonical form of molecular dynamics appropriate to the study of anisotropic media subjected to arbitrary external stress. We employ this isothermal--isotension ensemble in a study of a fcc→ close-packed structural phase transformation in a Lennard-Jones solid subjected to uniaxial compression. Our interpretation of the Nose theory does not involve a scaling of the time variable. This latter fact leads to simplifications when studying the time dependence of quantities

  19. Evaluation of LDA Ensembles Classifiers for Brain Computer Interface

    International Nuclear Information System (INIS)

    Arjona, Cristian; Pentácolo, José; Gareis, Iván; Atum, Yanina; Gentiletti, Gerardo; Acevedo, Rubén; Rufiner, Leonardo

    2011-01-01

    The Brain Computer Interface (BCI) translates brain activity into computer commands. To increase the performance of the BCI, to decode the user intentions it is necessary to get better the feature extraction and classification techniques. In this article the performance of a three linear discriminant analysis (LDA) classifiers ensemble is studied. The system based on ensemble can theoretically achieved better classification results than the individual counterpart, regarding individual classifier generation algorithm and the procedures for combine their outputs. Classic algorithms based on ensembles such as bagging and boosting are discussed here. For the application on BCI, it was concluded that the generated results using ER and AUC as performance index do not give enough information to establish which configuration is better.

  20. Adiabatic passage and ensemble control of quantum systems

    International Nuclear Information System (INIS)

    Leghtas, Z; Sarlette, A; Rouchon, P

    2011-01-01

    This paper considers population transfer between eigenstates of a finite quantum ladder controlled by a classical electric field. Using an appropriate change of variables, we show that this setting can be set in the framework of adiabatic passage, which is known to facilitate ensemble control of quantum systems. Building on this insight, we present a mathematical proof of robustness for a control protocol-chirped pulse-practised by experimentalists to drive an ensemble of quantum systems from the ground state to the most excited state. We then propose new adiabatic control protocols using a single chirped and amplitude-shaped pulse, to robustly perform any permutation of eigenstate populations, on an ensemble of systems with unknown coupling strengths. These adiabatic control protocols are illustrated by simulations on a four-level ladder.

  1. Generation of Exotic Quantum States of a Cold Atomic Ensemble

    DEFF Research Database (Denmark)

    Christensen, Stefan Lund

    Over the last decades quantum effects have become more and more controllable, leading to the implementations of various quantum information protocols. These protocols are all based on utilizing quantum correlation. In this thesis we consider how states of an atomic ensemble with such correlations...... can be created and characterized. First we consider a spin-squeezed state. This state is generated by performing quantum non-demolition measurements of the atomic population difference. We show a spectroscopically relevant noise reduction of -1.7dB, the ensemble is in a many-body entangled state...... — a nanofiber based light-atom interface. Using a dual-frequency probing method we measure and prepare an ensemble with a sub-Poissonian atom number distribution. This is a first step towards the implementation of more exotic quantum states....

  2. Optical properties of indium phosphide nanowire ensembles at various temperatures

    Energy Technology Data Exchange (ETDEWEB)

    Lohn, Andrew J; Onishi, Takehiro; Kobayashi, Nobuhiko P [Baskin School of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 (United States); Nanostructured Energy Conversion Technology and Research (NECTAR), Advanced Studies Laboratories, University of California Santa Cruz-NASA Ames Research Center, Moffett Field, CA 94035 (United States)

    2010-09-03

    Ensembles that contain two types (zincblende and wurtzite) of indium phosphide nanowires grown on non-single crystalline surfaces were studied by micro-photoluminescence and micro-Raman spectroscopy at various low temperatures. The obtained spectra are discussed with the emphasis on the effects of differing lattice types, geometries, and crystallographic orientations present within an ensemble of nanowires grown on non-single crystalline surfaces. In the photoluminescence spectra, a typical Varshni dependence of band gap energy on temperature was observed for emissions from zincblende nanowires and in the high temperature regime energy transfer from excitonic transitions and band-edge transitions was identified. In contrast, the photoluminescence emissions associated with wurtzite nanowires were rather insensitive to temperature. Raman spectra were collected simultaneously from zincblende and wurtzite nanowires coexisting in an ensemble. Raman peaks of the wurtzite nanowires are interpreted as those related to the zincblende nanowires by a folding of the phonon dispersion.

  3. Optical properties of indium phosphide nanowire ensembles at various temperatures

    International Nuclear Information System (INIS)

    Lohn, Andrew J; Onishi, Takehiro; Kobayashi, Nobuhiko P

    2010-01-01

    Ensembles that contain two types (zincblende and wurtzite) of indium phosphide nanowires grown on non-single crystalline surfaces were studied by micro-photoluminescence and micro-Raman spectroscopy at various low temperatures. The obtained spectra are discussed with the emphasis on the effects of differing lattice types, geometries, and crystallographic orientations present within an ensemble of nanowires grown on non-single crystalline surfaces. In the photoluminescence spectra, a typical Varshni dependence of band gap energy on temperature was observed for emissions from zincblende nanowires and in the high temperature regime energy transfer from excitonic transitions and band-edge transitions was identified. In contrast, the photoluminescence emissions associated with wurtzite nanowires were rather insensitive to temperature. Raman spectra were collected simultaneously from zincblende and wurtzite nanowires coexisting in an ensemble. Raman peaks of the wurtzite nanowires are interpreted as those related to the zincblende nanowires by a folding of the phonon dispersion.

  4. Spatio-temporal behaviour of medium-range ensemble forecasts

    Science.gov (United States)

    Kipling, Zak; Primo, Cristina; Charlton-Perez, Andrew

    2010-05-01

    Using the recently-developed mean-variance of logarithms (MVL) diagram, together with the TIGGE archive of medium-range ensemble forecasts from nine different centres, we present an analysis of the spatio-temporal dynamics of their perturbations, and show how the differences between models and perturbation techniques can explain the shape of their characteristic MVL curves. We also consider the use of the MVL diagram to compare the growth of perturbations within the ensemble with the growth of the forecast error, showing that there is a much closer correspondence for some models than others. We conclude by looking at how the MVL technique might assist in selecting models for inclusion in a multi-model ensemble, and suggest an experiment to test its potential in this context.

  5. Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

    KAUST Repository

    Liu, Bo

    2015-11-11

    We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

  6. A Brief Tutorial on the Ensemble Kalman Filter

    OpenAIRE

    Mandel, Jan

    2009-01-01

    The ensemble Kalman filter (EnKF) is a recursive filter suitable for problems with a large number of variables, such as discretizations of partial differential equations in geophysical models. The EnKF originated as a version of the Kalman filter for large problems (essentially, the covariance matrix is replaced by the sample covariance), and it is now an important data assimilation component of ensemble forecasting. EnKF is related to the particle filter (in this context, a particle is the s...

  7. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

  8. Breaking of ensembles of linear and nonlinear oscillators

    International Nuclear Information System (INIS)

    Buts, V.A.

    2016-01-01

    Some results concerning the study of the dynamics of ensembles of linear and nonlinear oscillators are stated. It is shown that, in general, a stable ensemble of linear oscillator has a limited number of oscillators. This number has been defined for some simple models. It is shown that the features of the dynamics of linear oscillators can be used for conversion of the low-frequency energy oscillations into high frequency oscillations. The dynamics of coupled nonlinear oscillators in most cases is chaotic. For such a case, it is shown that the statistical characteristics (moments) of chaotic motion can significantly reduce potential barriers that keep the particles in the capture region

  9. Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms

    KAUST Repository

    Aman, Beshir M.

    2012-12-01

    This work aims to enhance the Ensemble Kalman Filter performance by transforming the non-Gaussian state variables into Gaussian variables to be a step closer to optimality. This is done by using univariate and multivariate Box-Cox transformation. Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step and then transform back after applying the Kalman correction. In general, the results of the multivariate method was promising, despite the fact it over-estimated some variables.

  10. A short-range ensemble prediction system for southern Africa

    CSIR Research Space (South Africa)

    Park, R

    2012-10-01

    Full Text Available system for southern Africa R PARK, WA LANDMAN AND F ENGELBRECHT CSIR, PO Box 395, Pretoria, South Africa, 0001 Email: xxxxxxxxxxxxxx@csir.co.za ? www.csir.co.za INTRODUCTION This research has been conducted in order to develop a short-range ensemble... stream_source_info Park_2012.pdf.txt stream_content_type text/plain stream_size 7211 Content-Encoding ISO-8859-1 stream_name Park_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 A short-range ensemble prediction...

  11. Good and Bad Neighborhood Approximations for Outlier Detection Ensembles

    DEFF Research Database (Denmark)

    Kirner, Evelyn; Schubert, Erich; Zimek, Arthur

    2017-01-01

    Outlier detection methods have used approximate neighborhoods in filter-refinement approaches. Outlier detection ensembles have used artificially obfuscated neighborhoods to achieve diverse ensemble members. Here we argue that outlier detection models could be based on approximate neighborhoods...... in the first place, thus gaining in both efficiency and effectiveness. It depends, however, on the type of approximation, as only some seem beneficial for the task of outlier detection, while no (large) benefit can be seen for others. In particular, we argue that space-filling curves are beneficial...

  12. Ensemble system for Part-of-Speech tagging

    OpenAIRE

    Dell'Orletta, Felice

    2009-01-01

    The paper contains a description of the Felice-POS-Tagger and of its performance in Evalita 2009. Felice-POS-Tagger is an ensemble system that combines six different POS taggers. When evaluated on the official test set, the ensemble system outperforms each of the single tagger components and achieves the highest accuracy score in Evalita 2009 POS Closed Task. It is shown rst that the errors made from the dierent taggers are complementary, and then how to use this complementary behavior to the...

  13. The canonical ensemble redefined - 3. Ideal Bose gas

    International Nuclear Information System (INIS)

    Venkataraman, R.

    1984-12-01

    The ideal Bose gas solved in the redefined ensemble formalism exhibits a discontinuity in the specific heat suggesting that Bose-Einstein condensation is a second order phase transition. The deviations from the classical ideal gas behaviour are larger than those predicted by Gibbs ensemble. Below Tsub(c) the pressure is not independent of the volume. For a certain range of values of VT 3 , the peak in black body radiation shows a shift in the frequency scale and this could be detected, at least in principle, experimentally. (author)

  14. Kohn-Sham Theory for Ground-State Ensembles

    International Nuclear Information System (INIS)

    Ullrich, C. A.; Kohn, W.

    2001-01-01

    An electron density distribution n(r) which can be represented by that of a single-determinant ground state of noninteracting electrons in an external potential v(r) is called pure-state v -representable (P-VR). Most physical electronic systems are P-VR. Systems which require a weighted sum of several such determinants to represent their density are called ensemble v -representable (E-VR). This paper develops formal Kohn-Sham equations for E-VR physical systems, using the appropriate coupling constant integration. It also derives local density- and generalized gradient approximations, and conditions and corrections specific to ensembles

  15. Learning to Run with Actor-Critic Ensemble

    OpenAIRE

    Huang, Zhewei; Zhou, Shuchang; Zhuang, BoEr; Zhou, Xinyu

    2017-01-01

    We introduce an Actor-Critic Ensemble(ACE) method for improving the performance of Deep Deterministic Policy Gradient(DDPG) algorithm. At inference time, our method uses a critic ensemble to select the best action from proposals of multiple actors running in parallel. By having a larger candidate set, our method can avoid actions that have fatal consequences, while staying deterministic. Using ACE, we have won the 2nd place in NIPS'17 Learning to Run competition, under the name of "Megvii-hzw...

  16. Temperature profiles from MBT casts from the CIRRUS and CUMULUS from Ocean Weather Station K (OWS-K) and M (OWS-M) in the North Atlantic Ocean from 1969-01-01 to 1970-01-16 (NODC Accession 7000939)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathythermograph data were collected from the CIRRUS and CUMULUS within a 1-mile radius of Ocean Weather Station K (4500N 01600W), M (6600N 00200E), and in transit....

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

    Science.gov (United States)

    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

  18. Momentum distribution functions in ensembles: the inequivalence of microcannonical and canonical ensembles in a finite ultracold system.

    Science.gov (United States)

    Wang, Pei; Xianlong, Gao; Li, Haibin

    2013-08-01

    It is demonstrated in many thermodynamic textbooks that the equivalence of the different ensembles is achieved in the thermodynamic limit. In this present work we discuss the inequivalence of microcanonical and canonical ensembles in a finite ultracold system at low energies. We calculate the microcanonical momentum distribution function (MDF) in a system of identical fermions (bosons). We find that the microcanonical MDF deviates from the canonical one, which is the Fermi-Dirac (Bose-Einstein) function, in a finite system at low energies where the single-particle density of states and its inverse are finite.

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

    Science.gov (United States)

    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

  20. Development of multimodel ensemble based district level medium ...

    Indian Academy of Sciences (India)

    tively by computing the anomaly correlation coef- ficient between the predicted rainfall and observed rainfall. High resolution (lat./long.) gridded data ..... particularly in the prediction of intensity and mesoscale rainfall features causing inland flooding. During recent years, Ensemble. Prediction System (EPS) has emerged as ...

  1. ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Mikkelsen, T; Galmarini, S; Bianconi, R; French, S [eds.

    2003-11-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

  2. Korean Percussion Ensemble ("Samulnori") in the General Music Classroom

    Science.gov (United States)

    Kang, Sangmi; Yoo, Hyesoo

    2016-01-01

    This article introduces "samulnori" (Korean percussion ensemble), its cultural background, and instructional methods as parts of a classroom approach to teaching upper-level general music. We introduce five of eight sections from "youngnam nong-ak" (a style of samulnori) as a repertoire for teaching Korean percussion music to…

  3. Inhomogeneous ensembles of radical pairs in chemical compasses

    Science.gov (United States)

    Procopio, Maria; Ritz, Thorsten

    2016-11-01

    The biophysical basis for the ability of animals to detect the geomagnetic field and to use it for finding directions remains a mystery of sensory biology. One much debated hypothesis suggests that an ensemble of specialized light-induced radical pair reactions can provide the primary signal for a magnetic compass sensor. The question arises what features of such a radical pair ensemble could be optimized by evolution so as to improve the detection of the direction of weak magnetic fields. Here, we focus on the overlooked aspect of the noise arising from inhomogeneity of copies of biomolecules in a realistic biological environment. Such inhomogeneity leads to variations of the radical pair parameters, thereby deteriorating the signal arising from an ensemble and providing a source of noise. We investigate the effect of variations in hyperfine interactions between different copies of simple radical pairs on the directional response of a compass system. We find that the choice of radical pair parameters greatly influences how strongly the directional response of an ensemble is affected by inhomogeneity.

  4. ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Mikkelsen, T.; Galmarini, S.; Bianconi, R.; French, S. (eds.)

    2003-11-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

  5. Power to Detect Intervention Effects on Ensembles of Social Networks

    Science.gov (United States)

    Sweet, Tracy M.; Junker, Brian W.

    2016-01-01

    The hierarchical network model (HNM) is a framework introduced by Sweet, Thomas, and Junker for modeling interventions and other covariate effects on ensembles of social networks, such as what would be found in randomized controlled trials in education research. In this article, we develop calculations for the power to detect an intervention…

  6. Music Ensemble Participation: Personality Traits and Music Experience

    Science.gov (United States)

    Torrance, Tracy A.; Bugos, Jennifer A.

    2017-01-01

    The purpose of this study was two-fold: (1) to examine the relationship between personality type and ensemble choice and (2) to examine the differences in personality across age and music experience in young adults. Participants (N = 137; 68 instrumentalists, 69 vocalists) completed a demographic survey and the Big Five Personality Inventory.…

  7. Enhancing COSMO-DE ensemble forecasts by inexpensive techniques

    Directory of Open Access Journals (Sweden)

    Zied Ben Bouallègue

    2013-02-01

    Full Text Available COSMO-DE-EPS, a convection-permitting ensemble prediction system based on the high-resolution numerical weather prediction model COSMO-DE, is pre-operational since December 2010, providing probabilistic forecasts which cover Germany. This ensemble system comprises 20 members based on variations of the lateral boundary conditions, the physics parameterizations and the initial conditions. In order to increase the sample size in a computationally inexpensive way, COSMO-DE-EPS is combined with alternative ensemble techniques: the neighborhood method and the time-lagged approach. Their impact on the quality of the resulting probabilistic forecasts is assessed. Objective verification is performed over a six months period, scores based on the Brier score and its decomposition are shown for June 2011. The combination of the ensemble system with the alternative approaches improves probabilistic forecasts of precipitation in particular for high precipitation thresholds. Moreover, combining COSMO-DE-EPS with only the time-lagged approach improves the skill of area probabilities for precipitation and does not deteriorate the skill of 2 m-temperature and wind gusts forecasts.

  8. Dynamics of heterogeneous oscillator ensembles in terms of collective variables

    Science.gov (United States)

    Pikovsky, Arkady; Rosenblum, Michael

    2011-04-01

    We consider general heterogeneous ensembles of phase oscillators, sine coupled to arbitrary external fields. Starting with the infinitely large ensembles, we extend the Watanabe-Strogatz theory, valid for identical oscillators, to cover the case of an arbitrary parameter distribution. The obtained equations yield the description of the ensemble dynamics in terms of collective variables and constants of motion. As a particular case of the general setup we consider hierarchically organized ensembles, consisting of a finite number of subpopulations, whereas the number of elements in a subpopulation can be both finite or infinite. Next, we link the Watanabe-Strogatz and Ott-Antonsen theories and demonstrate that the latter one corresponds to a particular choice of constants of motion. The approach is applied to the standard Kuramoto-Sakaguchi model, to its extension for the case of nonlinear coupling, and to the description of two interacting subpopulations, exhibiting a chimera state. With these examples we illustrate that, although the asymptotic dynamics can be found within the framework of the Ott-Antonsen theory, the transients depend on the constants of motion. The most dramatic effect is the dependence of the basins of attraction of different synchronous regimes on the initial configuration of phases.

  9. Modelling of drug release from ensembles of aspirin microcapsules ...

    African Journals Online (AJOL)

    Purpose: In order to determine the drug release profile of an ensemble of aspirin crystals or microcapsules from its particle distribution a mathematical model that considered the individual release characteristics of the component single particles was developed. The model assumed that under sink conditions the release ...

  10. Cavity quantum electrodynamics with a Rydberg-blocked atomic ensemble

    DEFF Research Database (Denmark)

    Guerlin, Christine; Brion, Etienne; Esslinger, Tilman

    2010-01-01

    The realization of a Jaynes-Cummings model in the optical domain is proposed for an atomic ensemble. The scheme exploits the collective coupling of the atoms to a quantized cavity mode and the nonlinearity introduced by coupling to high-lying Rydberg states. A two-photon transition resonantly cou...

  11. Random walk loop soups and conformal loop ensembles

    NARCIS (Netherlands)

    van de Brug, T.; Camia, F.; Lis, M.

    2016-01-01

    The random walk loop soup is a Poissonian ensemble of lattice loops; it has been extensively studied because of its connections to the discrete Gaussian free field, but was originally introduced by Lawler and Trujillo Ferreras as a discrete version of the Brownian loop soup of Lawler and Werner, a

  12. Impact of hybrid GSI analysis using ETR ensembles

    Indian Academy of Sciences (India)

    Impact of hybrid GSI analysis using ETR ensembles. V S Prasad∗ and C J .... In this study, impact of hybrid ..... of water between vapour, clouds and ice (Damrath et al. 2000). ... flooding – June 2013; Weather and Climate Extremes 4. 22–34.

  13. Path planning in uncertain flow fields using ensemble method

    KAUST Repository

    Wang, Tong

    2016-08-20

    An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.

  14. Stacking Ensemble Learning for Short-Term Electricity Consumption Forecasting

    Directory of Open Access Journals (Sweden)

    Federico Divina

    2018-04-01

    Full Text Available The ability to predict short-term electric energy demand would provide several benefits, both at the economic and environmental level. For example, it would allow for an efficient use of resources in order to face the actual demand, reducing the costs associated to the production as well as the emission of CO 2 . To this aim, in this paper we propose a strategy based on ensemble learning in order to tackle the short-term load forecasting problem. In particular, our approach is based on a stacking ensemble learning scheme, where the predictions produced by three base learning methods are used by a top level method in order to produce final predictions. We tested the proposed scheme on a dataset reporting the energy consumption in Spain over more than nine years. The obtained experimental results show that an approach for short-term electricity consumption forecasting based on ensemble learning can help in combining predictions produced by weaker learning methods in order to obtain superior results. In particular, the system produces a lower error with respect to the existing state-of-the art techniques used on the same dataset. More importantly, this case study has shown that using an ensemble scheme can achieve very accurate predictions, and thus that it is a suitable approach for addressing the short-term load forecasting problem.

  15. The National Solo and Ensemble Contest 1929-1937

    Science.gov (United States)

    Meyers, Brian D.

    2012-01-01

    This study is the first investigation of the nine-year history of the National Solo and Ensemble Contests, held in the United States in conjunction with the National School Band and Orchestra Contests of the late 1920s and early to mid-1930s. Primary sources used include letters from those involved with the planning of the contests, meeting…

  16. An ensemble approach to the evolution of complex systems

    Indian Academy of Sciences (India)

    2014-03-15

    Mar 15, 2014 ... [Arpağ G and Erzan A 2014 An ensemble approach to the evolution of complex systems. J. Biosci. ... almost nothing about all the different ways in which your ...... energy cost to the organism of the maintenance, replication,.

  17. Exploiting ensemble learning for automatic cataract detection and grading.

    Science.gov (United States)

    Yang, Ji-Jiang; Li, Jianqiang; Shen, Ruifang; Zeng, Yang; He, Jian; Bi, Jing; Li, Yong; Zhang, Qinyan; Peng, Lihui; Wang, Qing

    2016-02-01

    Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a barrier to early intervention due to underlying costs. To date, studies reported in the literature utilize a single learning model for retinal image classification in grading cataract severity. We present an ensemble learning based approach as a means to improving diagnostic accuracy. Three independent feature sets, i.e., wavelet-, sketch-, and texture-based features, are extracted from each fundus image. For each feature set, two base learning models, i.e., Support Vector Machine and Back Propagation Neural Network, are built. Then, the ensemble methods, majority voting and stacking, are investigated to combine the multiple base learning models for final fundus image classification. Empirical experiments are conducted for cataract detection (two-class task, i.e., cataract or non-cataractous) and cataract grading (four-class task, i.e., non-cataractous, mild, moderate or severe) tasks. The best performance of the ensemble classifier is 93.2% and 84.5% in terms of the correct classification rates for cataract detection and grading tasks, respectively. The results demonstrate that the ensemble classifier outperforms the single learning model significantly, which also illustrates the effectiveness of the proposed approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Reliability of windstorm predictions in the ECMWF ensemble prediction system

    Science.gov (United States)

    Becker, Nico; Ulbrich, Uwe

    2016-04-01

    Windstorms caused by extratropical cyclones are one of the most dangerous natural hazards in the European region. Therefore, reliable predictions of such storm events are needed. Case studies have shown that ensemble prediction systems (EPS) are able to provide useful information about windstorms between two and five days prior to the event. In this work, ensemble predictions with the European Centre for Medium-Range Weather Forecasts (ECMWF) EPS are evaluated in a four year period. Within the 50 ensemble members, which are initialized every 12 hours and are run for 10 days, windstorms are identified and tracked in time and space. By using a clustering approach, different predictions of the same storm are identified in the different ensemble members and compared to reanalysis data. The occurrence probability of the predicted storms is estimated by fitting a bivariate normal distribution to the storm track positions. Our results show, for example, that predicted storm clusters with occurrence probabilities of more than 50% have a matching observed storm in 80% of all cases at a lead time of two days. The predicted occurrence probabilities are reliable up to 3 days lead time. At longer lead times the occurrence probabilities are overestimated by the EPS.

  19. Social behaviour shapes hypothalamic neural ensemble representations of conspecific sex

    Science.gov (United States)

    Remedios, Ryan; Kennedy, Ann; Zelikowsky, Moriel; Grewe, Benjamin F.; Schnitzer, Mark J.; Anderson, David J.

    2017-10-01

    All animals possess a repertoire of innate (or instinctive) behaviours, which can be performed without training. Whether such behaviours are mediated by anatomically distinct and/or genetically specified neural pathways remains unknown. Here we report that neural representations within the mouse hypothalamus, that underlie innate social behaviours, are shaped by social experience. Oestrogen receptor 1-expressing (Esr1+) neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) control mating and fighting in rodents. We used microendoscopy to image Esr1+ neuronal activity in the VMHvl of male mice engaged in these social behaviours. In sexually and socially experienced adult males, divergent and characteristic neural ensembles represented male versus female conspecifics. However, in inexperienced adult males, male and female intruders activated overlapping neuronal populations. Sex-specific neuronal ensembles gradually separated as the mice acquired social and sexual experience. In mice permitted to investigate but not to mount or attack conspecifics, ensemble divergence did not occur. However, 30 minutes of sexual experience with a female was sufficient to promote the separation of male and female ensembles and to induce an attack response 24 h later. These observations uncover an unexpected social experience-dependent component to the formation of hypothalamic neural assemblies controlling innate social behaviours. More generally, they reveal plasticity and dynamic coding in an evolutionarily ancient deep subcortical structure that is traditionally viewed as a ‘hard-wired’ system.

  20. Influence of horizontal resolution and ensemble size on model performance

    CSIR Research Space (South Africa)

    Dalton, A

    2014-10-01

    Full Text Available Conference of South African Society for Atmospheric Sciences (SASAS), Potchefstroom, 1-2 October 2014 Influence of horizontal resolution and ensemble size on model performance Amaris Dalton*¹, Willem A. Landman ¹ʾ² ¹Departmen of Geography, Geo...

  1. Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

    KAUST Repository

    Liu, Bo; Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

    2015-01-01

    (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence

  2. Bayesian model ensembling using meta-trained recurrent neural networks

    NARCIS (Netherlands)

    Ambrogioni, L.; Berezutskaya, Y.; Gü ç lü , U.; Borne, E.W.P. van den; Gü ç lü tü rk, Y.; Gerven, M.A.J. van; Maris, E.G.G.

    2017-01-01

    In this paper we demonstrate that a recurrent neural network meta-trained on an ensemble of arbitrary classification tasks can be used as an approximation of the Bayes optimal classifier. This result is obtained by relying on the framework of e-free approximate Bayesian inference, where the Bayesian

  3. Short-term ensemble radar rainfall forecasts for hydrological applications

    Science.gov (United States)

    Codo de Oliveira, M.; Rico-Ramirez, M. A.

    2016-12-01

    Flooding is a very common natural disaster around the world, putting local population and economy at risk. Forecasting floods several hours ahead and issuing warnings are of main importance to permit proper response in emergency situations. However, it is important to know the uncertainties related to the rainfall forecasting in order to produce more reliable forecasts. Nowcasting models (short-term rainfall forecasts) are able to produce high spatial and temporal resolution predictions that are useful in hydrological applications. Nonetheless, they are subject to uncertainties mainly due to the nowcasting model used, errors in radar rainfall estimation, temporal development of the velocity field and to the fact that precipitation processes such as growth and decay are not taken into account. In this study an ensemble generation scheme using rain gauge data as a reference to estimate radars errors is used to produce forecasts with up to 3h lead-time. The ensembles try to assess in a realistic way the residual uncertainties that remain even after correction algorithms are applied in the radar data. The ensembles produced are compered to a stochastic ensemble generator. Furthermore, the rainfall forecast output was used as an input in a hydrodynamic sewer network model and also in hydrological model for catchments of different sizes in north England. A comparative analysis was carried of how was carried out to assess how the radar uncertainties propagate into these models. The first named author is grateful to CAPES - Ciencia sem Fronteiras for funding this PhD research.

  4. Measures of trajectory ensemble disparity in nonequilibrium statistical dynamics

    International Nuclear Information System (INIS)

    Crooks, Gavin E; Sivak, David A

    2011-01-01

    Many interesting divergence measures between conjugate ensembles of nonequilibrium trajectories can be experimentally determined from the work distribution of the process. Herein, we review the statistical and physical significance of several of these measures, in particular the relative entropy (dissipation), Jeffreys divergence (hysteresis), Jensen–Shannon divergence (time-asymmetry), Chernoff divergence (work cumulant generating function), and Rényi divergence

  5. Ensemble modeling for aromatic production in Escherichia coli.

    Directory of Open Access Journals (Sweden)

    Matthew L Rizk

    2009-09-01

    Full Text Available Ensemble Modeling (EM is a recently developed method for metabolic modeling, particularly for utilizing the effect of enzyme tuning data on the production of a specific compound to refine the model. This approach is used here to investigate the production of aromatic products in Escherichia coli. Instead of using dynamic metabolite data to fit a model, the EM approach uses phenotypic data (effects of enzyme overexpression or knockouts on the steady state production rate to screen possible models. These data are routinely generated during strain design. An ensemble of models is constructed that all reach the same steady state and are based on the same mechanistic framework at the elementary reaction level. The behavior of the models spans the kinetics allowable by thermodynamics. Then by using existing data from the literature for the overexpression of genes coding for transketolase (Tkt, transaldolase (Tal, and phosphoenolpyruvate synthase (Pps to screen the ensemble, we arrive at a set of models that properly describes the known enzyme overexpression phenotypes. This subset of models becomes more predictive as additional data are used to refine the models. The final ensemble of models demonstrates the characteristic of the cell that Tkt is the first rate controlling step, and correctly predicts that only after Tkt is overexpressed does an increase in Pps increase the production rate of aromatics. This work demonstrates that EM is able to capture the result of enzyme overexpression on aromatic producing bacteria by successfully utilizing routinely generated enzyme tuning data to guide model learning.

  6. Canonical Ensemble Model for Black Hole Horizon of Schwarzschild ...

    Indian Academy of Sciences (India)

    Abstract. In this paper, we use the canonical ensemble model to discuss the radiation of a Schwarzschild–de Sitter black hole on the black hole horizon. Using this model, we calculate the probability distribution from function of the emission shell. And the statistical meaning which compare with the distribution function is ...

  7. Improving wave forecasting by integrating ensemble modelling and machine learning

    Science.gov (United States)

    O'Donncha, F.; Zhang, Y.; James, S. C.

    2017-12-01

    Modern smart-grid networks use technologies to instantly relay information on supply and demand to support effective decision making. Integration of renewable-energy resources with these systems demands accurate forecasting of energy production (and demand) capacities. For wave-energy converters, this requires wave-condition forecasting to enable estimates of energy production. Current operational wave forecasting systems exhibit substantial errors with wave-height RMSEs of 40 to 60 cm being typical, which limits the reliability of energy-generation predictions thereby impeding integration with the distribution grid. In this study, we integrate physics-based models with statistical learning aggregation techniques that combine forecasts from multiple, independent models into a single "best-estimate" prediction of the true state. The Simulating Waves Nearshore physics-based model is used to compute wind- and currents-augmented waves in the Monterey Bay area. Ensembles are developed based on multiple simulations perturbing input data (wave characteristics supplied at the model boundaries and winds) to the model. A learning-aggregation technique uses past observations and past model forecasts to calculate a weight for each model. The aggregated forecasts are compared to observation data to quantify the performance of the model ensemble and aggregation techniques. The appropriately weighted ensemble model outperforms an individual ensemble member with regard to forecasting wave conditions.

  8. Tweet-based Target Market Classification Using Ensemble Method

    Directory of Open Access Journals (Sweden)

    Muhammad Adi Khairul Anshary

    2016-09-01

    Full Text Available Target market classification is aimed at focusing marketing activities on the right targets. Classification of target markets can be done through data mining and by utilizing data from social media, e.g. Twitter. The end result of data mining are learning models that can classify new data. Ensemble methods can improve the accuracy of the models and therefore provide better results. In this study, classification of target markets was conducted on a dataset of 3000 tweets in order to extract features. Classification models were constructed to manipulate the training data using two ensemble methods (bagging and boosting. To investigate the effectiveness of the ensemble methods, this study used the CART (classification and regression tree algorithm for comparison. Three categories of consumer goods (computers, mobile phones and cameras and three categories of sentiments (positive, negative and neutral were classified towards three target-market categories. Machine learning was performed using Weka 3.6.9. The results of the test data showed that the bagging method improved the accuracy of CART with 1.9% (to 85.20%. On the other hand, for sentiment classification, the ensemble methods were not successful in increasing the accuracy of CART. The results of this study may be taken into consideration by companies who approach their customers through social media, especially Twitter.

  9. A grand-canonical ensemble of randomly triangulated surfaces

    International Nuclear Information System (INIS)

    Jurkiewicz, J.; Krzywicki, A.; Petersson, B.

    1986-01-01

    An algorithm is presented generating the grand-canonical ensemble of discrete, randomly triangulated Polyakov surfaces. The algorithm is used to calculate the susceptibility exponent, which controls the existence of the continuum limit of the considered model, for the dimensionality of the embedding space ranging from 0 to 20. (orig.)

  10. Middle School Drum Ensemble: An Unlikely Experience in Classroom Democracy

    Science.gov (United States)

    Barbre, James

    2013-01-01

    Though music has a long and successful history within education, it is often one of the first sacrificial lambs when school budgets tighten. Over the course of an academic year, a documentary film sought to tell the story of an American middle school drum ensemble. The context of this group provided an ideal way to examine the nature of student…

  11. Peer-Teaching in the Secondary Music Ensemble

    Science.gov (United States)

    Johnson, Erik

    2015-01-01

    Peer-teaching is an instructional technique that has been used by teachers world-wide to successfully engage, exercise and deepen student learning. Yet, in some instances, teachers find the application of peer-teaching in large music ensembles at the secondary level to be daunting. This article is meant to be a practical resource for secondary…

  12. Light localization in cold and dense atomic ensemble

    International Nuclear Information System (INIS)

    Sokolov, Igor

    2017-01-01

    We report on results of theoretical analysis of possibilities of light strong (Anderson) localization in a cold atomic ensemble. We predict appearance of localization in dense atomic systems in strong magnetic field. We prove that in absence of the field the light localization is impossible. (paper)

  13. The egg model - a geological ensemble for reservoir simulation

    NARCIS (Netherlands)

    Jansen, J.D.; Fonseca, R.M.; Kahrobaei, S.; Siraj, M.M.; Essen, van G.M.; Hof, Van den P.M.J.

    2014-01-01

    The ‘Egg Model’ is a synthetic reservoir model consisting of an ensemble of 101 relatively small three-dimensional realizations of a channelized oil reservoir produced under water flooding conditions with eight water injectors and four oil producers. It has been used in numerous publications to

  14. Precision bounds for gradient magnetometry with atomic ensembles

    Science.gov (United States)

    Apellaniz, Iagoba; Urizar-Lanz, Iñigo; Zimborás, Zoltán; Hyllus, Philipp; Tóth, Géza

    2018-05-01

    We study gradient magnetometry with an ensemble of atoms with arbitrary spin. We calculate precision bounds for estimating the gradient of the magnetic field based on the quantum Fisher information. For quantum states that are invariant under homogeneous magnetic fields, we need to measure a single observable to estimate the gradient. On the other hand, for states that are sensitive to homogeneous fields, a simultaneous measurement is needed, as the homogeneous field must also be estimated. We prove that for the cases studied in this paper, such a measurement is feasible. We present a method to calculate precision bounds for gradient estimation with a chain of atoms or with two spatially separated atomic ensembles. We also consider a single atomic ensemble with an arbitrary density profile, where the atoms cannot be addressed individually, and which is a very relevant case for experiments. Our model can take into account even correlations between particle positions. While in most of the discussion we consider an ensemble of localized particles that are classical with respect to their spatial degree of freedom, we also discuss the case of gradient metrology with a single Bose-Einstein condensate.

  15. Random matrix ensembles with random interactions: Results for ...

    Indian Academy of Sciences (India)

    ... Public Lectures · Lecture Workshops · Refresher Courses · Symposia · Live Streaming. Home; Journals; Pramana – Journal of Physics; Volume 73; Issue 3. Random matrix ensembles with random interactions: Results for EGUE(2)-(4). Manan Vyas Manan Vyas. Volume 73 Issue 3 September 2009 pp 521-531 ...

  16. An Ensemble Approach in Converging Contents of LMS and KMS

    Science.gov (United States)

    Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay

    2017-01-01

    Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the…

  17. Fire spread estimation on forest wildfire using ensemble kalman filter

    Science.gov (United States)

    Syarifah, Wardatus; Apriliani, Erna

    2018-04-01

    Wildfire is one of the most frequent disasters in the world, for example forest wildfire, causing population of forest decrease. Forest wildfire, whether naturally occurring or prescribed, are potential risks for ecosystems and human settlements. These risks can be managed by monitoring the weather, prescribing fires to limit available fuel, and creating firebreaks. With computer simulations we can predict and explore how fires may spread. The model of fire spread on forest wildfire was established to determine the fire properties. The fire spread model is prepared based on the equation of the diffusion reaction model. There are many methods to estimate the spread of fire. The Kalman Filter Ensemble Method is a modified estimation method of the Kalman Filter algorithm that can be used to estimate linear and non-linear system models. In this research will apply Ensemble Kalman Filter (EnKF) method to estimate the spread of fire on forest wildfire. Before applying the EnKF method, the fire spread model will be discreted using finite difference method. At the end, the analysis obtained illustrated by numerical simulation using software. The simulation results show that the Ensemble Kalman Filter method is closer to the system model when the ensemble value is greater, while the covariance value of the system model and the smaller the measurement.

  18. Realization of Deutsch-like algorithm using ensemble computing

    International Nuclear Information System (INIS)

    Wei Daxiu; Luo Jun; Sun Xianping; Zeng Xizhi

    2003-01-01

    The Deutsch-like algorithm [Phys. Rev. A. 63 (2001) 034101] distinguishes between even and odd query functions using fewer function calls than its possible classical counterpart in a two-qubit system. But the similar method cannot be applied to a multi-qubit system. We propose a new approach for solving Deutsch-like problem using ensemble computing. The proposed algorithm needs an ancillary qubit and can be easily extended to multi-qubit system with one query. Our ensemble algorithm beginning with a easily-prepared initial state has three main steps. The classifications of the functions can be obtained directly from the spectra of the ancilla qubit. We also demonstrate the new algorithm in a four-qubit molecular system using nuclear magnetic resonance (NMR). One hydrogen and three carbons are selected as the four qubits, and one of carbons is ancilla qubit. We choice two unitary transformations, corresponding to two functions (one odd function and one even function), to validate the ensemble algorithm. The results show that our experiment is successfully and our ensemble algorithm for solving the Deutsch-like problem is virtual

  19. An ensemble based nonlinear orthogonal matching pursuit algorithm for sparse history matching of reservoir models

    KAUST Repository

    Fsheikh, Ahmed H.; Wheeler, Mary Fanett; Hoteit, Ibrahim

    2013-01-01

    the dictionary, the solution is obtained by applying Tikhonov regularization. The proposed algorithm relies on approximate gradient estimation using an iterative stochastic ensemble method (ISEM). ISEM utilizes an ensemble of directional derivatives

  20. Skill prediction of local weather forecasts based on the ECMWF ensemble

    Directory of Open Access Journals (Sweden)

    C. Ziehmann

    2001-01-01

    Full Text Available Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF temperature and wind speed ensemble forecasts at 30 German stations. The results indicate that the population of the ensemble mode provides useful information for the uncertainty in temperature forecasts. The ensemble entropy is a similar good measure. This is not true for the spread if it is simply calculated as the variance of the ensemble members with respect to the ensemble mean. The number of clusters in the C regions is almost unrelated to the local skill. For wind forecasts, the results are less promising.

  1. Non-Boltzmann Ensembles and Monte Carlo Simulations

    International Nuclear Information System (INIS)

    Murthy, K. P. N.

    2016-01-01

    Boltzmann sampling based on Metropolis algorithm has been extensively used for simulating a canonical ensemble and for calculating macroscopic properties of a closed system at desired temperatures. An estimate of a mechanical property, like energy, of an equilibrium system, is made by averaging over a large number microstates generated by Boltzmann Monte Carlo methods. This is possible because we can assign a numerical value for energy to each microstate. However, a thermal property like entropy, is not easily accessible to these methods. The reason is simple. We can not assign a numerical value for entropy, to a microstate. Entropy is not a property associated with any single microstate. It is a collective property of all the microstates. Toward calculating entropy and other thermal properties, a non-Boltzmann Monte Carlo technique called Umbrella sampling was proposed some forty years ago. Umbrella sampling has since undergone several metamorphoses and we have now, multi-canonical Monte Carlo, entropic sampling, flat histogram methods, Wang-Landau algorithm etc . This class of methods generates non-Boltzmann ensembles which are un-physical. However, physical quantities can be calculated as follows. First un-weight a microstates of the entropic ensemble; then re-weight it to the desired physical ensemble. Carry out weighted average over the entropic ensemble to estimate physical quantities. In this talk I shall tell you of the most recent non- Boltzmann Monte Carlo method and show how to calculate free energy for a few systems. We first consider estimation of free energy as a function of energy at different temperatures to characterize phase transition in an hairpin DNA in the presence of an unzipping force. Next we consider free energy as a function of order parameter and to this end we estimate density of states g ( E , M ), as a function of both energy E , and order parameter M . This is carried out in two stages. We estimate g ( E ) in the first stage

  2. The role of 1-D and 3-D radiative heating in the organization of shallow cumulus convection and the formation of cloud streets

    Science.gov (United States)

    Jakub, Fabian; Mayer, Bernhard

    2017-11-01

    The formation of shallow cumulus cloud streets was historically attributed primarily to dynamics. Here, we focus on the interaction between radiatively induced surface heterogeneities and the resulting patterns in the flow. Our results suggest that solar radiative heating has the potential to organize clouds perpendicular to the sun's incidence angle. To quantify the extent of organization, we performed a high-resolution large-eddy simulation (LES) parameter study. We varied the horizontal wind speed, the surface heat capacity, the solar zenith and azimuth angles, and radiative transfer parameterizations (1-D and 3-D). As a quantitative measure we introduce a simple algorithm that provides a scalar quantity for the degree of organization and the alignment. We find that, even in the absence of a horizontal wind, 3-D radiative transfer produces cloud streets perpendicular to the sun's incident direction, whereas the 1-D approximation or constant surface fluxes produce randomly positioned circular clouds. Our reasoning for the enhancement or reduction of organization is the geometric position of the cloud's shadow and its corresponding surface fluxes. Furthermore, when increasing horizontal wind speeds to 5 or 10 m s-1, we observe the development of dynamically induced cloud streets. If, in addition, solar radiation illuminates the surface beneath the cloud, i.e., when the sun is positioned orthogonally to the mean wind field and the solar zenith angle is larger than 20°, the cloud-radiative feedback has the potential to significantly enhance the tendency to organize in cloud streets. In contrast, in the case of the 1-D approximation (or overhead sun), the tendency to organize is weaker or even prohibited because the shadow is cast directly beneath the cloud. In a land-surface-type situation, we find the organization of convection happening on a timescale of half an hour. The radiative feedback, which creates surface heterogeneities, is generally diminished for large

  3. The role of 1-D and 3-D radiative heating in the organization of shallow cumulus convection and the formation of cloud streets

    Directory of Open Access Journals (Sweden)

    F. Jakub

    2017-11-01

    Full Text Available The formation of shallow cumulus cloud streets was historically attributed primarily to dynamics. Here, we focus on the interaction between radiatively induced surface heterogeneities and the resulting patterns in the flow. Our results suggest that solar radiative heating has the potential to organize clouds perpendicular to the sun's incidence angle. To quantify the extent of organization, we performed a high-resolution large-eddy simulation (LES parameter study. We varied the horizontal wind speed, the surface heat capacity, the solar zenith and azimuth angles, and radiative transfer parameterizations (1-D and 3-D. As a quantitative measure we introduce a simple algorithm that provides a scalar quantity for the degree of organization and the alignment. We find that, even in the absence of a horizontal wind, 3-D radiative transfer produces cloud streets perpendicular to the sun's incident direction, whereas the 1-D approximation or constant surface fluxes produce randomly positioned circular clouds. Our reasoning for the enhancement or reduction of organization is the geometric position of the cloud's shadow and its corresponding surface fluxes. Furthermore, when increasing horizontal wind speeds to 5 or 10 m s−1, we observe the development of dynamically induced cloud streets. If, in addition, solar radiation illuminates the surface beneath the cloud, i.e., when the sun is positioned orthogonally to the mean wind field and the solar zenith angle is larger than 20°, the cloud-radiative feedback has the potential to significantly enhance the tendency to organize in cloud streets. In contrast, in the case of the 1-D approximation (or overhead sun, the tendency to organize is weaker or even prohibited because the shadow is cast directly beneath the cloud. In a land-surface-type situation, we find the organization of convection happening on a timescale of half an hour. The radiative feedback, which creates surface heterogeneities, is

  4. Association between expression of cumulus expansion markers and real-time proliferation of porcine follicular granulosa cells in a primary cell culture model.

    Science.gov (United States)

    Ciesiółka, S; Budna, J; Bryja, A; Kranc, W; Chachuła, A; Dyszkiewicz-Konwińska, M; Piotrowska, H; Bukowska, D; Antosik, P; Bruska, M; Brüssow, K P; Nowicki, M; Zabel, M; Kempisty, B

    2016-01-01

    Folliculogenesis is a compound process that involves both ovarian follicle growth and oocyte development, which is tightly attached to the follicular wall. During this process, cells that form the follicle structure undergo substantial morphological and molecular modifications that finally lead to differentiation and specialization of ovarian follicular cells. The differentiation of ovarian cells encompasses formation of follicle, which is composed of theca (TCs), mural granulosa (GCs), and cumulus cells (CCs). It was previously hypothesized that GCs and CCs represent undifferentiated and highly specialized follicular cells, respectively, which may have similar primordial cell origins. In this study, we investigated the expression pattern of cumulus expansion markers such as COX2, HAS2, PTX3, and TSG6 in porcine GCs during short-term, in vitro culture. We hypothesized that these genes may display an important function in GCs in relation to cellular real-time proliferation. The expression pattern of COX2, HAS2, PTX3, and TSG6 was evaluated after using RT-qPCR in relation to confocal microscopy observations of protein expression and distribution during real-time proliferation of porcine follicular GCs. The COX2 and HAS2 mRNAs were highly expressed after 120 h of in vitro culture (IVC), whereas PTX3 and TSG6 mRNAs were increased during the first 24-48 h of IVC (P less than 0.001, P less than 0.01). Conversely, all of the encoded proteins were highly expressed after 144-168 h of IVC as compared to other culture periods (P less than 0.001, P less than 0.01). When analyzing the realtime proliferation of GCs in vitro, we observed a logarithmic increase of cell proliferation between 0 h and 120 h of IVC. However, after 120-168 h of IVC, the cells reached the lag phase of proliferation. Since it is well accepted that porcine GCs undergo luteinization shortly after 24-48 h of IVC, the expression pattern of investigated genes indicated that Cox2 and Has2 are independent from

  5. Contributions of Heterogeneous Ice Nucleation, Large-Scale Circulation, and Shallow Cumulus Detrainment to Cloud Phase Transition in Mixed-Phase Clouds with NCAR CAM5

    Science.gov (United States)

    Liu, X.; Wang, Y.; Zhang, D.; Wang, Z.

    2016-12-01

    Mixed-phase clouds consisting of both liquid and ice water occur frequently at high-latitudes and in mid-latitude storm track regions. This type of clouds has been shown to play a critical role in the surface energy balance, surface air temperature, and sea ice melting in the Arctic. Cloud phase partitioning between liquid and ice water determines the cloud optical depth of mixed-phase clouds because of distinct optical properties of liquid and ice hydrometeors. The representation and simulation of cloud phase partitioning in state-of-the-art global climate models (GCMs) are associated with large biases. In this study, the cloud phase partition in mixed-phase clouds simulated from the NCAR Community Atmosphere Model version 5 (CAM5) is evaluated against satellite observations. Observation-based supercooled liquid fraction (SLF) is calculated from CloudSat, MODIS and CPR radar detected liquid and ice water paths for clouds with cloud-top temperatures between -40 and 0°C. Sensitivity tests with CAM5 are conducted for different heterogeneous ice nucleation parameterizations with respect to aerosol influence (Wang et al., 2014), different phase transition temperatures for detrained cloud water from shallow convection (Kay et al., 2016), and different CAM5 model configurations (free-run versus nudged winds and temperature, Zhang et al., 2015). A classical nucleation theory-based ice nucleation parameterization in mixed-phase clouds increases the SLF especially at temperatures colder than -20°C, and significantly improves the model agreement with observations in the Arctic. The change of transition temperature for detrained cloud water increases the SLF at higher temperatures and improves the SLF mostly over the Southern Ocean. Even with the improved SLF from the ice nucleation and shallow cumulus detrainment, the low SLF biases in some regions can only be improved through the improved circulation with the nudging technique. Our study highlights the challenges of

  6. REAL - Ensemble radar precipitation estimation for hydrology in a mountainous region

    OpenAIRE

    Germann, Urs; Berenguer Ferrer, Marc; Sempere Torres, Daniel; Zappa, Massimiliano

    2009-01-01

    An elegant solution to characterise the residual errors in radar precipitation estimates is to generate an ensemble of precipitation fields. The paper proposes a radar ensemble generator designed for usage in the Alps using LU decomposition (REAL), and presents first results from a real-time implementation coupling the radar ensemble with a semi-distributed rainfall–runoff model for flash flood modelling in a steep Alpine catchment. Each member of the radar ensemble is a possible realisati...

  7. Ensemble models of neutrophil trafficking in severe sepsis.

    Directory of Open Access Journals (Sweden)

    Sang Ok Song

    Full Text Available A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about 18% of the treated population that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental

  8. Online probabilistic learning with an ensemble of forecasts

    Science.gov (United States)

    Thorey, Jean; Mallet, Vivien; Chaussin, Christophe

    2016-04-01

    Our objective is to produce a calibrated weighted ensemble to forecast a univariate time series. In addition to a meteorological ensemble of forecasts, we rely on observations or analyses of the target variable. The celebrated Continuous Ranked Probability Score (CRPS) is used to evaluate the probabilistic forecasts. However applying the CRPS on weighted empirical distribution functions (deriving from the weighted ensemble) may introduce a bias because of which minimizing the CRPS does not produce the optimal weights. Thus we propose an unbiased version of the CRPS which relies on clusters of members and is strictly proper. We adapt online learning methods for the minimization of the CRPS. These methods generate the weights associated to the members in the forecasted empirical distribution function. The weights are updated before each forecast step using only past observations and forecasts. Our learning algorithms provide the theoretical guarantee that, in the long run, the CRPS of the weighted forecasts is at least as good as the CRPS of any weighted ensemble with weights constant in time. In particular, the performance of our forecast is better than that of any subset ensemble with uniform weights. A noteworthy advantage of our algorithm is that it does not require any assumption on the distributions of the observations and forecasts, both for the application and for the theoretical guarantee to hold. As application example on meteorological forecasts for photovoltaic production integration, we show that our algorithm generates a calibrated probabilistic forecast, with significant performance improvements on probabilistic diagnostic tools (the CRPS, the reliability diagram and the rank histogram).

  9. A genetic ensemble approach for gene-gene interaction identification

    Directory of Open Access Journals (Sweden)

    Ho Joshua WK

    2010-10-01

    Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

  10. A variational ensemble scheme for noisy image data assimilation

    Science.gov (United States)

    Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne

    2014-05-01

    Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow

  11. Ensemble atmospheric dispersion modeling for emergency response consequence assessments

    International Nuclear Information System (INIS)

    Addis, R.P.; Buckley, R.L.

    2003-01-01

    Full text: Prognostic atmospheric dispersion models are used to generate consequence assessments, which assist decision-makers in the event of a release from a nuclear facility. Differences in the forecast wind fields generated by various meteorological agencies, differences in the transport and diffusion models themselves, as well as differences in the way these models treat the release source term, all may result in differences in the simulated plumes. This talk will address the U.S. participation in the European ENSEMBLE project, and present a perspective an how ensemble techniques may be used to enable atmospheric modelers to provide decision-makers with a more realistic understanding of how both the atmosphere and the models behave. Meteorological forecasts generated by numerical models from national and multinational meteorological agencies provide individual realizations of three-dimensional, time dependent atmospheric wind fields. These wind fields may be used to drive atmospheric dispersion (transport and diffusion) models, or they may be used to initiate other, finer resolution meteorological models, which in turn drive dispersion models. Many modeling agencies now utilize ensemble-modeling techniques to determine how sensitive the prognostic fields are to minor perturbations in the model parameters. However, the European Union programs RTMOD and ENSEMBLE are the first projects to utilize a WEB based ensemble approach to interpret the output from atmospheric dispersion models. The ensembles produced are different from those generated by meteorological forecasting centers in that they are ensembles of dispersion model outputs from many different atmospheric transport and diffusion models utilizing prognostic atmospheric fields from several different forecast centers. As such, they enable a decision-maker to consider the uncertainty in the plume transport and growth as a result of the differences in the forecast wind fields as well as the differences in the

  12. Improving the ensemble optimization method through covariance matrix adaptation (CMA-EnOpt)

    NARCIS (Netherlands)

    Fonseca, R.M.; Leeuwenburgh, O.; Hof, P.M.J. van den; Jansen, J.D.

    2013-01-01

    Ensemble Optimization (EnOpt) is a rapidly emerging method for reservoir model based production optimization. EnOpt uses an ensemble of controls to approximate the gradient of the objective function with respect to the controls. Current implementations of EnOpt use a Gaussian ensemble with a

  13. A new deterministic Ensemble Kalman Filter with one-step-ahead smoothing for storm surge forecasting

    KAUST Repository

    Raboudi, Naila

    2016-01-01

    KF-OSA exploits the observation twice. The incoming observation is first used to smooth the ensemble at the previous time step. The resulting smoothed ensemble is then integrated forward to compute a "pseudo forecast" ensemble, which is again updated with the same

  14. The Effects of Classical Guitar Ensembles on Student Self-Perceptions and Acquisition of Music Skills

    Science.gov (United States)

    Kramer, John R.

    2012-01-01

    Classical guitar ensembles are increasing in the United States as popular alternatives to band, choir, and orchestra. Classical guitar ensembles are offered at many middle and high schools as fine arts electives as one of the only options for classical guitarists to participate in ensembles. The purpose of this study was to explore the development…

  15. A Comparative Case Study of Non-Music Major Participation in Two Contrasting Collegiate Choral Ensembles

    Science.gov (United States)

    Jones, Sara K.

    2018-01-01

    The purpose of this comparative case study was to examine the motivation for participation in traditional and non-traditional vocal ensembles by students who are not pursuing a career in music and the perceived benefits of this participation. Participants were selected from a traditional mixed choral ensemble and a student-run a cappella ensemble.…

  16. Large-Eddy Simulation of Shallow Cumulus over Land: A Composite Case Based on ARM Long-Term Observations at Its Southern Great Plains Site

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yunyan [Lawrence Livermore National Laboratory, Livermore, California; Klein, Stephen A. [Lawrence Livermore National Laboratory, Livermore, California; Fan, Jiwen [Pacific Northwest National Laboratory, Richland, Washington; Chandra, Arunchandra S. [Division of Meteorology and Physical Oceanography, University of Miami, Miami, Florida; Kollias, Pavlos [School of Marine and Atmospheric Sciences, Stony Brook University, State University of New York, Stony Brook, New York; Xie, Shaocheng [Lawrence Livermore National Laboratory, Livermore, California; Tang, Shuaiqi [Lawrence Livermore National Laboratory, Livermore, California

    2017-10-01

    Based on long-term observations by the Atmospheric Radiation Measurement program at its Southern Great Plains site, a new composite case of continental shallow cumulus (ShCu) convection is constructed for large-eddy simulations (LES) and single-column models. The case represents a typical daytime nonprecipitating ShCu whose formation and dissipation are driven by the local atmospheric conditions and land surface forcing and are not influenced by synoptic weather events. The case includes early morning initial profiles of temperature and moisture with a residual layer; diurnally varying sensible and latent heat fluxes, which represent a domain average over different land surface types; simplified large-scale horizontal advective tendencies and subsidence; and horizontal winds with prevailing direction and average speed. Observed composite cloud statistics are provided for model evaluation. The observed diurnal cycle is well reproduced by LES; however, the cloud amount, liquid water path, and shortwave radiative effect are generally underestimated. LES are compared between simulations with an all-or-nothing bulk microphysics and a spectral bin microphysics. The latter shows improved agreement with observations in the total cloud cover and the amount of clouds with depths greater than 300 m. When compared with radar retrievals of in-cloud air motion, LES produce comparable downdraft vertical velocities, but a larger updraft area, velocity, and updraft mass flux. Both observations and LES show a significantly larger in-cloud downdraft fraction and downdraft mass flux than marine ShCu.

  17. Cumulus cells gene expression profiling in terms of oocyte maturity in controlled ovarian hyperstimulation using GnRH agonist or GnRH antagonist.

    Science.gov (United States)

    Devjak, Rok; Fon Tacer, Klementina; Juvan, Peter; Virant Klun, Irma; Rozman, Damjana; Vrtačnik Bokal, Eda

    2012-01-01

    In in vitro fertilization (IVF) cycles controlled ovarian hyperstimulation (COH) is established by gonadotropins in combination with gonadotropin-releasing hormone (GnRH) agonists or antagonists, to prevent premature luteinizing hormone (LH) surge. The aim of our study was to improve the understanding of gene expression profile of cumulus cells (CC) in terms of ovarian stimulation protocol and oocyte maturity. We applied Affymetrix gene expression profiling in CC of oocytes at different maturation stages using either GnRH agonists or GnRH antagonists. Two analyses were performed: the first involved CC of immature metaphase I (MI) and mature metaphase II (MII) oocytes where 359 genes were differentially expressed, and the second involved the two GnRH analogues where no differentially expressed genes were observed at the entire transcriptome level. A further analysis of 359 differentially genes was performed, focusing on anti-Müllerian hormone receptor 2 (AMHR2), follicle stimulating hormone receptor (FSHR), vascular endothelial growth factor C (VEGFC) and serine protease inhibitor E2 (SERPINE2). Among other differentially expressed genes we observed a marked number of new genes connected to cell adhesion and neurotransmitters such as dopamine, glycine and γ-Aminobutyric acid (GABA). No differential expression in CC between the two GnRH analogues supports the findings of clinical studies where no significant difference in live birth rates between both GnRH analogues has been proven.

  18. Using synchronization in multi-model ensembles to improve prediction

    Science.gov (United States)

    Hiemstra, P.; Selten, F.

    2012-04-01

    In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of

  19. The Next-Generation Goddard Convective-Stratiform Heating Algorithm: New Model Simulations for Tropical and Continental Summertime Environments

    Science.gov (United States)

    Lang, S. E.; Tao, W. K.; Wu, D.

    2016-12-01

    The Goddard Convective-Stratiform Heating (or CSH) algorithm is used to retrieve estimates of cloud heating over the global Tropics using TRMM rainfall data and a set of look-up-tables (LUTs) derived from a series of multi-week cloud-resolving model (CRM) simulations using the Goddard Cumulus Ensemble model (or GCE). These simulations link satellite observables (i.e., surface rainfall and stratiform fraction) with cloud heating profiles, which are not directly observable. The strength of the algorithm relies in part on the representativeness of the simulations; more realistic simulations provide a stronger link between the observables and simulated heating profiles. The current "TRMM" version of the CSH algorithm relies on 2D GCE simulations using an improved version of the Goddard 3-class ice scheme (3ICE), a moderate-sized domain, and 1-km horizontal resolution. Updating the LUTs, which are suitable for tropical and continental summertime environments requires new, more realistic GCE simulations. New simulations are performed using a new, improved 4-class ice scheme, which has been shown to outperform the 3ICE scheme, especially for intense convection. Additional grid configurations are also tested and evaluated to find the best overall setup to for re-deriving and updating the CSH tropical/summertime LUTs.

  20. The Use of Artificial-Intelligence-Based Ensembles for Intrusion Detection: A Review

    Directory of Open Access Journals (Sweden)

    Gulshan Kumar

    2012-01-01

    Full Text Available In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI- based techniques play prominent role in development of ensemble for intrusion detection (ID and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1 architecture & approach followed; (2 different methods utilized in different phases of ensemble learning; (3 other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs.